Bio


Dr. Xing is currently the Jacob Haimson Professor of Medical Physics and Director of Medical Physics Division of Radiation Oncology Department at Stanford University. He also holds affiliate faculty positions in Department of Electrical engineering, Bio-X and Molecular Imaging Program at Stanford. Dr. Xing’s research has been focused on medical imaging, artificial intelligence in medicine, treatment planning, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. He has made unique and significant contributions to each of the above areas. Dr. Xing is an author on more than 400 peer reviewed publications, a co-inventor on many issued and pending patents, and a co- investigator or principal investigator on numerous NIH, DOD, RSNA, ACS and corporate grants. He is a fellow of AAPM (American Association of Physicists in Medicine) and AIMBE (American Institute for Medical and Biological Engineering). He is a recipient of Google Faculty Scholar Award. He is also on the editorial boards of a number of journals in medical physics and medical imaging.

Academic Appointments


Administrative Appointments


  • Associate Editor, Medical Physics Journal (2003 - 2008)
  • Member of international advisory board, Physics in Medicine and Bilogy (2008 - Present)
  • Member of Clinical Research and Cancer Epidemiology (CCE) Committee, American Cancer Society (2006 - Present)
  • Member of ZRG1 (Quick Trials on Imaging and Image-Guided Intervention) section, National Institute of Health (2008 - Present)
  • Director of Medical Physics Division, Department of Radiation Oncology, Stanford University (2009 - Present)
  • Director of Radiation Physics Division, Department of Radiation Oncology, Stanford University (2010 - Present)
  • Member of Senior Editorial Board, American Journal of Nuclear Medicine and Molecular Imaging (2010 - Present)
  • Member of Editorial Board, Journal of Gastrointestinal Oncology (2010 - Present)

Honors & Awards


  • Best of Medical Physics in Imaging, AAPM (2017)
  • Basic Science Award, ASTRO (2013)
  • Fellow, American Association of Physicists in Medicine (AAPM) (2012)
  • Best of Physics, American Association of Physicists in Medicine (2015)
  • Fellow, American Institute for Medical and Biological Engineering (AIMBE) (2016)
  • Google Faculty Research Award, Google Inc. (2016)
  • Concept Award for Breast Cancer Research, Department of Defense (2001)
  • Research Scholar Award, American Cancer Society (2001)
  • Basic Science Investigator Award, American Society of Therapeutic Radiology (ASTRO). (2002)
  • Research Scholar of 2005, American Cancer Society (2005)

Professional Education


  • PhD, Johns Hopkins University, Physics (1992)

Community and International Work


  • Clinical implementation of intensity modulated radiation therapy

    Partnering Organization(s)

    American Association of Physicists in Medicine (AAPM)

    Ongoing Project

    Yes

    Opportunities for Student Involvement

    Yes

Current Research and Scholarly Interests


Artificial intelligence in medicine
Medical imaging (instrumentation, image reconstruction and clinical applications)
Biologically conformal radiation therapy (BCRT)
Metabolic imaging (MRSI, PET/CT) for tumor delineation and assessment of therapeutic response;
Treatment planning and clinical decision-making
Radiobiology study using molecular imaging (small animal PET, CT, MRI, optical);

Clinical Trials


  • Cervical Nodal Mets in Squamous Cell Carcinoma of H&N - MRI, FDG-PET, & Histopathologic Correlation Not Recruiting

    The purpose of this study is to determine the value of novel non-invasive medical imaging methods for detecting the spread of head and neck squamous cell carcinoma to the lymph nodes in the neck by comparing their results to findings at the time of surgery.

    Stanford is currently not accepting patients for this trial. For more information, please contact Quynh-Thu Le, (650) 498 - 6184.

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  • Endoscopic Capillary Oximetry for Tumor Diagnosis in Head and Neck Cancer Not Recruiting

    Endoscopy is a standard part of the evaluation of patients with head and neck cancer used for determining the extent of tumor involvement. However, not all areas involved by tumor are apparent visually. Preliminary results indicate that compared with normal tissues, tumors have abnormal levels of capillary oxygenation. The purpose of this study is to determine the ability of non-pulsatile visible light tissue oxygen monitoring to differentiate normal and tumor tissue based on capillary oxygenation during endoscopy Should this be possible, this method could be used to mark tumor extent and invasion, even when that invasion is up to 5mm blow the tissue surface.

    Stanford is currently not accepting patients for this trial. For more information, please contact Peter Maxim, (650) 724 - 3018.

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  • Indirect Magnetic Resonance Lymphangiography of the Head and Neck Region Using Conventional Gadolinium-based Contrast Not Recruiting

    To determine the ability of magnetic resonance lymphangiography using conventional gadolinium injected directly into the tumor site and PET scan in detecting microscopic nodal metastasis in patients with newly diagnosed H&N cancers

    Stanford is currently not accepting patients for this trial. For more information, please contact Bill Loo, (650) 736 - 7143.

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  • Phase I Dose Escalation of Stereotactic Radiosurgical Boost for Locally Advanced Esophageal Cancer Not Recruiting

    To study the safety and feasibility of stereotactic radiation dose escalation following neoadjuvant chemotherapy with concurrent conventionally fractionated radiation, by evaluating the acute and late toxicity of treatment.

    Stanford is currently not accepting patients for this trial. For more information, please contact Laurie Ann Columbo, (650) 736 - 0792.

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  • Real-Time kV Imaging vs. Real-Time 3D Patient Surface Tracking for Head & Neck Cancer Not Recruiting

    To determine if a new optical system that can track a patient's movement during treatment can be used to measure motion and allow for motion adjustments in order to decrease the amount of healthy tissue that receives radiation without limiting our ability to cure cancers using radiation.

    Stanford is currently not accepting patients for this trial. For more information, please contact Brian Khong, (650) 725 - 4777.

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  • Real-Time MV/kV Image Guided Radiation Therapy Not Recruiting

    In current radiation therapy, imaging (typically, cone beam CT imaging or two orthogonal X-ray projection imaging) is done for patient setup before radiation dose delivery. Dose delivery typically takes 2 to 5 minutes depending on the delivery technique used for treatment. A tumor target may change its position during the dose delivery process. The goal of this project is develop a real-time imaging strategy to monitor the tumor position during dose delivery and evaluate its potential clinical impact.

    Stanford is currently not accepting patients for this trial. For more information, please contact Lei Xing, 650-498-7896.

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2020-21 Courses


Graduate and Fellowship Programs


All Publications


  • Deep 3D dose analysis for prediction of outcomes after liver stereotactic body radiation therapy Medical Image Computing and Computer Assisted Intervention - MICCAI 2018 Bulat, I., Diego, T. A., Yixuan, Y., Albert, K. C., Daniel, C. T., Lei, X. 2018: 684–92
  • Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine. Gut Bibault, J., Chang, D. T., Xing, L. 2020

    Abstract

    OBJECTIVE: The success of treatment planning relies critically on our ability to predict the potential benefit of a therapy. In colorectal cancer (CRC), several nomograms are available to predict different outcomes based on the use of tumour specific features. Our objective is to provide an accurate and explainable prediction of the risk to die within 10 years after CRC diagnosis, by incorporating the tumour features and the patient medical and demographic information.DESIGN: In the prostate, lung, colorectal and ovarian cancer screening (PLCO) Trial, participants (n=154 900) were randomised to screening with flexible sigmoidoscopy, with a repeat screening at 3 or 5 years, or to usual care. We selected patients who were diagnosed with CRC during the follow-up to train a gradient-boosted model to predict the risk to die within 10 years after CRC diagnosis. Using Shapley values, we determined the 20 most relevant features and provided explanation to prediction.RESULTS: During the follow-up, 2359 patients were diagnosed with CRC. Median follow-up was 16.8 years (14.4-18.9) for mortality. In total, 686 patients (29%) died from CRC during the follow-up. The dataset was randomly split into a training (n=1887) and a testing (n=472) dataset. The area under the receiver operating characteristic was 0.84 (±0.04) and accuracy was 0.83 (±0.04) with a 0.5 classification threshold. The model is available online for research use.CONCLUSIONS: We trained and validated a model with prospective data from a large multicentre cohort of patients. The model has high predictive performances at the individual scale. It could be used to discuss treatment strategies.

    View details for DOI 10.1136/gutjnl-2020-321799

    View details for PubMedID 32887732

  • Second window near-infrared dosimeter (NIR2D) system for radiation dosimetry. Physics in medicine and biology Kim, T. J., Cheng, K., Zhang, H., Liu, S., Skinner, L., Xing, L. 2020; 65 (17): 175013

    Abstract

    Fiber-coupled scintillation dosimeters are a cost-effective alternative to the conventional ion chambers in radiation dosimetry. However, stem effects from optical fibers such as Cerenkov radiation incur significant errors in the readout signal. Here we introduce a second near-infrared window dosimeter, dubbed as NIR2D, that can potentially be used as real-time radiation detector for clinical megavoltage beams. Lanthanide-based rare-earth NaYF4 nano-phosphors doped with both erbium and cerium elements were synthesized, and a compact 3D printed reader device integrated with a photodetector and data acquisition system was designed. The performance of the NIR2D was tested using a pre-clinical orthovoltage radiation source and a clinical megavoltage radiation source. The system was tested for dose linearity (100, 200, 600 MU), dose rate dependency (100, 200, 400, 600 MU min-1), and energy dependency (6, 10, 15 MV). Test results with the clinical linear accelerator demonstrated excellent dose linearity and dose rate independency when exposed to 6 MV linac beams-both data follows a linear trendline with R2 > 0.99. On the other hand, the NIR2D was energy dependent, where the readout dropped by 9% between 6 and 15 MV. For stem effects, we observed a finite Cerenkov contribution of 1%-3% when exposed between 100-600 MU min-1 (6 MV) and 3%-6% when exposed between 5-15 MV (600 MU min-1). While the stem effects were still observable, we expect that enhancing the current optical setup will simultaneously improve the scintillation signal and reduce the stem effects.

    View details for DOI 10.1088/1361-6560/ab9b56

    View details for PubMedID 32869751

  • Automatic Polyp Recognition in Colonoscopy Images Using Deep Learning and Two-Stage Pyramidal Feature Prediction IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING Jia, X., Mai, X., Cui, Y., Yuan, Y., Xing, X., Seo, H., Xing, L., Meng, M. 2020; 17 (3): 1570–84
  • Accelerating quantitative MR imaging with the incorporation of B1 compensation using deep learning. Magnetic resonance imaging Wu, Y., Ma, Y., Du, J., Xing, L. 2020

    Abstract

    Quantitative magnetic resonance imaging (MRI) attracts attention due to its support to quantitative image analysis and data driven medicine. However, the application of quantitative MRI is severely limited by the long data acquisition time required by repetitive image acquisition and measurement of field map. Inspired by recent development of artificial intelligence, we propose a deep learning strategy to accelerate the acquisition of quantitative MRI, where every quantitative T1 map is derived from two highly undersampled variable-contrast images with radiofrequency field inhomogeneity automatically compensated. In a multi-step framework, variable-contrast images are first jointly reconstructed from incoherently undersampled images using convolutional neural networks; then T1 map and B1 map are predicted from reconstructed images employing deep learning. Thus, the acceleration includes undersampling in every input image, a reduction in the number of variable contrast images, as well as a waiver of B1 map measurement. The strategy is validated in T1 mapping of cartilage. Acquired with a consistent imaging protocol, 1224 image sets from 51 subjects are used for the training of the prediction models, and 288 image sets from 12 subjects are used for testing. High degree of acceleration is achieved with image fidelity well maintained. The proposed method can be broadly applied to quantify other tissue properties (e.g. T2, T1rho) as well.

    View details for DOI 10.1016/j.mri.2020.06.011

    View details for PubMedID 32610065

  • Deep learning applications in automatic needle segmentation in ultrasound-guided prostate brachytherapy. Medical physics Wang, F., Xing, L., Bagshaw, H., Buyyounouski, M., Han, B. 2020

    Abstract

    PURPOSE: High-Dose-Rate (HDR) brachytherapy is one of the most effective ways to treat the prostate cancer, which is the second most common cancer in men worldwide. This treatment delivers highly conformal dose through the transperineal needle implants and is guided by a real time ultrasound (US) imaging system. Currently, the brachytherapy needles in the US images are manually segmented by physicists during the treatment, which is time-consuming and error-prone. In this study, we propose a set of deep learning based algorithms to accurately segment the brachytherapy needles and locate the needle tips from the US images.METHODS: Two deep neural networks are developed to address this problem. First, a modified deep U-Net is used to segment the pixels belonging to the brachytherapy needles from the US images. Second, an additional VGG-16 based deep convolutional network is combined with the segmentation network to predict the locations of the needle tips. The networks are trained and evaluated on a clinical US images dataset with labeled needle trajectories collected in our hospital (Institutional Review Board approval (IRB 41755)).RESULTS: The evaluation results show that our method can accurately extract the trajectories of the needles with a resolution of 0.668 mm and 0.319 mm in x and y direction respectively. 95.4% of the x direction and 99.2% of the y direction have error ≤ 2 mm. Moreover, The position resolutions of the tips are 0.721 mm, 0.369 mm and 1.877 mm in x, y and z directions respectively, while 94.2%, 98.3% and 67.5% of the data have error ≤ 2 mm.CONCLUSIONS: This paper proposed a neural network based algorithm to segment the brachytherapy needles from the US images and locate the needle tip. It can be used in the HDR brachytherapy to help improve the efficiency and quality of the treatments.

    View details for DOI 10.1002/mp.14328

    View details for PubMedID 32542758

  • Automated hepatobiliary toxicity prediction after liver stereotactic body radiation therapy with deep learning -based portal vein segmentation NEUROCOMPUTING Ibragimov, B., Toesca, D. S., Chang, D. T., Yuan, Y., Koong, A. C., Xing, L. 2020; 392: 181–88
  • Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state-of-art applications. Medical physics Seo, H., Badiei Khuzani, M., Vasudevan, V., Huang, C., Ren, H., Xiao, R., Jia, X., Xing, L. 2020; 47 (5): e148–e167

    Abstract

    In recent years, significant progress has been made in developing more accurate and efficient machine learning algorithms for segmentation of medical and natural images. In this review article, we highlight the imperative role of machine learning algorithms in enabling efficient and accurate segmentation in the field of medical imaging. We specifically focus on several key studies pertaining to the application of machine learning methods to biomedical image segmentation. We review classical machine learning algorithms such as Markov random fields, k-means clustering, random forest, etc. Although such classical learning models are often less accurate compared to the deep-learning techniques, they are often more sample efficient and have a less complex structure. We also review different deep-learning architectures, such as the artificial neural networks (ANNs), the convolutional neural networks (CNNs), and the recurrent neural networks (RNNs), and present the segmentation results attained by those learning models that were published in the past 3yr. We highlight the successes and limitations of each machine learning paradigm. In addition, we discuss several challenges related to the training of different machine learning models, and we present some heuristics to address those challenges.

    View details for DOI 10.1002/mp.13649

    View details for PubMedID 32418337

  • Electro-thermal therapy: Microsecond duration pulsed electric field tissue ablation with dynamic temperature control algorithms COMPUTERS IN BIOLOGY AND MEDICINE Sano, M. B., Petrella, R. A., Kaufman, J. D., Fesmire, C. C., Xing, L., Gerber, D., Fogle, C. A. 2020; 121: 103807

    Abstract

    Electro-thermal therapy (ETT) is a new cancer treatment modality which combines the use of high voltage pulsed electric fields, dynamic energy delivery rates, and closed loop thermal control algorithms to rapidly and reproducibly create focal ablations. This study examines the ablative potential and profile of pulsed electric field treatments delivered in conjunction with precise temperature control algorithms. An ex vivo perfused liver model was utilized to demonstrate the capability of 5000 V 2 μs duration bipolar electrical pulses and dynamic temperature control algorithms to produce ablations. Using a three applicator array, 4 cm ablation zones were created in under 27 min. In this configuration, the algorithms were able to rapidly achieve and maintain temperatures of 80 °C at the tissue-electrode interface. A simplified single applicator and grounding pad approach was used to correlate the measured ablation zones to electric field isocontours in order to determine lethal electric field thresholds of 708 V/cm and 867 V/cm for 45 °C and 60 °C treatments, respectively. These results establish ETT as a viable method for hepatic tumor treatment with ablation profiles equivalent to other energy based techniques. The single applicator and multi-applicator approaches demonstrated may enable the treatment of complex tumor geometries. The flexibility of ETT temperature control yields a malleable intervention which gives clinicians robust control over the ablation modality, treatment time, and safety profile.

    View details for DOI 10.1016/j.compbiomed.2020.103807

    View details for Web of Science ID 000542187300020

    View details for PubMedID 32568680

  • Temperature Dependence of High Frequency Irreversible Electroporation Evaluated in a 3D Tumor Model ANNALS OF BIOMEDICAL ENGINEERING Fesmire, C. C., Petrella, R. A., Fogle, C. A., Gerber, D. A., Xing, L., Sano, M. B. 2020; 48 (8): 2233–46

    Abstract

    Electroporation is a bioelectric phenomenon used to deliver target molecules into cells in vitro and irreversible electroporation (IRE) is an emerging cancer therapy used to treat inoperable tumors in situ. These phenomena are generally considered to be non-thermal in nature. In this study, a 3D tumor model was used to investigate the correlation between temperature and the effectiveness of standard clinical IRE and high frequency (H-FIRE) protocols. It was found for human glioblastoma cells that in the range of 2 to 37 °C the H-FIRE lethal electric field threshold value, which describes the minimum electric field to cause cell death, is highly dependent on temperature. Increasing the initial temperature from 2 to 37 °C resulted in a significant decrease in lethal electric field threshold from 1168 to 507 V/cm and a 139% increase in ablation size for H-FIRE burst treatments. Standard clinical protocol IRE treatments resulted in a decrease in lethal threshold from 485 to 453 V/cm and a 7% increase in ablation size over the same temperature range. Similar results were found for pancreatic cancer cells which indicate that tissue temperature may be a significant factor affecting H-FIRE ablation size and treatment planning in vivo while lower temperatures may be useful in maintaining cell viability for transfection applications.

    View details for DOI 10.1007/s10439-019-02423-w

    View details for Web of Science ID 000532898300001

    View details for PubMedID 32409902

  • Screening for chronic obstructive pulmonary disease with artificial intelligence LANCET DIGITAL HEALTH Bibault, J., Xing, L. 2020; 2 (5): E216–E217
  • Modified U-Net (mU-Net) With Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images IEEE TRANSACTIONS ON MEDICAL IMAGING Seo, H., Huang, C., Bassenne, M., Xiao, R., Xing, L. 2020; 39 (5): 1316–25

    Abstract

    Segmentation of livers and liver tumors is one of the most important steps in radiation therapy of hepatocellular carcinoma. The segmentation task is often done manually, making it tedious, labor intensive, and subject to intra-/inter- operator variations. While various algorithms for delineating organ-at-risks (OARs) and tumor targets have been proposed, automatic segmentation of livers and liver tumors remains intractable due to their low tissue contrast with respect to the surrounding organs and their deformable shape in CT images. The U-Net has gained increasing popularity recently for image analysis tasks and has shown promising results. Conventional U-Net architectures, however, suffer from three major drawbacks. First, skip connections allow for the duplicated transfer of low resolution information in feature maps to improve efficiency in learning, but this often leads to blurring of extracted image features. Secondly, high level features extracted by the network often do not contain enough high resolution edge information of the input, leading to greater uncertainty where high resolution edge dominantly affects the network's decisions such as liver and liver-tumor segmentation. Thirdly, it is generally difficult to optimize the number of pooling operations in order to extract high level global features, since the number of pooling operations used depends on the object size. To cope with these problems, we added a residual path with deconvolution and activation operations to the skip connection of the U-Net to avoid duplication of low resolution information of features. In the case of small object inputs, features in the skip connection are not incorporated with features in the residual path. Furthermore, the proposed architecture has additional convolution layers in the skip connection in order to extract high level global features of small object inputs as well as high level features of high resolution edge information of large object inputs. Efficacy of the modified U-Net (mU-Net) was demonstrated using the public dataset of Liver tumor segmentation (LiTS) challenge 2017. For liver-tumor segmentation, Dice similarity coefficient (DSC) of 89.72 %, volume of error (VOE) of 21.93 %, and relative volume difference (RVD) of - 0.49 % were obtained. For liver segmentation, DSC of 98.51 %, VOE of 3.07 %, and RVD of 0.26 % were calculated. For the public 3D Image Reconstruction for Comparison of Algorithm Database (3Dircadb), DSCs were 96.01 % for the liver and 68.14 % for liver-tumor segmentations, respectively. The proposed mU-Net outperformed existing state-of-art networks.

    View details for DOI 10.1109/TMI.2019.2948320

    View details for Web of Science ID 000532214700003

    View details for PubMedID 31634827

  • Densely Connected Neural Network With Unbalanced Discriminant and Category Sensitive Constraints for Polyp Recognition IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING Yuan, Y., Qin, W., Ibragimov, B., Zhang, G., Han, B., Meng, M., Xing, L. 2020; 17 (2): 574–83
  • REAL-TIME AUGMENTED BLADDER TUMOR DETECTION WITH DEEP LEARNING Chang, T., Shkolyar, E., Jia, X., Lee, T., Mach, K., Conti, S., Xing, L., Liao, J. LIPPINCOTT WILLIAMS & WILKINS. 2020: E1110
  • Hybrid Adversarial-Discriminative Network for Leukocyte Classification in Leukemia. Medical physics Zhang, C., Wu, S., Lu, Z., Shen, Y., Wang, J., Huang, P., Lou, J., Liu, C., Xing, L., Zhang, J., Xue, J., Li, D. 2020

    Abstract

    PURPOSE: Leukemia is a lethal disease that is harmful to bone marrow and overall blood health. The classification of white blood cell images is crucial for leukemia diagnosis. The purpose of this study is to classify white blood cells by extracting discriminative information from cell segmentation and combining it with the fine-grained features. We propose a hybrid adversarial residual network with support vector machine (SVM), which utilizes the extracted features to improve the classification accuracy for human peripheral white cells.METHODS: Firstly, we segment the cell and nucleus by utilizing an adversarial residual network, which contains a segmentation network and a discriminator network. To extract features that can handle the inter-class consistency problem effectively, we introduce the adversarial residual network. Then, we utilize convolutional neural network (CNN) features and histogram of oriented gradient (HOG) features, which can extract discriminative features from images of segmented cell nuclei. To utilize the representative features fully, a discriminative network is introduced to deal with neighboring information at different scales. Finally, we combine the vectors of HOG features with those of CNN features and feed them into a linear SVM to classify white blood cells into six types.RESULTS: We used three methods to evaluate the effect of leukocyte classification based on 5000 leukocyte images acquired from a local hospital. The first approach is to use the CNN features as the input of SVM to classify leukocytes, which achieved 94.23% specificity, 95.10% sensitivity, and 94.41% accuracy. The use of the HOG features for SVM achieved 83.50% specificity, 87.50% sensitivity, and 85.00% accuracy. The use of combined CNN and HOG features achieved 94.57% specificity, 96.11% sensitivity, and 95.93% accuracy.CONCLUSIONS: We propose a novel hybrid adversarial-discriminative network for the classification of microscopic leukocyte images. It improves the accuracy of cell classification, reduces the difficulty and time pressure of doctors' work, and economizes the valuable time of doctors in daily clinical diagnosis.

    View details for DOI 10.1002/mp.14144

    View details for PubMedID 32180243

  • Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI MAGNETIC RESONANCE IMAGING Wu, Y., Ma, Y., Capaldi, D., Liu, J., Zhao, W., Du, J., Xing, L. 2020; 66: 93–103
  • Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch Unet. Medical physics Chen, Y., Xing, L., Yu, L., Bagshaw, H. P., Buyyounouski, M. K., Han, B. 2020

    Abstract

    Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmentation in multiparametric magnetic resonance imaging (mpMRI) images contributing to the clinical practice.mpMRI images from 136 patient cases were collected from our institution, and all these cases contained suspicious lesions with Prostate Imaging Reporting and Data System (PI-RADS) score ≥ 4. The contours of the lesion and prostate were manually created on axial T2-weighted (T2W), apparent diffusion coefficient (ADC) and high b-value diffusion-weighted imaging (DWI) images to provide the ground truth data. Then a multiple branch UNet (MB-UNet) was proposed for the segmentation of indistinct target in multi-modality MRI images. An encoder module was designed with three branches for the three MRI modalities separately, to fully extract the high-level features provided by different MRI modalities; an input module was added by using three sub-branches for three consecutive image slices, to consider the contour consistency among different image slices; deep supervision strategy was also integrated into the network to speed up the convergency of the network and improve the performance. The probability maps of the background, normal prostate and lesion were output by the network to generate the segmentation of the lesion, and the performance was evaluated using the Dice similarity coefficient (DSC) as the main metric.A total of 162 lesions were contoured on 652 image slices, with 119 lesions in the peripheral zone, 38 in the transition zone, 4 in the central zone and 1 in the anterior fibromuscular stroma. All prostates were also contoured on 1,264 image slices. As for the segmentation of lesions in the testing set, MB-UNet achieved a per case DSC of 0.6333, specificity of 0.9993, sensitivity of 0.7056; and global DSC of 0.7205, specificity of 0.9993, sensitivity of 0.7409. All the three deep learning strategies adopted in this study contributed to the performance promotion of the MB-UNet. And missing the DWI modality would degrade the segmentation performance more markedly compared with the other two modalities.A deep learning-based approach with proposed MB-UNet was developed to automatically segment suspicious lesions in mpMRI images. This study makes it feasible to adopt boosting intraprostatic lesions in clinical practice to achieve better outcomes.

    View details for DOI 10.1002/mp.14517

    View details for PubMedID 33012016

  • High-Frequency Irreversible Electroporation Using 5,000-V Waveforms to Create Reproducible 2-and 4-cm Ablation Zones - A Laboratory Investigation Using Mechanically Perfused Liver JOURNAL OF VASCULAR AND INTERVENTIONAL RADIOLOGY Kaufman, J. D., Fesmire, C. C., Petrella, R. A., Fogle, C. A., Xing, L., Gerber, D., Sano, M. B. 2020; 31 (1): 162–68

    Abstract

    To investigate if high-frequency irreversible electroporation (H-FIRE) treatments can be delivered at higher voltages and with greater energy delivery rates than currently implemented in clinical irreversible electroporation protocols.Treatments using 3,000 V and 5,000 V were administered to mechanically perfused ex vivo porcine liver via a single applicator and grounding pad (A+GP) as well as a 4-applicator array (4AA). Integrated energized times (IET) 0.01-0.08 seconds and energy delivery rates 25-300 μs/s were investigated. Organs were preserved at 4°C for 10-15 hours before sectioning and gross analysis using a metabolic stain to identify the size and shape of ablation zones.A+GP ablations measured between 1.6 cm and 2.2 cm, which did not increase when IET was increased from 0.02 seconds to 0.08 seconds (P > .055; range, 1.9-2.1 cm). Changes in tissue color and texture consistent with thermal damage were observed for treatments with energy delivery rates 50-300 μs/s, but not for treatments delivered at 25 μs/s. Use of the 4AA with a 3-cm applicator spacing resulted in ablations measuring 4.4-4.9 cm with energy delivery times of 7-80 minutes.H-FIRE treatments can rapidly and reproducibly create 2-cm ablations using an A+GP configuration. Treatments without thermal injury were produced at the expense of extended treatment times. More rapid treatments resulted in ablations with varying degrees of thermal injury within the H-FIRE ablation zone. Production of 4-cm ablations is possible using a 4AA.

    View details for DOI 10.1016/j.jvir.2019.05.009

    View details for Web of Science ID 000507428900025

    View details for PubMedID 31530492

  • Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Zhao, W., Lv, T., Lee, R., Chen, Y., Xing, L. 2020; 25: 139–48

    Abstract

    Computed tomographic (CT) is a fundamental imaging modality to generate cross-sectional views of internal anatomy in a living subject or interrogate material composition of an object, and it has been routinely used in clinical applications and nondestructive testing. In a standard CT image, pixels having the same Hounsfield Units (HU) can correspond to different materials, and it is therefore challenging to differentiate and quantify materials. Dual-energy CT (DECT) is desirable to differentiate multiple materials, but the costly DECT scanners are not widely available as single-energy CT (SECT) scanners. Recent advancement in deep learning provides an enabling tool to map images between different modalities with incorporated prior knowledge. Here we develop a deep learning approach to perform DECT imaging by using the standard SECT data. The end point of the approach is a model capable of providing the high-energy CT image for a given input low-energy CT image. The feasibility of the deep learning-based DECT imaging method using a SECT data is demonstrated using contrast-enhanced DECT images and evaluated using clinical relevant indexes. This work opens new opportunities for numerous DECT clinical applications with a standard SECT data and may enable significantly simplified hardware design, scanning dose and image cost reduction for future DECT systems.

    View details for PubMedID 31797593

  • Deriving new soft tissue contrasts from conventional MR images using deep learning. Magnetic resonance imaging Wu, Y., Li, D., Xing, L., Gold, G. 2020

    Abstract

    Versatile soft tissue contrast in magnetic resonance imaging is a unique advantage of the imaging modality. However, the versatility is not fully exploited. In this study, we propose a deep learning-based strategy to derive more soft tissue contrasts from conventional MR images obtained in standard clinical MRI. Two types of experiments are performed. First, MR images corresponding to different pulse sequences are predicted from one or more images already acquired. As an example, we predict T1ρ weighted knee image from T2 weighted image and/or T1 weighted image. Furthermore, we estimate images corresponding to alternative imaging parameter values. In a representative case, variable flip angle images are predicted from a single T1 weighted image, whose accuracy is further validated in quantitative T1 map subsequently derived. To accomplish these tasks, images are retrospectively collected from 56 subjects, and self-attention convolutional neural network models are trained using 1104 knee images from 46 subjects and tested using 240 images from 10 other subjects. High accuracy has been achieved in resultant qualitative images as well as quantitative T1 maps. The proposed deep learning method can be broadly applied to obtain more versatile soft tissue contrasts without additional scans or used to normalize MR data that were inconsistently acquired for quantitative analysis.

    View details for DOI 10.1016/j.mri.2020.09.014

    View details for PubMedID 32956805

  • Deep learning-enhanced LED-based photoacoustic imaging Singh, M., Sivasubramanian, K., Sato, N., Ichihashi, F., Sankai, Y., Xing, L., Oraevsky, A. A., Wang, L. V. SPIE-INT SOC OPTICAL ENGINEERING. 2020

    View details for DOI 10.1117/12.2545654

    View details for Web of Science ID 000558347500030

  • Food based contrast agents for photoacoustic imaging Sivasubramanian, K., Kim, J., Cheng, K., Kim, C., Xing, L., Oraevsky, A. A., Wang, L. V. SPIE-INT SOC OPTICAL ENGINEERING. 2020

    View details for DOI 10.1117/12.2547404

    View details for Web of Science ID 000558347500034

  • Fast spot-scanning proton dose calculation method with uncertainty quantification using a three-dimensional convolutional neural network. Physics in medicine and biology Nomura, Y., Wang, J., Shirato, H., Shimizu, S., Xing, L. 2020

    Abstract

    This study proposes a near-real-time spot-scanning proton dose calculation method with probabilistic uncertainty estimation using a three-dimensional convolutional neural network (3D-CNN).CT images and clinical target volume contours of 215 head and neck cancer patients were collected from a public database. 1,484 and 488 plans were extracted for training and testing the 3D-CNN model, respectively. Spot beam data and single-field uniform dose (SFUD) labels were calculated for each plan using an open-source dose calculation toolkit. Variable spot data were converted into a fixed-size volume hereby called a "peak map" (PM). 300 epochs of end-to-end training was implemented using sets of stopping power ratio and PM as input. Moreover, transfer learning techniques were used to adjust the trained model to SFUD doses calculated with different beam parameters and calculation algorithm using only 7.95% of training data used for the base model. Finally, accuracy of the 3D-CNN-calculated doses and model uncertainty was reviewed with several evaluation metrics.The 3D-CNN model calculates 3D proton dose distributions accurately with a mean absolute error of 0.778 cGyE. The predicted uncertainty is correlated with dose errors at high contrast edges. Averaged Sørensen-Dice similarity coefficients between binarized outputs and ground truths are mostly above 80%. Once the 3D-CNN model was well-trained, it can be efficiently fine-tuned for different proton doses by transfer learning techniques. Inference time for calculating one dose distribution is around 0.8 seconds for a plan using 1,500 spot beams with a consumer grade GPU.A novel spot-scanning proton dose calculation method using 3D-CNN was developed. The 3D-CNN model is able to calculate 3D doses and uncertainty with any SFUD spot data and beam irradiation angles. Our proposed method should be readily extendable to other setups and plans and be useful for dose verification, image-guided proton therapy, or other applications.

    View details for DOI 10.1088/1361-6560/aba164

    View details for PubMedID 32604078

  • Verification of the machine delivery parameters of treatment plan via deep learning. Physics in medicine and biology Fan, J., Xing, L., Ma, M., Hu, W., Yang, Y. 2020

    Abstract

    We developed a generative adversarial network (GAN)-based deep learning approach to estimate the multileaf collimator (MLC) aperture and corresponding monitor units (MUs) from a given three dimensional (3D) dose distribution. The proposed design of adversari-al network, which integrates a residual block into pix2pix framework, jointly trains a "U-Net"-like architecture as generator and a convolutional "PatchGAN" classifier as dis-criminator. 199 patients, including nasopharyngeal, lung and rectum, treated with intensi-ty modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) tech-niques were utilized to train the network. Additional 47 patients were used to test the prediction accuracy of the proposed deep learning model. The Dice similarity coefficient (DSC) was calculated to evaluate the similarity between the MLC aperture shapes ob-tained from the treatment planning system (TPS) and the deep learning prediction. The average and standard deviation of the bias between the TPS generated MUs and predicted MUs were calculated to evaluate the MU prediction accuracy. Additionally, the differences between TPS and deep learning-predicted MLC leaf positions were compared. The average and standard deviation of DSC was 0.94 ± 0.043 for 47 testing patients. The average deviation of predicted MUs from the planned MUs normalized to each beam or arc was within 2% for all the testing patients. The average deviation of the predicted MLC leaf positions was around one pixel for all the testing patients. Our results demonstrated the feasibility and reliability of the proposed approach. The proposed technique has strong potential to improve the efficiency and accuracy of patient plan quality assurance (QA) process.

    View details for DOI 10.1088/1361-6560/aba165

    View details for PubMedID 32604082

  • A Deep Learning Framework for Prostate Localization in Cone Beam CT Guided Radiotherapy. Medical physics Liang, X., Zhao, W., Hristov, D. H., Buyyounouski, M. K., Hancock, S. L., Bagshaw, H., Zhang, Q., Xie, Y., Xing, L. 2020

    Abstract

    To develop a deep learning-based model for prostate planning target volume (PTV) localization on cone-beam CT (CBCT) to improve the workflow of CBCT-guided patient setup.A two-step task-based residual network (T2 RN) is proposed to automatically identify inherent landmarks in prostate PTV. The input to the T2 RN is the pre-treatment CBCT images of the patient, and the output is the deep learning-identified landmarks in the PTV. To ensure robust PTV localization, the T2 RN model is trained by using over thousand sets of CT images with labeled landmarks, each of the CTs corresponds to a different scenario of patient position and/or anatomy distribution generated by synthetically changing the planning CT (pCT) image. The changes, including translation, rotation, and deformation, represent vast possible clinical situations of anatomy variations during a course of radiation therapy (RT). The trained patient-specific T2 RN model is tested by using 240 CBCTs from six patients. The testing CBCTs consists of 120 original CBCTs and 120 synthetic CBCTs. The synthetic CBCTs are generated by applying rotation/translation transformations to each of the original CBCT.The systematic/random setup errors between the model prediction and the reference are found to be less than 0.25/2.46 mm and 0.14/1.41° in translation and rotation dimensions, respectively. Pearson's correlation coefficient between model prediction and the reference is higher than 0.94 in translation and rotation dimensions. The Bland-Altman plots show good agreement between the two techniques.A novel T2 RN deep learning technique is established to localize the prostate PTV for RT patient setup. Our results show that highly accurate marker-less prostate setup is achievable by leveraging the state-of-the-art deep learning strategy.

    View details for DOI 10.1002/mp.14355

    View details for PubMedID 32583418

  • High-speed X-ray-induced luminescence computed tomography. Journal of biophotonics Dai, X., Cheng, K., Zhao, W., Xing, L. 2020

    Abstract

    X-ray-induced luminescence computed tomography (XLCT) is an emerging molecular imaging. Challenges in improving spatial resolution and reducing the scan time in a whole-body field of view (FOV) still remain for practical in vivo applications. In this study, we present a novel XLCT technique capable of obtaining three-dimensional (3D) images from a single snapshot. Specifically, a customed two-planar-mirror component is integrated into a cone beam XLCT imaging system to obtain multiple optical views of an object simultaneously. Furthermore, a compressive sensing based algorithm is adopted to improve the efficiency of 3D XLCT image reconstruction. Numerical simulations and experiments were conducted to validate the single snapshot X-ray-induced luminescence computed tomography (SS-XLCT). The results show that the 3D distribution of the nanophosphor targets can be visualized much faster than conventional cone beam XLCT imaging method that was used in our comparisons while maintaining comparable spatial resolution as in conventional XLCT imaging. SS-XLCT has the potential to harness the power of XLCT for rapid whole-body in vivo molecular imaging of small animals. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1002/jbio.202000066

    View details for PubMedID 32445254

  • Deep learning for identification of critical regions associated with toxicities after liver stereotactic body radiation therapy. Medical physics Ibragimov, B., Toesca, D. A., Chang, D. T., Yuan, Y., Koong, A. C., Xing, L., Vogelius, I. R. 2020

    Abstract

    Radiation therapy (RT) is prescribed for curative and palliative treatment for around 50% of patients with solid tumors. Radiation-induced toxicities of healthy organs accompany many RTs and represent one of the main limiting factors during dose delivery. The existing RT planning solutions generally discard spatial dose distribution information and lose the ability to recognize radiosensitive regions of healthy organs potentially linked to toxicity manifestation. This study proposes a universal deep learning-based algorithm for recognitions of consistent dose patterns and generation of toxicity risk maps for the abdominal area.We investigated whether convolutional neural networks (CNNs) can automatically associate abdominal computed tomography (CT) images and RT dose plans with post-RT toxicities without being provided segmentation of abdominal organs. The CNNs were also applied to study RT plans, where doses at specific anatomical regions were reduced/increased, with the aim to pinpoint critical regions sparing of which significantly reduces toxicity risks. The obtained risk maps were computed for individual anatomical regions inside the liver and statistically compared to the existing clinical studies.A database of 122 liver stereotactic body RT (SBRT) executed at Stanford Hospital from July 2004 and November 2015 was assembled. All patients treated for primary liver cancer, mainly hepatocellular carcinoma and cholangiocarcinoma, with complete follow-ups were extracted from the database. The SBRT treatment doses ranged from 26 to 50 Gy delivered in 1-5 fractions for primary liver cancer. The patients were followed up for 1-68 months depending on the survival time. The CNNs were trained to recognize acute and late grade 3+ biliary stricture/obstruction, hepatic failure or decompensation, hepatobiliary infection, liver function test (LFT) elevation or/and portal vein thrombosis, named for convenience hepatobiliary (HB) toxicities. The toxicity prediction accuracy was of 0.73 measured in terms of the area under the receiving operator characteristic curve. Significantly higher risk scores (p < 0.05) of HB toxicity manifestation were associated with irradiation for the hepatobiliary tract in comparison to the risk scores for liver segments I-VIII and portal vein. This observation is in strong agreement with anatomical and clinical expectations.In this work, we proposed and validated a universal deep learning-based solution for the identification of radiosensitive anatomical regions. Without any prior anatomical knowledge, CNNs automatically recognized the importance of hepatobiliary tract sparing during liver SBRT.

    View details for DOI 10.1002/mp.14235

    View details for PubMedID 32406531

  • Restarted primal-dual Newton conjugate gradient method for enhanced spatial resolution of reconstructed cone-beam X-ray luminescence computed tomography images. Physics in medicine and biology Gao, P., Cheng, K., Schueler, E., Jia, M., Zhao, W., Xing, L. 2020

    Abstract

    Cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed as a promising imaging tool, which enables three-dimensional imaging of the distribution of nanophosphors (NPs) in small animals. However, the reconstruction performance is usually unsatisfactory in terms of spatial resolution due to the ill-posedness of CB-XLCT inverse problem. To alleviate this problem and to achieve high spatial resolution, a reconstruction method consisting of inner and outer iterations based on a restarted strategy is proposed. In this method, the primal-dual Newton Conjugate Gradient method (pdNCG) is adopted in the inner iterations to get fast reconstruction, which is used for resetting the permission region and increase the convergence speed of the outer iteration. To assess the performance of the method, numerical simulation and physical phantom experiments were conducted with a CB-XLCT system. The results demonstrate that compared with conventional reconstruction methods, the proposed re-pdNCG method can accurately and efficiently resolve the adjacent NPs with the least relative error.

    View details for DOI 10.1088/1361-6560/ab87fb

    View details for PubMedID 32268318

  • Wireless Capsule Endoscopy: A New Tool for Cancer Screening in the Colon With Deep-Learning-Based Polyp Recognition PROCEEDINGS OF THE IEEE Jia, X., Xing, X., Yuan, Y., Xing, L., Meng, M. 2020; 108 (1): 178–97
  • Beam data modeling of linear accelerators (linacs) through machine learning and its potential applications in fast and robust linac commissioning and quality assurance. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Zhao, W., Patil, I., Han, B., Yang, Y., Xing, L., Schüler, E. 2020

    Abstract

    To propose a novel machine learning-based method for reliable and accurate modeling of linac beam data applicable to the processes of linac commissioning and QA.We hypothesize that the beam data is a function of inherent linac features and percentage depth doses (PDDs) and profiles of different field sizes are correlated with each other. The correlation is formulated as a multivariable regression problem using a machine learning framework. Varian TrueBeam beam data sets (n=43) acquired from multiple institutions were used to evaluate the framework. The data sets included PDDs and profiles across different energies and field sizes. A multivariate regression model was trained for prediction of beam specific PDDs and profiles of different field sizes using a 10x10cm2 field as input.Predictions of PDDs were achieved with a mean absolute percent relative error (%RE) of 0.19-0.35% across the different beam energies investigated. The maximum mean absolute %RE was 0.93%. For profile prediction, the mean absolute %RE was 0.66-0.93% with a maximum absolute %RE of 3.76%. The largest uncertainties in the PDD and profile predictions were found at the build-up region and at the field penumbra, respectively. The prediction accuracy increased with the number of training sets up to around 20 training sets.Through this novel machine learning-based method we have shown accurate and reproducible generation of beam data for linac commissioning for routine radiation therapy. This method has the potential to simplify the linac commissioning procedure, save time and manpower while increasing the accuracy of the commissioning process.

    View details for DOI 10.1016/j.radonc.2020.09.057

    View details for PubMedID 33039427

  • Technical Note: Evaluation of Audiovisual Biofeedback Smartphone Application for Respiratory Monitoring in Radiation Oncology. Medical physics Capaldi, D. P., Nano, T. F., Zhang, H., Skinner, L. B., Xing, L. 2020

    Abstract

    Radiation dose delivered to targets located near the upper abdomen or thorax are significantly affected by respiratory motion, necessitating large margins, limiting dose escalation. Surrogate motion management devices, such as the Real-time Position Management (RPM™) system (Varian Medical Systems, Palo Alto, CA), are commonly used to improve normal tissue sparing. Alternative to current solutions, we have developed and evaluated the feasibility of a real-time position management system that leverages the motion data from the onboard hardware of Apple iOS devices to provide patients with visual coaching with the potential to improve the reproducibility of breathing as well as improve patient compliance and reduce treatment delivery time.The iOS application, coined the Instant Respiratory Feedback (IRF) system, was developed in Swift (Apple Inc., Cupertino, CA) using the Core-Motion library and implemented on an Apple iPhone® devices. Operation requires an iPhone®, a 3D printed arm, and a radiolucent projector screen system for feedback. Direct comparison between IRF, which leverages sensor fusion data from the iPhone®, and RPM™, an optical based system, was performed on multiple respiratory motion phantoms and volunteers. The IRF system and RPM™ camera tracking marker were placed on the same location allowing for simultaneous data acquisition. The IRF surrogate measurement of displacement was compared to the signal trace acquired using RPM™ with univariate linear regressions and Bland-Altman analysis.Periodic motion shows excellent agreement between both systems, and subject motion shows good agreement during regular and irregular breathing motion. Comparison of IRF and RPM™ show very similar signal traces that were significantly related across all phantoms, including those motion with different amplitude and frequency, and subjects' waveforms (all r>0.9, p<0.0001). We demonstrate the feasibility of four-dimensional cone beam computed tomography reconstruction using IRF can acquire dynamic phantom images with similar image quality as RPM™.Feasibility of an iOS application to provide real-time respiratory motion is demonstrated. This system generated comparable signal traces to a commercially available system and offers an alternative method to monitor respiratory motion.

    View details for DOI 10.1002/mp.14484

    View details for PubMedID 32969075

  • Technical Note: Machine learning approaches for range and dose verification in proton therapy using proton-induced positron emitters MEDICAL PHYSICS Li, Z., Wang, Y., Yu, Y., Fan, K., Xing, L., Peng, H. 2019; 46 (12): 5748–57

    Abstract

    Online proton range/dose verification based on measurements of proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between the dose distribution and the activity distribution of positron emitters in addition to the presence of noise, machine learning approaches were proposed to establish their relationship.Simulations were carried out with a spot-scanning proton system using GATE-8.0 and Geant4-10.3 toolkit with a computed tomography (CT)-based patient phantom. The one-dimensional (1D) distributions of positron emitters and radiation dose were obtained. A feedforward neural network classification model comprising two hidden layers, was developed to estimate whether the range is within a preset threshold. A recurrent neural network (RNN) regression model comprising three layers and ten neurons in each hidden layer was developed to estimate dose distribution. The performance was quantitatively studied in terms of mean squared error (MSE) and mean absolute error (MAE) under different signal-to-noise ratio (SNR) values.The feasibility of proton range and dose verification using the proposed neural network framework was demonstrated. The feedforward NN model achieves high classification accuracy close to 100% for individual classes without bias. The RNN model is able to accurately predict the 1D dose distribution for different energies and irradiation positions. When the SNR of the input activity profiles is above 4, the framework is able to predict with an MAE of ~0.60 mm and an MSE of ~0.066. Moreover, the model demonstrates a good capability of generalization.The RNN model is found to be effective in identifying the relationship between the distributions of dose and positron emitters. The machine learning-based framework and RNN models may be a useful tool to allow for accurate online range and dose verification based on proton-induced positron emitters.

    View details for DOI 10.1002/mp.13827

    View details for Web of Science ID 000516580200040

    View details for PubMedID 31529506

  • Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning. Nature biomedical engineering Shen, L., Zhao, W., Xing, L. 2019

    Abstract

    Tomographic imaging using penetrating waves generates cross-sectional views of the internal anatomy of a living subject. For artefact-free volumetric imaging, projection views from a large number of angular positions are required. Here we show that a deep-learning model trained to map projection radiographs of a patient to the corresponding 3D anatomy can subsequently generate volumetric tomographic X-ray images of the patient from a single projection view. We demonstrate the feasibility of the approach with upper-abdomen, lung, and head-and-neck computed tomography scans from three patients. Volumetric reconstruction via deep learning could be useful in image-guided interventional procedures such as radiation therapy and needle biopsy, and might help simplify the hardware of tomographic imaging systems.

    View details for DOI 10.1038/s41551-019-0466-4

    View details for PubMedID 31659306

  • X-ray-induced shortwave infrared luminescence computed tomography OPTICS LETTERS Dai, X., Cheng, K., Zhao, W., Xing, L. 2019; 44 (19): 4769–72

    Abstract

    X-ray luminescence computed tomography (XLCT) based on x-ray-excitable nanophosphors has been proposed as a new modality for molecular imaging. The technique has two main advantages compared to other modalities. First, autofluorescence, which is problematic for fluorescence imaging, can be substantially reduced. Second, deep-tissue in vivo imaging with high optical contrast and spatial resolution becomes achievable. Here, we extend the novel XLCT modality from the visible or infrared region to a shortwave infrared wavelength by developing an x-ray-induced shortwave infrared luminescence computed tomography (SWIR-XLCT). For this application, rare-earth nanophosphors (RENPs) were synthesized as core/shell structures consisting of a Ho-doped NaYbF4 core surrounded by a NaYF4 shell that emit light efficiently in the shortwave infrared spectral region under x-ray excitation. Through numerical simulations and phantom experiments, we showed the feasibility of SWIR-XLCT and demonstrated its potential for x-ray luminescence imaging with high spatial resolution and deep depth.

    View details for DOI 10.1364/OL.44.004769

    View details for Web of Science ID 000488503500037

    View details for PubMedID 31568438

  • Task Group 174 Report: Utilization of [F-18]Fluorodeoxyglucose Positron Emission Tomography ([F-18]FDG-PET) in Radiation Therapy MEDICAL PHYSICS Das, S. K., McGurk, R., Miften, M., Mutic, S., Bowsher, J., Bayouth, J., Erdi, Y., Mawlawi, O., Boellaard, R., Bowen, S. R., Xing, L., Bradley, J., Schoder, H., Yin, F., Sullivan, D. C., Kinahan, P. 2019; 46 (10): E706–E725

    Abstract

    The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is 18 F-fluorodeoxyglucose ([18 F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [18 F]FDG-PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [18 F]FDG-PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [18 F]FDG-PET for RT.

    View details for DOI 10.1002/mp.13676

    View details for Web of Science ID 000485848700001

    View details for PubMedID 31230358

  • In Vivo Translation of the CIRPI System: Revealing Molecular Pathology of Rabbit Aortic Atherosclerotic Plaques JOURNAL OF NUCLEAR MEDICINE Zaman, R. T., Yousefi, S., Chibana, H., Ikeno, F., Long, S. R., Gambhir, S. S., Chin, F. T., McConnell, M. V., Xing, L., Yeung, A. 2019; 60 (9): 1308–16
  • Range and dose verification in proton therapy using proton-induced positron emitters and recurrent neural networks (RNNs) PHYSICS IN MEDICINE AND BIOLOGY Liu, C., Li, Z., Hu, W., Xing, L., Peng, H. 2019; 64 (17): 175009

    Abstract

    Online proton range/dose verification based on measurements of proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between the dose distribution and the activity distribution of positron emitters, we aim to establish their relationship using recurrent neural network models (LSTM, BiLSTM, GRU, BiGRU and Seq2seq). Simulations were carried out with a spot-scanning proton system using Geant4-10.3 toolkit and a CT-based patient phantom. The 1D distributions of positron emitters and radiation dose were obtained. Training data were modeled for different beam energy, irradiation positions and counting statistics. The prediction accuracy of range and dose were quantitatively studied. The impact of including anatomical information (HU values in CT images) on the prediction performance was investigated. The BiGRU demonstrates the most stable and accurate performance with good capability of generalization, especially with the inclusion of anatomical information. When the signal-to-noise ratio (SNR) of the 1D activity profiles is about 3, the range accuracy can be within 0.5 mm and the dose accuracy close to the peak region is  <5% (relative uncertainty between prediction and raw input for all datasets). The feasibility of proton range and dose verification using the RNN-based framework was demonstrated. The RNN-based framework promises to provide a reliable and effective way for online monitoring, quality assurance and ultimately allows for adaptive proton therapy.

    View details for DOI 10.1088/1361-6560/ab3564

    View details for Web of Science ID 000484508700002

    View details for PubMedID 31342940

  • Potential of Gd-EOB-DTPA as an imaging biomarker for liver injury estimation after radiation therapy HEPATOBILIARY & PANCREATIC DISEASES INTERNATIONAL Sun, X., Jiang, X., Kuang, Y., Xing, L., Bu, L., Yuan, S., Yu, J., Zheng, S. 2019; 18 (4): 354–59

    Abstract

    Hepatic radiation injury severely restricts irradiation treatment for liver carcinoma. The purpose of this study was to investigate the clinical application of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI (EOB-MRI) in the assessment of liver function after external radiation therapy and to determine the relationship between focal liver reaction (FLR) and liver function.A total of 47 patients with liver malignancies who underwent external beam radiation therapy were enrolled. EOB-MRI was performed on each patient at approximately one month post-radiotherapy. The hepatobiliary (HPB) phase images from EOB-MRI were fused with the planning CT images, and the isodose lines from the patients' treatment plans were overlaid onto the fused images. The correlation of the EOB-MR image intensity distribution with the isodose lines was studied. We also compared liver function in patients between pre-treatment and post-treatment.Decreased uptake of Gd-EOB-DTPA, which was manifested by well-demarcated focal hypointensity of the liver parenchyma or FLR to high-dose radiation, was observed in the irradiated areas of 38 patients. The radiotherapy isodose line of decreased uptake area of Gd-EOB-DTPA was 30-46 Gy. The median corresponding dose curve of FLR was 34.4 Gy. Nine patients showed the absence of decreased uptake area of Gd-EOB-DTPA in the irradiated areas. Compared to the 38 patients with the presence of decreased uptake area of Gd-EOB-DTPA, 9 patients with the absence of decreased uptake area of Gd-EOB-DTPA showed significant higher levels of total bile acid, total bilirubin, direct bilirubin and alpha-fetoprotein (P < 0.05). There were no significant differences in alanine transaminase, aspartate aminotransferase, gamma-glutamyl transpeptidase or albumin levels between the two groups (P > 0.05).Visible uptake of Gd-EOB-DTPA by the liver parenchyma was significantly associated with liver function parameters. EOB-MRI can be a valuable imaging biomarker for the assessment of liver parenchyma function outside of radiation area.

    View details for DOI 10.1016/j.hbpd.2019.05.005

    View details for Web of Science ID 000481407500010

    View details for PubMedID 31221569

  • Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT). Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Zhao, W., Han, B., Yang, Y., Buyyounouski, M., Hancock, S. L., Bagshaw, H., Xing, L. 2019; 140: 167–74

    Abstract

    BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre-trained deep learning model to interpret routine projection kilovoltage (kV) X-ray images in image-guided radiation therapy (IGRT).MATERIALS AND METHODS: We developed a personalized region-based convolutional neural network to localize the prostate treatment target without implanted fiducials. To train the deep neural network (DNN), we used the patient's planning computed tomography (pCT) images with pre-delineated prostate target to generate a large amount of synthetic kV projection X-ray images in the geometry of onboard imager (OBI) system. The DNN model was evaluated by retrospectively studying 10 patients who underwent prostate IGRT. Three out of the ten patients who had implanted fiducials and the fiducials' positions in the OBI images acquired for treatment setup were examined to show the potential of the proposed method for prostate IGRT. Statistical analysis using Lin's concordance correlation coefficient was calculated to assess the results along with the difference between the digitally reconstructed radiographs (DRR) derived and DNN predicted locations of the prostate.RESULTS: Differences between the predicted target positions using DNN and their actual positions are (mean ± standard deviation) 1.58 ± 0.43 mm, 1.64 ± 0.43 mm, and 1.67 ± 0.36 mm in anterior-posterior, lateral, and oblique directions, respectively. Prostate position identified on the OBI kV images is also found to be consistent with that derived from the implanted fiducials.CONCLUSIONS: Highly accurate, markerless prostate localization based on deep learning is achievable. The proposed method is useful for daily patient positioning and real-time target tracking during prostate radiotherapy.

    View details for DOI 10.1016/j.radonc.2019.06.027

    View details for PubMedID 31302347

  • Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network MEDICAL PHYSICS Nomura, Y., Xu, Q., Shirato, H., Shimizu, S., Xing, L. 2019; 46 (7): 3142–55

    View details for DOI 10.1002/mp.13583

    View details for Web of Science ID 000475671900020

  • Real-Time Radiation Treatment Planning with Optimality Guarantees via Cluster and Bound Methods INFORMS JOURNAL ON COMPUTING Ungun, B., Xing, L., Boyd, S. 2019; 31 (3): 544–58
  • Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network PHYSICS IN MEDICINE AND BIOLOGY Ma, M., Kovalchuk, N., Buyyounouski, M. K., Xing, L., Yang, Y. 2019; 64 (12)
  • Dose Distribution Prediction in Isodose Feature-Preserving Voxelization Domain Using Deep Convolutional Neural Network. Medical physics Ma, M., Buyyounouski, M. K., Vasudevan, V., Xing, L., Yang, Y. 2019

    Abstract

    PURPOSE: To implement a framework for dose prediction using a deep convolutional neural network (CNN) based on the concept of isodose feature-preserving voxelization (IFPV) in simplifying the representation of the dose distribution.METHODS: The concept of IFPV was introduced for concise representation of a treatment plan. IFPV is a sparse voxelization scheme that partitions the voxels into subgroups according to their geometric, anatomical and dosimetric features. In this study a deep CNN was constructed to build up a dose prediction model in IFPV domain based on 60 volumetric modulated arc therapy (VMAT) treatment plans from a database of previously treated 70 prostate cancer patients. The dose prediction model learns the contour to dose relationship and predicts the dose distribution in IFPV domain given the input contours. Additional 10 independent prostate cases were selected as testing data. DVH comparison, dose difference maps and residual analysis with the sum of absolute residual (SAR) were used to evaluate the performance of the proposed method.RESULTS: The proposed IFPV-based method achieved good prediction performance in terms of DVH comparison and dose difference maps. Statistical results of SARs showed that the IFPV-based method is comparable with voxel-based method even though the number of dose representation points used in the IFPV-based method was substantially reduced. The proposed approach achieved mean SARs of 0.029 ± 0.020 and 0.077 ±0.030 for bladder and rectum, respectively, compared with mean SARs of 0.039±0.029 and 0.069±0.028 in the conventional voxel-based method.CONCLUSIONS: A novel deep CNN-based dose prediction method in IFPV domain was proposed. The proposed approach has great potential to significantly improve the efficiency of dose prediction and facilitate the treatment planning workflow. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1002/mp.13618

    View details for PubMedID 31112305

  • Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network. Physics in medicine and biology Ma, M., Kovalchuk, N., Buyyounouski, M. K., Xing, L., Yang, Y. 2019

    Abstract

    An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and quality. Recently machine learning techniques have been proposed for IMRT dose prediction based on patient's contour information from planning CT. In these existing prediction models geometric/anatomic features were learned for building the dose prediction models and few features that characterize the dosimetric properties of the patients were utilized. In this study we propose a method to incorporate the dosimetric features in the construction of a more reliable dose prediction model based on the deep convolutional neural network (CNN). In addition to the contour information, the dose distribution from a PTV-only plan (i.e., the plan with the best PTV coverage by sacrificing the OARs sparing) is also employed as the model input to build a deep learning based dose prediction model. A database of 60 volumetric modulated arc therapy (VMAT) plans for the prostate cancer patients was used for training. The trained prediction model was then tested on a cohort of 10 cases. Dose difference maps, DVHs, dosimetric endpoints and statistical analysis of the sum of absolute residuals (SARs) were used to evaluate the proposed method. Our results showed that the mean SARs for the PTV, bladder and rectum using our method were 0.007±0.003, 0.035±0.032 and 0.067±0.037 respectively, lower than the SARs obtained with the contours-based method, indicating the potential of the proposed approach in accurately predicting dose distribution.

    View details for PubMedID 31082805

  • Attention-aware fully convolutional neural network with convolutional long short-term memory network for ultrasound-based motion tracking MEDICAL PHYSICS Huang, P., Yu, G., Lu, H., Liu, D., Xing, L., Yin, Y., Kovalchuk, N., Xing, L., Li, D. 2019; 46 (5): 2275–85

    View details for DOI 10.1002/mp.13510

    View details for Web of Science ID 000467556800032

  • Attention-aware Fully Convolutional Neural Network with Convolutional Long Short-Term Memory Network for Ultrasound-Based Motion Tracking. Medical physics Huang, P., Yu, G., Lu, H., Liu, D., Xing, L., Yin, Y., Kovalchuk, N., Xing, L., Li, D. 2019

    Abstract

    PURPOSE: One of the promising options for motion management in radiation therapy (RT) is the use of Linac-compatible robotic-arm-mounted ultrasound imaging system due to its high soft tissue contrast, real-time capability, absence of ionizing radiation and low cost. The purpose of this work is to develop a novel deep learning-based real-time motion tracking strategy for ultrasound image-guided RT.METHODS: The proposed tracker combined the attention-aware Fully Convolutional Neural Network (FCNN) and the Convolutional Long Short-Term Memory network (CLSTM) that is end-to-end trainable. The glimpse sensor module was built inside the attention-aware FCNN to discard majority of background by focusing on a region containing the object of interest. FCNN extracted discriminating spatial features of glimpse to facilitate temporal modeling for CLSTM. The saliency mask computed from CLSTM refined the features particular to the tracked landmarks. Moreover, the multi-task loss strategy including bounding box loss, localization loss, saliency loss, and adaptive loss weighting term was utilized to facilitate training convergence and avoid over/under-fitting. The tracker was tested on the databases provided by MICCAI 2015 challenges, and the ground truth data was obtained with the help of brute force-based template matching technology.RESULTS: The mean tracking error of 0.97 ± 0.52 mm and maximum tracking error of 1.94 mm were observed for 85 point-landmarks across 39 ultrasound cases compared to the ground truth annotations. The tracking speed per frame per landmark with the GPU implementation ranged from 66 and 101 frames per second, which largely exceeded the ultrasound imaging rate.CONCLUSION: The results demonstrated the robustness and accuracy of the proposed deep learning-based motion estimation, despite of the existence of some known shortcomings of ultrasound imaging such as speckle noise. The tracking speed of the system was found to be remarkable, sufficiently fast for real-time applications in RT environment. The approach provides a valuable tool to guide RT treatment with beam gating or multi leaf collimator (MLC) tracking in real time. This article is protected by copyright. All rights reserved.

    View details for PubMedID 30912590

  • Design and Preliminary Experience of a Tele-Radiotherapy System for a Medical Alliance in China. Telemedicine journal and e-health : the official journal of the American Telemedicine Association Zou, L., Chen, X., Xu, C., Xing, L., Xie, Y. 2019

    Abstract

    BACKGROUND: The medical alliance and telemedicine are considered to be important means to solve the imbalance between regions and shortage of professionals and promote the homogenization of medical services. Sichuan Provincial People's Hospital Group (SPPHG) is a network of hospitals with different levels of expertise, and all the members with radiotherapy form a radiotherapy network (RTN). Addressing the inadequacy and imbalance of radiotherapy services of Sichuan Province, China, a tele-radiotherapy system for RTN-SPPHG is designed, which includes the business model and corresponding technical implementation of an information system.MATERIALS AND METHODS: In the RTN-SPPHG, a distributed remote collaboration business model is explored and a tele-radiotherapy information system is customized for this telemedicine model. Both the business model and tailored information system were evaluated in actual use.RESULTS: Based on the tele-radiotherapy system of RTN-SPPHG, multitype hospitals are linked together and serve as a whole. Through the internet, the experience of experts of Sichuan Provincial People's Hospital is effectively deployed to member hospitals at the grassroot level.CONCLUSIONS: A close-knit medical alliance based on a tele-radiotherapy system should be a way to rapidly improve radiotherapy services and promote the homogenization of service in a region.

    View details for PubMedID 30892144

  • Design and Preliminary Experience of a Tele-Radiotherapy System for a Medical Alliance in China TELEMEDICINE AND E-HEALTH Zou, L., Chen, X., Xu, C., Xing, L., Xie, Y. 2020; 26 (2): 235–43
  • Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI. Magnetic resonance imaging Wu, Y., Ma, Y., Capaldi, D. P., Liu, J., Zhao, W., Du, J., Xing, L. 2019

    Abstract

    For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via deep learning and utilized for image reconstruction. In this study, we developed a volumetric hierarchical deep residual convolutional neural network, referred to as T-Net, to provide a data-driven end-to-end mapping from sparsely sampled MR images to fully sampled MR images, where cartilage MR images were acquired using an Ultra-short TE sequence and retrospectively undersampled using pseudo-random Cartesian and radial acquisition schemes. The network had a hierarchical architecture that promoted the sparsity of feature maps and increased the receptive field, which were valuable for signal synthesis and artifact suppression. Relatively dense local connections and global shortcuts were established to facilitate residual learning and compensate for details lost in hierarchical processing. Additionally, volumetric processing was adopted to fully exploit spatial continuity in three-dimensional space. Data consistency was further enforced. The network was trained with 336 three-dimensional images (each consisting of 32 slices) and tested by 24 images. The incorporation of a priori information acquired via deep learning facilitated high acceleration factors (as high as 8) while maintaining high image fidelity (quantitatively evaluated using the structural similarity index measurement). The proposed T-Net had an improved performance as compared to several state-of-the-art networks.

    View details for PubMedID 30880112

  • A novel range-verification method using ionoacoustic wave generated from spherical gold markers for particle-beam therapy: a simulation study SCIENTIFIC REPORTS Takayanagi, T., Uesaka, T., Kitaoka, M., Unlu, M., Umegaki, K., Shirato, H., Xing, L., Matsuura, T. 2019; 9: 4011

    Abstract

    This study proposes a novel alternative range-verification method for proton beam with acoustic waves generated from spherical metal markers. When proton beam is incident on metal markers, most of the resulting pressure waves are confined in the markers because of the large difference in acoustic impedance between the metal and tissue. However, acoustic waves with frequency equal to marker's resonant frequency escape this confinement; the marker briefly acts as an acoustic transmitter. Herein, this phenomenon is exploited to measure the range of the proton beam. We test the proposed strategy in 3-D simulations, combining the dose calculations with modelling of acoustic-wave propagation. A spherical gold marker of 2.0 mm diameter was placed in water with a 60 MeV proton beam incident on it. We investigated the dependence of pressure waves on the width of beam pulse and marker position. At short beam pulse, specific high-frequency acoustic waves of 1.62 MHz originating from the marker were observed in wave simulations, whose amplitude correlated with the distance between the marker and Bragg peak. Results indicate that the Bragg peak position can be estimated by measuring the acoustic wave amplitudes from the marker, using a single detector properly designed for the resonance frequency.

    View details for DOI 10.1038/s41598-019-38889-w

    View details for Web of Science ID 000460627700099

    View details for PubMedID 30850625

    View details for PubMedCentralID PMC6408528

  • A convex optimization approach to radiation treatment planning with dose constraints OPTIMIZATION AND ENGINEERING Fu, A., Ungun, B., Xing, L., Boyd, S. 2019; 20 (1): 277–300
  • In Vivo Translation of the CIRPI System---Revealing Molecular Pathology of Rabbit Aortic Atherosclerotic Plaques. Journal of nuclear medicine : official publication, Society of Nuclear Medicine Zaman, R., Yousufi, S., Chibana, H., Ikeno, F., Long, S. R., Gambhir, S. S., Chin, F. T., McConnell, M. V., Xing, L., Yeung, A. 2019

    Abstract

    Introduction: Thin-cap fibro atheroma (TCFA), unstable lesions in coronary artery disease (CAD), that prones to rupture resulting in substantial morbidity and mortality worldwide. However, their small size and complex morphological/biological features make early detection and risk assessment difficult. To overcome this limitation, we tested our newly developed catheter-based Circumferential-Intravascular-Radioluminescence-Photoacoustic-Imaging (CIRPI) system in vivo rabbit abdominal aorta to detect and characterize TCFA. Methods: The CIRPI system includes a novel optical probe combining circumferential radioluminescence imaging (CRI) and photoacoustic tomography (PAT). The CIRPI system was tested in rabbit abdominal aorta in vivo (WHHL, n = 5) and controls (NZW, n = 2). Rabbits were fasted for 6 hours before 5.55*107 Bq 18F-FDG was injected one hour prior to the imaging procedure. The experiment was done under anesthetic. A bare metal stent was implanted in the dorsal abdominal aorta as landmark, followed by the 7F imaging catheters that were advanced up to the proximal stent edge (PSE). Our CIRPI and clinical OCT were performed using pullback and non-occlusive flushing techniques. Results were verified with histochemical analysis. Results: Our CIRPI system successfully detected the locations and characterized both stable and vulnerable aortic plaques in vivo among all WHHL rabbits. Calcification was detected from the stable plaque (540/560 nm), whereas TCFA exhibited phospholipids/cholesterol (1040 nm, 1210 nm). These findings were verified with clinical OCT showing an area of low attenuation filled with lipids within TCFA. PAT image illustrated broken elastic fiber/collagen that could be verified with the histochemical analysis. All WHHL rabbits exhibited sparse to severe macrophages. However, 4 WHHL rabbits showed both moderate to severe level of calcifications and cholesterol clefts. However, all rabbits exhibited broken elastic fibers and collagen deposition. Control rabbits showed normal wall thickness with no presence of plaque tissue compositions. These findings were verified with the OCT and histochemical analysis. Conclusion: Our novel multi-modality hybrid system has been successfully translated to in vivo evaluation of atherosclerotic plaque structure and biology in a pre-clinical rabbit models. This proposed a paradigm shift that unites molecular and pathologic imaging technologies. Therefore, it may enhance the clinical evaluation of TCFA, as well as expand our understanding of CAD.

    View details for PubMedID 30737298

  • Controlled Nano-Bio Interface of Functional Nanoprobes for in Vivo Monitoring Enzyme Activity in Tumors ACS NANO Sun, Z., Cheng, K., Yao, Y., Wu, F., Fung, J., Chen, H., Ma, X., Tu, Y., Xing, L., Xia, L., Cheng, Z. 2019; 13 (2): 1153–67

    Abstract

    Engineering inorganic nanoparticles with a biocompatible shell to improve their physicochemical properties is a vital step in taking advantage of their superior magnetic, optical, and photothermal properties as multifunctional molecular imaging probes for disease diagnosis and treatment. The grafting/peeling-off strategy we developed for nanoparticle surface coating can fully control the targeting capability of functional nanoprobes by changing their colloidal behaviors such as diffusion and sedimentation rates at the desired sites. We demonstrated that a cleavable coating layer initially immobilized on the surface of magnetic resonance imaging probes not only makes the nanoparticles water-soluble but also can be selectively removed by specific enzymes, thereby resulting in a significant decrease of their water solubility in an enzyme-rich environment. Upon removal of surface coating, the changes in hydrodynamic size and surface charges of nanoprobes as a result of interacting with biomolecules and proteins lead to dramatic changes in their in vivo colloidal behaviors ( i. e., slow diffusion rates, tendency to aggregate and precipitate), which were quantitatively evaluated by examining changes in their hydrodynamic sizes, magnetic properties, and count rates during the size measurement. Because the retention time of nanoprobes within the tumor tissues depends on the uptake and excretion rate of the nanoprobes through the tumors, selective activation of nanoprobes by a specific enzyme resulted in much higher tumor accumulation and longer retention time within the tumors than that of the inactive nanoprobes, which passively passed through the tumors. The imaging contrast effect of tumors using activatable nanoprobes was significantly improved over using inactive probes. Therefore, the grafting/peeling-off strategy, as a general design approach for surface modification of nanoprobes, offers a promising and highly efficient way to render the nanoparticles suitable for targeted imaging of tumors.

    View details for DOI 10.1021/acsnano.8b05825

    View details for Web of Science ID 000460199400020

    View details for PubMedID 30673268

  • Dosimetric features-driven machine learning model for DVH prediction in VMAT treatment planning MEDICAL PHYSICS Ma, M., Kovalchuk, N., Buyyounouski, M. K., Xing, L., Yang, Y. 2019; 46 (2): 857–67

    View details for DOI 10.1002/mp.13334

    View details for Web of Science ID 000459616200041

  • Prostate cancer classification with multiparametric MRI transfer learning model MEDICAL PHYSICS Yuan, Y., Qin, W., Buyyounouski, M., Ibragimov, B., Hancock, S., Han, B., Xing, L. 2019; 46 (2): 756–65

    View details for DOI 10.1002/mp.13367

    View details for Web of Science ID 000459616200032

  • Tensor framelet based iterative image reconstruction algorithm for low-dose multislice helical CT PLOS ONE Nam, H., Guo, M., Yu, H., Lee, K., Li, R., Han, B., Xing, L., Lee, R., Gao, H. 2019; 14 (1)
  • Tensor framelet based iterative image reconstruction algorithm for low-dose multislice helical CT. PloS one Nam, H., Guo, M., Yu, H., Lee, K., Li, R., Han, B., Xing, L., Lee, R., Gao, H. 2019; 14 (1): e0210410

    Abstract

    In this study, we investigate the feasibility of improving the imaging quality for low-dose multislice helical computed tomography (CT) via iterative reconstruction with tensor framelet (TF) regularization. TF based algorithm is a high-order generalization of isotropic total variation regularization. It is implemented on a GPU platform for a fast parallel algorithm of X-ray forward band backward projections, with the flying focal spot into account. The solution algorithm for image reconstruction is based on the alternating direction method of multipliers or the so-called split Bregman method. The proposed method is validated using the experimental data from a Siemens SOMATOM Definition 64-slice helical CT scanner, in comparison with FDK, the Katsevich and the total variation (TV) algorithm. To test the algorithm performance with low-dose data, ACR and Rando phantoms were scanned with different dosages and the data was equally undersampled with various factors. The proposed method is robust for the low-dose data with 25% undersampling factor. Quantitative metrics have demonstrated that the proposed algorithm achieves superior results over other existing methods.

    View details for PubMedID 30633760

  • Stochastic Primal-Dual Method for Learning Mixture Policies in Markov Decision Processes Khuzani, M., Vasudevan, V., Ren, H., Xing, L., IEEE IEEE. 2019: 1293–1300
  • Self-Attention Convolutional Neural Network for Improved MR Image Reconstruction. Information sciences Wu, Y., Ma, Y., Liu, J., Du, J., Xing, L. 2019; 490: 317–28

    Abstract

    MRI is an advanced imaging modality with the unfortunate disadvantage of long data acquisition time. To accelerate MR image acquisition while maintaining high image quality, extensive investigations have been conducted on image reconstruction of sparsely sampled MRI. Recently, deep convolutional neural networks have achieved promising results, yet the local receptive field in convolution neural network raises concerns regarding signal synthesis and artifact compensation. In this study, we proposed a deep learning-based reconstruction framework to provide improved image fidelity for accelerated MRI. We integrated the self-attention mechanism, which captured long-range dependencies across image regions, into a volumetric hierarchical deep residual convolutional neural network. Basically, a self-attention module was integrated to every convolutional layer, where signal at a position was calculated as a weighted sum of the features at all positions. Furthermore, relatively dense shortcut connections were employed, and data consistency was enforced. The proposed network, referred to as SAT-Net, was applied on cartilage MRI acquired using an ultrashort TE sequence and retrospectively undersampled in a pseudo-random Cartesian pattern. The network was trained using 336 three dimensional images (each containing 32 slices) and tested with 24 images that yielded improved outcome. The framework is generic and can be extended to various applications.

    View details for DOI 10.1016/j.ins.2019.03.080

    View details for PubMedID 32817993

    View details for PubMedCentralID PMC7430761

  • A deep learning approach for dual-energy CT imaging using a single-energy CT data Zhao, W., Lv, T., Gao, P., Shen, L., Dai, X., Cheng, K., Jia, M., Chen, Y., Xing, L., Matej, S., Metzler, S. D. SPIE-INT SOC OPTICAL ENGINEERING. 2019

    View details for DOI 10.1117/12.2534433

    View details for Web of Science ID 000535354300073

  • Deep DoseNet: A deep neural network for accurate dosimetric transformation between different spatial resolutions and/or different dose calculation algorithms for precision radiation therapy. Physics in medicine and biology Dong, P., Xing, L. 2019

    Abstract

    The purpose of this work is to introduce a novel deep learning strategy to obtain highly accurate dose plan by transforming from a dose distribution calculated using a low-cost algorithm (or algorithmic settings).25,168 slices of dose distribution are calculated using Eclipse treatment planning system V15.6 (Varian Medical Systems, Palo Alto, CA) on 10 patient CTs whose treatment sites ranging from lung, brain, abdomen and pelvis, with a grid size of 1.25x1.25x1.25mm using both anisotropic analytical algorithm (AAA) in 5mm resolution and Acuros XB algorithm (AXB) in 1.25mm resolution. The AAA dose slices, and the corresponding down sampled CT slices are combined to form a tensor with a size of 2x64x64, working as the input to the deep learning-based dose calculation network (Deep DoseNet), which outputs the calculated Acuros dose with a size of 256x256. The Deep DoseNet (DDN) consists of a feature extraction component and an upscaling part. The DDN converges after ~100 epochs with a learning rate of 10^-4, using ADAM.We compared up sampled AAA dose and DDN output with that of AXB. For the evaluation set, the average mean-square-error decreased from 4.7x10^-4 between AAA and AXB to 7.0x10^-5 between DDN and AXB, with an average improvement of ~ 12 times. The average Gamma index passing rate at 3mm3% improved from 76% between AAA and AXB to 91% between DDN and AXB. The average calculation time is less than 1 milliseconds for a single slice on a NVIDIA DGX workstation.DDN, trained with a large amount of dosimetric data, can be employed as a general-purpose dose calculation acceleration engine across various dose calculation algorithms.

    View details for DOI 10.1088/1361-6560/ab652d

    View details for PubMedID 31869825

  • Upconversion Luminescence Imaging of Tumors with EGFR-Affibody Conjugated Nanophosphors MRS ADVANCES Badieirostami, M., Carpenter, C., Pratx, G., Xing, L., Sun, C. 2019; 4 (46-47): 2461–70
  • Modified fast adaptive scatter kernel superposition (mfASKS) correction and its dosimetric impact on CBCT-based proton therapy dose calculation. Medical physics Nomura, Y., Xu, Q., Peng, H., Takao, S., Shimizu, S., Xing, L., Shirato, H. 2019

    Abstract

    While cone beam computed tomography (CBCT) is able to provide patient anatomical information, its image quality is severely degraded due to scatter contamination, which degrades the accuracy of CBCT-based dose distribution estimation in proton therapy. In this work, we combined two existing scatter kernel correction methods: the point-spread function (PSF)-based scatter kernel derivation method and the fast adaptive scatter kernel superposition (fASKS) model, and evaluated the impact of the modified fASKS (mfASKS) correction on the accuracy of proton dose distribution estimation. To evaluate feasibility of the mfASKS approach using accurate scatter distributions, both Monte Carlo simulations and experiments were performed for an on-board CBCT machine integrated with a proton therapy machine.We developed a strategy to modify central intensity, constant intensity, and amplitude of the scatter kernels derived from PSFs for the fASKS model. A parameter required for the fASKS model was derived by optimizing uniformity in the mfASKS-corrected reconstructed images. Subsequently, the mfASKS model was used to remove scatter in CBCT imaging. We quantitatively compared the Hounsfield Unit (HU) and proton stopping power ratio (SPR) images for five different phantoms. To assess improvement of dose calculation accuracy, a series of proton treatment plans were produced using the CBCT images with and without the mfASKS correction.The accuracies of both HU and SPR intensity quantifications are improved as a result of the mfASKS correction. Mean absolute water-equivalent path length difference to the true value decreases from 10.3 to 0.934 mm for the Gammex phantom (simulation). At the same time, mfASKS is able to offer more accurate dose distributions, especially at the distal fall-off region where noticeable dose overestimation is observed in the uncorrected scenario. Mean absolute relative error of proton range in the pelvic phantom improves from 5.03% to 2.57% (experiment).mfASKS enables more accurate CBCT-based proton dose calculation. This technique has significant implications in image-guided radiotherapy and dose verifications in adaptive proton therapy.

    View details for DOI 10.1002/mp.13878

    View details for PubMedID 31661161

  • Factor 10 Expedience of Monthly Linac Quality Assurance via an Ion Chamber Array and Automation Scripts. Technology in cancer research & treatment Skinner, L. B., Yang, Y., Hsu, A., Xing, L., Yu, A. S., Niedermayr, T. 2019; 18: 1533033819876897

    Abstract

    PURPOSE: While critical for safe and accurate radiotherapy, monthly quality assurance of medical linear accelerators is time-consuming and takes physics resources away from other valuable tasks. The previous methods at our institution required 5 hours to perform the mechanical and dosimetric monthly linear accelerator quality assurance tests. An improved workflow was developed to perform these tests with higher accuracy, with fewer error pathways, in significantly less time.METHODS: A commercial ion chamber array (IC profiler, Sun Nuclear, Melbourne, Florida) is combined with automation scripts to consolidate monthly linear accelerator QA. The array was used to measure output, flatness, symmetry, jaw positions, gated dose constancy, energy constancy, collimator walkout, crosshair centering, and dosimetric leaf gap constancy. Treatment plans were combined with automation scripts that interface with Sun Nuclear's graphical user interface. This workflow was implemented on a standard Varian clinac, with no special adaptations, and can be easily applied to other C-arm linear accelerators.RESULTS: These methods enable, in 30 minutes, measurement and analysis of 20 of the 26 dosimetric and mechanical monthly tests recommended by TG-142. This method also reduces uncertainties in the measured beam profile constancy, beam energy constancy, field size, and jaw position tests, compared to our previous methods. One drawback is the increased uncertainty associated with output constancy. Output differences between IC profiler and farmer chamber in plastic water measurements over a 6-month period, across 4 machines, were found to have a 0.3% standard deviation for photons and a 0.5% standard deviation for electrons, which is sufficient for verifying output accuracy according to TG-142 guidelines. To minimize error pathways, automation scripts which apply the required settings, as well as check the exported data file integrity were employed.CONCLUSIONS: The equipment, procedure, and scripts used here reduce the time burden of routine quality assurance tests and in most instances improve precision over our previous methods.

    View details for DOI 10.1177/1533033819876897

    View details for PubMedID 31707931

  • Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning. European journal of radiology Cao, L., Shi, R., Ge, Y., Xing, L., Zuo, P., Jia, Y., Liu, J., He, Y., Wang, X., Luan, S., Chai, X., Guo, W. 2019; 121: 108713

    Abstract

    This study sought to establish a robust and fully automated Type B aortic dissection (TBAD) segmentation method by leveraging the emerging deep learning techniques.Preoperative CTA images of 276 patients with TBAD were retrospectively collected from January 2011 to December 2018. Using a reproducible manual segmentation protocol of three labels (whole aorta, true lumen (TL), and false lumen (FL)), a ground truth database (n = 276) was established and randomly divided into training and testing sets in a rough 8:1 ratio. Three convolutional neural network (CNN) models were developed on the training set (n = 246): single one-task (CNN1), single multi-task (CNN2), and serial multi-task (CNN3) models. Performance was evaluated using the Dice coefficient score (DCS) and lumen volume accuracy on the testing set (n = 30). Pearson correlation, Intra-class correlation coefficients and Bland-Altman plots were used to evaluate the inter-observer measurement agreement.CNN3 performed the best, with mean DCSs of 0.93 ± 0.01, 0.93 ± 0.01 and 0.91 ± 0.02 for the whole aorta, TL, and FL, respectively (p < 0.05). Each label volume from CNN3 showed excellent agreement with the ground truth, with mean volume differences of -31.05 (-82.76 to 20.65) ml, 4.79 (-11.04 to 20.63) ml, and 8.67(-11.40 to 28.74) ml for the whole aorta, TL, and FL, respectively. The segmentation speed of CNN3 was 0.038 ± 0.006 s/image.Deep learning-based model provides a promising approach for accurate and efficient segmentation of TBAD and makes it possible for automated measurements of TBAD anatomical features.

    View details for DOI 10.1016/j.ejrad.2019.108713

    View details for PubMedID 31683252

  • High spatial resolution x-ray luminescence computed tomography and x-ray fluorescence computed tomography Dai, X., Sivasubramanian, K., Xing, L., Pogue, B. W., Gioux, S. SPIE-INT SOC OPTICAL ENGINEERING. 2019

    View details for DOI 10.1117/12.2511875

    View details for Web of Science ID 000492315000020

  • PROSTATE SEGMENTATION WITH ENCODER -DECODER DENSELY CONNECT CONVOLUTIONAL NETWORK (ED-DENSENET) Yuan, Y., Qin, W., Guo, X., Buyyounouski, M., Hancock, S., Hai, B., Xing, L., IEEE IEEE. 2019: 434–37
  • Harnessing the power of deep learning for volumetric CT imaging with single or limited number of projections Shen, L., Zhao, W., Xing, L., Schmidt, T. G., Chen, G. H., Bosmans, H. SPIE-INT SOC OPTICAL ENGINEERING. 2019

    View details for DOI 10.1117/12.2513032

    View details for Web of Science ID 000483585700072

  • Automatic marker-free target positioning and tracking for image-guided radiotherapy and interventions Zhao, W., Shen, L., Wu, Y., Han, B., Yang, Y., Xing, L., Fei, B., Linte, C. A. SPIE-INT SOC OPTICAL ENGINEERING. 2019

    View details for DOI 10.1117/12.2512166

    View details for Web of Science ID 000483683500010

  • Augmented Bladder Tumor Detection Using Deep Learning. European urology Shkolyar, E., Jia, X., Chang, T. C., Trivedi, D., Mach, K. E., Meng, M. Q., Xing, L., Liao, J. C. 2019

    Abstract

    Adequate tumor detection is critical in complete transurethral resection of bladder tumor (TURBT) to reduce cancer recurrence, but up to 20% of bladder tumors are missed by standard white light cystoscopy. Deep learning augmented cystoscopy may improve tumor localization, intraoperative navigation, and surgical resection of bladder cancer. We aimed to develop a deep learning algorithm for augmented cystoscopic detection of bladder cancer. Patients undergoing cystoscopy/TURBT were recruited and white light videos were recorded. Video frames containing histologically confirmed papillary urothelial carcinoma were selected and manually annotated. We constructed CystoNet, an image analysis platform based on convolutional neural networks, for automated bladder tumor detection using a development dataset of 95 patients for algorithm training and five patients for testing. Diagnostic performance of CystoNet was validated prospectively in an additional 54 patients. In the validation dataset, per-frame sensitivity and specificity were 90.9% (95% confidence interval [CI], 90.3-91.6%) and 98.6% (95% CI, 98.5-98.8%), respectively. Per-tumor sensitivity was 90.9% (95% CI, 90.3-91.6%). CystoNet detected 39 of 41 papillary and three of three flat bladder cancers. With high sensitivity and specificity, CystoNet may improve the diagnostic yield of cystoscopy and efficacy of TURBT. PATIENT SUMMARY: Conventional cystoscopy has recognized shortcomings in bladder cancer detection, with implications for recurrence. Cystoscopy augmented with artificial intelligence may improve cancer detection and resection.

    View details for DOI 10.1016/j.eururo.2019.08.032

    View details for PubMedID 31537407

  • Reduced acquisition time for L-shell x-ray fluorescence Computed tomography using polycapillary x-ray optics. Medical physics Vernekohl, D., Ahmad, M., Dai, X., Zhao, W., Cheng, K., Xing, L. 2019

    Abstract

    X-ray fluorescence computed tomography (XFCT) is an emerging molecular imaging modality for preclinical and clinical applications with high atomic number contrast agents. XFCT allows detection of molecular biomarkers at tissue depths of 4-9 mm at L-shell energies and several centimeters for K-shell energies, while maintaining highspatial resolution. This is typically not possible for other molecular imaging modalities. The purpose of this study is to demonstrate XFCT imaging with reduced acquisition times. To accomplish this, x-ray focusing polycapillary optics are utilized to simultaneously increase x-ray fluence rate and spatial resolution in L-shell XFCT imaging.A prototype imaging system using a polycapillary focusing optic was demonstrated. The optic, which was custom-designed for this prototype, provided a high fluence rate with a focal spot size of 2.6 mm at a source to isocenter distance of 3 cm with a ten times higher fluence rate compared to standard collimation. The study evaluates three different phantoms to explore different trade-offs and limitations of L-shell XFCT imaging. A low contrast gold phantom and a high contrast gold phantom, each with three target regions with gold concentrations of 60, 80, and 100 μg ml-1 for low contrast and 200, 600, and 1000 μg ml-1 for high contrast, and a mouse-sized water phantom with gold concentrations between 300-500 μg ml-1 were imaged. X-ray fluorescence photons were measured using a silicon drift detector (SDD) with an energy resolution of 180 eV FWHM at an x-ray energy of 11 keV. Images were reconstructed with an iterative image reconstruction algorithm and analyzed for contrast to noise ratio (CNR) and signal to noise ratio (SNR).The XFCT data acquisition could be reduced from 17 h to under one hour. The polycapillary x-ray optic increases the x-ray fluence rate and lowers the amount of background scatter which leads to reduced imaging time and improved sensitivity. The quantitative analysis of the reconstructed images validates that concentrations of 60 μg ml-1 of gold can be visualized with L-shell XFCT imaging. For a mouse sized phantom, a concentration of 300 μg ml-1 gold was detected within a 66 min measurement.With a high fluence rate pencil beam from a polycapillary x-ray source, a reduction in signal integration time is achieved. It is presented that subtle amounts of contrast agents can be detected with L-shell XFCT within biologically relevant time frames. Our basic measurements show that the polycapillary x-ray source technology is appropriate to realize preclinical L-shell XFCT imaging. The integration of more SDDs into the system will lower the dose and increase the sensitivity.

    View details for DOI 10.1002/mp.13822

    View details for PubMedID 31512753

  • Optimizing efficiency and safety in external beam radiotherapy using automated plan check (APC) tool and six sigma methodology. Journal of applied clinical medical physics Liu, S., Bush, K. K., Bertini, J., Fu, Y., Lewis, J. M., Pham, D. J., Yang, Y., Niedermayr, T. R., Skinner, L., Xing, L., Beadle, B. M., Hsu, A., Kovalchuk, N. 2019; 20 (8): 56–64

    Abstract

    To develop and implement an automated plan check (APC) tool using a Six Sigma methodology with the aim of improving safety and efficiency in external beam radiotherapy.The Six Sigma define-measure-analyze-improve-control (DMAIC) framework was used by measuring defects stemming from treatment planning that were reported to the departmental incidence learning system (ILS). The common error pathways observed in the reported data were combined with our departmental physics plan check list, and AAPM TG-275 identified items. Prioritized by risk priority number (RPN) and severity values, the check items were added to the APC tool developed using Varian Eclipse Scripting Application Programming Interface (ESAPI). At 9 months post-APC implementation, the tool encompassed 89 check items, and its effectiveness was evaluated by comparing RPN values and rates of reported errors. To test the efficiency gains, physics plan check time and reported error rate were prospectively compared for 20 treatment plans.The APC tool was successfully implemented for external beam plan checking. FMEA RPN ranking re-evaluation at 9 months post-APC demonstrated a statistically significant average decrease in RPN values from 129.2 to 83.7 (P < .05). After the introduction of APC, the average frequency of reported treatment-planning errors was reduced from 16.1% to 4.1%. For high-severity errors, the reduction was 82.7% for prescription/plan mismatches and 84.4% for incorrect shift note. The process shifted from 4σ to 5σ quality for isocenter-shift errors. The efficiency study showed a statistically significant decrease in plan check time (10.1 ± 7.3 min, P = .005) and decrease in errors propagating to physics plan check (80%).Incorporation of APC tool has significantly reduced the error rate. The DMAIC framework can provide an iterative and robust workflow to improve the efficiency and quality of treatment planning procedure enabling a safer radiotherapy process.

    View details for DOI 10.1002/acm2.12678

    View details for PubMedID 31423729

  • A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma. Theranostics Xu, L., Yang, P., Liang, W., Liu, W., Wang, W., Luo, C., Wang, J., Peng, Z., Xing, L., Huang, M., Zheng, S., Niu, T. 2019; 9 (18): 5374–85

    Abstract

    Purpose: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. Methods and Materials: A group of 106 ICC patients, who were diagnosed between April 2011 and February 2016, was used for prediction model training. Image features were extracted from T1-weighted contrast-enhanced MR images. A support vector machine (SVM) model was built by using the most LN status-related features, which were selected using the maximum relevance minimum redundancy (mRMR) algorithm. The mRMR method ranked each feature according to its relevance to the LN status and redundancy with other features. An SVM score was calculated for each patient to reflect the LN metastasis (LNM) probability from the SVM model. Finally, a combination nomogram was constructed by incorporating the SVM score and clinical features. An independent group of 42 patients who were diagnosed from March 2016 to November 2017 was used to validate the prediction models. The model performances were evaluated on discrimination, calibration, and clinical utility. Results: The SVM model was constructed based on five selected image features. Significant differences were found between patients with LNM and non-LNM in SVM scores in both groups (the training group: 0.5466 (interquartile range (IQR), 0.4059-0.6985) vs. 0.3226 (IQR, 0.0527-0.4659), P<0.0001; the validation group: 0.5831 (IQR, 0.3641-0.8162) vs. 0.3101 (IQR, 0.1029-0.4661), P=0.0015). The combination nomogram based on the SVM score, the CA 19-9 level, and the MR-reported LNM factor showed better discrimination in separating patients with LNM and non-LNM, comparing to the SVM model alone (AUC: the training group: 0.842 vs. 0.788; the validation group: 0.870 vs. 0.787). Favorable clinical utility was observed using the decision curve analysis for the nomogram. Conclusion: The nomogram, incorporating the SVM score, CA 19-9 level and the MR-reported LNM factor, provided an individualized LN status evaluation and helped clinicians guide the surgical decisions.

    View details for DOI 10.7150/thno.34149

    View details for PubMedID 31410221

    View details for PubMedCentralID PMC6691572

  • A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma THERANOSTICS Xu, L., Yang, P., Liang, W., Liu, W., Wang, W., Luo, C., Wang, J., Peng, Z., Xing, L., Huang, M., Zheng, S., Niu, T. 2019; 9 (18): 5374–85

    View details for DOI 10.7150/thno.34149

    View details for Web of Science ID 000474899500017

  • Simulation studies of time reversal-based protoacoustic reconstruction for range and dose verification in proton therapy. Medical physics Yu, Y., Li, Z., Zhang, D., Xing, L., Peng, H. 2019

    Abstract

    In vivo range verification in proton therapy is a critical step to help minimize range and dose uncertainty. We propose to employ a time reversal (TR)-based approach using proton-induced acoustics (protoacoustics) to reconstruct pressure/dose distribution in heterogeneous tissues.The dose distribution of mono-energetic proton pencil beam in a CT-based patient phantom was calculated by Monte Carlo simulation. K-wave toolbox was used to investigate protoacoustic pressurization, propagation and reconstruction in 2D. To address the tissue heterogeneity effect, a number of physical parameters, including mass density (ρ), speed of sound (c), volumetric thermal expansion coefficient (αV ), isobaric specific heat capacity (Cp ) and attenuation power law prefactor (α0 ), were empirically converted from CT number. The performance was evaluated using two figures of merit: mean square error (MSE) of pressure profiles and Bragg peak localization error (ΔBP ). The impact of six parameters of the TR inversion was examined, including number of sensors, sampling duration, sampling timestep, spill time, noise level and number of iterations.The quantitative accuracy of TR reconstruction and its dependency on the selected parameters is presented. Under optimum conditions, the positioning accuracy of the Bragg peak can be controlled below 1 mm. For instance, MSE is 0.0123 and ΔBP is 0.59 mm under the following conditions (32 sensors, sampling duration: 600 μs, sampling timestep: 40 ns, spill time: 1 μs, no noise).The feasibility of TR-based protoacoustic reconstruction in 2D for proton range verification was first demonstrated. The approach is not only applicable to pencil beam, but also has potential to be extended to passive scattering systems. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1002/mp.13661

    View details for PubMedID 31199511

  • Markerless pancreatic tumor target localization enabled by deep learning. International journal of radiation oncology, biology, physics Zhao, W., Shen, L., Han, B., Yang, Y., Cheng, K., Toesca, D. A., Koong, A. C., Chang, D. T., Xing, L. 2019

    Abstract

    To estimate the impact of radiotherapy (RT) on non-breast second malignant neoplasms (SMNs) in young women survivors of stage I-IIIA breast cancer.Women aged 20-44 years diagnosed with stage I-IIIA breast cancer (1988-2008) were identified in Surveillance, Epidemiology, and End Results (SEER) 9 registries. Bootstrapping approach and competing risk proportional hazards models were used to evaluate the effect of RT on non-breast SMN risk. The analysis was repeated in racial subgroups. Radio-tolerance score (RTS) analysis of normal airway epithelium was performed using Gene Expression Omnibus (GEO) datasets.Within records of 30,003 women with primary breast cancer, 20,516 eligible patients were identified (including 2,183 African Americans [AAs] and 16,009 Caucasians). The 25-year cumulative incidences of SMN were 5.2% and 3.6% (RT vs. no-RT) for AAs with 12.8-year and 17.4-year (RT vs. no-RT) median follow-up (HR=1.81, 95% bootstrapping confidence intervals [BCIs] [1.02, 2.50], P < 0.05); and 6.4% and 5.9% (RT vs. no-RT) for Caucasians with 14.3-year and 18.1-year (RT vs. no-RT) median follow-up (HR=1.10, 95% BCI [0.61, 1.40], P > 0.05). The largest portion of excess RT-related SMN risk was lung cancer (AA: HR=2.08, 95% BCI [1.02, 5.39], P < 0.05; Caucasian: HR=1.50, 95% BCI [0.84, 5.38], P > 0.05). STEPP analysis revealed higher post-RT non-breast SMN risk essentially throughout entire age range 20-44 years, with larger HR for RT in AAs. RTS of normal airway epithelium from young AA women was significantly lower than that from young Caucasian women (P = 0.038).With a projected 25-year follow-up, RT is associated with elevated risk of non-breast SMNs, particularly second lung cancer, in young women survivors of stage I-IIIA breast cancer, especially higher in AA women than Caucasian women.

    View details for DOI 10.1016/j.ijrobp.2019.05.071

    View details for PubMedID 31201892

  • Projection-domain scatter correction for cone beam computed tomography using a residual convolutional neural network. Medical physics Nomura, Y., Xu, Q., Shirato, H., Shimizu, S., Xing, L. 2019

    Abstract

    Scatter is a major factor degrading the image quality of cone beam computed tomography (CBCT). Conventional scatter correction strategies require handcrafted analytical models with ad hoc assumptions, which often leads to less accurate scatter removal. This study aims to develop an effective scatter correction method using a residual convolutional neural network (CNN).A U-net based 25-layer CNN was constructed for CBCT scatter correction. The establishment of the model consists of three steps: model training, validation and testing. For model training, a total of 1,800 pairs of x-ray projection and the corresponding scatter-only distribution in non-anthropomorphic phantoms taken in full-fan scan were generated using Monte Carlo simulation of a CBCT scanner installed with a proton therapy system. An end-to-end CNN training was implemented with two major loss functions for 100 epochs with a mini-batch size of 10. Image rotations and flips were randomly applied to augment the training datasets during training. For validation, 200 projections of a digital head phantom were collected. The proposed CNN-based method was compared to a conventional projection-domain scatter correction method named fast adaptive scatter kernel superposition (fASKS) method using 360 projections of an anthropomorphic head phantom. Two different loss functions were applied for the same CNN to evaluate the impact of loss functions on the final results. Furthermore, the CNN model trained with full-fan projections was fine-tuned for scatter correction in half-fan scan by using transfer learning with additional 360 half-fan projection pairs of non-anthropomorphic phantoms. The tuned-CNN model for half-fan scan was compared with the fASKS method as well as the CNN-based method without the fine-tuning using additional lung phantom projections.The CNN-based method provides projections with significantly reduced scatter and CBCT images with more accurate Hounsfield Units (HUs) than that of the fASKS-based method. Root mean squared error of the CNN-corrected projections was improved to 0.0862 compared to 0.278 for uncorrected projections or 0.117 for the fASKS-corrected projections. The CNN-corrected reconstruction provided better HU quantification, especially in regions near the air or bone interfaces. All four image quality measures, which include mean absolute error (MAE), mean squared error (MSE), peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), indicated that the CNN-corrected images were significantly better than that of the fASKS-corrected images. Moreover, the proposed transfer learning technique made it possible for the CNN model trained with full-fan projections to be applicable to remove scatters in half-fan projections after fine-tuning with only a small number of additional half-fan training datasets. SSIM value of the tuned-CNN-corrected images was 0.9993 compared to 0.9984 for the non-tuned-CNN-corrected images or 0.9990 for the fASKS-corrected images. Finally, the CNN-based method is computationally efficient - the correction time for the 360 projections only took less than 5 seconds in the reported experiments on a PC (4.20 GHz Intel Core-i7 CPU) with a single NVIDIA GTX 1070 GPU.The proposed deep learning-based method provides an effective tool for CBCT scatter correction and holds significant value for quantitative imaging and image guided radiation therapy (IGRT). This article is protected by copyright. All rights reserved.

    View details for PubMedID 31077390

  • Self-attention convolutional neural network for improved MR image reconstruction Information Science Wu, Y. 2019: 317-328
  • Neural networks for deep radiotherapy dose analysis and prediction of liver SBRT outcomes. IEEE journal of biomedical and health informatics Ibragimov, B., Toesca, D., Yuan, Y., Koong, A., Daniel, C., Xing, L. 2019

    Abstract

    Stereotactic body radiation therapy (SBRT) is a relatively novel treatment modality, with little post-treatment prognostic information reported. This study proposes a novel neural network-based paradigm for accurate prediction of liver SBRT outcomes. We assembled a database of patients treated with liver SBRT at our institution. Together with a 3D dose delivery plans for each SBRT treatment, other variables such as patients' demographics, quantified abdominal anatomy, history of liver comorbidities, other liver-directed therapies and liver function tests were collected. We developed a multi-path neural network with the convolutional path for 3D dose plan analysis and fully-connected path for other variables analysis, where the network was trained to predict post-SBRT survival and local cancer progression. To enhance the network robustness, it was initially pre-trained on a large database of CT images. Following n-fold cross-validation, the network automatically identified patients that are likely to have longer survival or late cancer recurrence, i.e. patients with the positive predicted outcome (PPO) of SBRT, and vice versa, i.e. negative predicted outcome (NPO). The predicted results agreed with actual SBRT outcomes with 56% of PPO patients and 0% NPO patients with primary liver cancer survived more than 2-years after SBRT. Similarly, 82% of PPO patients and 0% of NPO patients with metastatic liver cancer survived 2-year threshold. The obtained results were superior to the performance of support vector machine and random forest classifiers. Furthermore, the network was able to identify the critical-to-spare liver regions, and the critical clinical features associated with the highest risks of negative SBRT outcomes.

    View details for DOI 10.1109/JBHI.2019.2904078

    View details for PubMedID 30869633

  • Deep Generative Adversarial Neural Networks for Compressive Sensing MRI IEEE TRANSACTIONS ON MEDICAL IMAGING Mardani, M., Gong, E., Cheng, J. Y., Vasanawala, S. S., Zaharchuk, G., Xing, L., Pauly, J. M. 2019; 38 (1): 167–79

    Abstract

    Undersampled magnetic resonance image (MRI) reconstruction is typically an ill-posed linear inverse task. The time and resource intensive computations require tradeoffs between accuracy and speed. In addition, state-of-the-art compressed sensing (CS) analytics are not cognizant of the image diagnostic quality. To address these challenges, we propose a novel CS framework that uses generative adversarial networks (GAN) to model the (low-dimensional) manifold of high-quality MR images. Leveraging a mixture of least-squares (LS) GANs and pixel-wise l1/l2 cost, a deep residual network with skip connections is trained as the generator that learns to remove the aliasing artifacts by projecting onto the image manifold. The LSGAN learns the texture details, while the l1/l2 cost suppresses high-frequency noise. A discriminator network, which is a multilayer convolutional neural network (CNN), plays the role of a perceptual cost that is then jointly trained based on high-quality MR images to score the quality of retrieved images. In the operational phase, an initial aliased estimate (e.g., simply obtained by zero-filling) is propagated into the trained generator to output the desired reconstruction. This demands a very low computational overhead. Extensive evaluations are performed on a large contrast-enhanced MR dataset of pediatric patients. Images rated by expert radiologists corroborate that GANCS retrieves higher quality images with improved fine texture details compared with conventional Wavelet-based and dictionary-learning-based CS schemes as well as with deep-learning-based schemes using pixel-wise training. In addition, it offers reconstruction times of under a few milliseconds, which are two orders of magnitude faster than the current state-of-the-art CS-MRI schemes.

    View details for DOI 10.1109/TMI.2018.2858752

    View details for Web of Science ID 000455110500017

    View details for PubMedID 30040634

  • Prostate Cancer Classification with Multi-parametric MRI Transfer Learning Model. Medical physics Yuan, Y., Qin, W., Buyyounouski, M., Ibragimov, B., Hancock, S., Han, B., Xing, L. 2018

    Abstract

    PURPOSE: Prostate cancer classification has significantly impact on the prognosis and treatment planning of patients. Currently, the classifying is based on the Gleason score analysis of biopsied tissues, which is neither accurate nor risk-free. This study aims to learn discriminative features for prostate images and assist physicians to classify prostate cancer automatically.METHODS: We develop a novel multi-parametric magnetic resonance transfer learning (MPTL) method to automatically stage prostate cancer. We first establish a deep convolutional neural network with three branch architectures, which transfer pre-trained model to compute features from multi-parametric MRI images (mp-MRI) : T2w transaxial, T2w sagittal and apparent diffusion coefficient (ADC). The learned features are concatenated to represent information of mp-MRI sequences. A new image similarity constraint is then proposed to enable the distribution of the features within the same category in a narrow angle region. With the joint constraints of softmax loss and image similarity loss in the fine-tuning process, the MPTL can provide descriptive features with intraclass compactness and interclass separability.RESULTS: Two cohorts: 132 cases from our institutional review board approved patient database and 112 cases from the PROSTATEx-2 Challenge are utilized to evaluate the robustness and effectiveness of the proposed MPTL model. Our model achieved high accuracy of prostate cancer classification (accuracy of 86.92%). Moreover, the comparison results demonstrate that our method outperforms both hand-crafted feature based methods and existing deep learning models in prostate cancer classification with higher accuracy.CONCLUSION: The experiment results showed that the proposed method can learn discriminative features for prostate images and classify the cancer accurately. Our MPTL model could be further applied in the clinical practice to provide valuable information for cancer treatment and precision medicine. This article is protected by copyright. All rights reserved.

    View details for PubMedID 30597561

  • Dosimetric Features-Driven Machine Learning Model for DVHs Prediction in VMAT Treatment Planning. Medical physics Ma, M., Kovalchuk, N., Buyyounouski, M. K., Xing, L., Yang, Y. 2018

    Abstract

    PURPOSE: Few features characterizing the dosimetric properties of the patients are included in currently available dose-volume histogram (DVH) prediction models, making it intractable to build a correlative relationship between the input and output parameters. Here we use PTV-only treatment plans of the patients (i.e., the achievable dose distribution in the absence of organs-at-risks (OARs) constraints) to estimate the potentially achievable quality of treatment plans and establish a machine learning-based DVH prediction framework with the use of the dosimetric metric as model input parameters.METHODS: A support vector regression (SVR) approach was used as the backbone of our machine learning model. A database containing volumetric modulated arc therapy (VMAT) plans of 63 prostate cancer patients were used. For each patient, the PTV-only plan was generated first. A correlative relationship between the OAR DVH of the PTV-only plan (model input) and the corresponding DVH of the clinical treatment plan (CTP) (model output) was then established with the 53 training cases. The prediction model was tested by the validation cohort of 10 cases.RESULTS: For the training cohort, the checks of dosimetric endpoints (DEs) indicated that 52 out of 53 plans (98%) were within 10% error bound for bladder, and 45 out of 53 plans (85%) were within 10% error bound for rectum. In the validation tests, 92% and 96% of the DEs were within the 10% error bounds for bladder and rectum respectively, and 8 out of 10 validation plans (80%) were within 10% error bound for both bladder and rectum. The sum of absolute residuals (SAR) achieved mean 0.034 ± 0.028 and 0.046 ± 0.021 for the bladder and rectum, respectively.CONCLUSIONS: A novel dosimetric features-driven machine learning model with the use of PTV-only plan has been established for DVH prediction. The framework is capable of efficiently generating best achievable DVHs for VMAT planning. This article is protected by copyright. All rights reserved.

    View details for PubMedID 30536442

  • Learning deconvolutional deep neural network for high resolution medical image reconstruction INFORMATION SCIENCES Liu, H., Xu, J., Wu, Y., Guo, Q., Ibragimov, B., Xing, L. 2018; 468: 142–54
  • Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT MEDICAL PHYSICS Ibragimov, B., Toesca, D., Chang, D., Yuan, Y., Koong, A., Xing, L. 2018; 45 (10): 4763–74

    View details for DOI 10.1002/mp.13122

    View details for Web of Science ID 000446995000056

  • Editorial: Machine Learning With Radiation Oncology Big Data FRONTIERS IN ONCOLOGY Deng, J., El Naqa, I., Xing, L. 2018; 8: 416

    View details for DOI 10.3389/fonc.2018.00416

    View details for Web of Science ID 000445744800001

    View details for PubMedID 30319978

    View details for PubMedCentralID PMC6170661

  • Rare-Earth-Doped Nanoparticles for Short-Wave Infrared Fluorescence Bioimaging and Molecular Targeting of alpha(V)beta(3)-Expressing Tumors MOLECULAR IMAGING Naczynski, D., Stafford, J. H., Tuerkcan, S., Jenkins, C., Koh, A., Sun, C., Xing, L. 2018; 17
  • Cumulative dose of radiation therapy of hepatocellular carcinoma patients and its deterministic relation to radiation-induced liver disease MEDICAL DOSIMETRY Huang, P., Yu, G., Kapp, D. S., Bian, X., Ma, C., Li, H., Chen, J., Liang, Y., Zhang, Y., Qin, S., Xie, Y., Yang, Y., Yin, Y., Xing, L., Li, D. 2018; 43 (3): 258–66

    Abstract

    This study aimed to investigate the relationship between dose and radiation-induced liver disease (RILD) in patients with hepatocellular carcinoma (HCC) receiving 3-dimensional conformal radiotherapy (3DCRT). Twenty-three patients with HCC who received conventional fractionated 3DCRT, including 7 who were diagnosed with classic RILD, were enrolled in this retrospective investigation. Cone-beam computed tomography (CBCT) scans were acquired at the time of treatment for each patient. The beams from each patient's treatment plan were applied to each pretreatment CBCT (the modified CBCT or mCBCT) to construct the delivered dose distribution of the day considering inter-treatment anatomy changes. The daily doses were summed together with the help of deformable image registration (DIR) to obtain the adjusted cumulative dose (Dadjusted). The dose changes to the normal liver between the original planned dose (Dplan) and Dadjusted were evaluated by V20, V30, V40, and the mean dose to normal liver (MDTNL). Univariate analysis was performed to identify the significant dose changes. Among the 23 patients, the liver V20, V30, V40, and MDTNL showed significant differences between Dplan and Dadjusted, with average values of these parameters increased by 4.1%, 4.7%, 4.5%, and 3.9 Gy, respectively (p < 0.05). The adjusted liver dose in 21 patients (91%) was higher than the planned value. For patients without and with RILD,the MDTNL was increased on average by 3.5 Gy and 4.7 Gy, and normal tissue complication probability (NTCP) increased on average by 2.8% and 7.5%, respectively. Our study found that the adjusted cumulative dose based on calculations using pretreatment mCBCT differs significantly from planned dose; the use of the dosimetric results of the initial plan was found to be less predictive of RILD as compared with Dadjusted. Determination of a reconstructed Dadjusted using the mCBCT scans are more accurate in predicting RILD and has the potential to reduce the risk of RILD.

    View details for PubMedID 29198389

  • Feasibility of optimizing intensity-modulated radiation therapy plans based on measured mucosal dose adjacent to dental fillings and toxicity outcomes JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Seol, S., Aggarwal, S., von Eyben, R., Wang, Z., Chan, C., Say, C., Xing, L., Hara, W., Yang, Y., Quynh Thu Le 2018; 19 (5): 444–52

    Abstract

    We prospectively investigated the feasibility of IMRT treatment plan optimization based on dosimeter measurements of lateral tongue mucosal dose adjacent to the dental fillings and evaluated dose-toxicity relationship and factors affecting oral mucositis (OM) in head and neck cancer patients. Twenty-nine head and neck cancer patients with metallic dental fillings who were scheduled to undergo fractionated external beam radiation therapy (RT) ± chemotherapy were enrolled. The lateral tongue dose was measured and if the calculated dose for the entire treatment was ≥35 Gy, a re-plan was generated to reduce the lateral tongue mucosal dose. OM was graded weekly according to Common Terminology Criteria for Adverse Events version 4.0 and the patients completed the Oral Mucositis Weekly Questionnaire-Head and Neck Cancer. The result showed that it was not feasible to optimize the IMRT plan based on measured tongue dose in most of the patients who needed re-plan as re-planning compromised the target coverage in 60% of these patients. The duration of grade (Gr) 2 OM was correlated with measured lateral tongue dose (P = 0.050). Concurrent cetuximab was significantly associated with faster onset of Gr2 OM than concurrent cisplatin (P = 0.006) and with longer duration of OM (P = 0.041) compared to concurrent cisplatin or IMRT-alone. The pattern of reported pain over time was significantly different for each treatment type (RT and cetuximab, RT and cisplatin and RT-alone) and depending on the dose level (P = 0.006). In conclusion, optimizing the IMRT plan based on measured lateral tongue dose was not feasible. Measured lateral tongue dose was significantly correlated with longer duration of OM ≥Gr2, and concurrent cetuximab was associated with earlier onset and longer duration of OM ≥Gr2.

    View details for PubMedID 29984915

  • Generalized Adaptive Gaussian Markov Random Field for X-Ray Luminescence Computed Tomography IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Zhang, G., Tzoumas, S., Cheng, K., Liu, F., Liu, J., Luo, J., Bai, J., Xing, L. 2018; 65 (9): 2130–33

    Abstract

    X-ray luminescence computed tomography (XLCT) is an emerging and promising modality, but suffers from inferior reconstructions and smoothed target shapes. This work aims to improve the image quality with new mathematical framework.We present a Bayesian local regularization framework to tackle the ill-conditioness of XLCT. Different from traditional overall regularization strategies, the proposed method utilizes correlations of neighboring voxels to regularize the solution locally based on generalized adaptive Gaussian Markov random field (GAGMRF), and provides an adjustable parameter to facilitate the edge-preserving property.Numerical simulations and phantom experiments show that the GAGMRF method yields both high image quality and accurate target shapes.Compared to conventional L2 and L1 regularizations, GAGMRF provides a new and efficient model for high quality imaging based on the Bayesian framework.The GAGMRF method offers a flexible regularization framework to adapt to a wide range of biomedical applications.

    View details for DOI 10.1109/TBME.2017.2785364

    View details for Web of Science ID 000442349500023

    View details for PubMedID 29989945

  • Development of deep neural network forindividualized hepatobiliary toxicity prediction after liver SBRT. Medical physics Ibragimov, B., Toesca, D., Chang, D., Yuan, Y., Koong, A., Xing, L. 2018

    Abstract

    BACKGROUND: Accurate prediction of radiation toxicity of healthy organs-at-risks (OARs) critically determines the radiation therapy (RT) success. The existing dose volume histogram-based metric may grossly under/over-estimate the therapeutic toxicity after 27% in liver RT and 50% in head-and-neck RT. We propose the novel paradigm for toxicity prediction by leveraging the enormous potential of deep learning and go beyond the existing dose/volume histograms.EXPERIMENTAL DESIGN: We employed a database of 125 liver stereotactic body RT (SBRT) cases with follow-up data to train deep learning-based toxicity predictor. Convolutional neural networks (CNNs) were applied to discover the consistent patterns in 3D dose plans associated with toxicities. To enhance the predicting power, we first pre-train the CNNs with transfer learning from 3D CT images of 2644 human organs. CNNs were then trained on liver SBRT cases. Furthermore, non-dosimetric pre-treatment features, such as patients' demographics, underlying liver diseases, liver-directed therapies, were inputted into the fully-connected neural network for more comprehensive prediction. The saliency maps of CNNs were used to estimate the toxicity risks associated with irradiation of anatomical regions of specific OARs. In addition, we applied machine learning solutions to map numerical pre-treatment features with hepatobiliary toxicity manifestation.RESULTS: Among 125 liver SBRT patients, 58 were treated for liver metastases, 36 for hepatocellular carcinoma, 27 for cholangiocarcinoma and 4 for other histologies. We observed that CNN we able to achieve accurate hepatobiliary toxicity prediction with the AUC of 0.79, whereas combining CNN for 3D dose plan analysis and fully-connected neural networks for numerical feature analysis resulted in AUC of 0.85. Deep learning produces almost 2 times fewer false positive toxicity predictions in comparison to DVH-based predictions, when the number of false negatives, i.e. missed toxicities, was minimized. The CNN saliency maps automatically estimated the toxicity risks for portal vein (PV) regions. We discovered that irradiation of the proximal portal vein is associated with two-times higher toxicity risks (risk score: 0.66) that irradiation of the left portal vein (risk score: 0.31).CONCLUSIONS: The framework offers clinically accurate tools for hepatobiliary toxicity prediction and automatic identification of anatomical regions that are critical to spare during SBRT. This article is protected by copyright. All rights reserved.

    View details for PubMedID 30098025

  • Coded-Aperture Compressed Sensing X-Ray Luminescence Tomography IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Tzoumas, S., Vernekohl, D., Xing, L. 2018; 65 (8): 1892–95

    Abstract

    The purpose of this work is to introduce and study a novel imaging geometry for X-ray luminescence computed tomography (XLCT), termed coded aperture compressive X-ray luminescence tomography (CAC-XLCT).CAC-XLCT is studied through simulations of X-ray and diffuse light propagation and the implementation of a compressed sensing image reconstruction algorithm.CAC-XLCT is compared against cone beam XLCT considering simulated targets with varying complexity, and it is found to offer a remarkable enhancement in spatial resolution and image quality with only a small overhead in image acquisition time.XLCT has been mainly investigated so far in pencil beam and cone beam excitation geometries which suffer from either very long image acquisition time or low spatial resolution and accuracy. CAC-XLCT presents a very promising alternative, which can offer simultaneously high spatial resolution, high image quality, and fast image acquisition, appropriate for in vivo imaging.

    View details for DOI 10.1109/TBME.2017.2770148

    View details for Web of Science ID 000439382300023

    View details for PubMedID 29989958

  • Polarized x-ray excitation for scatter reduction in x-ray fluorescence computed tomography MEDICAL PHYSICS Vernekohl, D., Tzoumas, S., Zhao, W., Xing, L. 2018; 45 (8): 3741–48

    View details for DOI 10.1002/mp.12997

    View details for Web of Science ID 000441292000027

  • Segmentation of parotid glands from registered CT and MR images PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS Mocnik, D., Ibragimov, B., Xing, L., Strojan, P., Likar, B., Pernus, F., Vrtovec, T. 2018; 52: 33–41

    Abstract

    To develop an automatic multimodal method for segmentation of parotid glands (PGs) from pre-registered computed tomography (CT) and magnetic resonance (MR) images and compare its results to the results of an existing state-of-the-art algorithm that segments PGs from CT images only.Magnetic resonance images of head and neck were registered to the accompanying CT images using two different state-of-the-art registration procedures. The reference domains of registered image pairs were divided on the complementary PG regions and backgrounds according to the manual delineation of PGs on CT images, provided by a physician. Patches of intensity values from both image modalities, centered around randomly sampled voxels from the reference domain, served as positive or negative samples in the training of the convolutional neural network (CNN) classifier. The trained CNN accepted a previously unseen (registered) image pair and classified its voxels according to the resemblance of its patches to the patches used for training. The final segmentation was refined using a graph-cut algorithm, followed by the dilate-erode operations.Using the same image dataset, segmentation of PGs was performed using the proposed multimodal algorithm and an existing monomodal algorithm, which segments PGs from CT images only. The mean value of the achieved Dice overlapping coefficient for the proposed algorithm was 78.8%, while the corresponding mean value for the monomodal algorithm was 76.5%.Automatic PG segmentation on the planning CT image can be augmented with the MR image modality, leading to an improved RT planning of head and neck cancer.

    View details for PubMedID 30139607

    View details for PubMedCentralID PMC6110103

  • Isodose feature-preserving voxelization (IFPV) for radiation therapy treatment planning MEDICAL PHYSICS Liu, H., Xing, L. 2018; 45 (7): 3321–29

    Abstract

    Inverse planning involves iterative optimization of a large number of parameters and is known to be a labor-intensive procedure. To reduce the scale of computation and improve characterization of isodose plan, this paper presents an isodose feature-preserving voxelization (IFPV) framework for radiation therapy applications and demonstrates an implementation of inverse planning in the IFPV domain.A dose distribution in IFPV scheme is characterized by partitioning the voxels into subgroups according to their geometric and dosimetric values. Computationally, the isodose feature-preserving (IFP) clustering combines the conventional voxels that are spatially and dosimetrically close into physically meaningful clusters. A K-means algorithm and support vector machine (SVM) runs sequentially to group the voxels into IFP clusters. The former generates initial clusters according to the geometric and dosimetric information of the voxels and SVM is invoked to improve the connectivity of the IFP clusters. To illustrate the utility of the formalism, an inverse planning framework in the IFPV domain is implemented, and the resultant plans of three prostate IMRT and one head-and-neck cases are compared quantitatively with that obtained using conventional inverse planning technique.The IFPV generates models with significant dimensionality reduction without compromising the spatial resolution seen in traditional downsampling schemes. The implementation of inverse planning in IFPV domain is demonstrated. In addition to the improved computational efficiency, it is found that, for the cases studied here, the IFPV-domain inverse planning yields better treatment plans than that of DVH-based planning, primarily because of more effective use of both geometric and dose information of the system during plan optimization.The proposed IFPV provides a low parametric representation of isodose plan without compromising the essential characteristics of the plan, thus providing a practically valuable framework for various applications in radiation therapy.

    View details for PubMedID 29772065

    View details for PubMedCentralID PMC6041150

  • A unified material decomposition framework for quantitative dual- and triple-energy CT imaging MEDICAL PHYSICS Zhao, W., Vernekohl, D., Han, F., Han, B., Peng, H., Yang, Y., Xing, L., Min, J. K. 2018; 45 (7): 2964–77

    View details for DOI 10.1002/mp.12933

    View details for Web of Science ID 000438211400013

  • Monte Carlo tree search -based non-coplanar trajectory design for station parameter optimized radiation therapy (SPORT) PHYSICS IN MEDICINE AND BIOLOGY Dong, P., Liu, H., Xing, L. 2018; 63 (13)
  • Burst and continuous high frequency irreversible electroporation protocols evaluated in a 3D tumor model PHYSICS IN MEDICINE AND BIOLOGY Sano, M. B., Fesmire, C. C., DeWitt, M. R., Xing, L. 2018; 63 (13): 135022

    Abstract

    High frequency irreversible electroporation (H-FIRE) is an emerging cancer therapy which uses bursts of alternating polarity pulses to target and destroy the membranes of cells within a predictable volume. Typically, 2 µs pulses are rapidly repeated 24-50 times to create a 48-100 µs long energy burst. Bursts are repeated 100×  at 1 Hz, resulting in an integrated energized time of 0.01 s per treatment. A 3D in vitro tumor model was used to investigate H-FIRE parameters in search of optimal energy timing protocols. Monopolar IRE treatments (100  ×  100 µs positive polarity pulses) resulted in a lethal electric field threshold of 423 V cm-1. Baseline H-FIRE treatments (100  ×  100 µs bursts of 2 µs pulses) resulted in a lethal threshold of 818 V cm-1. Increasing the number of H-FIRE bursts from 100×  to 1000×  reduced the lethal threshold to 535 V cm-1. An alternative diffuse H-FIRE protocol, which delivers 4 µs pulse cycles (one positive and one negative 2 µs pulse) continuously at 100 Hz, resulted in the lowest H-FIRE lethal threshold of 476 V cm-1. Finite element simulations using 5 kV pulses predict an IRE ablation volume of 3.9 cm3 (1.7 cm diameter) and a maximum H-FIRE ablation volume of 5.3 cm3 (2.4 cm diameter) when a clinical electrode and grounding pad configuration is used. Ablations as large as 15.7 cm3 (3.3 cm diameter) are predicted for H-FIRE treatments with 10 kV pulses. These results combine to demonstrate the importance of electrode geometry, pulse timing, and clinical delivery protocols for the creation of large clinically meaningful ablations.

    View details for DOI 10.1088/1361-6560/aacb62

    View details for Web of Science ID 000437823200004

    View details for PubMedID 29978834

  • A Dual-Modality Hybrid Imaging System Harnesses Radioluminescence and Sound to Reveal Molecular Pathology of Atherosclerotic Plaques SCIENTIFIC REPORTS Zaman, R. T., Yousefi, S., Long, S. R., Saito, T., Mandella, M., Qiu, Z., Chen, R., Contag, C. H., Gambhir, S. S., Chin, F. T., Khuri-Yakub, B. T., McConnell, M. V., Shung, K., Xing, L. 2018; 8: 8992

    Abstract

    Atherosclerosis is a progressive inflammatory condition caused by an unstable lesion, called thin-cap fibro atheromata (TCFA) that underlies coronary artery disease (CAD)-one of the leading causes of death worldwide. Therefore, early clinical diagnosis and effective risk stratification is important for CAD management as well as preventing progression to catastrophic events. However, early detection could be difficult due to their small size, motion, obscuring 18F-FDG uptake by adjacent myocardium, and complex morphological/biological features. To overcome these limitations, we developed a catheter-based Circumferential-Intravascular-Radioluminescence-Photoacoustic-Imaging (CIRPI) system that can detect vulnerable plaques in coronary arteries and characterizes them with respect to pathology and biology. Our CIRPI system combined two imaging modalities: Circumferential Radioluminescence Imaging (CRI) and PhotoAcoustic Tomography (PAT) within a novel optical probe. The probe's CaF2:Eu based scintillating imaging window provides a 360° view of human (n = 7) and murine carotid (n = 10) arterial plaques by converting β-particles into visible photons during 18F-FDG decay. A 60× and 63× higher radioluminescent signals were detected from the human and murine plaque inflammations, respectively, compared to the control. The system's photoacoustic imaging provided a comprehensive analysis of the plaque compositions and its morphologic information. These results were further verified with IVIS-200, immunohistochemical analysis, and autoradiography.

    View details for PubMedID 29895966

  • Monte Carlo tree search -based non-coplanar trajectory design for station parameter optimized radiation therapy (SPORT). Physics in medicine and biology Dong, P., Liu, H., Xing, L. 2018

    Abstract

    PURPOSE: An important yet challenging problem in LINAC-based rotational arc radiation therapy is the design of beam trajectory, which requires simultaneous consideration of delivery efficiency and final dose distribution. In this work, we propose a novel trajectory selection strategy by developing a Monte Carlo tree search (MCTS) algorithm during the beam trajectory selection process. Methods: To search through the vast number of possible trajectories, MCTS algorithm was implemented. In this approach, a candidate trajectory is explored by starting from a leaf node and sequentially examining the next level of linked nodes with consideration of geometric and physical constraints. The maximum Upper Confidence Bounds for Trees, which is a function of average objective function value and the number of times the node under testing has been visited, was employed to intelligently select the trajectory. For each candidate trajectory, we run an inverse fluence map optimization with an infinity norm regularization. The ranking of the plan as measured by the corresponding objective function value was then fed back to update the statistics of the nodes on the trajectory. The method was evaluated with a chest wall and a brain case, and the results were compared with the coplanar and noncoplanar 4pi beam configurations. Results: For both clinical cases, the MCTS method found effective and easy-to-deliver trajectories within an hour. As compared with the coplanar plans, it offers much better sparing of the OARs while maintaining the PTV coverage. The quality of the MCTS-generated plan is found to be comparable to the 4pi plans. Conclusion: AI based on MCTS is valuable to facilitate the design of beam trajectory and paves the way for future clinical use of non-coplanar treatment delivery. .

    View details for PubMedID 29863493

  • A New Registration Method Based On Surface Image Guided Radiation Therapy Zhao, J., Huang, P., Xing, L., Yi, S., Zhang, B., Meng, F., Li, D. WILEY. 2018: E395
  • Reduction of Muscle Contractions during Irreversible Electroporation Therapy Using High-Frequency Bursts of Alternating Polarity Pulses: A Laboratory Investigation in an Ex Vivo Swine Model JOURNAL OF VASCULAR AND INTERVENTIONAL RADIOLOGY Sano, M. B., Fan, R. E., Cheng, K., Saenz, Y., Sonn, G. A., Hwang, G. L., Xing, L. 2018; 29 (6): 893–98
  • Polarized X-ray excitation for scatter reduction in X-ray fluorescence computed tomography. Medical physics Vernekohl, D., Tzoumas, S., Zhao, W., Xing, L. 2018

    Abstract

    PURPOSE: X-ray fluorescence computer tomography (XFCT) is a new molecular imaging modality which uses X-ray excitation to stimulate the emission of fluorescent photons in high atomic number contrast agents. Scatter contamination is one of the main challenges in XFCT imaging which limits the molecular sensitivity. When polarized X-rays are used, it is possible to reduce the scatter contamination significantly by placing detectors perpendicular to the polarization direction. This study quantifies scatter contamination for polarized and unpolarized X-ray excitation and determines the advantages of scatter reduction.METHODS: The amount of scatter in preclinical XFCT is quantified in Monte Carlo simulations. The fluorescent X-rays are emitted isotropically, while scattered X-rays propagate in polarization direction. The magnitude of scatter contamination is studied in XFCT simulations of a mouse phantom. In this study, the contrast agent gold is examined as an example but a scatter reduction from polarized excitation is also expected for other elements. The scatter reduction capability is examined for different polarization intensities with a monoenergetic X-ray excitation energy of 82 keV. The study evaluates two different geometrical shapes of CZT detectors which are modeled with an energy resolution of 1 keV FWHM at an X-ray energy of 80 keV. Benefits of a detector placement perpendicular to the polarization direction are shown in iterative and analytic image reconstruction including scatter correction. The contrast to noise ratio (CNR) and the normalized mean square error (NMSE) are analyzed and compared for the reconstructed images.RESULTS: A substantial scatter reduction for common detector sizes was achieved for 100% and 80% linear polarization while lower polarization intensities provide a decreased scatter reduction. By placing the detector perpendicular to the polarization direction, a scatter reduction by factor up to 5.5 can be achieved for common detector sizes. The image reconstruction showed that for a scatter magnitude decrease by a factor of 2.4, the molecular sensitivity could almost be doubled.CONCLUSION: Scatter reduction lowers the amount of noise in the projection datasets and reconstructed images which enhances molecular sensitivity at equal dose. The results support the use of linear polarized X-rays to reduce scatter in XFCT imaging. This article is protected by copyright. All rights reserved.

    View details for PubMedID 29800510

  • Artificial intelligence will soon change the landscape of medical physics research and practice MEDICAL PHYSICS Xing, L., Krupinski, E. A., Cai, J. 2018; 45 (5): 1791–93

    View details for DOI 10.1002/mp.12831

    View details for Web of Science ID 000432023100003

    View details for PubMedID 29476545

  • Synergistically Enhancing the Therapeutic Effect of Radiation Therapy with Radiation Activatable and Reactive Oxygen Species-Releasing Nanostructures ACS NANO Cheng, K., Sano, M., Jenkins, C. H., Zhang, G., Vernekohl, D., Zhao, W., Wei, C., Zhang, Y., Zhang, Z., Liu, Y., Cheng, Z., Xing, L. 2018; 12 (5): 4946–58

    Abstract

    Nanoparticle-based radio-sensitizers can amplify the effects of radiation therapy on tumor tissue even at relatively low concentrations while reducing the potential side effects to healthy surrounding tissues. In this study, we investigated a hybrid anisotropic nanostructure, composed of gold (Au) and titanium dioxide (TiO2), as a radio-sensitizer for radiation therapy of triple-negative breast cancer (TNBC). In contrast to other gold-based radio sensitizers, dumbbell-like Au-TiO2 nanoparticles (DATs) show a synergistic therapeutic effect on radiation therapy, mainly because of strong asymmetric electric coupling between the high atomic number metals and dielectric oxides at their interfaces. The generation of secondary electrons and reactive oxygen species (ROS) from DATs triggered by X-ray irradiation can significantly enhance the radiation effect. After endocytosed by cancer cells, DATs can generate a large amount of ROS under X-ray irradiation, eventually inducing cancer cell apoptosis. Significant tumor growth suppression and overall improvement in survival rate in a TNBC tumor model have been successfully demonstrated under DAT uptake for a radio-sensitized radiation therapy.

    View details for DOI 10.1021/acsnano.8b02038

    View details for Web of Science ID 000433404500095

    View details for PubMedID 29689158

  • A unified material decomposition framework for quantitative dual- and triple-energy CT imaging. Medical physics Zhao, W., Vernekohl, D., Han, F., Han, B., Peng, H., Yang, Y., Xing, L., Min, J. K. 2018

    Abstract

    PURPOSE: Many clinical applications depend critically on the accurate differentiation and classification of different types of materials in patient anatomy. This work introduces a unified framework for accurate nonlinear material decomposition and applies it, for the first time, in the concept of triple-energy CT (TECT) for enhanced material differentiation and classification as well as dual-energy CT (DECT).METHODS: We express polychromatic projection into a linear combination of line integrals of material-selective images. The material decomposition is then turned into a problem of minimizing the least-squares difference between measured and estimated CT projections. The optimization problem is solved iteratively by updating the line integrals. The proposed technique is evaluated by using several numerical phantom measurements under different scanning protocols. The triple-energy data acquisition is implemented at the scales of micro-CT and clinical CT imaging with commercial "TwinBeam" dual-source DECT configuration and a fast kV switching DECT configuration. Material decomposition and quantitative comparison with a photon counting detector and with the presence of a bow-tie filter are also performed.RESULTS: The proposed method provides quantitative material- and energy-selective images examining realistic configurations for both DECT and TECT measurements. Compared to the polychromatic kV CT images, virtual monochromatic images show superior image quality. For the mouse phantom, quantitative measurements show that the differences between gadodiamide and iodine concentrations obtained using TECT and idealized photon counting CT (PCCT) are smaller than 8 and 1mg/mL, respectively. TECT outperforms DECT for multicontrast CT imaging and is robust with respect to spectrum estimation. For the thorax phantom, the differences between the concentrations of the contrast map and the corresponding true reference values are smaller than 7mg/mL for all of the realistic configurations.CONCLUSIONS: A unified framework for both DECT and TECT imaging has been established for the accurate extraction of material compositions using currently available commercial DECT configurations. The novel technique is promising to provide an urgently needed solution for several CT-based diagnostic and therapy applications, especially for the diagnosis of cardiovascular and abdominal diseases where multicontrast imaging is involved.

    View details for PubMedID 29679500

  • Optimization of a single insertion electrode array for the creation of clinically relevant ablations using high-frequency irreversible electroporation COMPUTERS IN BIOLOGY AND MEDICINE Sano, M. B., DeWitt, M. R., Teeter, S. D., Xing, L. 2018; 95: 107–17

    Abstract

    High-frequency irreversible electroporation (H-FIRE) is an emerging ablation modality, delivering rapid bursts of bipolar microsecond-duration electrical pulses to non-thermally ablate tissue including tumors. With advantages over current electroporation techniques including mitigation of muscle stimulation and reduced susceptibility to heterogeneous tissue properties, H-FIRE may produce more uniform and predictable ablations and can potentially be delivered with a single applicator device. However, the resulting ablations tend to be smaller than those provided with equivalent energy monopolar pulse protocols. Here, we develop numerical simulations that demonstrate the potential for clinically relevant ablations with H-FIRE delivered via a single insertion technique comprised of an expandable array and a distally placed grounding pad. Based on existing in vivo data and new in vitro results, delivery of H-FIRE with a clinical IRE single electrode probe (1 cm long) is predicted to produce a 2.2 cm3 ablation while an optimized eight tine array produces a 3.2 cm3 ablation when the same H-FIRE bursts are delivered (5000 V). We demonstrate that alternative pulse protocols can be used to increase ablation volumes with this optimized array and these results indicate that in vivo investigation of a single insertion array and grounding pad are warranted.

    View details for DOI 10.1016/j.compbiomed.2018.02.009

    View details for Web of Science ID 000430768000011

    View details for PubMedID 29486332

  • Treatment of Cancer In Vitro Using Radiation and High-Frequency Bursts of Submicrosecond Electrical Pulses IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Sano, M. B., Volotskova, O., Xing, L. 2018; 65 (4): 928–35

    Abstract

    High-frequency irreversible electroporation (H-FIRE) is an emerging cancer therapy, which uses bursts of short duration, alternating polarity, high-voltage electrical pulses to focally ablate tumors. Here, we present a preliminary investigation of the combinatorial effects of H-FIRE and ionizing radiation. In vitro cell cultures were exposed to bursts of 500 ns pulses and single radiation doses of 2 or 20 Gy then analyzed for 14 days. H-FIRE and radiation therapy (RT) appear to induce different delayed cell death mechanisms and in all treatment groups combinatorial therapy resulted in lower overall viabilities. These results indicate that in vivo investigation of the antitumor efficacy of combined H-FIRE and RT is warranted.

    View details for DOI 10.1109/TBME.2017.2734887

    View details for Web of Science ID 000428526000023

    View details for PubMedID 28783621

  • Radiomics and radiogenomics for precision radiotherapy JOURNAL OF RADIATION RESEARCH Wu, J., Tha, K., Xing, L., Li, R. 2018; 59: I25–I31

    Abstract

    Imaging plays an important role in the diagnosis and staging of cancer, as well as in radiation treatment planning and evaluation of therapeutic response. Recently, there has been significant interest in extracting quantitative information from clinical standard-of-care images, i.e. radiomics, in order to provide a more comprehensive characterization of image phenotypes of the tumor. A number of studies have demonstrated that a deeper radiomic analysis can reveal novel image features that could provide useful diagnostic, prognostic or predictive information, improving upon currently used imaging metrics such as tumor size and volume. Furthermore, these imaging-derived phenotypes can be linked with genomic data, i.e. radiogenomics, in order to understand their biological underpinnings or further improve the prediction accuracy of clinical outcomes. In this article, we will provide an overview of radiomics and radiogenomics, including their rationale, technical and clinical aspects. We will also present some examples of the current results and some emerging paradigms in radiomics and radiogenomics for clinical oncology, with a focus on potential applications in radiotherapy. Finally, we will highlight the challenges in the field and suggest possible future directions in radiomics to maximize its potential impact on precision radiotherapy.

    View details for PubMedID 29385618

    View details for PubMedCentralID PMC5868194

  • Selection of external beam radiotherapy approaches for precise and accurate cancer treatment JOURNAL OF RADIATION RESEARCH Shirato, H., Quynh-Thu Le, Kobashi, K., Prayongrat, A., Takao, S., Shimizu, S., Giaccia, A., Xing, L., Umegaki, K. 2018; 59: I2–I10

    Abstract

    Physically precise external-beam radiotherapy (EBRT) technologies may not translate to the best outcome in individual patients. On the other hand, clinical considerations alone are often insufficient to guide the selection of a specific EBRT approach in patients. We examine the ways in which to compare different EBRT approaches based on physical, biological and clinical considerations, and how they can be enhanced with the addition of biophysical models and machine-learning strategies. The process of selecting an EBRT modality is expected to improve in tandem with knowledge-based treatment planning.

    View details for PubMedID 29373709

    View details for PubMedCentralID PMC5868193

  • Imaging cellular pharmacokinetics of F-18-FDG and 6-NBDG uptake by inflammatory and stem cells PLOS ONE Zaman, R. T., Tuerkcan, S., Mahmoudi, M., Saito, T., Yang, P. C., Chin, F. T., McConnell, M. V., Xing, L. 2018; 13 (2): e0192662

    Abstract

    Myocardial infarction (MI) causes significant loss of cardiomyocytes, myocardial tissue damage, and impairment of myocardial function. The inability of cardiomyocytes to proliferate prevents the heart from self-regeneration. The treatment for advanced heart failure following an MI is heart transplantation despite the limited availability of the organs. Thus, stem-cell-based cardiac therapies could ultimately prevent heart failure by repairing injured myocardium that reverses cardiomyocyte loss. However, stem-cell-based therapies lack understanding of the mechanisms behind a successful therapy, including difficulty tracking stem cells to provide information on cell migration, proliferation and differentiation. In this study, we have investigated the interaction between different types of stem and inflammatory cells and cell-targeted imaging molecules, 18F-FDG and 6-NBDG, to identify uptake patterns and pharmacokinetics in vitro.Macrophages (both M1 and M2), human induced pluripotent stem cells (hiPSCs), and human amniotic mesenchymal stem cells (hAMSCs) were incubated with either 18F-FDG or 6-NBDG. Excess radiotracer and fluorescence were removed and a 100 μm-thin CdWO4 scintillator plate was placed on top of the cells for radioluminescence microscopy imaging of 18F-FDG uptake, while no scintillator was needed for fluorescence imaging of 6-NBDG uptake. Light produced following beta decay was imaged with a highly sensitive inverted microscope (LV200, Olympus) and an Electron Multiplying Charge-Couple Device (EM-CCD) camera. Custom-written software was developed in MATLAB for image processing.The average cellular activity of 18F-FDG in a single cell of hAMSCs (0.670±0.028 fCi/μm2, P = 0.001) was 20% and 36% higher compared to uptake in hiPSCs (0.540±0.026 fCi/μm2, P = 0.003) and macrophages (0.430±0.023 fCi/μm2, P = 0.002), respectively. hAMSCs exhibited the slowest influx (0.210 min-1) but the fastest efflux (0.327 min-1) rate compared to the other tested cell lines for 18F-FDG. This cell line also has the highest phosphorylation but exhibited the lowest rate of de-phosphorylation. The uptake pattern for 6-NBDG was very different in these three cell lines. The average cellular activity of 6-NBDG in a single cell of macrophages (0.570±0.230 fM/μm2, P = 0.004) was 38% and 14% higher compared to hiPSCs (0.350±0.160 fM/μm2, P = 0.001) and hAMSCs (0.490±0.028 fM/μm2, P = 0.006), respectively. The influx (0.276 min-1), efflux (0.612 min-1), phosphorylation (0.269 min-1), and de-phosphorylation (0.049 min-1) rates were also highest for macrophages compared to the other two tested cell lines.hAMSCs were found to be 2-3× more sensitive to 18F-FDG molecule compared to hiPSCs/macrophages. However, macrophages exhibited the most sensitivity towards 6-NBDG. Based on this result, hAMSCs targeted with 18F-FDG could be more suitable for understanding the mechanisms behind successful therapy for treating MI patients by gathering information on cell migration, proliferation and differentiation.

    View details for PubMedID 29462173

  • Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation. Physics in medicine and biology Qin, W., Wu, J., Han, F., Yuan, Y., Zhao, W., Ibragimov, B., Gu, J., Xing, L. 2018; 63 (9): 095017

    Abstract

    Segmentation of liver in abdominal computed tomography (CT) is an important step for radiation therapy planning of hepatocellular carcinoma. Practically, a fully automatic segmentation of liver remains challenging because of low soft tissue contrast between liver and its surrounding organs, and its highly deformable shape. The purpose of this work is to develop a novel superpixel-based and boundary sensitive convolutional neural network (SBBS-CNN) pipeline for automated liver segmentation. The entire CT images were first partitioned into superpixel regions, where nearby pixels with similar CT number were aggregated. Secondly, we converted the conventional binary segmentation into a multinomial classification by labeling the superpixels into three classes: interior liver, liver boundary, and non-liver background. By doing this, the boundary region of the liver was explicitly identified and highlighted for the subsequent classification. Thirdly, we computed an entropy-based saliency map for each CT volume, and leveraged this map to guide the sampling of image patches over the superpixels. In this way, more patches were extracted from informative regions (e.g. the liver boundary with irregular changes) and fewer patches were extracted from homogeneous regions. Finally, deep CNN pipeline was built and trained to predict the probability map of the liver boundary. We tested the proposed algorithm in a cohort of 100 patients. With 10-fold cross validation, the SBBS-CNN achieved mean Dice similarity coefficients of 97.31  ±  0.36% and average symmetric surface distance of 1.77  ±  0.49 mm. Moreover, it showed superior performance in comparison with state-of-art methods, including U-Net, pixel-based CNN, active contour, level-sets and graph-cut algorithms. SBBS-CNN provides an accurate and effective tool for automated liver segmentation. It is also envisioned that the proposed framework is directly applicable in other medical image segmentation scenarios.

    View details for PubMedID 29633960

  • RIIS-DenseNet: Rotation-Invariant and Image Similarity Constrained Densely Connected Convolutional Network for Polyp Detection Yuan, Y., Qin, W., Ibragimov, B., Han, B., Xing, L., Frangi, A. F., Schnabel, J. A., Davatzikos, C., AlberolaLopez, C., Fichtinger, G. SPRINGER INTERNATIONAL PUBLISHING AG. 2018: 620–28
  • Line-Enhanced Deformable Registration of Pulmonary Computed Tomography Images Before and After Radiation Therapy With Radiation-Induced Fibrosis TECHNOLOGY IN CANCER RESEARCH & TREATMENT King, M., Sensakovic, W. F., Maxim, P., Diehn, M., Loo, B. W., Xing, L. 2018; 17
  • Rare-Earth-Doped Nanoparticles for Short-Wave Infrared Fluorescence Bioimaging and Molecular Targeting of alphaVbeta3-Expressing Tumors. Molecular imaging Naczynski, D. J., Stafford, J. H., Turkcan, S., Jenkins, C., Koh, A. L., Sun, C., Xing, L. 2018; 17: 1536012118799131

    Abstract

    The use of short-wave infrared (SWIR) light for fluorescence bioimaging offers the advantage of reduced photon scattering and improved tissue penetration compared to traditional shorter wavelength imaging approaches. While several nanomaterials have been shown capable of generating SWIR emissions, rare-earth-doped nanoparticles (REs) have emerged as an exceptionally bright and biocompatible class of SWIR emitters. Here, we demonstrate SWIR imaging of REs for several applications, including lymphatic mapping, real-time monitoring of probe biodistribution, and molecular targeting of the alphavbeta3 integrin in a tumor model. We further quantified the resolution and depth penetration limits of SWIR light emitted by REs in a customized imaging unit engineered for SWIR imaging of live small animals. Our results indicate that SWIR light has broad utility for preclinical biomedical imaging and demonstrates the potential for molecular imaging using targeted REs.

    View details for PubMedID 30246593

  • Strategies for prediction and mitigation of radiation-induced liver toxicity. Journal of radiation research Toesca, D. A., Ibragimov, B., Koong, A. J., Xing, L., Koong, A. C., Chang, D. T. 2018

    Abstract

    Although well described in the 1960s, liver toxicity secondary to radiation therapy, commonly known as radiation-induced liver disease (RILD), remains a major challenge. RILD encompasses two distinct clinical entities, a 'classic' form, composed of anicteric hepatomegaly, ascites and elevated alkaline phosphatase; and a 'non-classic' form, with liver transaminases elevated to more than five times the reference value, or worsening of liver metabolic function represented as an increase of 2 or more points in the Child-Pugh score classification. The risk of occurrence of RILD has historically limited the applicability of radiation for the treatment of liver malignancies. With the development of 3D conformal radiation therapy, which allowed for partial organ irradiation based on computed tomography treatment planning, there has been a resurgence of interest in the use of liver irradiation. Since then, a large body of evidence regarding the liver tolerance to conventionally fractionated radiation has been produced, but severe liver toxicities has continued to be reported. More recently, improvements in diagnostic imaging, radiation treatment planning technology and delivery systems have prompted the development of stereotactic body radiotherapy (SBRT), by which high doses of radiation can be delivered with high target accuracy and a steep dose gradient at the tumor - normal tissue interface, offering an opportunity of decreasing toxicity rates while improving tumor control. Here, we present an overview of the role SBRT has played in the management of liver tumors, addressing the challenges and opportunities to reduce the incidence of RILD, such as adaptive approaches and machine-learning-based predictive models.

    View details for PubMedID 29432550

  • A computation study on an integrated alternating direction method of multipliers for large scale optimization OPTIMIZATION LETTERS Zarepisheh, M., Xing, L., Ye, Y. 2018; 12 (1): 3–15
  • Line-Enhanced Deformable Registration of Pulmonary Computed Tomography Images Before and After Radiation Therapy With Radiation-Induced Fibrosis. Technology in cancer research & treatment King, M., Sensakovic, W. F., Maxim, P., Diehn, M., Loo, B. W., Xing, L. 2018; 17: 1533034617749419

    Abstract

    PURPOSE: The deformable registration of pulmonary computed tomography images before and after radiation therapy is challenging due to anatomic changes from radiation fibrosis. We hypothesize that a line-enhanced registration algorithm can reduce landmark error over the entire lung, including the irradiated regions, when compared to an intensity-based deformable registration algorithm.MATERIALS: Two intensity-based B-spline deformable registration algorithms of pre-radiation therapy and post-radiation therapy images were compared. The first was a control intensity-based algorithm that utilized computed tomography images without modification. The second was a line enhancement algorithm that incorporated a Hessian-based line enhancement filter prior to deformable image registration. Registrations were evaluated based on the landmark error between user-identified landmark pairs and the overlap ratio.RESULTS: Twenty-one patients with pre-radiation therapy and post-radiation therapy scans were included. The median time interval between scans was 1.2 years (range: 0.3-3.3 years). Median landmark errors for the line enhancement algorithm were significantly lower than those for the control algorithm over the entire lung (1.67 vs 1.83 mm; P < .01), as well as within the 0 to 5 Gy (1.40 vs 1.57; P < .01) and >5 Gy (2.25 vs 3.31; P < .01) dose intervals. The median lung mask overlap ratio for the line enhancement algorithm (96.2%) was greater than that for the control algorithm (95.8%; P < .01). Landmark error within the >5 Gy dose interval demonstrated a significant inverse relationship with post-radiation therapy fibrosis enhancement after line enhancement filtration (Pearson correlation coefficient = -0.48; P = .03).CONCLUSION: The line enhancement registration algorithm is a promising method for registering images before and after radiation therapy.

    View details for PubMedID 29343206

  • Reduction of Muscle Contractions during Irreversible Electroporation Therapy Using High-Frequency Bursts of Alternating Polarity Pulses: A Laboratory Investigation in an ExVivo Swine Model. Journal of vascular and interventional radiology : JVIR Sano, M. B., Fan, R. E., Cheng, K., Saenz, Y., Sonn, G. A., Hwang, G. L., Xing, L. 2018; 29 (6): 893

    Abstract

    PURPOSE: To compare the intensity of muscle contractions in irreversible electroporation (IRE) treatments when traditional IRE and high-frequency IRE (H-FIRE) waveforms are used in combination with a single applicator and distal grounding pad (A+GP) configuration.MATERIALS AND METHODS: An exvivo in situ porcine model was used to compare muscle contractions induced by traditional monopolar IRE waveforms vs high-frequency bipolar IRE waveforms. Pulses with voltages between 200 and 5,000 V were investigated, and muscle contractions were recorded by using accelerometers placed on or near the applicators.RESULTS: H-FIRE waveforms reduced the intensity of muscle contractions in comparison with traditional monopolar IRE pulses. A high-energy burst of 2-mus alternating-polarity pulses energized for 200 mus at 4,500 V produced less intense muscle contractions than traditional IRE pulses, which were 25-100 mus in duration at 3,000 V.CONCLUSIONS: H-FIRE appears to be an effective technique to mitigate the muscle contractions associated with traditional IRE pulses. This may enable the use of voltages greater than 3,000 V necessary for the creation of large ablations invivo.

    View details for PubMedID 29628296

  • Synthesis, Characterization, and Biomedical Applications of a Targeted Dual-Modal Near-Infrared-II Fluorescence and Photoacoustic Imaging Nanoprobe ACS NANO Cheng, K., Chen, H., Jenkins, C. H., Zhang, G., Zhao, W., Zhang, Z., Han, F., Fung, J., Yang, M., Jiang, Y., Xing, L., Cheng, Z. 2017; 11 (12): 12276–91

    Abstract

    Our development of multifunctional dual-modal imaging probes aims to integrate the benefits from both second near-infrared (NIR-II) fluorescence (1000-1700 nm) and photoacoustic imaging with an ultimate goal of improving overall cancer diagnosis efficacy. Herein we designed a donor-acceptor chromophore based nanoparticle (DAP) as a dual-modal image contrast agent has strong absorption in the NIR-I window and a strong fluorescence emission peak in the NIR-II region. The dual-modal DAPs composed of D-π-A-π-D-type chromophores were PEGylated through nanoprecipitation. The multifunctional DAP surface was thus available for subsequent bioconjugation of EGFR Affibody (Ac-Cys-ZEGFR:1907) to target EGFR-positive cancers. The Affibody-conjugated DAPs appeared as highly monodisperse nanoparticles (∼30 nm) with strong absorption in the NIR-I window (at ca. 680 nm) and an extremely high fluorescence in the NIR-II region (maximum peak at 1000 nm). Consequently, the Affibody-DAPs show significantly enhanced photoacoustic and NIR-II fluorescence contrast effects in both in vitro and in vivo experiments. Moreover, the Affibody-DAPs have the capability to selectively target EGFR-positive tumors in an FTC-133 subcutaneous mouse model with relatively high photoacoustic and fluorescent signals. By taking advantage of high spatial resolution and excellent temporal resolution, photoacoustic/NIR-II fluorescence imaging with targeted dual-modal contrast agents allows us to specifically image and detect various cancers and diseases in an accurate manner.

    View details for PubMedID 29202225

  • A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning PHYSICS IN MEDICINE AND BIOLOGY Liu, H., Dong, P., Xing, L. 2017; 62 (16): 6428–45

    Abstract

    [Formula: see text]-minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the [Formula: see text]-based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the [Formula: see text]-minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the [Formula: see text]-minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the [Formula: see text]-minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

    View details for PubMedID 28726687

  • Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation PHYSICS IN MEDICINE AND BIOLOGY Han, H., Gao, H., Xing, L. 2017; 62 (16): 6408–27

    Abstract

    Excessive radiation exposure is still a major concern in 4D cone-beam computed tomography (4D-CBCT) due to its prolonged scanning duration. Radiation dose can be effectively reduced by either under-sampling the x-ray projections or reducing the x-ray flux. However, 4D-CBCT reconstruction under such low-dose protocols is prone to image artifacts and noise. In this work, we propose a novel joint regularization-based iterative reconstruction method for low-dose 4D-CBCT. To tackle the under-sampling problem, we employ spatiotemporal tensor framelet (STF) regularization to take advantage of the spatiotemporal coherence of the patient anatomy in 4D images. To simultaneously suppress the image noise caused by photon starvation, we also incorporate spatiotemporal nonlocal total variation (SNTV) regularization to make use of the nonlocal self-recursiveness of anatomical structures in the spatial and temporal domains. Under the joint STF-SNTV regularization, the proposed iterative reconstruction approach is evaluated first using two digital phantoms and then using physical experiment data in the low-dose context of both under-sampled and noisy projections. Compared with existing approaches via either STF or SNTV regularization alone, the presented hybrid approach achieves improved image quality, and is particularly effective for the reconstruction of low-dose 4D-CBCT data that are not only sparse but noisy.

    View details for PubMedID 28726684

  • Segmentation of Pathological Structures by Landmark-Assisted Deformable Models IEEE TRANSACTIONS ON MEDICAL IMAGING Ibragimov, B., Korez, R., Likar, B., Pernus, F., Xing, L., Vrtovec, T. 2017; 36 (7): 1457–69

    Abstract

    Computerized segmentation of pathological structures in medical images is challenging, as, in addition to unclear image boundaries, image artifacts, and traces of surgical activities, the shape of pathological structures may be very different from the shape of normal structures. Even if a sufficient number of pathological training samples are collected, statistical shape modeling cannot always capture shape features of pathological samples as they may be suppressed by shape features of a considerably larger number of healthy samples. At the same time, landmarking can be efficient in analyzing pathological structures but often lacks robustness. In this paper, we combine the advantages of landmark detection and deformable models into a novel supervised multi-energy segmentation framework that can efficiently segment structures with pathological shape. The framework adopts the theory of Laplacian shape editing, that was introduced in the field of computer graphics, so that the limitations of statistical shape modeling are avoided. The performance of the proposed framework was validated by segmenting fractured lumbar vertebrae from 3-D computed tomography images, atrophic corpora callosa from 2-D magnetic resonance (MR) cross-sections and cancerous prostates from 3D MR images, resulting respectively in a Dice coefficient of 84.7 ± 5.0%, 85.3 ± 4.8% and 78.3 ± 5.1%, and boundary distance of 1.14 ± 0.49mm, 1.42 ± 0.45mm and 2.27 ± 0.52mm. The obtained results were shown to be superior in comparison to existing deformable model-based segmentation algorithms.

    View details for DOI 10.1109/TMI.2017.2667578

    View details for Web of Science ID 000404981000008

    View details for PubMedID 28207388

  • Using a handheld stereo depth camera to overcome limited field-of-view in simulation imaging for radiation therapy treatment planning MEDICAL PHYSICS Jenkins, C., Xing, L., Yu, A. 2017; 44 (5): 1857-1864

    Abstract

    A correct body contour is essential for reliable treatment planning in radiation therapy. While modern medical imaging technologies provide highly accurate patient modeling, there are times when a patient's anatomy cannot be fully captured or there is a lack of easy access to computed tomography (CT) simulation. Here, we provide a practical solution to the surface contour truncation problem by using a handheld stereo depth camera (HSDC) to obtain the missing surface anatomy and a surface-surface image registration to stich the surface data into the CT dataset for treatment planning.For a subject with truncated simulation CT images, a HSDC is used to capture the surface information of the truncated anatomy. A mesh surface model is created using a software tool provided by the camera manufacturer. A surface-to-surface registration technique is used to merge the mesh model with the CT and fill in the missing surface information thereby obtaining a complete surface model of the subject. To evaluate the accuracy of the proposed approach, experiments were performed with the following steps. First, we selected three previously treated patients and fabricated a phantom mimicking each patient using the corresponding CT images and a 3D printer. Second, we removed part of the CT images of each patient to create hypothetical cases with image truncations. Next, a HSDC was used to image the 3D-printed phantoms and the HSDC-derived surface models were registered with the hypothetically truncated CT images. The contours obtained using the approach were then compared with the ground truth contours derived from the original simulation CT without image truncation. The distance between the two contours was calculated in order to evaluate the accuracy of the method. Finally, the dosimetric impact of the approach is assessed by comparing the volume within the 95% isodose line and global maximum dose (Dmax ) computed based on the two surface contours for the breast case that exhibited the largest contour variation in the treated breast.A systematic strategy of using a 3D HSDC to compensate for missing surface information caused by the truncation of CT images was established. Our study showed that the proposed technique was able to reliably provide the full contours for treatment planning in the case of severe CT image truncation(s). The root-mean-square error for the registration between the aligned HDSC surface model and the ground truth data was found to be 2.1 mm. The average distance between the two models was 0.4 ± 1.7 mm (mean ± SD). Maximum deviations occurred in areas of high concavity or when the skin was close to the couch. The breast tissue covered by 95% isodose line decreased by 3% and Dmax increased by 0.2% with the use of the HSDC model.The use of HSDC for obtaining missing surface data during simulation has a number of advantages, such as, ease of use, low cost, and no additional ionizing radiation. It may provide a clinically practical solution to deal with the longstanding problem of CT image truncations in radiation therapy treatment planning.

    View details for DOI 10.1002/mp.12207

    View details for Web of Science ID 000401154000024

    View details for PubMedID 28295413

  • Harnessing Radioluminescence and Sound to Reveal Molecular Pathology of Atherosclerotic Plaques Zaman, R., Yousefi, S., Long, S., Contag, C., Gambhir, S., Khuri-Yakub, B., Xing, L. SOC NUCLEAR MEDICINE INC. 2017
  • Using measurable dosimetric quantities to characterize the inter-structural tradeoff in inverse planning. Physics in medicine and biology Liu, H., Dong, P., Xing, L. 2017

    Abstract

    Traditional inverse planning relies on the use of weighting factors to balance the conflicting requirements of different structures. The manual trial-and-error determination of the weighting factors has long been recognized as a time-consuming part of treatment planning. The purpose of this work is to develop an inverse planning framework that parameterizes the dosimetric tradeoff among the structures with physically meaningful quantities to simplify the search for clinically sensible plans. In this formalism, instead of using the weighting factors, permissible variation range of the prescription dose or dose volume histogram (DVH) of the involved structures are used to characterize the "importance" of the structures. The inverse planning is then formulated into a convex feasibility problem, called the dosimetric variation-controlled model (DVCM), whose goal is to generate plans with dosimetric or DVH variations of the structures consistent with the pre-specified values. For simplicity, the dosimetric variation range for a structure is extracted from a library of previous cases who possess similar anatomy and prescription. A two-phase procedure (TPP) is designed to solve the model. The first Phase identifies a physically feasible plan to satisfy the prescribed dosimetric variation, and the second phase automatically improves the plan in case there is room for further improvement. The proposed technique is applied to plan two prostate cases and two head-and-neck cases and the results are compared with that obtained using a conventional CVaR approach and with a moment-based optimization scheme. Our results show that the strategy is able to generate clinically sensible plans with little trial and error. In all cases, the TPP generates a very competitive plan as compared to those obtained using the alternative approaches. Particularly, in the planning of one of the head-and-neck case, the TPP leads to a non-trivial improvement in the resultant dose distribution - the fractional volumes receiving a dose above 20 Gy for spinal cord are reduced by more than 40% when compared to the alternative schemes, while maintaining the same PTV coverage. With physically more meaningful modeling of the inter-structural tradeoff, the reported technique enables us to substantially reduce the need for trial-and-error adjustment of the model parameters. The new formalism also opens new opportunities for incorporating prior knowledge to facilitate the treatment planning process.

    View details for DOI 10.1088/1361-6560/aa6fcb

    View details for PubMedID 28447959

  • Segmentation-free x-ray energy spectrum estimation for computed tomography using dual-energy material decomposition JOURNAL OF MEDICAL IMAGING Zhao, W., Xing, L., Zhang, Q., Xie, Q., Niu, T. 2017; 4 (2): 023506

    Abstract

    An x-ray energy spectrum plays an essential role in computed tomography (CT) imaging and related tasks. Because of the high photon flux of clinical CT scanners, most of the spectrum estimation methods are indirect and usually suffer from various limitations. In this study, we aim to provide a segmentation-free, indirect transmission measurement-based energy spectrum estimation method using dual-energy material decomposition. The general principle of this method is to minimize the quadratic error between the polychromatic forward projection and the raw projection to calibrate a set of unknown weights, which are used to express the unknown spectrum together with a set of model spectra. The polychromatic forward projection is performed using material-specific images, which are obtained using dual-energy material decomposition. The algorithm was evaluated using numerical simulations, experimental phantom data, and realistic patient data. The results show that the estimated spectrum matches the reference spectrum quite well and the method is robust. Extensive studies suggest that the method provides an accurate estimate of the CT spectrum without dedicated physical phantom and prolonged workflow. This paper may be attractive for CT dose calculation, artifacts reduction, polychromatic image reconstruction, and other spectrum-involved CT applications.

    View details for DOI 10.1117/1.JMI.4.2.023506

    View details for Web of Science ID 000405944600014

    View details for PubMedID 28680909

    View details for PubMedCentralID PMC5492812

  • Binary moving-blocker-based scatter correction in cone-beam computed tomography with width-truncated projections: proof of concept PHYSICS IN MEDICINE AND BIOLOGY Lee, H., Fahimian, B. P., Xing, L. 2017; 62 (6): 2176-2193

    Abstract

    This paper proposes a binary moving-blocker (BMB)-based technique for scatter correction in cone-beam computed tomography (CBCT). In concept, a beam blocker consisting of lead strips, mounted in front of the x-ray tube, moves rapidly in and out of the beam during a single gantry rotation. The projections are acquired in alternating phases of blocked and unblocked cone beams, where the blocked phase results in a stripe pattern in the width direction. To derive the scatter map from the blocked projections, 1D B-Spline interpolation/extrapolation is applied by using the detected information in the shaded regions. The scatter map of the unblocked projections is corrected by averaging two scatter maps that correspond to their adjacent blocked projections. The scatter-corrected projections are obtained by subtracting the corresponding scatter maps from the projection data and are utilized to generate the CBCT image by a compressed-sensing (CS)-based iterative reconstruction algorithm. Catphan504 and pelvis phantoms were used to evaluate the method's performance. The proposed BMB-based technique provided an effective method to enhance the image quality by suppressing scatter-induced artifacts, such as ring artifacts around the bowtie area. Compared to CBCT without a blocker, the spatial nonuniformity was reduced from 9.1% to 3.1%. The root-mean-square error of the CT numbers in the regions of interest (ROIs) was reduced from 30.2 HU to 3.8 HU. In addition to high resolution, comparable to that of the benchmark image, the CS-based reconstruction also led to a better contrast-to-noise ratio in seven ROIs. The proposed technique enables complete scatter-corrected CBCT imaging with width-truncated projections and allows reducing the acquisition time to approximately half. This work may have significant implications for image-guided or adaptive radiation therapy, where CBCT is often used.

    View details for DOI 10.1088/1361-6560/aa5913

    View details for Web of Science ID 000395801000002

    View details for PubMedID 28079527

  • Robust Estimation of Electron Density From Anatomic Magnetic Resonance Imaging of the Brain Using a Unifying Multi-Atlas Approach. International journal of radiation oncology, biology, physics Ren, S., Hara, W., Wang, L., Buyyounouski, M. K., Le, Q., Xing, L., Li, R. 2017; 97 (4): 849-857

    Abstract

    To develop a reliable method to estimate electron density based on anatomic magnetic resonance imaging (MRI) of the brain.We proposed a unifying multi-atlas approach for electron density estimation based on standard T1- and T2-weighted MRI. First, a composite atlas was constructed through a voxelwise matching process using multiple atlases, with the goal of mitigating effects of inherent anatomic variations between patients. Next we computed for each voxel 2 kinds of conditional probabilities: (1) electron density given its image intensity on T1- and T2-weighted MR images; and (2) electron density given its spatial location in a reference anatomy, obtained by deformable image registration. These were combined into a unifying posterior probability density function using the Bayesian formalism, which provided the optimal estimates for electron density. We evaluated the method on 10 patients using leave-one-patient-out cross-validation. Receiver operating characteristic analyses for detecting different tissue types were performed.The proposed method significantly reduced the errors in electron density estimation, with a mean absolute Hounsfield unit error of 119, compared with 140 and 144 (P<.0001) using conventional T1-weighted intensity and geometry-based approaches, respectively. For detection of bony anatomy, the proposed method achieved an 89% area under the curve, 86% sensitivity, 88% specificity, and 90% accuracy, which improved upon intensity and geometry-based approaches (area under the curve: 79% and 80%, respectively).The proposed multi-atlas approach provides robust electron density estimation and bone detection based on anatomic MRI. If validated on a larger population, our work could enable the use of MRI as a primary modality for radiation treatment planning.

    View details for DOI 10.1016/j.ijrobp.2016.11.053

    View details for PubMedID 28244422

  • Development of an autonomous treatment planning strategy for radiation therapy with effective use of population-based prior data. Medical physics Wang, H., Dong, P., Liu, H., Xing, L. 2017; 44 (2): 389-396

    Abstract

    Current treatment planning remains a costly and labor intensive procedure and requires multiple trial-and-error adjustments of system parameters such as the weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning strategy with effective use of prior knowledge and in a clinically realistic treatment planning platform to facilitate radiation therapy workflow.Our technique consists of three major components: (i) a clinical treatment planning system (TPS); (ii) a formulation of decision-function constructed using an assemble of prior treatment plans; (iii) a plan evaluator or decision-function and an outer-loop optimization independent of the clinical TPS to assess the TPS-generated plan and to drive the search toward a solution optimizing the decision-function. Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines for querying and interacting with the TPS. These subroutines are called back in the outer-loop optimization program to navigate the plan selection process through the solution space iteratively. The utility of the approach is demonstrated by using clinical prostate and head-and-neck cases.An autonomous treatment planning technique with effective use of an assemble of prior treatment plans is developed to automatically maneuver the clinical treatment planning process in the platform of a commercial TPS. The process mimics the decision-making process of a human planner and provides a clinically sensible treatment plan automatically, thus reducing/eliminating the tedious manual trial-and-errors of treatment planning. It is found that the prostate and head-and-neck treatment plans generated using the approach compare favorably with that used for the patients' actual treatments.Clinical inverse treatment planning process can be automated effectively with the guidance of an assemble of prior treatment plans. The approach has the potential to significantly improve the radiation therapy workflow.

    View details for DOI 10.1002/mp.12058

    View details for PubMedID 28133746

  • Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks. Medical physics Ibragimov, B., Xing, L. 2017; 44 (2): 547-557

    Abstract

    Accurate segmentation of organs-at-risks (OARs) is the key step for efficient planning of radiation therapy for head and neck (HaN) cancer treatment. In the work, we proposed the first deep learning-based algorithm, for segmentation of OARs in HaN CT images, and compared its performance against state-of-the-art automated segmentation algorithms, commercial software, and interobserver variability.Convolutional neural networks (CNNs)-a concept from the field of deep learning-were used to study consistent intensity patterns of OARs from training CT images and to segment the OAR in a previously unseen test CT image. For CNN training, we extracted a representative number of positive intensity patches around voxels that belong to the OAR of interest in training CT images, and negative intensity patches around voxels that belong to the surrounding structures. These patches then passed through a sequence of CNN layers that captured local image features such as corners, end-points, and edges, and combined them into more complex high-order features that can efficiently describe the OAR. The trained network was applied to classify voxels in a region of interest in the test image where the corresponding OAR is expected to be located. We then smoothed the obtained classification results by using Markov random fields algorithm. We finally extracted the largest connected component of the smoothed voxels classified as the OAR by CNN, performed dilate-erode operations to remove cavities of the component, which resulted in segmentation of the OAR in the test image.The performance of CNNs was validated on segmentation of spinal cord, mandible, parotid glands, submandibular glands, larynx, pharynx, eye globes, optic nerves, and optic chiasm using 50 CT images. The obtained segmentation results varied from 37.4% Dice coefficient (DSC) for chiasm to 89.5% DSC for mandible. We also analyzed the performance of state-of-the-art algorithms and commercial software reported in the literature, and observed that CNNs demonstrate similar or superior performance on segmentation of spinal cord, mandible, parotid glands, larynx, pharynx, eye globes, and optic nerves, but inferior performance on segmentation of submandibular glands and optic chiasm.We concluded that convolution neural networks can accurately segment most of OARs using a representative database of 50 HaN CT images. At the same time, inclusion of additional information, for example, MR images, may be beneficial to some OARs with poorly visible boundaries.

    View details for DOI 10.1002/mp.12045

    View details for PubMedID 28205307

    View details for PubMedCentralID PMC5383420

  • Asymmetric Waveforms Decrease Lethal Thresholds in High Frequency Irreversible Electroporation Therapies SCIENTIFIC REPORTS Sano, M. B., Fan, R. E., Xing, L. 2017; 7

    Abstract

    Irreversible electroporation (IRE) is a promising non-thermal treatment for inoperable tumors which uses short (50-100 μs) high voltage monopolar pulses to disrupt the membranes of cells within a well-defined volume. Challenges with IRE include complex treatment planning and the induction of intense muscle contractions. High frequency IRE (H-FIRE) uses bursts of ultrashort (0.25-5 μs) alternating polarity pulses to produce more predictable ablations and alleviate muscle contractions associated with IRE. However, H-FIRE generally ablates smaller volumes of tissue than IRE. This study shows that asymmetric H-FIRE waveforms can be used to create ablation volumes equivalent to standard IRE treatments. Lethal thresholds (LT) of 505 V/cm and 1316 V/cm were found for brain cancer cells when 100 μs IRE and 2 μs symmetric H-FIRE waveforms were used. In contrast, LT as low as 536 V/cm were found for 2 μs asymmetric H-FIRE waveforms. Reversible electroporation thresholds were 54% lower than LTs for symmetric waveforms and 33% lower for asymmetric waveforms indicating that waveform symmetry can be used to tune the relative sizes of reversible and irreversible ablation zones. Numerical simulations predicted that asymmetric H-FIRE waveforms are capable of producing ablation volumes which were 5.8-6.3x larger than symmetric H-FIRE waveforms indicating that in vivo investigation of asymmetric waveforms is warranted.

    View details for DOI 10.1038/srep40747

    View details for Web of Science ID 000392345600001

    View details for PubMedID 28106146

    View details for PubMedCentralID PMC5247773

  • Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours PHYSICS IN MEDICINE AND BIOLOGY Li, D., Liu, L., Chen, J., Li, H., Yin, Y., Ibragimov, B., Xing, L. 2017; 62 (1): 272-288

    Abstract

    Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

    View details for DOI 10.1088/1361-6560/62/1/272

    View details for PubMedID 27991439

  • Pixel response-based EPID dosimetry for patient specific QA JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Han, B., Ding, A., Lu, M., Xing, L. 2017; 18 (1): 9-17

    Abstract

    Increasing use of high dose rate, flattening filter free (FFF), and/or small-sized field beams presents a significant challenge to the medical physics community. In this work, we develop a strategy of using a high spatial resolution and high frame rate amorphous silicon flat panel electronic portal imaging device (EPID) for dosimetric measurements of these challenging cases, as well as for conventional external beam therapy. To convert a series of raw EPID-measured radiation field images into water-based dose distribution, a pixel-to-pixel dose-response function of the EPID specific to the linac is essential. The response function was obtained by using a Monte Carlo simulation of the photon transport in the EPID with a comprehensive calibration. After the raw image was converted into the primary incident photon fluence, the fluence was further convolved into a water-based dose distribution of the dynamic field by using a pregenerated pencil-beam kernel. The EPID-based dosimetric measurement technique was validated using beams with and without flattening filter of all energies available in Varian TrueBeam STx™. Both regularly and irregularly shaped fields measured using a PTW 729 ion chamber array in plastic water phantom. The technique was also applied to measure the distribution for a total of 23 treatment plans of different energies to evaluate the accuracy of the proposed approach. The EPID measurements of square fields of 4 × 4 cm2 to 20 × 20 cm2, circular fields of 2-15 cm diameters, rectangular fields of various sizes, and irregular MLC fields were in accordance with measurements using a Farmer chamber and/or ion chamber array. The 2D absolute dose maps generated from EPID raw images agreed with ion chamber measurements to within 1.5% for all fields. For the 23 patient cases examined in this work, the average γ-index passing rate were found to be 99.2 ± 0.6%, 97.4 ± 2.4%, and 72.6 ± 8.4%, respectively, for criterions of 3 mm/3%, 2 mm/2%, and 1 mm/1%. The high spatial resolution and high frame rate EPID provides an accurate and efficient dosimetric tool for QA of modern radiation therapy. Accurate absolute 2D dose maps can be generated from the system for an independent dosimetric verification of treatment delivery.

    View details for DOI 10.1002/acm2.12007

    View details for Web of Science ID 000393176200002

    View details for PubMedCentralID PMC5393354

  • Fully automated quantitative cephalometry using convolutional neural networks. Journal of medical imaging (Bellingham, Wash.) Arik, S. Ö., Ibragimov, B., Xing, L. 2017; 4 (1): 014501-?

    Abstract

    Quantitative cephalometry plays an essential role in clinical diagnosis, treatment, and surgery. Development of fully automated techniques for these procedures is important to enable consistently accurate computerized analyses. We study the application of deep convolutional neural networks (CNNs) for fully automated quantitative cephalometry for the first time. The proposed framework utilizes CNNs for detection of landmarks that describe the anatomy of the depicted patient and yield quantitative estimation of pathologies in the jaws and skull base regions. We use a publicly available cephalometric x-ray image dataset to train CNNs for recognition of landmark appearance patterns. CNNs are trained to output probabilistic estimations of different landmark locations, which are combined using a shape-based model. We evaluate the overall framework on the test set and compare with other proposed techniques. We use the estimated landmark locations to assess anatomically relevant measurements and classify them into different anatomical types. Overall, our results demonstrate high anatomical landmark detection accuracy ([Formula: see text] to 2% higher success detection rate for a 2-mm range compared with the top benchmarks in the literature) and high anatomical type classification accuracy ([Formula: see text] average classification accuracy for test set). We demonstrate that CNNs, which merely input raw image patches, are promising for accurate quantitative cephalometry.

    View details for DOI 10.1117/1.JMI.4.1.014501

    View details for PubMedID 28097213

    View details for PubMedCentralID PMC5220585

  • Recurrent Generative Adversarial Neural Networks for Compressive Imaging Mardani, M., Gong, E., Cheng, J. Y., Pauly, J., Xing, L., IEEE IEEE. 2017
  • Combining deep learning with anatomy analysis for segmentation of portal vein for liver SBRT planning. Physics in medicine and biology Ibragimov, B., Toesca, D., Chang, D., Koong, A., Xing, L. 2017

    Abstract

    Automated segmentation of portal vein (PV) for liver radiotherapy planning is a challenging task due to potentially low vasculature contrast, complex PV anatomy and image artifacts originated from fiducial markers and vasculature stents. In this paper, we propose a novel framework for automated PV segmentation from computed tomography (CT) images. We apply convolutional neural networks (CNN) to learn consistent appearance patterns of PV using a training set of CT images with reference annotations and then enhance PV in previously unseen CT images. Markov Random Fields (MRF) were further used to smooth the CNN enhancement results and remove isolated mis-segmented regions. Finally, CNN-MRF-based enhancement was augmented with PV centerline detection that was based on PV anatomical properties such as tubularity and branch composition. The framework was validated on a clinical database with 72 CT images of patients scheduled to liver stereotactic body radiation therapy. The obtained segmentation accuracy was DSC = 0.83 and η = 1.08 in terms of the median Dice coefficient and mean symmetric surface distance, respectively, when segmentation is encompassed into the PV region of interest. The obtained results indicate that CNN can be used for accurate segmentation of PV and potentially integrated into liver radiation therapy planning.

    View details for PubMedID 28994665

  • Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method IEEE TRANSACTIONS ON MEDICAL IMAGING Zhang, G., Liu, F., Liu, J., Luo, J., Xie, Y., Bai, J., Xing, L. 2017; 36 (1): 225-235

    Abstract

    X-ray luminescence computed tomography (XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. Combining the principles of X-ray excitation of luminescence-based probes and optical signal detection, XLCT naturally fuses functional and anatomical images and provides complementary information for a wide range of applications in biomedical research. In order to improve the data acquisition efficiency of previously developed narrow-beam XLCT, a cone beam XLCT (CB-XLCT) mode is adopted here to take advantage of the useful geometric features of cone beam excitation. Practically, a major hurdle in using cone beam X-ray for XLCT is that the inverse problem here is seriously ill-conditioned, hindering us to achieve good image quality. In this paper, we propose a novel Bayesian method to tackle the bottleneck in CB-XLCT reconstruction. The method utilizes a local regularization strategy based on Gaussian Markov random field to mitigate the ill-conditioness of CB-XLCT. An alternating optimization scheme is then used to automatically calculate all the unknown hyperparameters while an iterative coordinate descent algorithm is adopted to reconstruct the image with a voxel-based closed-form solution. Results of numerical simulations and mouse experiments show that the self-adaptive Bayesian method significantly improves the CB-XLCT image quality as compared with conventional methods.

    View details for DOI 10.1109/TMI.2016.2603843

    View details for Web of Science ID 000392418000020

    View details for PubMedID 27576245

    View details for PubMedCentralID PMC5391999

  • Feasibility study of Compton cameras for x-ray fluorescence computed tomography with humans PHYSICS IN MEDICINE AND BIOLOGY Vernekohl, D., Ahmad, M., Chinn, G., Xing, L. 2016; 61 (24): 8521-8540

    Abstract

    X-ray fluorescence imaging is a promising imaging technique able to depict the spatial distributions of low amounts of molecular agents in vivo. Currently, the translation of the technique to preclinical and clinical applications is hindered by long scanning times as objects are scanned with flux-limited narrow pencil beams. The study presents a novel imaging approach combining x-ray fluorescence imaging with Compton imaging. Compton cameras leverage the imaging performance of XFCT and abolish the need for pencil beam excitation. The study examines the potential of this new imaging approach on the base of Monte-Carlo simulations. In the work, it is first presented that the particular option of slice/fan-beam x-ray excitation has advantages in image reconstruction in regard of processing time and image quality compared to traditional volumetric Compton imaging. In a second experiment, the feasibility of the approach for clinical applications with tracer agents made from gold nano-particles is examined in a simulated lung scan scenario. The high energy of characteristic x-ray photons from gold is advantageous for deep tissue penetration and has lower angular blurring in the Compton camera. It is found that Doppler broadening in the first detector stage of the Compton camera adds the largest contribution on the angular blurring; physically limiting the spatial resolution. Following the analysis of the results from the spatial resolution test, resolutions in the order of one centimeter are achievable with the approach in the center of the lung. The concept of Compton imaging allows one to distinguish to some extent between scattered photons and x-ray fluorescent photons based on their difference in emission position. The results predict that molecular sensitivities down to 240 pM l(-1) for 5 mm diameter lesions at 15 mGy for 50 nm diameter gold nano-particles are achievable. A 45-fold speed up time for data acquisition compared to traditional pencil beam XFCT could be achieved for lung imaging at the cost of a small sensitivity decrease.

    View details for DOI 10.1088/0031-9155/61/24/8521

    View details for Web of Science ID 000388688800007

    View details for PubMedID 27845933

  • A depth-sensing technique on 3D-printed compensator for total body irradiation patient measurement and treatment planning. Medical physics Lee, M., Han, B., Jenkins, C., Xing, L., Suh, T. 2016; 43 (11): 6137-?

    Abstract

    The purpose of total body irradiation (TBI) techniques is to deliver a uniform radiation dose to the entire volume of a patient's body. Due to variations in the thickness of the patient, it is difficult to produce such a uniform dose distribution throughout the body. In many techniques, a compensator is used to adjust the dose delivered to various sections of the patient. The current study aims to develop and validate an innovative method of using depth-sensing cameras and 3D printing techniques for TBI treatment planning and compensator fabrication.A tablet with an integrated depth-sensing camera and motion tracking sensors was used to scan a RANDO™ phantom positioned in a TBI treatment booth to detect and store the 3D surface in a point cloud format. The accuracy of the detected surface was evaluated by comparing extracted body thickness measurements with corresponding measurements from computed tomography (CT) scan images. The thickness, source to surface distance, and off-axis distance of the phantom at different body section were measured for TBI treatment planning. A detailed compensator design was calculated to achieve a uniform dose distribution throughout the phantom. The compensator was fabricated using a 3D printer, silicone molding, and a mixture of wax and tungsten powder. In vivo dosimetry measurements were performed using optically stimulated luminescent detectors.The scan of the phantom took approximately 30 s. The mean error for thickness measurements at each section of phantom relative to CT was 0.48 ± 0.27 cm. The average fabrication error for the 3D-printed compensator was 0.16 ± 0.15 mm. In vivo measurements for an end-to-end test showed that overall dose differences were within 5%.A technique for planning and fabricating a compensator for TBI treatment using a depth camera equipped tablet and a 3D printer was demonstrated to be sufficiently accurate to be considered for further investigation.

    View details for PubMedID 27806603

  • Automatic deformable surface registration for medical applications by radial basis function-based robust point-matching COMPUTERS IN BIOLOGY AND MEDICINE Kim, Y., Na, Y. H., Xing, L., Lee, R., Park, S. 2016; 77: 173-181

    Abstract

    Deformable surface mesh registration is a useful technique for various medical applications, such as intra-operative treatment guidance and intra- or inter-patient study. In this paper, we propose an automatic deformable mesh registration technique. The proposed method iteratively deforms a source mesh to a target mesh without manual feature extraction. Each iteration of the registration consists of two steps, automatic correspondence finding using robust point-matching (RPM) and local deformation using a radial basis function (RBF). The proposed RBF-based RPM algorithm solves the interlocking problems of correspondence and deformation using a deterministic annealing framework with fuzzy correspondence and RBF interpolation. Simulation tests showed promising results, with the average deviations decreasing by factors of 21.2 and 11.9, respectively. In the human model test, the average deviation decreased from 1.72±1.88mm to 0.57±0.66mm. We demonstrate the effectiveness of the proposed method by presenting some medical applications.

    View details for DOI 10.1016/j.compbiomed.2016.07.013

    View details for Web of Science ID 000384866000017

    View details for PubMedID 27567399

    View details for PubMedCentralID PMC5035630

  • Flexible radioluminescence imaging for FDG-guided surgery MEDICAL PHYSICS King, M. T., Jenkins, C. H., Sun, C., Carpenter, C. M., Ma, X., Cheng, K., Quynh-Thu Le, Q. T., Sunwoo, J. B., Cheng, Z., Pratx, G., Xing, L. 2016; 43 (10)

    Abstract

    Flexible radioluminescence imaging (Flex-RLI) is an optical method for imaging (18)F-fluorodeoxyglucose (FDG)-avid tumors. The authors hypothesize that a gadolinium oxysulfide: terbium (GOS:Tb) flexible scintillator, which loosely conforms to the body contour, can enhance tumor signal-to-background ratio (SBR) compared with RLI, which utilizes a flat scintillator. The purpose of this paper is to characterize flex-RLI with respect to alternative modalities including RLI, beta-RLI (RLI with gamma rejection), and Cerenkov luminescence imaging (CLI).The photon sensitivity, spatial resolution, and signal linearity of flex-RLI were characterized with in vitro phantoms. In vivo experiments utilizing 13 nude mice inoculated with the head and neck (UMSCC1-Luc) cell line were then conducted in accordance with the institutional Administrative Panel on Laboratory Animal Care. After intravenous injection of (18)F-FDG, the tumor SBR values for flex-RLI were compared to those for RLI, beta-RLI, and CLI using the Wilcoxon signed rank test.With respect to photon sensitivity, RLI, beta-RLI, and flex-RLI produced 1216.2, 407.0, and 98.6 times more radiance per second than CLI. Respective full-width half maximum values across a 0.5 mm capillary tube were 6.9, 6.4, 2.2, and 1.5 mm, respectively. Flex-RLI demonstrated a near perfect correlation with (18)F activity (r = 0.99). Signal uniformity for flex-RLI improved after more aggressive homogenization of the GOS powder with the silicone elastomer during formulation. In vivo, the SBR value for flex-RLI (median 1.29; interquartile range 1.18-1.36) was statistically greater than that for RLI (1.08; 1.02-1.14; p < 0.01) by 26%. However, there was no statistically significant difference in SBR values between flex-RLI and beta-RLI (p = 0.92). Furthermore, there was no statistically significant difference in SBR values between flex-RLI and CLI (p = 0.11) in a more limited dataset.Flex-RLI provides high quality images with SBRs comparable to those from CLI and beta-RLI in a single 10 s acquisition.

    View details for DOI 10.1118/1.4961745

    View details for PubMedID 27782732

  • Automatic multiorgan segmentation in CT images of the male pelvis using region-specific hierarchical appearance cluster models MEDICAL PHYSICS Li, D., Zang, P., Chai, X., Cui, Y., Li, R., Xing, L. 2016; 43 (10)

    Abstract

    Accurate segmentation of pelvic organs in CT images is of great importance in external beam radiotherapy for prostate cancer. The aim of this studying is to develop a novel method for automatic, multiorgan segmentation of the male pelvis.The authors' segmentation method consists of several stages. First, a pretreatment includes parameterization, principal component analysis (PCA), and an established process of region-specific hierarchical appearance cluster (RSHAC) model which was executed on the training dataset. After the preprocessing, online automatic segmentation of new CT images is achieved by combining the RSHAC model with the PCA-based point distribution model. Fifty pelvic CT from eight prostate cancer patients were used as the training dataset. From another 20 prostate cancer patients, 210 CT images were used for independent validation of the segmentation method.In the training dataset, 15 PCA modes were needed to represent 95% of shape variations of pelvic organs. When tested on the validation dataset, the authors' segmentation method had an average Dice similarity coefficient and mean absolute distance of 0.751 and 0.371 cm, 0.783 and 0.303 cm, 0.573 and 0.604 cm for prostate, bladder, and rectum, respectively. The automated segmentation process took on average 5 min on a personal computer equipped with Core 2 Duo CPU of 2.8 GHz and 8 GB RAM.The authors have developed an efficient and reliable method for automatic segmentation of multiple organs in the male pelvis. This method should be useful for treatment planning and adaptive replanning for prostate cancer radiotherapy. With this method, the physicist can improve the work efficiency and stability.

    View details for DOI 10.1118/1.4962468

    View details for PubMedID 27782723

  • Automating quality assurance of digital linear accelerators using a radioluminescent phosphor coated phantom and optical imaging. Physics in medicine and biology Jenkins, C. H., Naczynski, D. J., Yu, S. S., Yang, Y., Xing, L. 2016; 61 (17): L29-37

    Abstract

    Performing mechanical and geometric quality assurance (QA) tests for medical linear accelerators (LINAC) is a predominantly manual process that consumes significant time and resources. In order to alleviate this burden this study proposes a novel strategy to automate the process of performing these tests. The autonomous QA system consists of three parts: (1) a customized phantom coated with radioluminescent material; (2) an optical imaging system capable of visualizing the incidence of the radiation beam, light field or lasers on the phantom; and (3) software to process the captured signals. The radioluminescent phantom, which enables visualization of the radiation beam on the same surface as the light field and lasers, is placed on the couch and imaged while a predefined treatment plan is delivered from the LINAC. The captured images are then processed to self-calibrate the system and perform measurements for evaluating light field/radiation coincidence, jaw position indicators, cross-hair centering, treatment couch position indicators and localizing laser alignment. System accuracy is probed by intentionally introducing errors and by comparing with current clinical methods. The accuracy of self-calibration is evaluated by examining measurement repeatability under fixed and variable phantom setups. The integrated system was able to automatically collect, analyze and report the results for the mechanical alignment tests specified by TG-142. The average difference between introduced and measured errors was 0.13 mm. The system was shown to be consistent with current techniques. Measurement variability increased slightly from 0.1 mm to 0.2 mm when the phantom setup was varied, but no significant difference in the mean measurement value was detected. Total measurement time was less than 10 minutes for all tests as a result of automation. The system's unique features of a phosphor-coated phantom and fully automated, operator independent self-calibration offer the potential to streamline the QA process for modern LINACs.

    View details for DOI 10.1088/0031-9155/61/17/L29

    View details for PubMedID 27514654

  • Production of Spherical Ablations Using Nonthermal Irreversible Electroporation: A Laboratory Investigation Using a Single Electrode and Grounding Pad. Journal of vascular and interventional radiology Sano, M. B., Fan, R. E., Hwang, G. L., Sonn, G. A., Xing, L. 2016; 27 (9): 1432-1440 e3

    Abstract

    To mathematically model and test ex vivo a modified technique of irreversible electroporation (IRE) to produce large spherical ablations by using a single probe.Computed simulations were performed by using varying voltages, electrode exposure lengths, and tissue types. A vegetable (potato) tissue model was then used to compare ablations created by conventional and high-frequency IRE protocols by using 2 probe configurations: a single probe with two collinear electrodes (2EP) or a single electrode configured with a grounding pad (P+GP). The new P+GP electrode configuration was evaluated in ex vivo liver tissue.The P+GP configuration produced more spherical ablation volumes than the 2EP configuration in computed simulations and tissue models. In prostate tissue, computed simulations predicted ablation volumes at 3,000 V of 1.6 cm(3) for the P+GP configurations, compared with 0.94 cm(3) for the 2EP configuration; in liver tissue, the predicted ablation volumes were 4.7 times larger than those in the prostate. Vegetable model studies verify that the P+GP configuration produces larger and more spherical ablations than those produced by the 2EP. High-frequency IRE treatment of ex vivo liver with the P+GP configuration created a 2.84 × 2.21-cm ablation zone.Computer modeling showed that P+GP configuration for IRE procedures yields ablations that are larger than the 2EP configuration, creating substantial ablation zones with a single electrode placement. When tested in tissue models and an ex vivo liver model, the P+GP configuration created ablation zones that appear to be of clinically relevant size and shape.

    View details for DOI 10.1016/j.jvir.2016.05.032

    View details for PubMedID 27478129

  • Fabrication of a customized bone scaffold using a homemade medical 3D printer for comminuted fractures JOURNAL OF THE KOREAN PHYSICAL SOCIETY Yoon, D., Jung, J., Shin, H., Kim, M., Choe, B., Kim, S., Suh, T. S., Lee, K. S., Xing, L. 2016; 69 (5): 852-857
  • Optimization of rotational arc station parameter optimized radiation therapy. Medical physics Dong, P., Ungun, B., Boyd, S., Xing, L. 2016; 43 (9): 4973-?

    Abstract

    To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites.The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU.Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case.The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.

    View details for DOI 10.1118/1.4960000

    View details for PubMedID 27587028

    View details for PubMedCentralID PMC4975754

  • Early Change in Metabolic Tumor Heterogeneity during Chemoradiotherapy and Its Prognostic Value for Patients with Locally Advanced Non-Small Cell Lung Cancer PLOS ONE Dong, X., Sun, X., Sun, L., Maxim, P. G., Xing, L., Huang, Y., Li, W., Wan, H., Zhao, X., Xing, L., Yu, J. 2016; 11 (6)

    Abstract

    To observe the early change of metabolic tumor heterogeneity during chemoradiotherapy and to determine its prognostic value for patients with locally advanced non-small cell lung cancer (NSCLC).From January 2007 to March 2010, 58 patients with NSCLC were included who were received 18F-fluorodeoxyglucose (18F-FDG) PET/CT before and following 40 Gy radiotherapy with the concurrent cisplatin-based chemotherapy (CCRT). Primary tumor FDG uptake heterogeneity was determined using global and local scale textural features extracted from standardized uptake value (SUV) histogram analysis (coefficient of variation [COV], skewness, kurtosis, area under the curve of the cumulative SUV histogram [AUC-CSH]) and normalized gray-level co-occurrence matrix (contrast, dissimilarity, entropy, homogeneity). SUVmax and metabolic tumor volume (MTV) were also evaluated. Correlations were analyzed between parameters on baseline or during treatments with tumor response, progression-free survival (PFS), and overall survival (OS).Compared with non-responders, responders showed significantly greater pre-treatment COV, contrast and MTV (AUC = 0.781, 0.804, 0.686, respectively). Receiver-operating-characteristic curve analysis showed that early change of tumor textural analysis serves as a response predictor with higher sensitivity (73.2%~92.1%) and specificity (80.0%~83.6%) than baseline parameters. Change in AUC-CSH and dissimilarity during CCRT could also predict response with optimal cut-off values (33.0% and 28.7%, respectively). The patients with greater changes in contrast and AUC-CSH had significantly higher 5-year OS (P = 0.008, P = 0.034) and PFS (P = 0.007, P = 0.039). In multivariate analysis, only change in contrast was found as the independent prognostic factor of PFS (HR 0.476, P = 0.021) and OS (HR 0.519, P = 0.015).The metabolic tumor heterogeneity change during CCRT characterized by global and local scale textural features may be valuable for predicting treatment response and survival for patients with locally advanced NSCLC.

    View details for DOI 10.1371/journal.pone.0157836

    View details for Web of Science ID 000378212000047

    View details for PubMedID 27322376

    View details for PubMedCentralID PMC4913903

  • High Resolution X-ray-Induced Acoustic Tomography SCIENTIFIC REPORTS Xiang, L., Tang, S., Ahmad, M., Xing, L. 2016; 6

    Abstract

    Absorption based CT imaging has been an invaluable tool in medical diagnosis, biology, and materials science. However, CT requires a large set of projection data and high radiation dose to achieve superior image quality. In this letter, we report a new imaging modality, X-ray Induced Acoustic Tomography (XACT), which takes advantages of high sensitivity to X-ray absorption and high ultrasonic resolution in a single modality. A single projection X-ray exposure is sufficient to generate acoustic signals in 3D space because the X-ray generated acoustic waves are of a spherical nature and propagate in all directions from their point of generation. We demonstrate the successful reconstruction of gold fiducial markers with a spatial resolution of about 350 μm. XACT reveals a new imaging mechanism and provides uncharted opportunities for structural determination with X-ray.

    View details for DOI 10.1038/srep26118

    View details for Web of Science ID 000376061600001

    View details for PubMedID 27189746

    View details for PubMedCentralID PMC4870558

  • Dosimetric analysis of isocentrically shielded volumetric modulated arc therapy for locally recurrent nasopharyngeal cancer SCIENTIFIC REPORTS Lu, J., Huang, B., Xing, L., Chang, D. T., Peng, X., Xie, L., Lin, Z., Li, M. 2016; 6

    Abstract

    This study aimed to investigate the dosimetric characteristics of an isocentrically shielded RapidArc (IS-RA) technique for treatment of locally recurrent nasopharyngeal cancer (lrNPC). In IS-RA, the isocenter was placed at the center of the pre-irradiated brainstem (BS)/spinal cord (SC) and the jaws were set to shield the BS/SC while ensuring the target coverage during the whole gantry rotation. For fifteen patients, the IS-RA plans were compared with the conventional RapidArc (C-RA) regarding target coverage, organ-at-risk (OAR) sparing and monitor units (MUs). The relationship between the dose reduction of BS/SC and some geometric parameters including the angle extended by the target with respect to the axis of BS/SC (Ang_BSSC), the minimum distance between the target and BS/SC (Dist_Min) and the target volume were evaluated. The IS-RA reduced the BS/SC doses by approximately 1-4 Gy on average over the C-RA, with more MUs. The IS-RA demonstrated similar target coverage and sparing of other OARs except for slightly improved sparing of optic structures. More dose reduction in the isocentric region was observed in the cases with larger Ang_BSSC or smaller Dist_Min. Our results indicated that the IS-RA significantly improves the sparing of BS/SC without compromising dosimetric requirements of other involved structures for lrNPC.

    View details for DOI 10.1038/srep25959

    View details for PubMedID 27173670

  • Dual-Modal NIR-II Fluorescence and Photoacoustic Imaging of Thyroid Carcinoma Using EGFR-targeted Donor-Acceptor Chromophore Based Nanoprobes Cheng, K., Chen, H., Jenkins, C., Zhang, Z., Sun, Z., Fung, J., Hong, X., Xing, L., Cheng, Z. SOC NUCLEAR MEDICINE INC. 2016
  • A model-based scatter artifacts correction for cone beam CT MEDICAL PHYSICS Zhao, W., Vernekohl, D., Zhu, J., Wang, L., Xing, L. 2016; 43 (4): 1736-1753

    Abstract

    Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging.The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical image guided radiation therapy were performed. Scatter correction in both projection domain and image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated.Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the residual image is reduced from -21.8 to -0.2 HU and 0.7 HU for projection domain and image domain, respectively. The contrast of the in vivo human images is greatly improved after correction.The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.

    View details for DOI 10.1118/1.4943796

    View details for Web of Science ID 000373711000015

    View details for PubMedID 27036571

    View details for PubMedCentralID PMC4798999

  • Using edge-preserving algorithm with non-local mean for significantly improved image-domain material decomposition in dual-energy CT PHYSICS IN MEDICINE AND BIOLOGY Zhao, W., Niu, T., Xing, L., Xie, Y., Xiong, G., Elmore, K., Zhu, J., Wang, L., Min, J. K. 2016; 61 (3): 1332-1351

    Abstract

    Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from to , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.

    View details for DOI 10.1088/0031-9155/61/3/1332

    View details for Web of Science ID 000369517000025

  • Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images RADIOLOGY Cui, Y., Tha, K. K., Terasaka, S., Yamaguchi, S., Wang, J., Kudo, K., Xing, L., Shirato, H., Li, R. 2016; 278 (2): 546-553

    Abstract

    Purpose To develop and independently validate prognostic imaging biomarkers for predicting survival in patients with glioblastoma on the basis of multiregion quantitative image analysis. Materials and Methods This retrospective study was approved by the local institutional review board, and informed consent was waived. A total of 79 patients from two independent cohorts were included. The discovery and validation cohorts consisted of 46 and 33 patients with glioblastoma from the Cancer Imaging Archive (TCIA) and the local institution, respectively. Preoperative T1-weighted contrast material-enhanced and T2-weighted fluid-attenuation inversion recovery magnetic resonance (MR) images were analyzed. For each patient, we semiautomatically delineated the tumor and performed automated intratumor segmentation, dividing the tumor into spatially distinct subregions that demonstrate coherent intensity patterns across multiparametric MR imaging. Within each subregion and for the entire tumor, we extracted quantitative imaging features, including those that fully capture the differential contrast of multimodality MR imaging. A multivariate sparse Cox regression model was trained by using TCIA data and tested on the validation cohort. Results The optimal prognostic model identified five imaging biomarkers that quantified tumor surface area and intensity distributions of the tumor and its subregions. In the validation cohort, our prognostic model achieved a concordance index of 0.67 and significant stratification of overall survival by using the log-rank test (P = .018), which outperformed conventional prognostic factors, such as age (concordance index, 0.57; P = .389) and tumor volume (concordance index, 0.59; P = .409). Conclusion The multiregion analysis presented here establishes a general strategy to effectively characterize intratumor heterogeneity manifested at multimodality imaging and has the potential to reveal useful prognostic imaging biomarkers in glioblastoma. (©) RSNA, 2015 Online supplemental material is available for this article.

    View details for DOI 10.1148/radiol.2015150358

    View details for PubMedID 26348233

  • Novel benzo-bis(1,2,5-thiadiazole) fluorophores for in vivo NIR-II imaging of cancer CHEMICAL SCIENCE Sun, Y., Qu, C., Chen, H., He, M., Tang, C., Shou, K., Hong, S., Yang, M., Jiang, Y., Ding, B., Xiao, Y., Xing, L., Hong, X., Cheng, Z. 2016; 7 (9): 6203-6207

    Abstract

    Optical imaging of diseases represents a highly dynamic and multidisciplinary research area, and second near-infrared window (NIR-II, 1000-1700 nm) imaging is at the forefront of the research on optical imaging techniques. Small-molecule based NIR-II (1000-1700 nm) dyes are highly promising candidates for in vivo molecular imaging because of their high biocompatibility, fast excretion, and high clinical translation ability. However, research reports on small-molecule based NIR-II dyes and probes are rare. Herein, we designed a series of fluorescent compounds (Q1, Q2, Q3, and Q4) and investigated the relationships between their structures and absorption/fluorescence properties. Q4 (maximum emission at 1100 nm) stood out as the dye with the best physical properties and thus was selected as a scaffold for the facile construction of two types of water-soluble and biocompatible NIR-II probes (Q4NPs and SCH1100). Highly specific gastrin-releasing peptide receptor (GRPR) targeted NIR-II imaging of prostate cancer in living mice was achieved using the small-molecule probe SCH1100, which represents the first small peptide based NIR-II probe for targeted cancer imaging. The attractive imaging properties of Q4-based NIR-II probes open up many opportunities for molecular imaging and clinical translation in the unique NIR-II window.

    View details for DOI 10.1039/c6sc01561a

    View details for Web of Science ID 000382488500072

    View details for PubMedCentralID PMC6024204

  • Comparison of a Large Area CZT Detector to a Spectroscopic CdTe Detector for X-ray Fluorescence Computed 'Tomography Vernekohl, D., Streicher, M., Ahmad, M., Xing, L., He, Z., IEEE IEEE. 2016
  • X-ray Fluorescence Computed Tomography with a Compton Camera for a Clinical Application Vernekohl, D., Ahmad, M., Chinn, G., Xing, L., IEEE IEEE. 2016
  • 4DCT and 4D Cone-Beam CT Reconstruction Using Temporal Regularizations GRAPHICS PROCESSING UNIT-BASED HIGH PERFORMANCE COMPUTING IN RADIATION THERAPY Gao, H., Guo, M., Li, R., Xing, L., Jia, Jiang, S. B. 2016: 63–82
  • Minimizing normal tissue dose spillage via broad-range optimization of hundreds of intensity modulated beams for treating multiple brain targets JOURNAL OF RADIOSURGERY AND SBRT Dong, P., Hossain, S., Keeling, V., Ahmad, S., Xing, L., Ma, L. 2016; 4 (2): 107–15

    Abstract

    Variable normal tissue dose and inter-target dose interplay effects have been reported in volumetric modulated arc therapy (VMAT) of multiple brain metastases. In order to minimize such adverse effects, a Broad-Range Optimization of Modulated Beam Approach (BROOMBA) was developed whereby hundreds of intensity-modulated beams surrounding the central axis of the skull were progressively selected and optimized. To investigate technical feasibility and potential dosimetric benefits of BROOMBA, we first developed such an approach on a standalone workstation and then implemented it for a multi-center benchmark case involving 3 to 12 multiple brain metastases. The BROOMBA planning results was compared with VMAT treatment plans of the same case using coplanar and non-coplanar arc beams. We have found that BROOMBA consistently outperformed VMAT plans in terms of low-level normal brain sparing and reduction in the dose interplay effects among the targets. For example, when planning simultaneous treatment of 12 targets, BROOMBA lowered the normal brain dose by as much as 65% versus conventional VMAT treatment plans and the dose interplay effects across 8 Gy to 12 Gy levels was reduced to be negligible. In conclusion, we have demonstrated BROOMBA as a powerful tool for improving the planning quality of multiple brain metastases treatments via modern high-output linear accelerators.

    View details for PubMedID 29296435

  • Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Wang, H., Xing, L. 2016; 17 (6): 189-203

    Abstract

    An autopilot scheme of volumetric-modulated arc therapy (VMAT)/intensity-modulated radiation therapy (IMRT) planning with the guidance of prior knowl-edge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner-TPS interactions as subroutines. The TPS used in this study is a Windows-based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subrou-tines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed "scripting" method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer-loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner-TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process.

    View details for Web of Science ID 000388927500017

    View details for PubMedCentralID PMC5690512

  • Automatic liver contouring for radiotherapy treatment planning PHYSICS IN MEDICINE AND BIOLOGY Li, D., Liu, L., Kapp, D. S., Xing, L. 2015; 60 (19): 7461-7483

    Abstract

    To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems.The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours.The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group are on an average 2.15-2.57%, 2.96-3.23%, and 91.01-97.21% for the CT images with normal appearing livers, 2.28-3.62%, 3.15-4.33%, and 86.14-93.53% for the CT images with hepatocellular carcinoma or liver metastases, and 2.37-3.96%, 3.25-4.57%, and 82.23-89.44% for the 4D-CT images also with hepatocellular carcinoma or liver metastases, respectively.The proposed three-step method can achieve efficient automatic liver contouring for planning CT and 4D-CT images with follow-up treatment planning and should find widespread applications in future treatment planning systems.

    View details for DOI 10.1088/0031-9155/60/19/7461

    View details for Web of Science ID 000364661100006

    View details for PubMedID 26352291

  • Theoretical detection threshold of the proton-acoustic range verification technique. Medical physics Ahmad, M., Xiang, L., Yousefi, S., Xing, L. 2015; 42 (10): 5735-?

    Abstract

    Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits.An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum.The calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz.The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10(6) protons/pulse and beam current.

    View details for DOI 10.1118/1.4929939

    View details for PubMedID 26429247

    View details for PubMedCentralID PMC4567582

  • Experimental validation of L-shell x-ray fluorescence computed tomography imaging: phantom study. Journal of medical imaging (Bellingham, Wash.) Bazalova-Carter, M., Ahmad, M., Xing, L., Fahrig, R. 2015; 2 (4): 043501-?

    Abstract

    Thanks to the current advances in nanoscience, molecular biochemistry, and x-ray detector technology, x-ray fluorescence computed tomography (XFCT) has been considered for molecular imaging of probes containing high atomic number elements, such as gold nanoparticles. The commonly used XFCT imaging performed with K-shell x rays appears to have insufficient imaging sensitivity to detect the low gold concentrations observed in small animal studies. Low energy fluorescence L-shell x rays have exhibited higher signal-to-background ratio and appeared as a promising XFCT mode with greatly enhanced sensitivity. The aim of this work was to experimentally demonstrate the feasibility of L-shell XFCT imaging and to assess its achievable sensitivity. We built an experimental L-shell XFCT imaging system consisting of a miniature x-ray tube and two spectrometers, a silicon drift detector (SDD), and a CdTe detector placed at [Formula: see text] with respect to the excitation beam. We imaged a 28-mm-diameter water phantom with 4-mm-diameter Eppendorf tubes containing gold solutions with concentrations of 0.06 to 0.1% Au. While all Au vials were detectable in the SDD L-shell XFCT image, none of the vials were visible in the CdTe L-shell XFCT image. The detectability limit of the presented L-shell XFCT SDD imaging setup was 0.007% Au, a concentration observed in small animal studies.

    View details for DOI 10.1117/1.JMI.2.4.043501

    View details for PubMedID 26839910

    View details for PubMedCentralID PMC4729219

  • ß-Radioluminescence Imaging: A Comparative Evaluation with Cerenkov Luminescence Imaging. Journal of nuclear medicine : official publication, Society of Nuclear Medicine King, M. T., Carpenter, C. M., Sun, C., Ma, X., Le, Q., Sunwoo, J. B., Cheng, Z., Pratx, G., Xing, L. 2015; 56 (9): 1458-1464

    Abstract

    Cerenkov luminescence imaging (CLI) can provide high-resolution images of (18)F-FDG-avid tumors but requires prolonged acquisition times because of low photon sensitivity. In this study, we proposed a new modality, termed β-radioluminescence imaging (β-RLI), which incorporates a scintillator with a γ-rejection strategy for imaging β particles. We performed a comparative evaluation of β-RLI with CLI in both in vitro and in vivo systems.Using in vitro phantoms, we characterized the photon sensitivity and resolution of CLI and β-RLI. We also conducted a series of in vivo experiments with xenograft mouse models using both amelanotic (A375, UMSCC1-Luc) and melanotic (B16F10-Luc) cell lines. The B16F10 and UMSCC1 cell lines were transfected with the luciferase gene (Luc). CLI was acquired over 300 s, and β-RLI was acquired using two 10-s acquisitions. We correlated (18)F -: FDG activities, as assessed by PET, with tumor radiances for both β-RLI and CLI. We also compared tumor signal-to-background ratios (SBRs) between these modalities for amelanotic and melanotic tumors.For in vitro experiments, the photon sensitivity for β-RLI was 560-fold greater than that for CLI. However, the spatial resolution for β-RLI (4.4 mm) was inferior to that of CLI (1.0 mm). For in vivo experiments, correlations between (18)F-FDG activity and tumor radiance were 0.52 (P < 0.01) for β-RLI, 0.81 (P = 0.01) for amelanotic lesions with CLI, and -0.08 (negative contrast; P = 0.80) for melanotic lesions with CLI. Nine of 13 melanotic lesions had an SBR less than 1 for CLI, despite an SBR greater than 1 among all lesions for β-RLI.β-RLI can produce functional images of both amelanotic and melanotic tumors in a shorter time frame than CLI. Further engineering developments are needed to realize the full clinical potential of this modality.

    View details for DOI 10.2967/jnumed.115.158337

    View details for PubMedID 26205301

  • beta-Radioluminescence Imaging: A Comparative Evaluation with Cerenkov Luminescence Imaging JOURNAL OF NUCLEAR MEDICINE King, M. T., Carpenter, C. M., Sun, C., Ma, X., Quynh-Thu Le, Q. T., Sunwoo, J. B., Cheng, Z., Pratx, G., Xing, L. 2015; 56 (9): 1458-1464

    Abstract

    Cerenkov luminescence imaging (CLI) can provide high-resolution images of (18)F-FDG-avid tumors but requires prolonged acquisition times because of low photon sensitivity. In this study, we proposed a new modality, termed β-radioluminescence imaging (β-RLI), which incorporates a scintillator with a γ-rejection strategy for imaging β particles. We performed a comparative evaluation of β-RLI with CLI in both in vitro and in vivo systems.Using in vitro phantoms, we characterized the photon sensitivity and resolution of CLI and β-RLI. We also conducted a series of in vivo experiments with xenograft mouse models using both amelanotic (A375, UMSCC1-Luc) and melanotic (B16F10-Luc) cell lines. The B16F10 and UMSCC1 cell lines were transfected with the luciferase gene (Luc). CLI was acquired over 300 s, and β-RLI was acquired using two 10-s acquisitions. We correlated (18)F -: FDG activities, as assessed by PET, with tumor radiances for both β-RLI and CLI. We also compared tumor signal-to-background ratios (SBRs) between these modalities for amelanotic and melanotic tumors.For in vitro experiments, the photon sensitivity for β-RLI was 560-fold greater than that for CLI. However, the spatial resolution for β-RLI (4.4 mm) was inferior to that of CLI (1.0 mm). For in vivo experiments, correlations between (18)F-FDG activity and tumor radiance were 0.52 (P < 0.01) for β-RLI, 0.81 (P = 0.01) for amelanotic lesions with CLI, and -0.08 (negative contrast; P = 0.80) for melanotic lesions with CLI. Nine of 13 melanotic lesions had an SBR less than 1 for CLI, despite an SBR greater than 1 among all lesions for β-RLI.β-RLI can produce functional images of both amelanotic and melanotic tumors in a shorter time frame than CLI. Further engineering developments are needed to realize the full clinical potential of this modality.

    View details for DOI 10.2967/jnumed.115.158337

    View details for Web of Science ID 000361153000036

  • Efficient Radioisotope Energy Transfer by Gold Nanoclusters for Molecular Imaging SMALL Volotskova, O., Sun, C., Stafford, J. H., Koh, A. L., Ma, X., Cheng, Z., Cui, B., Pratx, G., Xing, L. 2015; 11 (32): 4002-4008

    Abstract

    Beta-emitting isotopes Fluorine-18 and Yttrium-90 are tested for their potential to stimulate gold nanoclusters conjugated with blood serum proteins (AuNCs). AuNCs excited by either medical radioisotope are found to be highly effective ionizing radiation energy transfer mediators, suitable for in vivo optical imaging. AuNCs synthesized with protein templates convert beta-decaying radioisotope energy into tissue-penetrating optical signals between 620 and 800 nm. Optical signals are not detected from AuNCs incubated with Technetium-99m, a pure gamma emitter that is used as a control. Optical emission from AuNCs is not proportional to Cerenkov radiation, indicating that the energy transfer between the radionuclide and AuNC is only partially mediated by Cerenkov photons. A direct Coulombic interaction is proposed as a novel and significant mechanism of energy transfer between decaying radionuclides and AuNCs.

    View details for DOI 10.1002/smll.201500907

    View details for Web of Science ID 000360226300016

  • Analysis of Long-Term 4-Dimensional Computed Tomography Regional Ventilation After Radiation Therapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS King, M. T., Maxim, P. G., Diehn, M., Loo, B. W., Xing, L. 2015; 92 (3): 683-690

    Abstract

    To determine whether regional ventilation, as measured using 4-dimensional computed tomography (4D-CT), declines after radiation therapy (RT).We analyzed pretreatment 4D-CT scans associated with 2 RT courses. We quantified regional pulmonary function over equivalent dose in 2 Gy (EQD2α/β=3) intervals of 0 to 5 Gy, 5 to 20 Gy, 20 to 40 Gy, and >40 Gy using percentile-normalized intensity-based (VentInt) and Jacobian-based (VentJac) ventilation metrics. We modeled the impact of dose on mean ventilation (Vent¯) and regional tidal volume (rTV: tidal volume [TV] within a dose interval normalized to total lung TV). We also identified clinical and dosimetric factors that affected regional ventilation changes (ΔVent¯ and ΔrTV) after RT for the >20 Gy dose interval.After RT, Vent¯Int exhibited statistically significant dose-dependent declines within the 20 to 40 Gy (-5.0%; P=.03) and >40 Gy (-6.8%; P<.01) intervals. Vent¯Jac exhibited a declining trend after RT only for the >40 Gy interval (-4.6%; P=.07). Factors associated with ΔVent¯Int for the >20 Gy dose interval included airway stenosis progression (P=.03) and gross tumor volume (P=.09). Both rTVInt and rTVJac were associated with small (<2%) but significant declines after RT for 20 to 40 Gy and >40 Gy intervals. Factors associated with declining rTVInt (P<.05) for the >20 Gy dose interval included airway stenosis progression, greater V20 (volume of lung receiving >20 Gy), and smaller fraction of emphysema in V20. The association between the absence of chronic obstructive pulmonary disease and declining rTV trended toward significance (P=.09).Regional ventilation, as measured using 4D-CT, demonstrates a dose-dependent decline after RT. Our results support the use of 4D-CT ventilation imaging for monitoring regional pulmonary function change after RT.

    View details for DOI 10.1016/j.ijrobp.2015.02.037

    View details for Web of Science ID 000355636800032

    View details for PubMedID 25936813

  • Development of an accurate EPID-based output measurement and dosimetric verification tool for electron beam therapy. Medical physics Ding, A., Xing, L., Han, B. 2015; 42 (7): 4190-?

    Abstract

    To develop an efficient and robust tool for output measurement and absolute dose verification of electron beam therapy by using a high spatial-resolution and high frame-rate amorphous silicon flat panel electronic portal imaging device (EPID).The dosimetric characteristics of the EPID, including saturation, linearity, and ghosting effect, were first investigated on a Varian Clinac 21EX accelerator. The response kernels of the individual pixels of the EPID to all available electron energies (6, 9, 12, 16, and 20 MeV) were calculated by using Monte Carlo (MC) simulations, which formed the basis to deconvolve an EPID raw images to the incident electron fluence map. The two-dimensional (2D) dose distribution at reference depths in water was obtained by using the constructed fluence map with a MC simulated pencil beam kernel with consideration of the geometric and structural information of the EPID. Output factor measurements were carried out with the EPID at a nominal source-surface distance of 100 cm for 2 × 2, 3 × 3, 6 × 6, 10 × 10, and 15 × 15 cm(2) fields for all available electron energies, and the results were compared with that measured in a solid water phantom using film and a Farmer-type ion chamber. The dose distributions at a reference depth specific to each energy and the flatness and symmetry of the 10 × 10 cm(2) electron beam were also measured using EPID, and the results were compared with ion chamber array and water scan measurements. Finally, three patient cases with various field sizes and irregular cutout shapes were also investigated.EPID-measured dose changed linearly with the monitor units and showed little ghosting effect for dose rate up to 600 MU/min. The flatness and symmetry measured with the EPID were found to be consistent with ion chamber array and water scan measurements. The EPID-measured output factors for standard square fields of 2 × 2, 3 × 3, 6 × 6, 10 × 10, 15 × 15 cm(2) agreed with film and ion chamber measurements. The average discrepancy between EPID and ion chamber/film measurements was 0.81% ± 0.60% (SD) and 1.34% ± 0.75%, respectively. For the three clinical cases, the difference in output between the EPID- and ion chamber array measured values was found to be 1.13% ± 0.11%, 0.54% ± 0.10%, and 0.74% ± 0.11%, respectively. Furthermore, the γ-index analysis showed an excellent agreement between the EPID- and ion chamber array measured dose distributions: 100% of the pixels passed the criteria of 3%/3 mm. When the γ-index was set to be 2%/2 mm, the pass rate was found to be 99.0% ± 0.07%, 98.2% ± 0.14%, and 100% for the three cases.The EPID dosimetry system developed in this work provides an accurate and reliable tool for routine output measurement and dosimetric verification of electron beam therapy. Coupled with its portability and ease of use, the proposed system promises to replace the current film-based approach for fast and reliable assessment of small and irregular electron field dosimetry.

    View details for DOI 10.1118/1.4922400

    View details for PubMedID 26133618

    View details for PubMedCentralID PMC4474956

  • MO-FG-303-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Automating LINAC QA: Design and Testing of An Image Acquisition and Processing System Utilizing a Combination of Radioluminescent Phosphors, Embedded X-Ray Markers and Optical Measurements. Medical physics Jenkins, C., Naczynski, D., Yu, S., Xing, L. 2015; 42 (6): 3566-?

    Abstract

    The recent development of phosphors to visualize radiation beams from linear accelerators (LINAC) offers a unique opportunity for evaluating radiation fields within the context of the treatment space. The purpose of this study was to establish an automated, self-calibrating prototype system for performing quality assurance (QA) measurements.A thin layer of Gd₂O₂S:Tb phosphor and fiducial markers were embedded on several planar faces of a custom-designed phantom. The phantom was arbitrarily placed near iso-center on the couch of a LINAC equipped with on-board megavoltage (MV) and kilovoltage (kV) imagers. A plan consisting of several beams and integrated image acquisitions was delivered. Images of the phantom were collected throughout the delivery. Salient features, such as fiducials, crosshairs and beam edges were then extracted from these images used to calibrate the system, adjust for variations in phantom placement, and perform measurements. Beam edges were visualized by imaging the light generated by the phosphor on the phantom enabling direct comparison with the light field and laser locations. Registration of MV, kV and optical image data was performed using the embedded fiducial markers, enabling comparison of imaging center locations. Measurements specified by TG-142 were calculated and compared with those obtained from a commercially available QA system.The system was able to automatically extract the location of the fiducials, lasers, light field and radiation field from the acquired images regardless of phantom positioning. It was also able to automatically identify the locations of fiducial markers on kV and MV images. All collected measurements were within TG-142 guidelines. The difference between the prototype and commercially available system were less than 0.2 mm.The prototype system demonstrated the capability of accurately and autonomously evaluating various TG-142 parameters independent of operator input and phantom setup.

    View details for DOI 10.1118/1.4925414

    View details for PubMedID 26128711

  • Augmenting Atlas-Based Segmentation by Incorporating Image Features Proximal to the Atlas Contours Li, D., Liu, L., Kapp, D. S., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2015: 3294–95
  • Automating Liver Segmentation Via Combined Global and Local Optimization Li, D., Wang, J., Kapp, D. S., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2015: 3294
  • WE-AB-BRB-02: Development of a Micro-Sized Dosimeter for Real-Time Dose Monitoring and Small Field Dosimetry. Medical physics Volotskova, O., Jenkins, C., Fahimian, B., Xing, L. 2015; 42 (6): 3649-?

    Abstract

    To investigate a miniature optical dosimeter for real-time, high-resolution dosimetry, and explore its potential applications for in vivo measurements and small field dosimetry.A micro-sized hemispherical (400 µm radius) scintillating detector was constructed from lanthanide activated phosphors doped with Europium (GOS:Eu) and encapsulated in a 17 gauge plastic catheter. A photon counting PMT and CCD-chip spectrometer were used to detect signals emitted from the detector. A single band-passing spectral approach (630nm) was implemented to discriminate the micro-phosphor optical signal from background signals (Cerenkov radiation) in the optical fiber. To test real-time monitoring capabilities, a 3D-printed phantom was used to detect an 192Ir HDR brachytherapy source at locations ranging from 1 to 4 cm radially and 12 cm along the travel axis of the HDR wire. To test the application of the micro-sized detector for small field dosimetry, the linearity of detector was characterized through irradiation of 6MV photon beam at dose-rates ranging from 100 to 600 MU, and the effect of field size was characterized through detections of beams ranging from 30×30 to 1×1 cm2 size.With a 1 second integration time for the spectrometer, the recorded measurements indicated that the micro-sized detector allowed accurate detection of source position at distances of up to 6 cm along the axis of travel in water. EB measurements showed that the detected signal was linearly correlated with dose rate (R^2 = 0.99). The crossbeam profile was determined with a step size of ∼500 µm.Miniaturization of optical dosimeters is shown to be possible through the construction of lanthanide activated doped phosphors detectors. The small size of the detector makes it amenable to a variety of applications, including real-time dose delivery verification during HDR brachytherapy and EB beam calibrations in small fields.

    View details for DOI 10.1118/1.4925843

    View details for PubMedID 26129140

  • TU-CD-304-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Trajectory Modulated Arc Therapy: Development of Novel Arc Delivery Techniques Integrating Dynamic Table Motion for Extended Volume Treatments. Medical physics Chin, E., Otto, K., Hoppe, R., Million, L., Loo, B., Koong, A., Xing, L., Hsu, A., Fahimian, B. 2015; 42 (6): 3598-?

    Abstract

    Integration of coordinated robotic table motion with inversely-planned arc delivery has the potential to resolve table-top delivery limitations of large-field treatments such as Total Body Irradiation (TBI), Total Lymphoid Irradiation (TLI), and Cranial-Spinal Irradiation (CSI). We formulate the foundation for Trajectory Modulated Arc Therapy (TMAT), and using Varian Developer Mode capabilities, experimentally investigate its practical implementation for such techniques.A MATLAB algorithm was developed for inverse planning optimization of the table motion, MLC positions, and gantry motion under extended-SSD geometry. To maximize the effective field size, delivery trajectories for TMAT TBI were formed with the table rotated at 270° IEC and dropped vertically to 152.5cm SSD. Preliminary testing of algorithm parameters was done through retrospective planning analysis. Robotic delivery was programmed using custom XML scripting on the TrueBeam Developer Mode platform. Final dose was calculated using the Eclipse AAA algorithm. Initial verification of delivery accuracy was measured using OSLDs on a solid water phantom of varying thickness.A comparison of DVH curves demonstrated that dynamic couch motion irradiation was sufficiently approximated by static control points spaced in intervals of less than 2cm. Optimized MLC motion decreased the average lung dose to 68.5% of the prescription dose. The programmed irradiation integrating coordinated table motion was deliverable on a TrueBeam STx linac in 6.7 min. With the couch translating under an open 10cmx20cm field angled at 10°, OSLD measurements along the midline of a solid water phantom at depths of 3, 5, and 9cm were within 3% of the TPS AAA algorithm with an average deviation of 1.2%.A treatment planning and delivery system for Trajectory Modulated Arc Therapy of extended volumes has been established and experimentally demonstrated for TBI. Extension to other treatment techniques such as TLI and CSI is readily achievable through the developed platform. Grant Funding by Varian Medical Systems.

    View details for DOI 10.1118/1.4925570

    View details for PubMedID 26128865

  • SU-F-BRB-11: An Integrated Alternating Direction Method of Multipliers for Treatment Planning Optimization. Medical physics Zarepisheh, M., Ye, Y., Xing, L. 2015; 42 (6): 3532-?

    Abstract

    To propose a new parallel-friendly optimization algorithm, based on alternating direction method of multipliers (ADMM), for solving optimization problems emerging in treatment planning and imagingADMM, emerging as a powerful tool for distributed optimization, is employed here for IMRT treatment planning. We modify the existing ADMM by integrating that with two optimization techniques known as Barzilai-Borwein gradient method and line search. We apply original and integrated ADMM, with various penalty parameter values, on three IMRT treatment planning cases and we compare their performance. Each algorithm terminates once it found a solution within the relative error of 1E-4 from the optimal solution. We also compare the performance of original and integrated ADMM against the commercial optimization software CPLEX.Our experiments on three different cancer sites (prostate, head and neck, and GYN) indicate that integrated ADMM is much faster than original ADMM (5.8 times faster on average). Moreover, while the performance of original ADMM heavily depends on the selected penalty parameter, integrated ADMM performs very robust against the penalty parameter. Compared to the commercial software CPLEX, integrated ADMM turns out to be around 4-7 times faster.Integrated ADMM is a very efficient optimization algorithm to cope with the large-scale optimization problems. It is a parallel-friendly optimization algorithm and provides an idea platform for cloud-based treatment planning and imaging.

    View details for DOI 10.1118/1.4925206

    View details for PubMedID 26128506

  • TH-AB-204-09: High-Sensitivity L-Shell X-Ray Fluorescence CT Imaging of Gold. Medical physics Bazalova-Carter, M., Ahmad, M., Xing, L., Fahrig, R. 2015; 42 (6): 3715-?

    Abstract

    To experimentally demonstrate the feasibility of L-shell x-ray fluorescence CT (XFCT) imaging of gold contrast.We have built an experimental L-shell XFCT imaging system consisting of two photon-counting detectors, a silicon drift detector (SDD) and a CdTe detector, a miniature x-ray tube, and a programmable translation/rotation stage. A 2.8-mm diameter water phantom containing 4-mm vials with gold solutions of 0.06%, 0.08%, and 0.1% Au located at 4mm depth was constructed. The phantom was imaged with the L-shell XFCT system in 1st generation CT geometry with a 1-mm 50-kV x-ray beam. XFCT data was acquired with both detectors placed at ±120° with respect to the excitation beam at 30 translation and 36 rotation steps. L-shell XFCT images were reconstructed with maximum-likelihood expectation-maximization using gold Lα and Lβ fluorescence x-rays for both detectors.SDD L- shell x-ray fluorescence (XRF) signal was approximately 13 times higher than CdTe XRF signal due to the higher measured SDD energy resolution of 220eV @ 14keV compared to the CdTe energy resolution of 660eV. While all 0.06-0.1% Au vials were detectable in the SDD L-shell XFCT image, none of the vials were visible in the CdTe L-shell XFCT image. The contrast-to-noise ratio of the 0.1% Au vial was 87.1 and 3.2 in the SDD and CdTe L-shell XFCT images, respectively. SDD L-shell XFCT signal was linear with Au concentration (R2>0.99). The detectability limits of the presented L-shell XFCT imaging setup were 0.007% and 0.126% Au for L-shell XFCT imaging performed with the SDD and CdTe detector, respectively.We have demonstrated the feasibility of L- shell XFCT imaging of gold located at shallow depths inside a small animal sized phantom. The very high sensitivity of L-shell XFCT, permitting detection of Au concentrations as low as 0.06%, has not previously been achieved experimentally using conventional K-shell XFCT.

    View details for DOI 10.1118/1.4926176

    View details for PubMedID 26129475

  • TH-AB-204-11: X-Ray Fluorescence CT Induced by Proton Beam: Experiments and Simulations. Medical physics Bazalova-Carter, M., Ahmad, M., Matsuura, T., Takao, S., Matsuo, Y., Fahrig, R., Shirato, H., Umegaki, K., Xing, L. 2015; 42 (6): 3716-?

    Abstract

    To demonstrate the feasibility of x-ray fluorescence computed tomography induced with proton beams (pXFCT) for imaging of gold contrast agent by means of experiments and Monte Carlo (MC) simulations.A 7-cm diameter water phantom containing 2.2-cm diameter vials filled with gold solutions of 3-5% Au (percent weight concentration) was imaged with pXFCT using a 7-mm FWHM 220-MeV proton beam and a 3×3mm(2) CdTe photon-counting detector. The phantom was imaged in 1st generation CT scanner geometry using a programmable rotation/translation stage and 21 translation steps separated by 3.3 mm and 36 rotation steps in 10° intervals. Each of the 756 x-ray spectra was acquired for 20 s using 5×10(1)⁰ incident protons with the CdTe detector placed at 45 cm from the isocenter and at 90° with respect to the proton beam. The 220 MeV proton beam was stopped in a solid water beam dump and the total imaging time was 4.2 hours. The experimental pXFCT data acquisition geometry was modeled based on the actual and a simplified geometry with the TOPAS MC code. pXFCT images were reconstructed based on experimental and MC-simulated x-ray spectra with filtered back-projection using Kα peaks of gold.All gold vials were visible in both the experimental and simulated pXFCT images. Contrast-to-noise ratio (CNR) of the 3% Au vial was 5.8 and 11.5 in the experimental and simulated pXFCT image, respectively. pXFCT detection limit of the experimental setup was determined to be 1.8% Au, which was twice as high as the MC-simulated detection limit. Further MC simulations revealed that x-ray scatter from the beam dump was the main contribution to x-ray fluorescence signal contamination.We have demonstrated the feasibility of proton-induced XFCT imaging of gold. We anticipate that pXFCT imaging sensitivity will be improved in an optimized pXFCT imaging system utilizing beam collimation.

    View details for DOI 10.1118/1.4926178

    View details for PubMedID 26129479

  • Strained Cyclooctyne as a Molecular Platform for Construction of Multimodal Imaging Probes ANGEWANDTE CHEMIE-INTERNATIONAL EDITION Sun, Y., Ma, X., Cheng, K., Wu, B., Duan, J., Chen, H., Bu, L., Zhang, R., Hu, X., Deng, Z., Xing, L., Hong, X., Cheng, Z. 2015; 54 (20): 5981-5984

    Abstract

    Small-molecule-based multimodal and multifunctional imaging probes play prominent roles in biomedical research and have high clinical translation ability. A novel multimodal imaging platform using base-catalyzed double addition of thiols to a strained internal alkyne such as bicyclo[6.1.0]nonyne has been established in this study, thus allowing highly selective assembly of various functional units in a protecting-group-free manner. Using this molecular platform, novel dual-modality (PET and NIRF) uPAR-targeted imaging probe: (64)Cu-CHS1 was prepared and evaluated in U87MG cells and tumor-bearing mice models. The excellent PET/NIRF imaging characteristics such as good tumor uptake (3.69%ID/g at 2 h post-injection), high tumor contrast, and specificity were achieved in the small-animal models. These attractive imaging properties make (64)Cu-CHS1 a promising probe for clinical use.

    View details for DOI 10.1002/anie.201500941

    View details for Web of Science ID 000354255400031

    View details for PubMedID 25800807

  • Scintillating balloon-enabled fiber-optic system for radionuclide imaging of atherosclerotic plaques. Journal of nuclear medicine Zaman, R. T., Kosuge, H., Carpenter, C., Sun, C., McConnell, M. V., Xing, L. 2015; 56 (5): 771-777

    Abstract

    Atherosclerosis underlies coronary artery disease, the leading cause of death in the United States and worldwide. Detection of coronary plaque inflammation remains challenging. In this study, we developed a scintillating balloon-enabled fiber-optic radionuclide imaging (SBRI) system to improve the sensitivity and resolution of plaque imaging using (18)F-FDG, a marker of vascular inflammation, and tested it in a murine model.The fiber-optic system uses a Complementary Metal-Oxide Silicon (CMOS) camera with a distal ferrule terminated with a wide-angle lens. The novelty of this system is a scintillating balloon in the front of the wide-angle lens to image light from the decay of (18)F-FDG emission signal. To identify the optimal scintillating materials with respect to resolution, we calculated the modulation transfer function of yttrium-aluminum-garnet doped with cerium, anthracene, and calcium fluoride doped with europium (CaF2:Eu) phosphors using an edge pattern and a thin-line optical phantom. The scintillating balloon was then fabricated from 10 mL of silicone RTV catalyst mixed with 1 mL of base and 50 mg of CaF2:Eu per mL. The addition of a lutetium oxyorthosilicate scintillating crystal (500 μm thick) to the balloon was also investigated. The SBRI system was tested in a murine atherosclerosis model: carotid-ligated mice (n = 5) were injected with (18)F-FDG, followed by ex vivo imaging of the macrophage-rich carotid plaques and nonligated controls. Confirmatory imaging of carotid plaques and controls was also performed by an external optical imaging system and autoradiography.Analyses of the different phosphors showed that CaF2:Eu enabled the best resolution of 1.2 μm. The SBRI system detected almost a 4-fold-higher radioluminescence signal from the ligated left carotid artery than the nonligated right carotid: 1.63 × 10(2) ± 4.01 × 10(1) vs. 4.21 × 10(1) ± 2.09 × 10(0) (photon counts), P = 0.006. We found no significant benefit to adding a scintillating crystal to the balloon: 1.65 × 10(2) ± 4.07 × 10(1) vs. 4.44 × 10(1) ± 2.17 × 10(0) (photon counts), P = 0.005. Both external optical imaging and autoradiography confirmed the high signal from the (18)F-FDG in carotid plaques versus controls.This SBRI system provides high-resolution and sensitive detection of (18)F-FDG uptake by murine atherosclerotic plaques.

    View details for DOI 10.2967/jnumed.114.153239

    View details for PubMedID 25858046

  • Optimized Detector Angular Configuration Increases the Sensitivity of X-ray Fluorescence Computed Tomography (XFCT) IEEE TRANSACTIONS ON MEDICAL IMAGING Ahmad, M., Bazalova-Carter, M., Fahrig, R., Xing, L. 2015; 34 (5): 1140-1147

    Abstract

    In this work, we demonstrated that an optimized detector angular configuration based on the anisotropic energy distribution of background scattered X-rays improves X-ray fluorescence computed tomography (XFCT) detection sensitivity. We built an XFCT imaging system composed of a bench-top fluoroscopy X-ray source, a CdTe X-ray detector, and a phantom motion stage. We imaged a 6.4-cm-diameter phantom containing different concentrations of gold solution and investigated the effect of detector angular configuration on XFCT image quality. Based on our previous theoretical study, three detector angles were considered. The X-ray fluorescence detector was first placed at 145 (°) (approximating back-scatter) to minimize scatter X-rays. XFCT image quality was compared to images acquired with the detector at 60 (°) (forward-scatter) and 90 (°) (side-scatter). The datasets for the three different detector positions were also combined to approximate an isotropically arranged detector. The sensitivity was optimized with detector in the 145 (°) back-scatter configuration counting the 78-keV gold Kβ1 X-rays. The improvement arose from the reduced energy of scattered X-ray at the 145 (°) position and the large energy separation from gold K β1 X-rays. The lowest detected concentration in this configuration was 2.5 mgAu/mL (or 0.25% Au with SNR = 4.3). This concentration could not be detected with the 60 (°) , 90 (°) , or isotropic configurations (SNRs = 1.3, 0, 2.3, respectively). XFCT imaging dose of 14 mGy was in the range of typical clinical X-ray CT imaging doses. To our knowledge, the sensitivity achieved in this experiment is the highest in any XFCT experiment using an ordinary bench-top X-ray source in a phantom larger than a mouse ( > 3 cm).

    View details for DOI 10.1109/TMI.2014.2376813

    View details for Web of Science ID 000353899600011

    View details for PubMedID 25474808

  • Beam's-eye-view dosimetrics (BEVD) guided rotational station parameter optimized radiation therapy (SPORT) planning based on reweighted total-variation minimization PHYSICS IN MEDICINE AND BIOLOGY Kim, H., Li, R., Lee, R., Xing, L. 2015; 60 (5): N71-N82

    Abstract

    Conventional VMAT optimizes aperture shapes and weights at uniformly sampled stations, which is a generalization of the concept of a control point. Recently, rotational station parameter optimized radiation therapy (SPORT) has been proposed to improve the plan quality by inserting beams to the regions that demand additional intensity modulations, thus formulating nonuniform beam sampling. This work presents a new rotational SPORT planning strategy based on reweighted total-variation (TV) minimization (min.), using beam’s-eye-view dosimetrics (BEVD) guided beam selection. The convex programming based reweighted TV min. assures the simplified fluence-map, which facilitates single-aperture selection at each station for single-arc delivery. For the rotational arc treatment planning and non-uniform beam angle setting, the mathematical model needs to be modified by additional penalty term describing the fluence-map similarity and by determination of appropriate angular weighting factors. The proposed algorithm with additional penalty term is capable of achieving more efficient and deliverable plans adaptive to the conventional VMAT and SPORT planning schemes by reducing the dose delivery time about 5 to 10 s in three clinical cases (one prostate and two head-and-neck (HN) cases with a single and multiple targets). The BEVD guided beam selection provides effective and yet easy calculating methodology to select angles for denser, non-uniform angular sampling in SPORT planning. Our BEVD guided SPORT treatment schemes improve the dose sparing to femoral heads in the prostate and brainstem, parotid glands and oral cavity in the two HN cases, where the mean dose reduction of those organs ranges from 0.5 to 2.5 Gy. Also, it increases the conformation number assessing the dose conformity to the target from 0.84, 0.75 and 0.74 to 0.86, 0.79 and 0.80 in the prostate and two HN cases, while preserving the delivery efficiency, relative to conventional single-arc VMAT plans.

    View details for DOI 10.1088/0031-9155/60/5/N71

    View details for PubMedID 25675281

  • Optimization approaches to volumetric modulated arc therapy planning MEDICAL PHYSICS Unkelbach, J., Bortfeld, T., Craft, D., Alber, M., Bangert, M., Bokrantz, R., Chen, D., Li, R., Xing, L., Men, C., Nill, S., Papp, D., Romeijn, E., Salari, E. 2015; 42 (3): 1367-1377

    Abstract

    Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed.

    View details for DOI 10.1118/1.4908224

    View details for Web of Science ID 000350661500022

    View details for PubMedID 25735291

  • Oral administration of aflatoxin G(1) induces chronic alveolar inflammation associated with lung tumorigenesis TOXICOLOGY LETTERS Liu, C., Shen, H., Yi, L., Shao, P., Soulika, A. M., Meng, X., Xing, L., Yan, X., Zhang, X. 2015; 232 (3): 547-556

    Abstract

    Our previous studies showed oral gavage of aflatoxin G₁ (AFG₁) induced lung adenocarcinoma in NIH mice. We recently found that a single intratracheal administration of AFG₁ caused chronic inflammatory changes in rat alveolar septum. Here, we examine whether oral gavage of AFG₁ induces chronic lung inflammation and how it contributes to carcinogenesis. We evaluated chronic lung inflammatory responses in Balb/c mice after oral gavage of AFG₁ for 1, 3 and 6 months. Inflammatory responses were heightened in the lung alveolar septum, 3 and 6 months after AFG₁ treatment, evidenced by increased macrophages and lymphocytes infiltration, up-regulation of NF-κB and p-STAT3, and cytokines production. High expression levels of superoxide dismutase (SOD-2) and hemoxygenase-1 (HO-1), two established markers of oxidative stress, were detected in alveolar epithelium of AFG₁-treated mice. Promoted alveolar type II cell (AT-II) proliferation in alveolar epithelium and angiogenesis, as well as increased COX-2 expression were also observed in lung tissues of AFG₁-treated mice. Furthermore, we prolonged survival of the mice in the above model for another 6 months to examine the contribution of AFG₁-induced chronic inflammation to lung tumorigenesis. Twelve months later, we observed that AFG₁ induced alveolar epithelial hyperplasia and adenocarcinoma in Balb/c mice. Up-regulation of NF-κB, p-STAT3, and COX-2 was also induced in lung adenocarcinoma, thus establishing a link between AFG₁-induced chronic inflammation and lung tumorigenesis. This is the first study to show that oral administration of AFG₁ could induce chronic lung inflammation, which may provide a pro-tumor microenvironment to contribute to lung tumorigenesis.

    View details for DOI 10.1016/j.toxlet.2014.11.002

    View details for Web of Science ID 000348200800001

    View details for PubMedID 25445582

  • Proton-induced x-ray fluorescence CT imaging. Medical physics Bazalova-Carter, M., Ahmad, M., Matsuura, T., Takao, S., Matsuo, Y., Fahrig, R., Shirato, H., Umegaki, K., Xing, L. 2015; 42 (2): 900-?

    Abstract

    To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations.First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%-5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm(2) CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%-5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data.A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R(2) > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images.Proton-induced x-ray fluorescence CT imaging of 3%-5% gold solutions in a small animal sized water phantom has been demonstrated for the first time by means of experiments and MC simulations.

    View details for DOI 10.1118/1.4906169

    View details for PubMedID 25652502

    View details for PubMedCentralID PMC4312343

  • Simultaneous beam sampling and aperture shape optimization for SPORT. Medical physics Zarepisheh, M., Li, R., Ye, Y., Xing, L. 2015; 42 (2): 1012-?

    Abstract

    Station parameter optimized radiation therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in which the station parameters of a delivery system, such as aperture shape and weight, couch position/angle, gantry/collimator angle, can be optimized simultaneously. SPORT promises to deliver remarkable radiation dose distributions in an efficient manner, yet there exists no optimization algorithm for its implementation. The purpose of this work is to develop an algorithm to simultaneously optimize the beam sampling and aperture shapes.The authors build a mathematical model with the fundamental station point parameters as the decision variables. To solve the resulting large-scale optimization problem, the authors devise an effective algorithm by integrating three advanced optimization techniques: column generation, subgradient method, and pattern search. Column generation adds the most beneficial stations sequentially until the plan quality improvement saturates and provides a good starting point for the subsequent optimization. It also adds the new stations during the algorithm if beneficial. For each update resulted from column generation, the subgradient method improves the selected stations locally by reshaping the apertures and updating the beam angles toward a descent subgradient direction. The algorithm continues to improve the selected stations locally and globally by a pattern search algorithm to explore the part of search space not reachable by the subgradient method. By combining these three techniques together, all plausible combinations of station parameters are searched efficiently to yield the optimal solution.A SPORT optimization framework with seamlessly integration of three complementary algorithms, column generation, subgradient method, and pattern search, was established. The proposed technique was applied to two previously treated clinical cases: a head and neck and a prostate case. It significantly improved the target conformality and at the same time critical structure sparing compared with conventional intensity modulated radiation therapy (IMRT). In the head and neck case, for example, the average PTV coverage D99% for two PTVs, cord and brainstem max doses, and right parotid gland mean dose were improved, respectively, by about 7%, 37%, 12%, and 16%.The proposed method automatically determines the number of the stations required to generate a satisfactory plan and optimizes simultaneously the involved station parameters, leading to improved quality of the resultant treatment plans as compared with the conventional IMRT plans.

    View details for DOI 10.1118/1.4906253

    View details for PubMedID 25652514

  • Independent calculation of monitor units for VMAT and SPORT. Medical physics Chen, X., Bush, K., Ding, A., Xing, L. 2015; 42 (2): 918-?

    Abstract

    Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT).The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms.For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation.A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

    View details for DOI 10.1118/1.4906185

    View details for PubMedID 25652504

    View details for PubMedCentralID PMC4312348

  • X-ray-Induced Shortwave Infrared Biomedical Imaging Using Rare-Earth Nanoprobes. Nano letters Naczynski, D. J., Sun, C., Türkcan, S., Jenkins, C., Koh, A. L., Ikeda, D., Pratx, G., Xing, L. 2015; 15 (1): 96-102

    Abstract

    Shortwave infrared (SWIR or NIR-II) light provides significant advantages for imaging biological structures due to reduced autofluorescence and photon scattering. Here, we report on the development of rare-earth nanoprobes that exhibit SWIR luminescence following X-ray irradiation. We demonstrate the ability of X-ray-induced SWIR luminescence (X-IR) to monitor biodistribution and map lymphatic drainage. Our results indicate X-IR imaging is a promising new modality for preclinical applications and has potential for dual-modality molecular disease imaging.

    View details for DOI 10.1021/nl504123r

    View details for PubMedID 25485705

    View details for PubMedCentralID PMC4296927

  • Monitoring external beam radiotherapy using real-time beam visualization. Medical physics Jenkins, C. H., Naczynski, D. J., Yu, S. S., Xing, L. 2015; 42 (1): 5-?

    Abstract

    To characterize the performance of a novel radiation therapy monitoring technique that utilizes a flexible scintillating film, common optical detectors, and image processing algorithms for real-time beam visualization (RT-BV).Scintillating films were formed by mixing Gd2O2S:Tb (GOS) with silicone and casting the mixture at room temperature. The films were placed in the path of therapeutic beams generated by medical linear accelerators (LINAC). The emitted light was subsequently captured using a CMOS digital camera. Image processing algorithms were used to extract the intensity, shape, and location of the radiation field at various beam energies, dose rates, and collimator locations. The measurement results were compared with known collimator settings to validate the performance of the imaging system.The RT-BV system achieved a sufficient contrast-to-noise ratio to enable real-time monitoring of the LINAC beam at 20 fps with normal ambient lighting in the LINAC room. The RT-BV system successfully identified collimator movements with sub-millimeter resolution.The RT-BV system is capable of localizing radiation therapy beams with sub-millimeter precision and tracking beam movement at video-rate exposure.

    View details for DOI 10.1118/1.4901255

    View details for PubMedID 25563243

    View details for PubMedCentralID PMC4265127

  • Feasibility-Seeking and Superiorization Algorithms Applied to Inverse Treatment Planning in Radiation Therapy Davidi, R., Censor, Y., Schulte, R. W., Geneser, S., Xing, L., Reich, S., Zaslavski, A. J. AMER MATHEMATICAL SOC. 2015: 83–92
  • Accuracy of surface registration compared to conventional volumetric registration in patient positioning for head-and-neck radiotherapy: A simulation study using patient data MEDICAL PHYSICS Kim, Y., Li, R., Na, Y. H., Lee, R., Xing, L. 2014; 41 (12)

    Abstract

    3D optical surface imaging has been applied to patient positioning in radiation therapy (RT). The optical patient positioning system is advantageous over conventional method using cone-beam computed tomography (CBCT) in that it is radiation free, frameless, and is capable of real-time monitoring. While the conventional radiographic method uses volumetric registration, the optical system uses surface matching for patient alignment. The relative accuracy of these two methods has not yet been sufficiently investigated. This study aims to investigate the theoretical accuracy of the surface registration based on a simulation study using patient data.This study compares the relative accuracy of surface and volumetric registration in head-and-neck RT. The authors examined 26 patient data sets, each consisting of planning CT data acquired before treatment and patient setup CBCT data acquired at the time of treatment. As input data of surface registration, patient's skin surfaces were created by contouring patient skin from planning CT and treatment CBCT. Surface registration was performed using the iterative closest points algorithm by point-plane closest, which minimizes the normal distance between source points and target surfaces. Six degrees of freedom (three translations and three rotations) were used in both surface and volumetric registrations and the results were compared. The accuracy of each method was estimated by digital phantom tests.Based on the results of 26 patients, the authors found that the average and maximum root-mean-square translation deviation between the surface and volumetric registrations were 2.7 and 5.2 mm, respectively. The residual error of the surface registration was calculated to have an average of 0.9 mm and a maximum of 1.7 mm.Surface registration may lead to results different from those of the conventional volumetric registration. Only limited accuracy can be achieved for patient positioning with an approach based solely on surface information.

    View details for DOI 10.1118/1.4898103

    View details for Web of Science ID 000346176300004

    View details for PubMedID 25471948

    View details for PubMedCentralID PMC4235652

  • A unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planning PHYSICS IN MEDICINE AND BIOLOGY Gudur, M. S., Hara, W., Le, Q., Wang, L., Xing, L., Li, R. 2014; 59 (21): 6595-6606

    Abstract

    MRI significantly improves the accuracy and reliability of target delineation in radiation therapy for certain tumors due to its superior soft tissue contrast compared to CT. A treatment planning process with MRI as the sole imaging modality will eliminate systematic CT/MRI co-registration errors, reduce cost and radiation exposure, and simplify clinical workflow. However, MRI lacks the key electron density information necessary for accurate dose calculation and generating reference images for patient setup. The purpose of this work is to develop a unifying method to derive electron density from standard T1-weighted MRI. We propose to combine both intensity and geometry information into a unifying probabilistic Bayesian framework for electron density mapping. For each voxel, we compute two conditional probability density functions (PDFs) of electron density given its: (1) T1-weighted MRI intensity, and (2) geometry in a reference anatomy, obtained by deformable image registration between the MRI of the atlas and test patient. The two conditional PDFs containing intensity and geometry information are combined into a unifying posterior PDF, whose mean value corresponds to the optimal electron density value under the mean-square error criterion. We evaluated the algorithm's accuracy of electron density mapping and its ability to detect bone in the head for eight patients, using an additional patient as the atlas or template. Mean absolute HU error between the estimated and true CT, as well as receiver operating characteristics for bone detection (HU > 200) were calculated. The performance was compared with a global intensity approach based on T1 and no density correction (set whole head to water). The proposed technique significantly reduced the errors in electron density estimation, with a mean absolute HU error of 126, compared with 139 for deformable registration (p = 2  ×  10(-4)), 283 for the intensity approach (p = 2  ×  10(-6)) and 282 without density correction (p = 5  ×  10(-6)). For 90% sensitivity in bone detection, the proposed method achieved a specificity of 86%, compared with 80, 11 and 10% using deformable registration, intensity and without density correction, respectively. Notably, the Bayesian approach was more robust against anatomical differences between patients, with a specificity of 62% in the worst case (patient), compared to 30% specificity in registration-based approach. In conclusion, the proposed unifying Bayesian method provides accurate electron density estimation and bone detection from MRI of the head with highly heterogeneous anatomy.

    View details for DOI 10.1088/0031-9155/59/21/6595

    View details for Web of Science ID 000343092900020

  • A unifying probabilistic Bayesian approach to derive electron density from MRI for radiation therapy treatment planning. Physics in medicine and biology Gudur, M. S., Hara, W., Le, Q., Wang, L., Xing, L., Li, R. 2014; 59 (21): 6595-6606

    Abstract

    MRI significantly improves the accuracy and reliability of target delineation in radiation therapy for certain tumors due to its superior soft tissue contrast compared to CT. A treatment planning process with MRI as the sole imaging modality will eliminate systematic CT/MRI co-registration errors, reduce cost and radiation exposure, and simplify clinical workflow. However, MRI lacks the key electron density information necessary for accurate dose calculation and generating reference images for patient setup. The purpose of this work is to develop a unifying method to derive electron density from standard T1-weighted MRI. We propose to combine both intensity and geometry information into a unifying probabilistic Bayesian framework for electron density mapping. For each voxel, we compute two conditional probability density functions (PDFs) of electron density given its: (1) T1-weighted MRI intensity, and (2) geometry in a reference anatomy, obtained by deformable image registration between the MRI of the atlas and test patient. The two conditional PDFs containing intensity and geometry information are combined into a unifying posterior PDF, whose mean value corresponds to the optimal electron density value under the mean-square error criterion. We evaluated the algorithm's accuracy of electron density mapping and its ability to detect bone in the head for eight patients, using an additional patient as the atlas or template. Mean absolute HU error between the estimated and true CT, as well as receiver operating characteristics for bone detection (HU > 200) were calculated. The performance was compared with a global intensity approach based on T1 and no density correction (set whole head to water). The proposed technique significantly reduced the errors in electron density estimation, with a mean absolute HU error of 126, compared with 139 for deformable registration (p = 2  ×  10(-4)), 283 for the intensity approach (p = 2  ×  10(-6)) and 282 without density correction (p = 5  ×  10(-6)). For 90% sensitivity in bone detection, the proposed method achieved a specificity of 86%, compared with 80, 11 and 10% using deformable registration, intensity and without density correction, respectively. Notably, the Bayesian approach was more robust against anatomical differences between patients, with a specificity of 62% in the worst case (patient), compared to 30% specificity in registration-based approach. In conclusion, the proposed unifying Bayesian method provides accurate electron density estimation and bone detection from MRI of the head with highly heterogeneous anatomy.

    View details for DOI 10.1088/0031-9155/59/21/6595

    View details for PubMedID 25321341

  • Cerenkov Luminescence Endoscopy: Improved Molecular Sensitivity with beta(-)-Emitting Radiotracers JOURNAL OF NUCLEAR MEDICINE Carpenter, C. M., Ma, X., Liu, H., Sun, C., Pratx, G., Wang, J., Gambhir, S. S., Xing, L., Cheng, Z. 2014; 55 (11): 1905-1909

    Abstract

    Cerenkov luminescence endoscopy (CLE) is an optical technique that captures the Cerenkov photons emitted from highly energetic moving charged particles (β(+) or β(-)) and can be used to monitor the distribution of many clinically available radioactive probes. A main limitation of CLE is its limited sensitivity to small concentrations of radiotracer, especially when used with a light guide. We investigated the improvement in the sensitivity of CLE brought about by using a β(-) radiotracer that improved Cerenkov signal due to both higher β-particle energy and lower γ noise in the imaging optics because of the lack of positron annihilation.The signal-to-noise ratio (SNR) of (90)Y was compared with that of (18)F in both phantoms and small-animal tumor models. Sensitivity and noise characteristics were demonstrated using vials of activity both at the surface and beneath 1 cm of tissue. Rodent U87MG glioma xenograft models were imaged with radiotracers bound to arginine-glycine-aspartate (RGD) peptides to determine the SNR.γ noise from (18)F was demonstrated by both an observed blurring across the field of view and a more pronounced fall-off with distance. A decreased γ background and increased energy of the β particles resulted in a 207-fold improvement in the sensitivity of (90)Y compared with (18)F in phantoms. (90)Y-bound RGD peptide produced a higher tumor-to-background SNR than (18)F in a mouse model.The use of (90)Y for Cerenkov endoscopic imaging enabled superior results compared with an (18)F radiotracer.

    View details for DOI 10.2967/jnumed.114.139105

    View details for Web of Science ID 000344209200024

  • Cerenkov luminescence endoscopy: improved molecular sensitivity with ß--emitting radiotracers. Journal of nuclear medicine : official publication, Society of Nuclear Medicine Carpenter, C. M., Ma, X., Liu, H., Sun, C., Pratx, G., Wang, J., Gambhir, S. S., Xing, L., Cheng, Z. 2014; 55 (11): 1905-1909

    Abstract

    Cerenkov luminescence endoscopy (CLE) is an optical technique that captures the Cerenkov photons emitted from highly energetic moving charged particles (β(+) or β(-)) and can be used to monitor the distribution of many clinically available radioactive probes. A main limitation of CLE is its limited sensitivity to small concentrations of radiotracer, especially when used with a light guide. We investigated the improvement in the sensitivity of CLE brought about by using a β(-) radiotracer that improved Cerenkov signal due to both higher β-particle energy and lower γ noise in the imaging optics because of the lack of positron annihilation.The signal-to-noise ratio (SNR) of (90)Y was compared with that of (18)F in both phantoms and small-animal tumor models. Sensitivity and noise characteristics were demonstrated using vials of activity both at the surface and beneath 1 cm of tissue. Rodent U87MG glioma xenograft models were imaged with radiotracers bound to arginine-glycine-aspartate (RGD) peptides to determine the SNR.γ noise from (18)F was demonstrated by both an observed blurring across the field of view and a more pronounced fall-off with distance. A decreased γ background and increased energy of the β particles resulted in a 207-fold improvement in the sensitivity of (90)Y compared with (18)F in phantoms. (90)Y-bound RGD peptide produced a higher tumor-to-background SNR than (18)F in a mouse model.The use of (90)Y for Cerenkov endoscopic imaging enabled superior results compared with an (18)F radiotracer.

    View details for DOI 10.2967/jnumed.114.139105

    View details for PubMedID 25300598

  • Transferring Biomarker into Molecular Probe: Melanin Nanoparticle as a Naturally Active Platform for Multimodality Imaging JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Fan, Q., Cheng, K., Hu, X., Ma, X., Zhang, R., Yang, M., Lu, X., Xing, L., Huang, W., Gambhir, S. S., Cheng, Z. 2014; 136 (43): 15185-15194

    Abstract

    Developing multifunctional and easily prepared nanoplatforms with integrated different modalities is highly challenging for molecular imaging. Here, we report the successful transferring an important molecular target, melanin, into a novel mul-timodality imaging nanoplatform. Melanin is abundantly expressed in melanotic melanomas and thus has been actively studied as a target for melanoma imaging. In our work, the multifunctional biopolymer nanoplatform based on ultrasmall (< 10 nm) water-soluble melanin nanoparticle (MNP) was developed and showed unique photoacoustic property and natural binding ability with metal ions (for example, 64Cu2+, Fe3+). Therefore MNP can serve not only as a photoacoustic contrast agent, but also as a nanoplatform for positron emission tomography (PET) and magnetic resonance imaging (MRI). Traditional passive nanoplatforms require complicated and time-consuming processes for pre-building reporting moieties or chemical modifications using active groups to integrate different contrast properties into one entity. In comparison, utilizing functional biomarker melanin can greatly simplify the building process. We further conjugated αvβ3 integrins targeting peptide, cyclic c(RGDfC) peptide, to MNPs and this allowed targeting of these nanoparticles to allow for greater U87MG tumor accumulation than that simply possible due to the enhanced permeability and retention (EPR) effect. The multimodal properties of MNPs demonstrate the high potential of endogenous materials with multifunctions as nanoplatforms for molecular theranostics and clinical translation.

    View details for DOI 10.1021/ja505412p

    View details for Web of Science ID 000344042900018

  • Transferring biomarker into molecular probe: melanin nanoparticle as a naturally active platform for multimodality imaging. Journal of the American Chemical Society Fan, Q., Cheng, K., Hu, X., Ma, X., Zhang, R., Yang, M., Lu, X., Xing, L., Huang, W., Gambhir, S. S., Cheng, Z. 2014; 136 (43): 15185-15194

    Abstract

    Developing multifunctional and easily prepared nanoplatforms with integrated different modalities is highly challenging for molecular imaging. Here, we report the successful transferring an important molecular target, melanin, into a novel mul-timodality imaging nanoplatform. Melanin is abundantly expressed in melanotic melanomas and thus has been actively studied as a target for melanoma imaging. In our work, the multifunctional biopolymer nanoplatform based on ultrasmall (< 10 nm) water-soluble melanin nanoparticle (MNP) was developed and showed unique photoacoustic property and natural binding ability with metal ions (for example, 64Cu2+, Fe3+). Therefore MNP can serve not only as a photoacoustic contrast agent, but also as a nanoplatform for positron emission tomography (PET) and magnetic resonance imaging (MRI). Traditional passive nanoplatforms require complicated and time-consuming processes for pre-building reporting moieties or chemical modifications using active groups to integrate different contrast properties into one entity. In comparison, utilizing functional biomarker melanin can greatly simplify the building process. We further conjugated αvβ3 integrins targeting peptide, cyclic c(RGDfC) peptide, to MNPs and this allowed targeting of these nanoparticles to allow for greater U87MG tumor accumulation than that simply possible due to the enhanced permeability and retention (EPR) effect. The multimodal properties of MNPs demonstrate the high potential of endogenous materials with multifunctions as nanoplatforms for molecular theranostics and clinical translation.

    View details for DOI 10.1021/ja505412p

    View details for PubMedID 25292385

  • Dual-gated volumetric modulated arc therapy RADIATION ONCOLOGY Fahimian, B., Wu, J., Wu, H., Geneser, S., Xing, L. 2014; 9

    Abstract

    Gated Volumetric Modulated Arc Therapy (VMAT) is an emerging radiation therapy modality for treatment of tumors affected by respiratory motion. However, gating significantly prolongs the treatment time, as delivery is only activated during a single respiratory phase. To enhance the efficiency of gated VMAT delivery, a novel dual-gated VMAT (DG-VMAT) technique, in which delivery is executed at both exhale and inhale phases in a given arc rotation, is developed and experimentally evaluated.Arc delivery at two phases is realized by sequentially interleaving control points consisting of MUs, MLC sequences, and angles of VMAT plans generated at the exhale and inhale phases. Dual-gated delivery is initiated when a respiration gating signal enters the exhale window; when the exhale delivery concludes, the beam turns off and the gantry rolls back to the starting position for the inhale window. The process is then repeated until both inhale and exhale arcs are fully delivered. DG-VMAT plan delivery accuracy was assessed using a pinpoint chamber and diode array phantom undergoing programmed motion.DG-VMAT delivery was experimentally implemented through custom XML scripting in Varian's TrueBeam™ STx Developer Mode. Relative to single gated delivery at exhale, the treatment time was improved by 95.5% for a sinusoidal breathing pattern. The pinpoint chamber dose measurement agreed with the calculated dose within 0.7%. For the DG-VMAT delivery, 97.5% of the diode array measurements passed the 3%/3 mm gamma criterion.The feasibility of DG-VMAT delivery scheme has been experimentally demonstrated for the first time. By leveraging the stability and natural pauses that occur at end-inspiration and end-exhalation, DG-VMAT provides a practical method for enhancing gated delivery efficiency by up to a factor of two.

    View details for DOI 10.1186/1748-717X-9-209

    View details for Web of Science ID 000344119800001

    View details for PubMedCentralID PMC4261568

  • Fiber-Optic System for Dual-Modality Imaging of Glucose Probes F-18-FDG and 6-NBDG in Atherosclerotic Plaques PLOS ONE Zaman, R. T., Kosuge, H., Pratx, G., Carpenter, C., Xing, L., McConnell, M. V. 2014; 9 (9)

    Abstract

    Atherosclerosis is a progressive inflammatory condition that underlies coronary artery disease (CAD)-the leading cause of death in the United States. Thus, the ultimate goal of this research is to advance our understanding of human CAD by improving the characterization of metabolically active vulnerable plaques within the coronary arteries using a novel catheter-based imaging system. The aims of this study include (1) developing a novel fiber-optic imaging system with a scintillator to detect both 18F and fluorescent glucose probes, and (2) validating the system on ex vivo murine plaques.A novel design implements a flexible fiber-optic catheter consisting of both a radio-luminescence and a fluorescence imaging system to detect radionuclide 18F-fluorodeoxyglucose (18F-FDG) and the fluorescent analog 6-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-6-Deoxyglucose (6-NBDG), respectively. Murine macrophage-rich atherosclerotic carotid plaques were imaged ex vivo after intravenous delivery of 18F-FDG or 6-NBDG. Confirmatory optical imaging by IVIS-200 and autoradiography were also performed.Our fiber-optic imaging system successfully visualized both 18F-FDG and 6-NBDG probes in atherosclerotic plaques. For 18F-FDG, the ligated left carotid arteries (LCs) exhibited 4.9-fold higher radioluminescence signal intensity compared to the non-ligated right carotid arteries (RCs) (2.6 × 10(4) ± 1.4 × 10(3) vs. 5.4 × 10(3) ± 1.3 × 10(3) A.U., P = 0.008). Similarly, for 6-NBDG, the ligated LCs emitted 4.3-fold brighter fluorescent signals than the control RCs (1.6 × 10(2) ± 2.7 × 10(1) vs. 3.8 × 10(1) ± 5.9 A.U., P = 0.002). The higher uptake of both 18F-FDG and 6-NBDG in ligated LCs were confirmed with the IVIS-200 system. Autoradiography further verified the higher uptake of 18F-FDG by the LCs.This novel fiber-optic imaging system was sensitive to both radionuclide and fluorescent glucose probes taken up by murine atherosclerotic plaques. In addition, 6-NBDG is a promising novel fluorescent probe for detecting macrophage-rich atherosclerotic plaques.

    View details for DOI 10.1371/journal.pone.0108108

    View details for Web of Science ID 000342921200083

    View details for PubMedCentralID PMC4169475

  • Quality control procedures for dynamic treatment delivery techniques involving couch motion. Medical physics Yu, V. Y., Fahimian, B. P., Xing, L., Hristov, D. H. 2014; 41 (8): 081712-?

    Abstract

    In this study, the authors introduce and demonstrate quality control procedures for evaluating the geometric and dosimetric fidelity of dynamic treatment delivery techniques involving treatment couch motion synchronous with gantry and multileaf collimator (MLC). Tests were designed to evaluate positional accuracy, velocity constancy and accuracy for dynamic couch motion under a realistic weight load. A test evaluating the geometric accuracy of the system in delivering treatments over complex dynamic trajectories was also devised. Custom XML scripts that control the Varian TrueBeam™ STx (Serial #3) axes in Developer Mode were written to implement the delivery sequences for the tests. Delivered dose patterns were captured with radiographic film or the electronic portal imaging device. The couch translational accuracy in dynamic treatment mode was 0.01 cm. Rotational accuracy was within 0.3°, with 0.04 cm displacement of the rotational axis. Dose intensity profiles capturing the velocity constancy and accuracy for translations and rotation exhibited standard deviation and maximum deviations below 3%. For complex delivery involving MLC and couch motions, the overall translational accuracy for reproducing programmed patterns was within 0.06 cm. The authors conclude that in Developer Mode, TrueBeam™ is capable of delivering dynamic treatment delivery techniques involving couch motion with good geometric and dosimetric fidelity.

    View details for DOI 10.1118/1.4886757

    View details for PubMedID 25086522

  • Feasibility of a Table-Top Total Body Irradiation Technique using Robotic Couch Motion Chin, E., Otto, K., Hoppe, R., Hsu, A., Loo, B., Million, L., Xing, L., Fahimian, B. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2014: 15

    View details for DOI 10.1118/1.4894898

    View details for Web of Science ID 000341068100118

  • Quality control procedures for dynamic treatment delivery techniques involving couch motion MEDICAL PHYSICS Yu, V. Y., Fahinnian, B. R., Xing, L., Hristov, D. H. 2014; 41 (8): 164-170

    Abstract

    In this study, the authors introduce and demonstrate quality control procedures for evaluating the geometric and dosimetric fidelity of dynamic treatment delivery techniques involving treatment couch motion synchronous with gantry and multileaf collimator (MLC). Tests were designed to evaluate positional accuracy, velocity constancy and accuracy for dynamic couch motion under a realistic weight load. A test evaluating the geometric accuracy of the system in delivering treatments over complex dynamic trajectories was also devised. Custom XML scripts that control the Varian TrueBeam™ STx (Serial #3) axes in Developer Mode were written to implement the delivery sequences for the tests. Delivered dose patterns were captured with radiographic film or the electronic portal imaging device. The couch translational accuracy in dynamic treatment mode was 0.01 cm. Rotational accuracy was within 0.3°, with 0.04 cm displacement of the rotational axis. Dose intensity profiles capturing the velocity constancy and accuracy for translations and rotation exhibited standard deviation and maximum deviations below 3%. For complex delivery involving MLC and couch motions, the overall translational accuracy for reproducing programmed patterns was within 0.06 cm. The authors conclude that in Developer Mode, TrueBeam™ is capable of delivering dynamic treatment delivery techniques involving couch motion with good geometric and dosimetric fidelity.

    View details for DOI 10.1118/1.4886757

    View details for Web of Science ID 000341068100014

  • A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods PHYSICS IN MEDICINE AND BIOLOGY Choi, K., Li, R., Nam, H., Xing, L. 2014; 59 (12): 3097-3119

    Abstract

    As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

    View details for DOI 10.1088/0031-9155/59/12/3097

    View details for Web of Science ID 000337176600014

    View details for PubMedID 24840019

  • PHD Inhibition Mitigates and Protects Against Radiation-Induced Gastrointestinal Toxicity via HIF2. Science translational medicine Taniguchi, C. M., Miao, Y. R., Diep, A. N., Wu, C., Rankin, E. B., Atwood, T. F., Xing, L., Giaccia, A. J. 2014; 6 (236): 236ra64-?

    Abstract

    Radiation-induced gastrointestinal (GI) toxicity can be a major source of morbidity and mortality after radiation exposure. There is an unmet need for effective preventative or mitigative treatments against the potentially fatal diarrhea and water loss induced by radiation damage to the GI tract. We report that prolyl hydroxylase inhibition by genetic knockout or pharmacologic inhibition of all PHD (prolyl hydroxylase domain) isoforms by the small-molecule dimethyloxallyl glycine (DMOG) increases hypoxia-inducible factor (HIF) expression, improves epithelial integrity, reduces apoptosis, and increases intestinal angiogenesis, all of which are essential for radioprotection. HIF2, but not HIF1, is both necessary and sufficient to prevent radiation-induced GI toxicity and death. Increased vascular endothelial growth factor (VEGF) expression contributes to the protective effects of HIF2, because inhibition of VEGF function reversed the radioprotection and radiomitigation afforded by DMOG. Additionally, mortality from abdominal or total body irradiation was reduced even when DMOG was given 24 hours after exposure. Thus, prolyl hydroxylase inhibition represents a treatment strategy to protect against and mitigate GI toxicity from both therapeutic radiation and potentially lethal radiation exposures.

    View details for DOI 10.1126/scitranslmed.3008523

    View details for PubMedID 24828078

    View details for PubMedCentralID PMC4136475

  • Order of Magnitude Sensitivity Increase in X-ray Fluorescence Computed Tomography (XFCT) Imaging With an Optimized Spectro-Spatial Detector Configuration: Theory and Simulation IEEE TRANSACTIONS ON MEDICAL IMAGING Ahmad, M., Bazalova, M., Xiang, L., Xing, L. 2014; 33 (5): 1119-1128

    Abstract

    The purpose of this study was to increase the sensitivity of XFCT imaging by optimizing the data acquisition geometry for reduced scatter X-rays. The placement of detectors and detector energy window were chosen to minimize scatter X-rays. We performed both theoretical calculations and Monte Carlo simulations of this optimized detector configuration on a mouse-sized phantom containing various gold concentrations. The sensitivity limits were determined for three different X-ray spectra: a monoenergetic source, a Gaussian source, and a conventional X-ray tube source. Scatter X-rays were minimized using a backscatter detector orientation (scatter direction > 110(°) to the primary X-ray beam). The optimized configuration simultaneously reduced the number of detectors and improved the image signal-to-noise ratio. The sensitivity of the optimized configuration was 10 μg/mL (10 pM) at 2 mGy dose with the mono-energetic source, which is an order of magnitude improvement over the unoptimized configuration (102 pM without the optimization). Similar improvements were seen with the Gaussian spectrum source and conventional X-ray tube source. The optimization improvements were predicted in the theoretical model and also demonstrated in simulations. The sensitivity of XFCT imaging can be enhanced by an order of magnitude with the data acquisition optimization, greatly enhancing the potential of this modality for future use in clinical molecular imaging.

    View details for DOI 10.1109/TMI.2014.2305101

    View details for Web of Science ID 000335379500010

    View details for PubMedID 24770916

  • Feasibility evaluation of radioluminescence for oncologic imaging King, M., Carpenter, C., Sun, C., Pratx, G., Xing, L. SOC NUCLEAR MEDICINE INC. 2014
  • A novel radioluminescence microscope for imaging radiotracers at the single-cell level Pratx, G., Natarajan, A., Turkcan, S., Sasportas, L., Axente, M., Gambhir, S., Xing, L. SOC NUCLEAR MEDICINE INC. 2014
  • Synergistic Assembly of Heavy Metal Clusters and Luminescent Organic Bridging Ligands in Metal-Organic Frameworks for Highly Efficient X-ray Scintillation JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Wang, C., Volotskova, O., Lu, K., Ahmad, M., Sun, C., Xing, L., Lin, W. 2014; 136 (17): 6171-6174

    Abstract

    We have designed two metal-organic frameworks (MOFs) to efficiently convert X-ray to visible-light luminescence. The MOFs are constructed from M6(μ3-O)4(μ3-OH)4(carboxylate)12 (M = Hf or Zr) secondary building units (SBUs) and anthracene-based dicarboxylate bridging ligands. The high atomic number of Zr and Hf in the SBUs serves as effective X-ray antenna by absorbing X-ray photons and converting them to fast electrons through the photoelectric effect. The generated electrons then excite multiple anthracene-based emitters in the MOF through inelastic scattering, leading to efficient generation of detectable photons in the visible spectrum. The MOF materials thus serve as efficient X-ray scintillators via synergistic X-ray absorption by the metal-cluster SBUs and optical emission by the bridging ligands.

    View details for DOI 10.1021/ja500671h

    View details for Web of Science ID 000335369200006

    View details for PubMedID 24730683

  • Assessing the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy. International journal of radiation oncology, biology, physics Azcona, J. D., Xing, L., Chen, X., Bush, K., Li, R. 2014; 88 (5): 1167-1174

    Abstract

    To develop a method for dose reconstruction by incorporating the interplay effect between aperture modulation and target motion, and to assess the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy (VMAT).Clinical VMAT plans were delivered with the TrueBeam linac for 8 patients with prostate cancer. The real-time target motion during dose delivery was determined based on the 2-dimensional fiducial localization using an onboard electronic portal imaging device. The target shift in each image was correlated with the control point with the same gantry angle in the VMAT plan. An in-house-developed Monte Carlo simulation tool was used to calculate the 3-dimensional dose distribution for each control point individually, taking into account the corresponding real-time target motion (assuming a nondeformable target with no rotation). The delivered target dose was then estimated by accumulating the dose from all control points in the plan. On the basis of this information, dose-volume histograms and 3-dimensional dose distributions were calculated to assess their degradation from the planned dose caused by target motion. Thirty-two prostate motion trajectories were analyzed.The minimum dose to 0.03 cm(3) of the gross tumor volume (D0.03cc) was only slightly degraded after taking motion into account, with a minimum value of 94.1% of the planned dose among all patients and fractions. However, the gross tumor volume receiving prescription dose (V100%) could be largely affected by motion, dropping below 60% in 1 trajectory. We did not observe a correlation between motion magnitude and dose degradation.Prostate motion degrades the delivered dose to the target in an unpredictable way, although its effect is reduced over multiple fractions, and for most patients the degradation is small. Patients with greater prostate motion or those treated with stereotactic body radiation therapy would benefit from real-time prostate tracking to reduce the margin.

    View details for DOI 10.1016/j.ijrobp.2013.12.015

    View details for PubMedID 24661670

  • Assessing the Dosimetric Impact of Real-Time Prostate Motion During Volumetric Modulated Arc Therapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Diego Azcona, J., Xing, L., Chen, X., Bush, K., Li, R. 2014; 88 (5): 1167-1174

    Abstract

    To develop a method for dose reconstruction by incorporating the interplay effect between aperture modulation and target motion, and to assess the dosimetric impact of real-time prostate motion during volumetric modulated arc therapy (VMAT).Clinical VMAT plans were delivered with the TrueBeam linac for 8 patients with prostate cancer. The real-time target motion during dose delivery was determined based on the 2-dimensional fiducial localization using an onboard electronic portal imaging device. The target shift in each image was correlated with the control point with the same gantry angle in the VMAT plan. An in-house-developed Monte Carlo simulation tool was used to calculate the 3-dimensional dose distribution for each control point individually, taking into account the corresponding real-time target motion (assuming a nondeformable target with no rotation). The delivered target dose was then estimated by accumulating the dose from all control points in the plan. On the basis of this information, dose-volume histograms and 3-dimensional dose distributions were calculated to assess their degradation from the planned dose caused by target motion. Thirty-two prostate motion trajectories were analyzed.The minimum dose to 0.03 cm(3) of the gross tumor volume (D0.03cc) was only slightly degraded after taking motion into account, with a minimum value of 94.1% of the planned dose among all patients and fractions. However, the gross tumor volume receiving prescription dose (V100%) could be largely affected by motion, dropping below 60% in 1 trajectory. We did not observe a correlation between motion magnitude and dose degradation.Prostate motion degrades the delivered dose to the target in an unpredictable way, although its effect is reduced over multiple fractions, and for most patients the degradation is small. Patients with greater prostate motion or those treated with stereotactic body radiation therapy would benefit from real-time prostate tracking to reduce the margin.

    View details for DOI 10.1016/j.ijrobp.2013.12.015

    View details for Web of Science ID 000333460200027

  • Nonisocentric treatment strategy for breast radiation therapy: a proof of concept study. International journal of radiation oncology, biology, physics Li, R., Xing, L., Horst, K. C., Bush, K. 2014; 88 (4): 920-926

    Abstract

    To propose a nonisocentric treatment strategy as a special form of station parameter optimized radiation therapy, to improve sparing of critical structures while preserving target coverage in breast radiation therapy.To minimize the volume of exposed lung and heart in breast irradiation, we propose a novel nonisocentric treatment scheme by strategically placing nonconverging beams with multiple isocenters. As its name suggests, the central axes of these beams do not intersect at a single isocenter as in conventional breast treatment planning. Rather, the isocenter locations and beam directions are carefully selected, in that each beam is only responsible for a certain subvolume of the target, so as to minimize the volume of irradiated normal tissue. When put together, the beams will provide an adequate coverage of the target and expose only a minimal amount of normal tissue to radiation. We apply the nonisocentric planning technique to 2 previously treated clinical cases (breast and chest wall).The proposed nonisocentric technique substantially improved sparing of the ipsilateral lung. Compared with conventional isocentric plans using 2 tangential beams, the mean lung dose was reduced by 38% and 50% using the proposed technique, and the volume of the ipsilateral lung receiving ≥20 Gy was reduced by a factor of approximately 2 and 3 for the breast and chest wall cases, respectively. The improvement in lung sparing is even greater compared with volumetric modulated arc therapy.A nonisocentric implementation of station parameter optimized radiation therapy has been proposed for breast radiation therapy. The new treatment scheme overcomes the limitations of existing approaches and affords a useful tool for conformal breast radiation therapy, especially in cases with extreme chest wall curvature.

    View details for DOI 10.1016/j.ijrobp.2013.12.029

    View details for PubMedID 24606852

  • Nonisocentric treatment strategy for breast radiation therapy: a proof of concept study. International journal of radiation oncology, biology, physics Li, R., Xing, L., Horst, K. C., Bush, K. 2014; 88 (4): 920-926

    Abstract

    To propose a nonisocentric treatment strategy as a special form of station parameter optimized radiation therapy, to improve sparing of critical structures while preserving target coverage in breast radiation therapy.To minimize the volume of exposed lung and heart in breast irradiation, we propose a novel nonisocentric treatment scheme by strategically placing nonconverging beams with multiple isocenters. As its name suggests, the central axes of these beams do not intersect at a single isocenter as in conventional breast treatment planning. Rather, the isocenter locations and beam directions are carefully selected, in that each beam is only responsible for a certain subvolume of the target, so as to minimize the volume of irradiated normal tissue. When put together, the beams will provide an adequate coverage of the target and expose only a minimal amount of normal tissue to radiation. We apply the nonisocentric planning technique to 2 previously treated clinical cases (breast and chest wall).The proposed nonisocentric technique substantially improved sparing of the ipsilateral lung. Compared with conventional isocentric plans using 2 tangential beams, the mean lung dose was reduced by 38% and 50% using the proposed technique, and the volume of the ipsilateral lung receiving ≥20 Gy was reduced by a factor of approximately 2 and 3 for the breast and chest wall cases, respectively. The improvement in lung sparing is even greater compared with volumetric modulated arc therapy.A nonisocentric implementation of station parameter optimized radiation therapy has been proposed for breast radiation therapy. The new treatment scheme overcomes the limitations of existing approaches and affords a useful tool for conformal breast radiation therapy, especially in cases with extreme chest wall curvature.

    View details for DOI 10.1016/j.ijrobp.2013.12.029

    View details for PubMedID 24606852

  • L-shell x-ray fluorescence computed tomography (XFCT) imaging of Cisplatin PHYSICS IN MEDICINE AND BIOLOGY Bazalova, M., Ahmad, M., Pratx, G., Xing, L. 2014; 59 (1): 219-232

    Abstract

    X-ray fluorescence computed tomography (XFCT) imaging has been focused on the detection of K-shell x-rays. The potential utility of L-shell x-ray XFCT is, however, not well studied. Here we report the first Monte Carlo (MC) simulation of preclinical L-shell XFCT imaging of Cisplatin. We built MC models for both L- and K-shell XFCT with different excitation energies (15 and 30 keV for L-shell and 80 keV for K-shell XFCT). Two small-animal sized imaging phantoms of 2 and 4 cm diameter containing a series of objects of 0.6 to 2.7 mm in diameter at 0.7 to 16 mm depths with 10 to 250 µg mL(-1) concentrations of Pt are used in the study. Transmitted and scattered x-rays were collected with photon-integrating transmission detector and photon-counting detector arc, respectively. Collected data were rearranged into XFCT and transmission CT sinograms for image reconstruction. XFCT images were reconstructed with filtered back-projection and with iterative maximum-likelihood expectation maximization without and with attenuation correction. While K-shell XFCT was capable of providing an accurate measurement of Cisplatin concentration, its sensitivity was 4.4 and 3.0 times lower than that of L-shell XFCT with 15 keV excitation beam for the 2 cm and 4 cm diameter phantom, respectively. With the inclusion of excitation and fluorescence beam attenuation correction, we found that L-shell XFCT was capable of providing fairly accurate information of Cisplatin concentration distribution. With a dose of 29 and 58 mGy, clinically relevant Cisplatin Pt concentrations of 10 µg mg(-1) could be imaged with L-shell XFCT inside a 2 cm and 4 cm diameter object, respectively.

    View details for DOI 10.1088/0031-9155/59/1/219

    View details for Web of Science ID 000328549200011

    View details for PubMedID 24334507

    View details for PubMedCentralID PMC3928148

  • Hard X-ray-induced optical luminescence via biomolecule-directed metal clusters CHEMICAL COMMUNICATIONS Osakada, Y., Pratx, G., Sun, C., Sakamoto, M., Ahmad, M., Volotskova, O., Ong, Q., Teranishi, T., Harada, Y., Xing, L., Cui, B. 2014; 50 (27): 3549-3551

    Abstract

    Here, we demonstrate that biomolecule-directed metal clusters are applicable in the study of hard X-ray excited optical luminescence, promising a new direction in the development of novel X-ray-activated imaging probes.

    View details for DOI 10.1039/c3cc48661c

    View details for Web of Science ID 000332483200003

    View details for PubMedID 24463467

  • X-Ray Luminescence and X-Ray Fluorescence Computed Tomography: New Molecular Imaging Modalities IEEE ACCESS Ahmad, M., Pratx, G., Bazalova, M., Xing, L. 2014; 2: 1051-1061
  • Fiber-optic system for dual-modality imaging of glucose probes 18F-FDG and 6-NBDG in atherosclerotic plaques. PloS one Zaman, R. T., Kosuge, H., Pratx, G., Carpenter, C., Xing, L., McConnell, M. V. 2014; 9 (9)

    Abstract

    Atherosclerosis is a progressive inflammatory condition that underlies coronary artery disease (CAD)-the leading cause of death in the United States. Thus, the ultimate goal of this research is to advance our understanding of human CAD by improving the characterization of metabolically active vulnerable plaques within the coronary arteries using a novel catheter-based imaging system. The aims of this study include (1) developing a novel fiber-optic imaging system with a scintillator to detect both 18F and fluorescent glucose probes, and (2) validating the system on ex vivo murine plaques.A novel design implements a flexible fiber-optic catheter consisting of both a radio-luminescence and a fluorescence imaging system to detect radionuclide 18F-fluorodeoxyglucose (18F-FDG) and the fluorescent analog 6-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-6-Deoxyglucose (6-NBDG), respectively. Murine macrophage-rich atherosclerotic carotid plaques were imaged ex vivo after intravenous delivery of 18F-FDG or 6-NBDG. Confirmatory optical imaging by IVIS-200 and autoradiography were also performed.Our fiber-optic imaging system successfully visualized both 18F-FDG and 6-NBDG probes in atherosclerotic plaques. For 18F-FDG, the ligated left carotid arteries (LCs) exhibited 4.9-fold higher radioluminescence signal intensity compared to the non-ligated right carotid arteries (RCs) (2.6 × 10(4) ± 1.4 × 10(3) vs. 5.4 × 10(3) ± 1.3 × 10(3) A.U., P = 0.008). Similarly, for 6-NBDG, the ligated LCs emitted 4.3-fold brighter fluorescent signals than the control RCs (1.6 × 10(2) ± 2.7 × 10(1) vs. 3.8 × 10(1) ± 5.9 A.U., P = 0.002). The higher uptake of both 18F-FDG and 6-NBDG in ligated LCs were confirmed with the IVIS-200 system. Autoradiography further verified the higher uptake of 18F-FDG by the LCs.This novel fiber-optic imaging system was sensitive to both radionuclide and fluorescent glucose probes taken up by murine atherosclerotic plaques. In addition, 6-NBDG is a promising novel fluorescent probe for detecting macrophage-rich atherosclerotic plaques.

    View details for DOI 10.1371/journal.pone.0108108

    View details for PubMedID 25233472

    View details for PubMedCentralID PMC4169475

  • Inverse planning in the age of digital LINACs: station parameter optimized radiation therapy (SPORT) 17th International Conference on the Use of Computers in Radiation Therapy (ICCR) Xing, L., Li, R. IOP PUBLISHING LTD. 2014
  • Clinical implementation of intrafraction cone beam computed tomography imaging during lung tumor stereotactic ablative radiation therapy. International journal of radiation oncology, biology, physics Li, R., Han, B., Meng, B., Maxim, P. G., Xing, L., Koong, A. C., Diehn, M., Loo, B. W. 2013; 87 (5): 917-923

    Abstract

    To develop and clinically evaluate a volumetric imaging technique for assessing intrafraction geometric and dosimetric accuracy of stereotactic ablative radiation therapy (SABR).Twenty patients received SABR for lung tumors using volumetric modulated arc therapy (VMAT). At the beginning of each fraction, pretreatment cone beam computed tomography (CBCT) was used to align the soft-tissue tumor position with that in the planning CT. Concurrent with dose delivery, we acquired fluoroscopic radiograph projections during VMAT using the Varian on-board imaging system. Those kilovolt projections acquired during millivolt beam-on were automatically extracted, and intrafraction CBCT images were reconstructed using the filtered backprojection technique. We determined the time-averaged target shift during VMAT by calculating the center of mass of the tumor target in the intrafraction CBCT relative to the planning CT. To estimate the dosimetric impact of the target shift during treatment, we recalculated the dose to the GTV after shifting the entire patient anatomy according to the time-averaged target shift determined earlier.The mean target shift from intrafraction CBCT to planning CT was 1.6, 1.0, and 1.5 mm; the 95th percentile shift was 5.2, 3.1, 3.6 mm; and the maximum shift was 5.7, 3.6, and 4.9 mm along the anterior-posterior, left-right, and superior-inferior directions. Thus, the time-averaged intrafraction gross tumor volume (GTV) position was always within the planning target volume. We observed some degree of target blurring in the intrafraction CBCT, indicating imperfect breath-hold reproducibility or residual motion of the GTV during treatment. By our estimated dose recalculation, the GTV was consistently covered by the prescription dose (PD), that is, V100% above 0.97 for all patients, and minimum dose to GTV >100% PD for 18 patients and >95% PD for all patients.Intrafraction CBCT during VMAT can provide geometric and dosimetric verification of SABR valuable for quality assurance and potentially for treatment adaptation.

    View details for DOI 10.1016/j.ijrobp.2013.08.015

    View details for PubMedID 24113060

  • Clinical implementation of intrafraction cone beam computed tomography imaging during lung tumor stereotactic ablative radiation therapy. International journal of radiation oncology, biology, physics Li, R., Han, B., Meng, B., Maxim, P. G., Xing, L., Koong, A. C., Diehn, M., Loo, B. W. 2013; 87 (5): 917-923

    Abstract

    To develop and clinically evaluate a volumetric imaging technique for assessing intrafraction geometric and dosimetric accuracy of stereotactic ablative radiation therapy (SABR).Twenty patients received SABR for lung tumors using volumetric modulated arc therapy (VMAT). At the beginning of each fraction, pretreatment cone beam computed tomography (CBCT) was used to align the soft-tissue tumor position with that in the planning CT. Concurrent with dose delivery, we acquired fluoroscopic radiograph projections during VMAT using the Varian on-board imaging system. Those kilovolt projections acquired during millivolt beam-on were automatically extracted, and intrafraction CBCT images were reconstructed using the filtered backprojection technique. We determined the time-averaged target shift during VMAT by calculating the center of mass of the tumor target in the intrafraction CBCT relative to the planning CT. To estimate the dosimetric impact of the target shift during treatment, we recalculated the dose to the GTV after shifting the entire patient anatomy according to the time-averaged target shift determined earlier.The mean target shift from intrafraction CBCT to planning CT was 1.6, 1.0, and 1.5 mm; the 95th percentile shift was 5.2, 3.1, 3.6 mm; and the maximum shift was 5.7, 3.6, and 4.9 mm along the anterior-posterior, left-right, and superior-inferior directions. Thus, the time-averaged intrafraction gross tumor volume (GTV) position was always within the planning target volume. We observed some degree of target blurring in the intrafraction CBCT, indicating imperfect breath-hold reproducibility or residual motion of the GTV during treatment. By our estimated dose recalculation, the GTV was consistently covered by the prescription dose (PD), that is, V100% above 0.97 for all patients, and minimum dose to GTV >100% PD for 18 patients and >95% PD for all patients.Intrafraction CBCT during VMAT can provide geometric and dosimetric verification of SABR valuable for quality assurance and potentially for treatment adaptation.

    View details for DOI 10.1016/j.ijrobp.2013.08.015

    View details for PubMedID 24113060

  • Trajectory modulated prone breast irradiation: A LINAC-based technique combining intensity modulated delivery and motion of the couch RADIOTHERAPY AND ONCOLOGY Fahimian, B., Yu, V., Horst, K., Xing, L., Hristov, D. 2013; 109 (3): 475-481

    Abstract

    External beam radiation therapy (EBRT) provides a non-invasive treatment alternative for accelerated partial breast irradiation (APBI), however, limitations in achievable dose conformity of current EBRT techniques have been correlated to reported toxicity. To enhance the conformity of EBRT APBI, a technique for conventional LINACs is developed, which through combined motion of the couch, intensity modulated delivery, and a prone breast setup, enables wide-angular coronal arc irradiation of the ipsilateral breast without irradiating through the thorax and contralateral breast.A couch trajectory optimization technique was developed to determine the trajectories that concurrently avoid collision with the LINAC and maintain the target within the MLC apertures. Inverse treatment planning was performed along the derived trajectory. The technique was experimentally implemented by programming the Varian TrueBeam™ STx in Developer Mode. The dosimetric accuracy of the delivery was evaluated by ion chamber and film measurements in phantom.The resulting optimized trajectory was shown to be necessarily non-isocentric, and contain both translation and rotations of the couch. Film measurements resulted in 93% of the points in the measured two-dimensional dose maps passing the 3%/3mm Gamma criterion. Preliminary treatment plan comparison to 5-field 3D-conformal, IMRT, and VMAT demonstrated enhancement in conformity, and reduction of the normal tissue V50% and V100% parameters that have been correlated with EBRT toxicity.The feasibility of wide-angular intensity modulated partial breast irradiation using motion of the couch has been demonstrated experimentally on a standard LINAC for the first time. For patients eligible for a prone setup, the technique may enable improvement of dose conformity and associated dose-volume parameters correlated with toxicity.

    View details for DOI 10.1016/j.radonc.2013.10.031

    View details for Web of Science ID 000329482000027

    View details for PubMedID 24231240

  • Atherosclerotic Plaque Detection With a Fluorescence/Radionuclide Intravascular Imaging System for 18F-FDG and 6-NBDG Zaman, R., Kosuge, H., Pratx, G., Carpenter, C., Xing, L., McConnell, M. V. LIPPINCOTT WILLIAMS & WILKINS. 2013
  • Cone beam CT imaging with limited angle of projections and prior knowledge for volumetric verification of non-coplanar beam radiation therapy: a proof of concept study. Physics in medicine and biology Meng, B., Xing, L., Han, B., Koong, A., Chang, D., Cheng, J., Li, R. 2013; 58 (21): 7777-7789

    Abstract

    Non-coplanar beams are important for treatment of both cranial and noncranial tumors. Treatment verification of such beams with couch rotation/kicks, however, is challenging, particularly for the application of cone beam CT (CBCT). In this situation, only limited and unconventional imaging angles are feasible to avoid collision between the gantry, couch, patient, and on-board imaging system. The purpose of this work is to develop a CBCT verification strategy for patients undergoing non-coplanar radiation therapy. We propose an image reconstruction scheme that integrates a prior image constrained compressed sensing (PICCS) technique with image registration. Planning CT or CBCT acquired at the neutral position is rotated and translated according to the nominal couch rotation/translation to serve as the initial prior image. Here, the nominal couch movement is chosen to have a rotational error of 5° and translational error of 8 mm from the ground truth in one or more axes or directions. The proposed reconstruction scheme alternates between two major steps. First, an image is reconstructed using the PICCS technique implemented with total-variation minimization and simultaneous algebraic reconstruction. Second, the rotational/translational setup errors are corrected and the prior image is updated by applying rigid image registration between the reconstructed image and the previous prior image. The PICCS algorithm and rigid image registration are alternated iteratively until the registration results fall below a predetermined threshold. The proposed reconstruction algorithm is evaluated with an anthropomorphic digital phantom and physical head phantom. The proposed algorithm provides useful volumetric images for patient setup using projections with an angular range as small as 60°. It reduced the translational setup errors from 8 mm to generally <1 mm and the rotational setup errors from 5° to <1°. Compared with the PICCS algorithm alone, the integration of rigid registration significantly improved the reconstructed image quality, with a reduction of mostly 2-3 folds (up to 100) in root mean square image error. The proposed algorithm provides a remedy for solving the problem of non-coplanar CBCT reconstruction from limited angle of projections by combining the PICCS technique and rigid image registration in an iterative framework. In this proof of concept study, non-coplanar beams with couch rotations of 45° can be effectively verified with the CBCT technique.

    View details for DOI 10.1088/0031-9155/58/21/7777

    View details for PubMedID 24140954

  • An assessment of PTV margin based on actual accumulated dose for prostate cancer radiotherapy PHYSICS IN MEDICINE AND BIOLOGY Wen, N., Kumarasiri, A., Nurushev, T., Burmeister, J., Xing, L., Liu, D., Glide-Hurst, C., Kim, J., Zhong, H., Movsas, B., Chetty, I. J. 2013; 58 (21): 7733–44

    Abstract

    The purpose of this work is to present the results of a margin reduction study involving dosimetric and radiobiologic assessment of cumulative dose distributions, computed using an image guided adaptive radiotherapy based framework. Eight prostate cancer patients, treated with 7-9, 6 MV, intensity modulated radiation therapy (IMRT) fields, were included in this study. The workflow consists of cone beam CT (CBCT) based localization, deformable image registration of the CBCT to simulation CT image datasets (SIM-CT), dose reconstruction and dose accumulation on the SIM-CT, and plan evaluation using radiobiological models. For each patient, three IMRT plans were generated with different margins applied to the CTV. The PTV margin for the original plan was 10 mm and 6 mm at the prostate/anterior rectal wall interface (10/6 mm) and was reduced to: (a) 5/3 mm, and (b) 3 mm uniformly. The average percent reductions in predicted tumor control probability (TCP) in the accumulated (actual) plans in comparison to the original plans over eight patients were 0.4%, 0.7% and 11.0% with 10/6 mm, 5/3 mm and 3 mm uniform margin respectively. The mean increase in predicted normal tissue complication probability (NTCP) for grades 2/3 rectal bleeding for the actual plans in comparison to the static plans with margins of 10/6, 5/3 and 3 mm uniformly was 3.5%, 2.8% and 2.4% respectively. For the actual dose distributions, predicted NTCP for late rectal bleeding was reduced by 3.6% on average when the margin was reduced from 10/6 mm to 5/3 mm, and further reduced by 1.0% on average when the margin was reduced to 3 mm. The average reduction in complication free tumor control probability (P+) in the actual plans in comparison to the original plans with margins of 10/6, 5/3 and 3 mm was 3.7%, 2.4% and 13.6% correspondingly. The significant reduction of TCP and P+ in the actual plan with 3 mm margin came from one outlier, where individualizing patient treatment plans through margin adaptation based on biological models, might yield higher quality treatments.

    View details for DOI 10.1088/0031-9155/58/21/7733

    View details for Web of Science ID 000326377100020

    View details for PubMedID 24140847

    View details for PubMedCentralID PMC4073000

  • High-Resolution Radioluminescence Microscopy of F-18-FDG Uptake by Reconstructing the beta-Ionization Track JOURNAL OF NUCLEAR MEDICINE Pratx, G., Chen, K., Sun, C., Axente, M., Sasportas, L., Carpenter, C., Xing, L. 2013; 54 (10): 1841-1846

    Abstract

    Radioluminescence microscopy is a new method for imaging radionuclide uptake by single live cells with a fluorescence microscope. Here, we report a particle-counting scheme that improves spatial resolution by overcoming the β-range limit.Short frames (10 μs-1 s) were acquired using a high-gain camera coupled to a microscope to capture individual ionization tracks. Optical reconstruction of the β-ionization track (ORBIT) was performed to localize individual β decays, which were aggregated into a composite image. The new approach was evaluated by imaging the uptake of (18)F-FDG in nonconfluent breast cancer cells.After image reconstruction, ORBIT resulted in better definition of individual cells. This effect was particularly noticeable in small clusters (2-4 cells), which occur naturally even for nonconfluent cell cultures. The annihilation and Bremsstrahlung photon background signal was markedly lower. Single-cell measurements of (18)F-FDG uptake that were computed from ORBIT images more closely matched the uptake of the fluorescent glucose analog (Pearson correlation coefficient, 0.54 vs. 0.44, respectively).ORBIT can image the uptake of a radiotracer in living cells with spatial resolution better than the β range. In principle, ORBIT may also allow for greater quantitative accuracy because the decay rate is measured more directly, with no dependency on the β-particle energy.

    View details for DOI 10.2967/jnumed.112.113365

    View details for Web of Science ID 000325341300027

    View details for PubMedID 24003077

  • An introduction to molecular imaging in radiation oncology: A report by the AAPM Working Group on Molecular Imaging in Radiation Oncology (WGMIR) MEDICAL PHYSICS Munley, M. T., Kagadis, G. C., McGee, K. P., Kirov, A. S., Jang, S., Mutic, S., Jeraj, R., Xing, L., Bourland, J. D. 2013; 40 (10)

    Abstract

    Molecular imaging is the direct or indirect noninvasive monitoring and recording of the spatial and temporal distribution of in vivo molecular, genetic, and/or cellular processes for biochemical, biological, diagnostic, or therapeutic applications. Molecular images that indicate the presence of malignancy can be acquired using optical, ultrasonic, radiologic, radionuclide, and magnetic resonance techniques. For the radiation oncology physicist in particular, these methods and their roles in molecular imaging of oncologic processes are reviewed with respect to their physical bases and imaging characteristics, including signal intensity, spatial scale, and spatial resolution. Relevant molecular terminology is defined as an educational assist. Current and future clinical applications in oncologic diagnosis and treatment are discussed. National initiatives for the development of basic science and clinical molecular imaging techniques and expertise are reviewed, illustrating research opportunities in as well as the importance of this growing field.

    View details for DOI 10.1118/1.4819818

    View details for Web of Science ID 000325394400004

    View details for PubMedID 24089890

  • Toward a web-based real-time radiation treatment planning system in a cloud computing environment PHYSICS IN MEDICINE AND BIOLOGY Na, Y. H., Suh, T., Kapp, D. S., Xing, L. 2013; 58 (18): 6525-6540

    Abstract

    To exploit the potential dosimetric advantages of intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), an in-depth approach is required to provide efficient computing methods. This needs to incorporate clinically related organ specific constraints, Monte Carlo (MC) dose calculations, and large-scale plan optimization. This paper describes our first steps toward a web-based real-time radiation treatment planning system in a cloud computing environment (CCE). The Amazon Elastic Compute Cloud (EC2) with a master node (named m2.xlarge containing 17.1 GB of memory, two virtual cores with 3.25 EC2 Compute Units each, 420 GB of instance storage, 64-bit platform) is used as the backbone of cloud computing for dose calculation and plan optimization. The master node is able to scale the workers on an 'on-demand' basis. MC dose calculation is employed to generate accurate beamlet dose kernels by parallel tasks. The intensity modulation optimization uses total-variation regularization (TVR) and generates piecewise constant fluence maps for each initial beam direction in a distributed manner over the CCE. The optimized fluence maps are segmented into deliverable apertures. The shape of each aperture is iteratively rectified to be a sequence of arcs using the manufacture's constraints. The output plan file from the EC2 is sent to the simple storage service. Three de-identified clinical cancer treatment plans have been studied for evaluating the performance of the new planning platform with 6 MV flattening filter free beams (40 × 40 cm(2)) from the Varian TrueBeam(TM) STx linear accelerator. A CCE leads to speed-ups of up to 14-fold for both dose kernel calculations and plan optimizations in the head and neck, lung, and prostate cancer cases considered in this study. The proposed system relies on a CCE that is able to provide an infrastructure for parallel and distributed computing. The resultant plans from the cloud computing are identical to PC-based IMRT and VMAT plans, confirming the reliability of the cloud computing platform. This cloud computing infrastructure has been established for a radiation treatment planning. It substantially improves the speed of inverse planning and makes future on-treatment adaptive re-planning possible.

    View details for DOI 10.1088/0031-9155/58/18/6525

    View details for Web of Science ID 000324573400019

    View details for PubMedID 24002571

  • Automatic prostate tracking and motion assessment in volumetric modulated arc therapy with an electronic portal imaging device. International journal of radiation oncology, biology, physics Azcona, J. D., Li, R., Mok, E., Hancock, S., Xing, L. 2013; 86 (4): 762-768

    Abstract

    PURPOSE: To assess the prostate intrafraction motion in volumetric modulated arc therapy treatments using cine megavoltage (MV) images acquired with an electronic portal imaging device (EPID). METHODS AND MATERIALS: Ten prostate cancer patients were treated with volumetric modulated arc therapy using a Varian TrueBeam linear accelerator equipped with an EPID for acquiring cine MV images during treatment. Cine MV images acquisition was scheduled for single or multiple treatment fractions (between 1 and 8). A novel automatic fiducial detection algorithm that can handle irregular multileaf collimator apertures, field edges, fast leaf and gantry movement, and MV image noise and artifacts in patient anatomy was used. All sets of images (approximately 25,000 images in total) were analyzed to measure the positioning accuracy of implanted fiducial markers and assess the prostate movement. RESULTS: Prostate motion can vary greatly in magnitude among different patients. Different motion patterns were identified, showing its unpredictability. The mean displacement and standard deviation of the intrafraction motion was generally less than 2.0 ± 2.0 mm in each of the spatial directions. In certain patients, however, the percentage of the treatment time in which the prostate is displaced more than 5 mm from its planned position in at least 1 spatial direction was 10% or more. The maximum prostate displacement observed was 13.3 mm. CONCLUSION: Prostate tracking and motion assessment was performed with MV imaging and an EPID. The amount of prostate motion observed suggests that patients will benefit from its real-time monitoring. Megavoltage imaging can provide the basis for real-time prostate tracking using conventional linear accelerators.

    View details for DOI 10.1016/j.ijrobp.2013.03.007

    View details for PubMedID 23608236

  • Sequentially reweighted TV minimization for CT metal artifact reduction MEDICAL PHYSICS Zhang, X., Xing, L. 2013; 40 (7)

    Abstract

    Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions.A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach.Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties.The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.

    View details for DOI 10.1118/1.4811129

    View details for Web of Science ID 000321272200044

    View details for PubMedID 23822444

    View details for PubMedCentralID PMC3710254

  • Improving IMRT delivery efficiency with reweighted L1-minimization for inverse planning MEDICAL PHYSICS Kim, H., Becker, S., Lee, R., Lee, S., Shin, S., Candes, E., Xing, L., Li, R. 2013; 40 (7)

    Abstract

    This study presents an improved technique to further simplify the fluence-map in intensity modulated radiation therapy (IMRT) inverse planning, thereby reducing plan complexity and improving delivery efficiency, while maintaining the plan quality.First-order total-variation (TV) minimization (min.) based on L1-norm has been proposed to reduce the complexity of fluence-map in IMRT by generating sparse fluence-map variations. However, with stronger dose sparing to the critical structures, the inevitable increase in the fluence-map complexity can lead to inefficient dose delivery. Theoretically, L0-min. is the ideal solution for the sparse signal recovery problem, yet practically intractable due to its nonconvexity of the objective function. As an alternative, the authors use the iteratively reweighted L1-min. technique to incorporate the benefits of the L0-norm into the tractability of L1-min. The weight multiplied to each element is inversely related to the magnitude of the corresponding element, which is iteratively updated by the reweighting process. The proposed penalizing process combined with TV min. further improves sparsity in the fluence-map variations, hence ultimately enhancing the delivery efficiency. To validate the proposed method, this work compares three treatment plans obtained from quadratic min. (generally used in clinic IMRT), conventional TV min., and our proposed reweighted TV min. techniques, implemented by a large-scale L1-solver (template for first-order conic solver), for five patient clinical data. Criteria such as conformation number (CN), modulation index (MI), and estimated treatment time are employed to assess the relationship between the plan quality and delivery efficiency.The proposed method yields simpler fluence-maps than the quadratic and conventional TV based techniques. To attain a given CN and dose sparing to the critical organs for 5 clinical cases, the proposed method reduces the number of segments by 10-15 and 30-35, relative to TV min. and quadratic min. based plans, while MIs decreases by about 20%-30% and 40%-60% over the plans by two existing techniques, respectively. With such conditions, the total treatment time of the plans obtained from our proposed method can be reduced by 12-30 s and 30-80 s mainly due to greatly shorter multileaf collimator (MLC) traveling time in IMRT step-and-shoot delivery.The reweighted L1-minimization technique provides a promising solution to simplify the fluence-map variations in IMRT inverse planning. It improves the delivery efficiency by reducing the entire segments and treatment time, while maintaining the plan quality in terms of target conformity and critical structure sparing.

    View details for DOI 10.1118/1.4811100

    View details for PubMedID 23822423

  • Tissue feature-based intra-fractional motion tracking for stereoscopic x-ray image guided radiotherapy. Physics in medicine and biology Xie, Y., Xing, L., Gu, J., Liu, W. 2013; 58 (11): 3615-3630

    Abstract

    Real-time knowledge of tumor position during radiation therapy is essential to overcome the adverse effect of intra-fractional organ motion. The goal of this work is to develop a tumor tracking strategy by effectively utilizing the inherent image features of stereoscopic x-ray images acquired during dose delivery. In stereoscopic x-ray image guided radiation delivery, two orthogonal x-ray images are acquired either simultaneously or sequentially. The essence of markerless tumor tracking is the reliable identification of inherent points with distinct tissue features on each projection image and their association between two images. The identification of the feature points on a planar x-ray image is realized by searching for points with high intensity gradient. The feature points are associated by using the scale invariance features transform descriptor. The performance of the proposed technique is evaluated by using images of a motion phantom and four archived clinical cases acquired using either a CyberKnife equipped with a stereoscopic x-ray imaging system, or a LINAC equipped with an onboard kV imager and an electronic portal imaging device. In the phantom study, the results obtained using the proposed method agree with the measurements to within 2 mm in all three directions. In the clinical study, the mean error is 0.48 ± 0.46 mm for four patient data with 144 sequential images. In this work, a tissue feature-based tracking method for stereoscopic x-ray image guided radiation therapy is developed. The technique avoids the invasive procedure of fiducial implantation and may greatly facilitate the clinical workflow.

    View details for DOI 10.1088/0031-9155/58/11/3615

    View details for PubMedID 23648334

  • X-ray excitable luminescent polymer dots doped with an iridium(iii) complex. Chemical communications Osakada, Y., Pratx, G., Hanson, L., Solomon, P. E., Xing, L., Cui, B. 2013; 49 (39): 4319-4321

    Abstract

    In this study, cyclometalated iridium(III) complex-doped polymer dots were synthesized and shown to emit luminescence upon X-ray irradiation, potentially serving as a new probe for molecular imaging during X-ray computed tomography.

    View details for DOI 10.1039/c2cc37169c

    View details for PubMedID 23320256

  • Image-guided resection of malignant gliomas using ?uorescent nanoparticles. Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology Su, X., Cheng, K., Wang, C., Xing, L., Wu, H., Cheng, Z. 2013; 5 (3): 219-232

    Abstract

    Intraoperative fluorescence imaging especially near-infrared fluorescence (NIRF) imaging has the potential to revolutionize neurosurgery by providing high sensitivity and real-time image guidance to surgeons for defining gliomas margins. Fluorescence probes including targeted nanoprobes are expected to improve the specificity and selectivity for intraoperative fluorescence or NIRF tumor imaging. The main focus of this article is to provide a brief overview of intraoperative fluorescence imaging systems and probes including fluorescein sodium, 5-aminolevulinic acid, dye-containing nanoparticles, and targeted NIRF nanoprobes for their applications in image-guided resection of malignant gliomas. Moreover, photoacoustic imaging is a promising molecular imaging modality, and its potential applications for brain tumor imaging are also briefly discussed.

    View details for DOI 10.1002/wnan.1212

    View details for PubMedID 23378052

  • Optimization of normalized prescription isodose selection for stereotactic body radiation therapy: Conventional vs robotic linac MEDICAL PHYSICS Ding, C., Solberg, T. D., Hrycushko, B., Xing, L., Heinzerling, J., Timmerman, R. D. 2013; 40 (5)

    Abstract

    Although modern technology has allowed for target dose escalation by minimizing normal tissue dose, the dose delivered to a tumor and surrounding tissues still depends largely on the inherent characteristics of the radiation delivery platform. This work aims to determine the optimal prescription isodose line that minimizes normal tissue irradiation for stereotactic body radiation therapy (SBRT) for a conventional linear accelerator and a robotic delivery platform.Spherical targets with diameters of 10, 20, and 30 mm were constructed in the lungs and liver of a computer based digital torso phantom which simulates respiratory and cardiac motion. Normal tissue contours included normal lung, normal liver, and a concentric 10 mm shell of normal tissue extending from the spherical target surface. For linac planning, noncoplanar, nonopposing three dimensional (3D) conformal beams were designed, and variable prescription isodose lines were achieved by varying the MLC block margin. For CyberKnife planning, variable prescription isodose lines were achieved by inverse planning. True 4D dose calculations were used for the moving target and surrounding tissue based on each of ten phases of a 4D CT dataset. Doses of 60 Gy in three fractions were prescribed to cover 95% of the target tumor. Commonly used conformality, dosimetric, and radiobiological indices for lung and liver SBRT were used to compare different plans and determine the optimally prescribed isodose line for each treatment platform.For linac plans, the average optimal prescription isodose line based on all indices evaluated occurred between 59% and 69% for lung tumors and between 67% and 77% for liver tumors depending on the tumor size. CyberKnife plans had average optimal prescription isodose lines occurring between 40% and 48% for lung tumors and between 41% and 42% depending on the tumor size. However, prescription isodose lines under 50% are not advised to prevent large heterogeneous dose distributions within the target.The choice of prescription isodose line was shown to have a significant impact on parameters commonly used as constraints for lung and liver SBRT treatment planning for both linac-based and CyberKnife delivery platforms. By methodically choosing the prescription isodose line, normal tissue toxicities from SBRT may be reduced.

    View details for DOI 10.1118/1.4798944

    View details for Web of Science ID 000318553900008

    View details for PubMedID 23635253

  • An adaptive planning strategy for station parameter optimized radiation therapy (SPORT): Segmentally boosted VMAT. Medical physics Li, R., Xing, L. 2013; 40 (5): 050701-?

    Abstract

    Conventional volumetric modulated arc therapy (VMAT) discretizes the angular space into equally spaced control points during planning and then optimizes the apertures and weights of the control points. The aperture at an angle in between two control points is obtained through interpolation. This approach tacitly ignores the differential need for intensity modulation of different angles. As such, multiple arcs are often required, which may oversample some angle(s) and undersample others. The purpose of this work is to develop a segmentally boosted VMAT scheme to eliminate the need for multiple arcs in VMAT treatment with improved dose distribution and∕or delivery efficiency.The essence of the new treatment scheme is how to identify the need of individual angles for intensity modulation and to provide the necessary beam intensity modulation for those beam angles that need it. We introduce a "demand metric" at each control point to decide which station or control points need intensity modulation. To boost the modulation at selected stations, additional segments are added in the vicinity of the selected stations. The added segments are then optimized together with the original set of station or control points as a whole. The authors apply the segmentally boosted planning technique to four previously treated clinical cases: two head and neck (HN) cases, one prostate case, and one liver case. The proposed planning technique is compared with conventional one-arc and two-arc VMAT.The proposed segmentally boosted VMAT technique achieves better critical structure sparing than one-arc VMAT with similar or better target coverage in all four clinical cases. The segmentally boosted VMAT also outperforms two-arc VMAT for the two complicated HN cases, yet with ∼30% reduction in the machine monitor units (MUs) relative to two-arc VMAT, which leads to less leakage∕scatter dose to the patient and can potentially translate into faster dose delivery. For the less challenging prostate and liver cases, similar critical structure sparing as the two-arc VMAT plans was obtained using the segmentally boosted VMAT. The benefit for the two simpler cases is the reduction of MUs and improvement of treatment delivery efficiency.Segmentally boosted VMAT achieves better dose conformality and∕or reduced MUs through effective consideration of the need of individual beam angles for intensity modulation. Elimination of the need for multiple arcs in rotational arc therapy while improving the dose distribution should lead to improved workflow and treatment efficacy, thus may have significant implication to radiation oncology practice.

    View details for DOI 10.1118/1.4802748

    View details for PubMedID 23635247

    View details for PubMedCentralID PMC3656955

  • First study of on-treatment volumetric imaging during respiratory gated VMAT. Medical physics Choi, K., Xing, L., Koong, A., Li, R. 2013; 40 (4): 040701-?

    Abstract

    To obtain on-treatment volumetric patient anatomy during respiratory gated volumetric modulated arc therapy (VMAT).On-board imaging device integrated with Linacs offers a viable tool for obtaining patient anatomy during radiation treatment delivery. In this study, the authors acquired beam-level kV images during gated VMAT treatments using a Varian TrueBeam™STx Linac. These kV projection images are triggered by a respiratory gating signal and can be acquired immediately before treatment MV beam on at every breathing cycle during delivery. Because the kV images are acquired with an on-board imaging device during a rotational arc therapy, they provide the patient anatomical information from many different angles or projection views (typically 20-40). To reconstruct the volumetric image representing patient anatomy during the VMAT treatment, the authors used a compressed sensing method with a fast first-order optimization algorithm. The conventional FDK reconstruction was also used for comparison purposes. The method was tested on a dynamic anthropomorphic physical phantom as well as a lung patient.The reconstructed volumetric images for a dynamic anthropomorphic physical phantom and a lung patient showed clearly visible soft-tissue target as well as other anatomical structures, with the proposed compressed sensing-based image reconstruction method. Compared with FDK, the compressed sensing method leads to a ≈ two and threefold increase in contrast-to-noise ratio around the target area in the phantom and patient case, respectively.The proposed technique provides on-treatment volumetric patient anatomy, with only a fraction (<10%) of the imaging dose used in conventional CBCT procedures. This anatomical information may be valuable for geometric verification and treatment guidance, and useful for verification of treatment dose delivery, accumulation, and adaptation in the future.

    View details for DOI 10.1118/1.4794925

    View details for PubMedID 23556870

    View details for PubMedCentralID PMC3612119

  • Development of a fast and feasible spectrum modeling technique for flattening filter free beams MEDICAL PHYSICS Cho, W., Bush, K., Mok, E., Xing, L., Suh, T. 2013; 40 (4)

    Abstract

    To develop a fast and robust technique for the determination of optimized photon spectra for flattening filter free (FFF) beams to be applied in convolution/superposition dose calculations.A two-step optimization method was developed to derive optimal photon spectra for FFF beams. In the first step, a simple functional form of the photon spectra proposed by Ali ["Functional forms for photon spectra of clinical linacs," Phys. Med. Biol. 57, 31-50 (2011)] is used to determine generalized shapes of the photon spectra. In this method, the photon spectra were defined for the ranges of field sizes to consider the variations of the contributions of scattered photons with field size. Percent depth doses (PDDs) for each field size were measured and calculated to define a cost function, and a collapsed cone convolution (CCC) algorithm was used to calculate the PDDs. In the second step, the generalized functional form of the photon spectra was fine-tuned in a process whereby the weights of photon fluence became the optimizing free parameters. A line search method was used for the optimization and first order derivatives with respect to the optimizing parameters were derived from the CCC algorithm to enhance the speed of the optimization. The derived photon spectra were evaluated, and the dose distributions using the optimized spectra were validated.The optimal spectra demonstrate small variations with field size for the 6 MV FFF beam and relatively large variations for the 10 MV FFF beam. The mean energies of the optimized 6 MV FFF spectra were decreased from 1.31 MeV for a 3 × 3 cm(2) field to 1.21 MeV for a 40 × 40 cm(2) field, and from 2.33 MeV at 3 × 3 cm(2) to 2.18 MeV at 40 × 40 cm(2) for the 10 MV FFF beam. The developed method could significantly improve the agreement between the calculated and measured PDDs. Root mean square differences on the optimized PDDs were observed to be 0.41% (3 × 3 cm(2)) down to 0.21% (40 × 40 cm(2)) for the 6 MV FFF beam, and 0.35% (3 × 3 cm(2)) down to 0.29% (40 × 40 cm(2)) for the 10 MV FFF beam. The first order derivatives from the functional form were found to improve the speed of computational time up to 20 times compared to the other techniques.The derived photon spectra resulted in good agreements with measured PDDs over the range of field sizes investigated. The suggested method is easily applicable to commercial radiation treatment planning systems since it only requires measured PDDs as input.

    View details for DOI 10.1118/1.4797469

    View details for Web of Science ID 000317945900027

    View details for PubMedID 23556891

  • Dosimetric analysis of organs at risk during expiratory gating in stereotactic body radiation therapy for pancreatic cancer. International journal of radiation oncology, biology, physics Taniguchi, C. M., Murphy, J. D., Eclov, N., Atwood, T. F., Kielar, K. N., Christman-Skieller, C., Mok, E., Xing, L., Koong, A. C., Chang, D. T. 2013; 85 (4): 1090-1095

    Abstract

    To determine how the respiratory phase impacts dose to normal organs during stereotactic body radiation therapy (SBRT) for pancreatic cancer.Eighteen consecutive patients with locally advanced, unresectable pancreatic adenocarcinoma treated with SBRT were included in this study. On the treatment planning 4-dimensional computed tomography (CT) scan, the planning target volume (PTV), defined as the gross tumor volume plus 3-mm margin, the duodenum, and the stomach were contoured on the end-expiration (CTexp) and end-inspiration (CTinsp) phases for each patient. A separate treatment plan was constructed for both phases with the dose prescription of 33 Gy in 5 fractions with 95% coverage of the PTV by the 100% isodose line. The dose-volume histogram (DVH) endpoints, volume of duodenum that received 20 Gy (V20), V25, and V30 and maximum dose to 5 cc of contoured organ (D5cc), D1cc, and D0.1cc, were evaluated.Dosimetric parameters for the duodenum, including V25, V30, D1cc, and D0.1cc improved by planning on the CTexp compared to those on the CTinsp. There was a statistically significant overlap of the PTV with the duodenum but not the stomach during the CTinsp compared to the CTexp (0.38 ± 0.17 cc vs 0.01 ± 0.01 cc, P=.048). A larger expansion of the PTV, in accordance with a Danish phase 2 trial, showed even more overlapping volume of duodenum on the CTinsp compared to that on the CTexp (5.5 ± 0.9 cc vs 3.0 ± 0.8 cc, P=.0003) but no statistical difference for any stomach dosimetric DVH parameter.Dose to the duodenum was higher when treating on the inspiratory than on the expiratory phase. These data suggest that expiratory gating may be preferable to inspiratory breath-hold and free breathing strategies for minimizing risk of toxicity.

    View details for DOI 10.1016/j.ijrobp.2012.07.2366

    View details for PubMedID 23273994

  • Dosimetric Analysis of Organs at Risk During Expiratory Gating in Stereotactic Body Radiation Therapy for Pancreatic Cancer INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Taniguchi, C. M., Murphy, J. D., Eclov, N., Atwood, T. F., Phd, K. N., Christman-Skieller, C., Mok, E., Xing, L., Koong, A. C., Chang, D. T. 2013; 85 (4): 1090-1095

    Abstract

    To determine how the respiratory phase impacts dose to normal organs during stereotactic body radiation therapy (SBRT) for pancreatic cancer.Eighteen consecutive patients with locally advanced, unresectable pancreatic adenocarcinoma treated with SBRT were included in this study. On the treatment planning 4-dimensional computed tomography (CT) scan, the planning target volume (PTV), defined as the gross tumor volume plus 3-mm margin, the duodenum, and the stomach were contoured on the end-expiration (CTexp) and end-inspiration (CTinsp) phases for each patient. A separate treatment plan was constructed for both phases with the dose prescription of 33 Gy in 5 fractions with 95% coverage of the PTV by the 100% isodose line. The dose-volume histogram (DVH) endpoints, volume of duodenum that received 20 Gy (V20), V25, and V30 and maximum dose to 5 cc of contoured organ (D5cc), D1cc, and D0.1cc, were evaluated.Dosimetric parameters for the duodenum, including V25, V30, D1cc, and D0.1cc improved by planning on the CTexp compared to those on the CTinsp. There was a statistically significant overlap of the PTV with the duodenum but not the stomach during the CTinsp compared to the CTexp (0.38 ± 0.17 cc vs 0.01 ± 0.01 cc, P=.048). A larger expansion of the PTV, in accordance with a Danish phase 2 trial, showed even more overlapping volume of duodenum on the CTinsp compared to that on the CTexp (5.5 ± 0.9 cc vs 3.0 ± 0.8 cc, P=.0003) but no statistical difference for any stomach dosimetric DVH parameter.Dose to the duodenum was higher when treating on the inspiratory than on the expiratory phase. These data suggest that expiratory gating may be preferable to inspiratory breath-hold and free breathing strategies for minimizing risk of toxicity.

    View details for DOI 10.1016/j.ijrobp.2012.07.2366

    View details for Web of Science ID 000315809300047

  • Development of XFCT imaging strategy for monitoring the spatial distribution of platinum-based chemodrugs: Instrumentation and phantom validation MEDICAL PHYSICS Kuang, Y., Pratx, G., Bazalova, M., Qian, J., Meng, B., Xing, L. 2013; 40 (3)

    Abstract

    Developing an imaging method to directly monitor the spatial distribution of platinum-based (Pt) drugs at the tumor region is of critical importance for early assessment of treatment efficacy and personalized treatment. In this study, the authors investigated the feasibility of imaging platinum (Pt)-based drug distribution using x-ray fluorescence (XRF, a.k.a. characteristic x ray) CT (XFCT).A 5-mm-diameter pencil beam produced by a polychromatic x-ray source equipped with a tungsten anode was used to stimulate emission of XRF photons from Pt drug embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The x-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used for the K-shell XRF peak isolation and sinogram generation for Pt. The distribution and concentration of Pt were reconstructed with an iterative maximum likelihood expectation maximization algorithm. The capability of XFCT to multiplexed imaging of Pt, gadolinium (Gd), and iodine (I) within a water phantom was also investigated.Measured XRF spectrum showed a sharp peak characteristic of Pt with a narrow full-width at half-maximum (FWHM) (FWHMKα1 = 1.138 keV, FWHMKα2 = 1.052 keV). The distribution of Pt drug in the water phantom was clearly identifiable on the reconstructed XRF images. Our results showed a linear relationship between the XRF intensity of Pt and its concentrations (R(2) = 0.995), suggesting that XFCT is capable of quantitative imaging. A transmission CT image was also obtained to show the potential of the approach for providing attenuation correction and morphological information. Finally, the distribution of Pt, Gd, and I in the water phantom was clearly identifiable in the reconstructed images from XFCT multiplexed imaging.XFCT is a promising modality for monitoring the spatial distribution of Pt drugs. The technique may be useful in tailoring tumor treatment regimen in the future.

    View details for DOI 10.1118/1.4789917

    View details for Web of Science ID 000316369400003

    View details for PubMedID 23464279

    View details for PubMedCentralID PMC3585826

  • Development and clinical evaluation of automatic fiducial detection for tumor tracking in cine megavoltage images during volumetric modulated arc therapy MEDICAL PHYSICS Azcona, J. D., Li, R., Mok, E., Hancock, S., Xing, L. 2013; 40 (3)

    Abstract

    Real-time tracking of implanted fiducials in cine megavoltage (MV) imaging during volumetric modulated arc therapy (VMAT) delivery is complicated due to the inherent low contrast of MV images and potential blockage of dynamic leaves configurations. The purpose of this work is to develop a clinically practical autodetection algorithm for motion management during VMAT.The expected field-specific segments and the planned fiducial position from the Eclipse (Varian Medical Systems, Palo Alto, CA) treatment planning system were projected onto the MV images. The fiducials were enhanced by applying a Laplacian of Gaussian filter in the spatial domain for each image, with a blob-shaped object as the impulse response. The search of implanted fiducials was then performed on a region of interest centered on the projection of the fiducial when it was within an open field including the case when it was close to the field edge or partially occluded by the leaves. A universal template formula was proposed for template matching and normalized cross correlation was employed for its simplicity and computational efficiency. The search region for every image was adaptively updated through a prediction model that employed the 3D position of the fiducial estimated from the localized positions in previous images. This prediction model allowed the actual fiducial position to be tracked dynamically and was used to initialize the search region. The artifacts caused by electronic interference during the acquisition were effectively removed. A score map was computed by combining both morphological information and image intensity. The pixel location with the highest score was selected as the detected fiducial position. The sets of cine MV images taken during treatment were analyzed with in-house developed software written in MATLAB (The Mathworks, Inc., Natick, MA). Five prostate patients were analyzed to assess the algorithm performance by measuring their positioning accuracy during treatment.The algorithm was able to accurately localize the fiducial position on MV images with success rates of more than 90% per case. The percentage of images in which each fiducial was localized in the studied cases varied between 23% and 65%, with at least one fiducial having been localized between 40% and 95% of the images. This depended mainly on the modulation of the plan and fiducial blockage. The prostate movement in the presented cases varied between 0.8 and 3.5 mm (mean values). The maximum displacement detected among all patients was of 5.7 mm.An algorithm for automatic detection of fiducial markers in cine MV images has been developed and tested with five clinical cases. Despite the challenges posed by complex beam aperture shapes, fiducial localization close to the field edge, partial occlusion of fiducials, fast leaf and gantry movement, and inherently low MV image quality, good localization results were achieved in patient images. This work provides a technique for enabling real-time accurate fiducial detection and tumor tracking during VMAT treatments without the use of extra imaging dose.

    View details for DOI 10.1118/1.4791646

    View details for Web of Science ID 000316369400011

    View details for PubMedID 23464303

    View details for PubMedCentralID PMC3592890

  • Point/counterpoint. DASSIM-RT is likely to become the method of choice over conventional IMRT and VMAT for delivery of highly conformal radiotherapy. Medical physics Xing, L., Phillips, M. H., Orton, C. G. 2013; 40 (2): 020601-?

    View details for DOI 10.1118/1.4773025

    View details for PubMedID 23387721

  • First Demonstration of Multiplexed X-Ray Fluorescence Computed Tomography (XFCT) Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING Kuang, Y., Pratx, G., Bazalova, M., Meng, B., Qian, J., Xing, L. 2013; 32 (2): 262-267

    Abstract

    Simultaneous imaging of multiple probes or biomarkers represents a critical step toward high specificity molecular imaging. In this work, we propose to utilize the element-specific nature of the X-ray fluorescence (XRF) signal for imaging multiple elements simultaneously (multiplexing) using XRF computed tomography (XFCT). A 5-mm-diameter pencil beam produced by a polychromatic X-ray source (150 kV, 20 mA) was used to stimulate emission of XRF photons from 2% (weight/volume) gold (Au), gadolinium (Gd), and barium (Ba) embedded within a water phantom. The phantom was translated and rotated relative to the stationary pencil beam in a first-generation CT geometry. The X-ray energy spectrum was collected for 18 s at each position using a cadmium telluride detector. The spectra were then used to isolate the K shell XRF peak and to generate sinograms for the three elements of interest. The distribution and concentration of the three elements were reconstructed with the iterative maximum likelihood expectation maximization algorithm. The linearity between the XFCT intensity and the concentrations of elements of interest was investigated. We found that measured XRF spectra showed sharp peaks characteristic of Au, Gd, and Ba. The narrow full-width at half-maximum (FWHM) of the peaks strongly supports the potential of XFCT for multiplexed imaging of Au, Gd, and Ba ( FWHM(Au,Kα1) = 0.619 keV, FWHM(Au,Kα2)=1.371 keV , FWHM(Gd,Kα)=1.297 keV, FWHM(Gd,Kβ)=0.974 keV , FWHM(Ba,Kα)=0.852 keV, and FWHM(Ba,Kβ)=0.594 keV ). The distribution of Au, Gd, and Ba in the water phantom was clearly identifiable in the reconstructed XRF images. Our results showed linear relationships between the XRF intensity of each tested element and their concentrations ( R(2)(Au)=0.944 , R(Gd)(2)=0.986, and R(Ba)(2)=0.999), suggesting that XFCT is capable of quantitative imaging. Finally, a transmission CT image was obtained to show the potential of the approach for providing attenuation correction and morphological information. In conclusion, XFCT is a promising modality for multiplexed imaging of high atomic number probes.

    View details for DOI 10.1109/TMI.2012.2223709

    View details for Web of Science ID 000314367100011

    View details for PubMedID 23076031

  • Single-scan patient-specific scatter correction in computed tomography using peripheral detection of scatter and compressed sensing scatter retrieval MEDICAL PHYSICS Meng, B., Lee, H., Xing, L., Fahimian, B. P. 2013; 40 (1)

    Abstract

    X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space.The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme.The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphan©504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction.A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction.

    View details for DOI 10.1118/1.4769421

    View details for Web of Science ID 000313033200032

    View details for PubMedID 23298098

    View details for PubMedCentralID PMC3543379

  • Enhancement of four-dimensional cone-beam computed tomography by compressed sensing with Bregman iteration JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY Choi, K., Fahimian, B. P., Li, T., Suh, T., Lei, X. 2013; 21 (2): 177-192

    Abstract

    In four-dimensional (4D) cone-beam computed tomography (CBCT), there is a spatio-temporal tradeoff that currently limits the accuracy. The aim of this study is to develop a Bregman iteration based formalism for high quality 4D CBCT image reconstruction from a limited number of low-dose projections. The 4D CBCT problem is first divided into multiple 3D CBCT subproblems by grouping the projection images corresponding to the phases. To maximally utilize the information from the under-sampled projection data, a compressed sensing (CS) method with Bregman iterations is employed for solving each subproblem. We formulate an unconstrained optimization problem based on least-square criterion regularized by total-variation. The least-square criterion reflects the inconsistency between the measured and the estimated line integrals. Furthermore, the unconstrained problem is updated and solved repeatedly by Bregman iterations. The performance of the proposed algorithm is demonstrated through a series of simulation studies and phantom experiments, and the results are compared to those of previously implemented compressed sensing technique using other gradient-based methods as well as conventional filtered back-projection (FBP) results. The simulation and experimental studies have shown that artifact suppressed images can be obtained with as small as 41 projections per phase, which is adequate for clinical 4D CBCT reconstruction. With such small number of projections, the conventional FDK failed to yield meaningful 4D CBCT images, and CS technique using conjugate gradient was not able to recover sharp edges. The proposed method significantly reduces the radiation dose and scanning time to achieve the high quality images compared to the 4D CBCT imaging based on the conventional FDK technique and the existing CS techniques.

    View details for DOI 10.3233/XST-130371

    View details for Web of Science ID 000319344700003

    View details for PubMedID 23694910

  • X-ray induced photoacoustic tomography Conference on Photons Plus Ultrasound - Imaging and Sensing Xiang, L., Han, B., Carpenter, C., Pratx, G., Kuang, Y., Xing, L. SPIE-INT SOC OPTICAL ENGINEERING. 2013

    View details for DOI 10.1117/12.2005765

    View details for Web of Science ID 000322832800032

  • X-ray acoustic computed tomography with pulsed x-ray beam from a medical linear accelerator MEDICAL PHYSICS Xiang, L., Han, B., Carpenter, C., Pratx, G., Kuang, Y., Xing, L. 2013; 40 (1)

    Abstract

    The feasibility of medical imaging using a medical linear accelerator to generate acoustic waves is investigated. This modality, x-ray acoustic computed tomography (XACT), has the potential to enable deeper tissue penetration in tissue than photoacoustic tomography via laser excitation.Short pulsed (μs-range) 10 MV x-ray beams with dose-rate of approximately 30 Gy∕min were generated from a medical linear accelerator. The acoustic signals were collected with an ultrasound transducer (500 KHz central frequency) positioned around an object. The transducer, driven by a computer-controlled step motor to scan around the object, detected the resulting acoustic signals in the imaging plane at each scanning position. A pulse preamplifier, with a bandwidth of 20 KHz-2 MHz at -3 dB, and switchable gains of 40 and 60 dB, received the signals from the transducer and delivered the amplified signals to a secondary amplifier. The secondary amplifier had bandwidth of 20 KHz-30 MHz at -3 dB, and a gain range of 10-60 dB. Signals were recorded and averaged 128 times by an oscilloscope. A sampling rate of 100 MHz was used to record 2500 data points at each view angle. One set of data incorporated 200 positions as the receiver moved 360°. The x-ray generated acoustic image was then reconstructed with the filtered back projection algorithm.The x-ray generated acoustic signals were detected from a lead rod embedded in a chicken breast tissue. The authors found that the acoustic signal was proportional to the x-ray dose deposition, with a correlation of 0.998. The two-dimensional XACT images of the lead rod embedded in chicken breast tissue were found to be in good agreement with the shape of the object.The first x-ray acoustic computed tomography image is presented. The new modality may be useful for a number of applications, such as providing the location of a fiducial, or monitoring x-ray dose distribution during radiation therapy. Although much work is needed to improve the image quality of XACT and to explore its performance in other irradiation energies, the benefits of this modality, as highlighted in this work, encourage further study.

    View details for DOI 10.1118/1.4771935

    View details for Web of Science ID 000313033200003

    View details for PubMedID 23298069

    View details for PubMedCentralID PMC3537718

  • Practical Implementation of a Collapsed Cone Convolution Algorithm for a Radiation Treatment Planning System JOURNAL OF THE KOREAN PHYSICAL SOCIETY Cho, W., Suh, T., Park, J., Xing, L., Lee, J. 2012; 61 (12): 2073-2083
  • 4D cone beam CT via spatiotemporal tensor framelet MEDICAL PHYSICS Gao, H., Li, R., Lin, Y., Xing, L. 2012; 39 (11): 6943-6946

    Abstract

    On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose.The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization.Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet.By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

    View details for DOI 10.1118/1.4762288

    View details for Web of Science ID 000310726300042

    View details for PubMedID 23127087

    View details for PubMedCentralID PMC3494730

  • Prone Partial Breast Coronal Arc Irradiation: Combining Intensity Modulated Delivery With Dynamic Motion of the Couch 54th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) Fahimian, B. P., Yu, V., Xing, L., Horst, K., Hristov, D. ELSEVIER SCIENCE INC. 2012: S214–S214
  • Binary Moving Blocker-based Scatter Correction for Single Scan Cone Beam CT System With Off-Centered Detector 54th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) LEE, H., Fahimian, B. P., Xing, L. ELSEVIER SCIENCE INC. 2012: S797–S797
  • Development of XFCT Imaging Strategy for Monitoring the Spatial Distribution of Platinum Drugs: Instrumentation and Phantom Validation 54th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) Kuang, Y., Pratx, G., Qian, J., Meng, B., Bazalova, M., Xing, L. ELSEVIER SCIENCE INC. 2012: S132–S133
  • Prospectively Gated CBCT for Volumetric Image Guidance in SBRT 54th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) Fahimian, B. P., Xing, L. ELSEVIER SCIENCE INC. 2012: S199–S200
  • Single Scan Scatter Correction in Cone Beam CT Using a Stationary Boundary Blocker and Compressed Sensing-based Scatter Estimation 54th Annual Meeting of the American-Society-for-Radiation-Oncology (ASTRO) Meng, B., LEE, H., Xing, L., Fahimian, B. P. ELSEVIER SCIENCE INC. 2012: S82–S83
  • Effect of Li-deficiency impurities on the electron-overdoped LiFeAs superconductor PHYSICAL REVIEW B Wang, M., Wang, M., Miao, H., CARR, S. V., Abernathy, D. L., Stone, M. B., Wang, X. C., Xing, L., Jin, C. Q., Zhang, X., Hu, J., Xiang, T., Ding, H., Dai, P. 2012; 86 (14)
  • Radioluminescence Microscopy: Measuring the Heterogeneous Uptake of Radiotracers in Single Living Cells PLOS ONE Pratx, G., Chen, K., Sun, C., Martin, L., Carpenter, C. M., Olcott, P. D., Xing, L. 2012; 7 (10)

    Abstract

    Radiotracers play an important role in interrogating molecular processes both in vitro and in vivo. However, current methods are limited to measuring average radiotracer uptake in large cell populations and, as a result, lack the ability to quantify cell-to-cell variations. Here we apply a new technique, termed radioluminescence microscopy, to visualize radiotracer uptake in single living cells, in a standard fluorescence microscopy environment. In this technique, live cells are cultured sparsely on a thin scintillator plate and incubated with a radiotracer. Light produced following beta decay is measured using a highly sensitive microscope. Radioluminescence microscopy revealed strong heterogeneity in the uptake of [(18)F]fluoro-deoxyglucose (FDG) in single cells, which was found consistent with fluorescence imaging of a glucose analog. We also verified that dynamic uptake of FDG in single cells followed the standard two-tissue compartmental model. Last, we transfected cells with a fusion PET/fluorescence reporter gene and found that uptake of FHBG (a PET radiotracer for transgene expression) coincided with expression of the fluorescent protein. Together, these results indicate that radioluminescence microscopy can visualize radiotracer uptake with single-cell resolution, which may find a use in the precise characterization of radiotracers.

    View details for DOI 10.1371/journal.pone.0046285

    View details for Web of Science ID 000309454000029

    View details for PubMedID 23056276

    View details for PubMedCentralID PMC3463617

  • Intraoperative Imaging of Tumors Using Cerenkov Luminescence Endoscopy: A Feasibility Experimental Study JOURNAL OF NUCLEAR MEDICINE Liu, H., Carpenter, C. M., Jiang, H., Pratx, G., Sun, C., Buchin, M. P., Gambhir, S. S., Xing, L., Cheng, Z. 2012; 53 (10): 1579-1584

    Abstract

    Cerenkov luminescence imaging (CLI) is an emerging new molecular imaging modality that is relatively inexpensive, easy to use, and has high throughput. CLI can image clinically available PET and SPECT probes using optical instrumentation. Cerenkov luminescence endoscopy (CLE) is one of the most intriguing applications that promise potential clinical translation. We developed a prototype customized fiberscopic Cerenkov imaging system to investigate the potential in guiding minimally invasive surgical resection.All experiments were performed in a dark chamber. Cerenkov luminescence from (18)F-FDG samples containing decaying radioactivity was transmitted through an optical fiber bundle and imaged by an intensified charge-coupled device camera. Phantoms filled with (18)F-FDG were used to assess the imaging spatial resolution. Finally, mice bearing subcutaneous C6 glioma cells were injected intravenously with (18)F-FDG to determine the feasibility of in vivo imaging. The tumor tissues were exposed, and CLI was performed on the mouse before and after surgical removal of the tumor using the fiber-based imaging system and compared with a commercial optical imaging system.The sensitivity of this particular setup was approximately 45 kBq (1.21 μCi)/300 μL. The 3 smallest sets of cylindric holes in a commercial SPECT phantom were identifiable via this system, demonstrating that the system has a resolution better than 1.2 mm. Finally, the in vivo tumor imaging study demonstrated the feasibility of using CLI to guide the resection of tumor tissues.This proof-of-concept study explored the feasibility of using fiber-based CLE for the detection of tumor tissue in vivo for guided surgery. With further improvements of the imaging sensitivity and spatial resolution of the current system, CLE may have a significant application in the clinical setting in the near future.

    View details for DOI 10.2967/jnumed.111.098541

    View details for Web of Science ID 000309432400017

    View details for PubMedID 22904353

  • Significance of intraplaque neovascularisation for vulnerability: optical coherence tomography study HEART Tian, J., Hou, J., Xing, L., Kim, S., Yonetsu, T., Kato, K., Lee, H., Zhang, S., Yu, B., Jang, I. 2012; 98 (20): 1504-1509

    Abstract

    This study aimed to investigate the role of intraplaque neovascularisation (NV) in culprit lesions and non-culprit lesions of unstable angina pectoris (UAP) and in lesions of stable angina pectoris (SAP) using optical coherence tomography (OCT).This study was a retrospective study.The significance of NV for culprit and non-culprit plaques remains unclear.A total of 356 plaques from 92 UAP patients and 25 SAP patients who underwent OCT imaging were divided into three groups: culprit lesions in UAP (92), non-culprit lesions in UAP (203) and lesions of SAP (61).NV and plaque characteristics were examined by OCT and plaques with and without NV were compared.Among UAP culprit lesions, plaques with NV had significantly higher incidence of thin cap fibroatheroma (81% vs 47%, p=0.002) compared with those without NV. In addition, the fibrous cap was thinner (56±20 μm vs 75±30 μm, p<0.001), lipid arc was greater (254±66° vs 222±65°, p=0.024) and lipid core length was longer (13±5 mm vs 10±6 mm, p=0.007). No significant difference was observed between non-culprit lesions of UAP with and without NV, and between lesions of SAP with and without NV.In patients with UAP, the culprit plaques with NV had vulnerable features such as thinner fibrous cap, greater lipid arc, longer lipid core length and more frequent thin cap fibroatheroma compared with those without NV. In both non-culprit lesions of UAP patients and in lesions of SAP patients NV was not associated with vulnerable plaque characteristics.

    View details for DOI 10.1136/heartjnl-2012-302445

    View details for Web of Science ID 000309116600008

    View details for PubMedID 22869676

  • Evaluation of the deformation and corresponding dosimetric implications in prostate cancer treatment PHYSICS IN MEDICINE AND BIOLOGY Wen, N., Glide-Hurst, C., Nurushev, T., Xing, L., Kim, J., Zhong, H., Liu, D., Liu, M., Burmeister, J., Movsas, B., Chetty, I. J. 2012; 57 (17): 5361-5379

    Abstract

    The cone-beam computed tomography (CBCT) imaging modality is an integral component of image-guided adaptive radiation therapy (IGART), which uses patient-specific dynamic/temporal information for potential treatment plan modification. In this study, an offline process for the integral component IGART framework has been implemented that consists of deformable image registration (DIR) and its validation, dose reconstruction, dose accumulation and dose verification. This study compares the differences between planned and estimated delivered doses under an IGART framework of five patients undergoing prostate cancer radiation therapy. The dose calculation accuracy on CBCT was verified by measurements made in a Rando pelvic phantom. The accuracy of DIR on patient image sets was evaluated in three ways: landmark matching with fiducial markers, visual image evaluation and unbalanced energy (UE); UE has been previously demonstrated to be a feasible method for the validation of DIR accuracy at a voxel level. The dose calculated on each CBCT image set was reconstructed and accumulated over all fractions to reflect the 'actual dose' delivered to the patient. The deformably accumulated (delivered) plans were then compared to the original (static) plans to evaluate tumor and normal tissue dose discrepancies. The results support the utility of adaptive planning, which can be used to fully elucidate the dosimetric impact based on the simulated delivered dose to achieve the desired tumor control and normal tissue sparing, which may be of particular importance in the context of hypofractionated radiotherapy regimens.

    View details for DOI 10.1088/0031-9155/57/17/5361

    View details for Web of Science ID 000307876600002

    View details for PubMedID 22863976

    View details for PubMedCentralID PMC3652266

  • Predictors for Neoatherosclerosis A Retrospective Observational Study From the Optical Coherence Tomography Registry CIRCULATION-CARDIOVASCULAR IMAGING Yonetsu, T., Kato, K., Kim, S., Xing, L., Jia, H., McNulty, I., Lee, H., Zhang, S., Uemura, S., Jang, Y., Kang, S., Park, S., Lee, S., Yu, B., kakuta, T., Jang, I. 2012; 5 (5): 660-666

    Abstract

    Recent studies have reported development of neoatherosclerosis (NA) inside the stents several years after stent implantation. The aim of this study was to determine the predictors for NA using optical coherence tomography.From a total of 1080 patients who underwent optical coherence tomography, we identified 179 stents in 151 patients in which the mean neointimal thickness was >100 µm. The presence of lipid-laden neointima or calcification inside the stents was defined as NA in the present study. Patient characteristics, stent type, and time since stent implantation (stent age) were compared between stents with or without NA. Univariable and multivariable logistic regression analyses were used to assess the independent predictors. In univariate analysis, stent age ≥48 months (Odds ratio [OR], 4.48; [95% CI 2.68-9.65]; P<0.001), drug-eluting stents (OR, 2.66; [95% CI, 1.38-5.16]; P=0.004), age ≥65 years (OR, 1.91; [95% CI, 1.05-3.44]; P=0.032), current smoking (OR, 2.30; [95% CI, 1.10-4.82]; P=0.024), chronic kidney disease (OR, 4.17; [95% CI, 1.42-12.23]; P=0.009), and angiotensin-converting enzyme inhibitors or angiotensin II receptor blockade use (OR, 0.42; [95% CI, 0.22-0.80]; P=0.008) were significant predictors. In multivariate analysis, stent age ≥48 months, all subtypes of drug-eluting stent, current smoking, chronic kidney disease, and angiotensin-converting enzyme inhibitors/angiotensin II receptor blockade use remained independent predictors for NA.In addition to the stent type and the stent age, patient characteristics, including current smoking, chronic kidney disease, and angiotensin-converting enzyme inhibitors/angiotensin II receptor blockade, were associated with the presence of NA. This result may support the importance of secondary prevention after stent implantation.

    View details for DOI 10.1161/CIRCIMAGING.112.976167

    View details for Web of Science ID 000313574200018

    View details for PubMedID 22798521

  • Volumetric modulated arc therapy planning method for supine craniospinal irradiation JOURNAL OF RADIATION ONCOLOGY Chen, J., Chen, C., Atwood, T. F., Gibbs, I. C., Soltys, S. G., Fasola, C., Xing, L. 2012; 1 (3): 291–97
  • Tracking the motion trajectories of junction structures in 4D CT images of the lung PHYSICS IN MEDICINE AND BIOLOGY Xiong, G., Chen, C., Chen, J., Xie, Y., Xing, L. 2012; 57 (15): 4905-4930

    Abstract

    Respiratory motion poses a major challenge in lung radiotherapy. Based on 4D CT images, a variety of intensity-based deformable registration techniques have been proposed to study the pulmonary motion. However, the accuracy achievable with these approaches can be sub-optimal because the deformation is defined globally in space. Therefore, the accuracy of the alignment of local structures may be compromised. In this work, we propose a novel method to detect a large collection of natural junction structures in the lung and use them as the reliable markers to track the lung motion. Specifically, detection of the junction centers and sizes is achieved by analysis of local shape profiles on one segmented image. To track the temporal trajectory of a junction, the image intensities within a small region of interest surrounding the center are selected as its signature. Under the assumption of the cyclic motion, we describe the trajectory by a closed B-spline curve and search for the control points by maximizing a metric of combined correlation coefficients. Local extrema are suppressed by improving the initial conditions using random walks from pair-wise optimizations. Several descriptors are introduced to analyze the motion trajectories. Our method was applied to 13 real 4D CT images. More than 700 junctions in each case are detected with an average positive predictive value of greater than 90%. The average tracking error between automated and manual tracking is sub-voxel and smaller than the published results using the same set of data.

    View details for DOI 10.1088/0031-9155/57/15/4905

    View details for Web of Science ID 000306521900015

    View details for PubMedID 22796656

  • Real-time tumor motion estimation using respiratory surrogate via memory-based learning PHYSICS IN MEDICINE AND BIOLOGY Li, R., Lewis, J. H., Berbeco, R. I., Xing, L. 2012; 57 (15): 4771-4786

    Abstract

    Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

    View details for DOI 10.1088/0031-9155/57/15/4771

    View details for Web of Science ID 000306521900007

    View details for PubMedID 22772042

    View details for PubMedCentralID PMC3658941

  • Intrafraction Verification of Gated RapidArc by Using Beam-Level Kilovoltage X-Ray Images INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Li, R., Mok, E., Chang, D. T., Daly, M., Loo, B. W., Diehn, M., Quynh-Thu Le, Q. T., Koong, A., Xing, L. 2012; 83 (5): E709-E715

    Abstract

    To verify the geometric accuracy of gated RapidArc treatment using kV images acquired during dose delivery.Twenty patients were treated using the gated RapidArc technique with a Varian TrueBeam STx linear accelerator. One to 7 metallic fiducial markers were implanted inside or near the tumor target before treatment simulation. For patient setup and treatment verification purposes, the internal target volume (ITV) was created, corresponding to each implanted marker. The gating signal was generated from the Real-time Position Management (RPM) system. At the beginning of each fraction, individualized respiratory gating amplitude thresholds were set based on fluoroscopic image guidance. During the treatment, we acquired kV images immediately before MV beam-on at every breathing cycle, using the on-board imaging system. After the treatment, all implanted markers were detected, and their 3-dimensional (3D) positions in the patient were estimated using software developed in-house. The distance from the marker to the corresponding ITV was calculated for each patient by averaging over all markers and all fractions.The average 3D distance between the markers and their ITVs was 0.8 ± 0.5 mm (range, 0-1.7 mm) and was 2.1 ± 1.2 mm at the 95th percentile (range, 0-3.8 mm). On average, a left-right margin of 0.6 mm, an anterior-posterior margin of 0.8 mm, and a superior-inferior margin of 1.5 mm is required to account for 95% of the intrafraction uncertainty in RPM-based RapidArc gating.To our knowledge, this is the first clinical report of intrafraction verification of respiration-gated RapidArc treatment in stereotactic ablative radiation therapy. For some patients, the markers deviated significantly from the ITV by more than 2 mm at the beginning of the MV beam-on. This emphasizes the need for gating techniques with beam-on/-off controlled directly by the actual position of the tumor target instead of external surrogates such as RPM.

    View details for DOI 10.1016/j.ijrobp.2012.03.006

    View details for PubMedID 22554582

  • Investigation of X-ray Fluorescence Computed Tomography (XFCT) and K-Edge Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING Bazalova, M., Kuang, Y., Pratx, G., Xing, L. 2012; 31 (8): 1620-1627

    Abstract

    This work provides a comprehensive Monte Carlo study of X-ray fluorescence computed tomography (XFCT) and K-edge imaging system, including the system design, the influence of various imaging components, the sensitivity and resolution under various conditions. We modified the widely used EGSnrc/DOSXYZnrc code to simulate XFCT images of two acrylic phantoms loaded with various concentrations of gold nanoparticles and Cisplatin for a number of XFCT geometries. In particular, reconstructed signal as a function of the width of the detector ring, its angular coverage and energy resolution were studied. We found that XFCT imaging sensitivity of the modeled systems consisting of a conventional X-ray tube and a full 2-cm-wide energy-resolving detector ring was 0.061% and 0.042% for gold nanoparticles and Cisplatin, respectively, for a dose of ∼ 10 cGy. Contrast-to-noise ratio (CNR) of XFCT images of the simulated acrylic phantoms was higher than that of transmission K-edge images for contrast concentrations below 0.4%.

    View details for DOI 10.1109/TMI.2012.2201165

    View details for Web of Science ID 000307120600010

    View details for PubMedID 22692896

  • Efficient IMRT inverse planning with a new L1-solver: template for first-order conic solver PHYSICS IN MEDICINE AND BIOLOGY Kim, H., Suh, T., Lee, R., Xing, L., Li, R. 2012; 57 (13): 4139-4153

    Abstract

    Intensity modulated radiation therapy (IMRT) inverse planning using total-variation (TV) regularization has been proposed to reduce the complexity of fluence maps and facilitate dose delivery. Conventionally, the optimization problem with L-1 norm is solved with quadratic programming (QP), which is time consuming and memory expensive due to the second-order Newton update. This study proposes to use a new algorithm, template for first-order conic solver (TFOCS), for fast and memory-efficient optimization in IMRT inverse planning. The TFOCS utilizes dual-variable updates and first-order approaches for TV minimization without the need to compute and store the enlarged Hessian matrix required for Newton update in the QP technique. To evaluate the effectiveness and efficiency of the proposed method, two clinical cases were used for IMRT inverse planning: a head and neck case and a prostate case. For comparison, the conventional QP-based method for the TV form was adopted to solve the fluence map optimization problem in the above two cases. The convergence criteria and algorithm parameters were selected to achieve similar dose conformity for a fair comparison between the two methods. Compared with conventional QP-based approach, the proposed TFOCS-based method shows a remarkable improvement in computational efficiency for fluence map optimization, while maintaining the conformal dose distribution. Compared with QP-based algorithms, the computational speed using TFOCS for fluence optimization is increased by a factor of 4 to 6, and at the same time the memory requirement is reduced by a factor of 3 to 4. Therefore, TFOCS provides an effective, fast and memory-efficient method for IMRT inverse planning. The unique features of the approach should be particularly important in inverse planning involving a large number of beams, such as in VMAT and dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT).

    View details for DOI 10.1088/0031-9155/57/13/4139

    View details for Web of Science ID 000305803600006

    View details for PubMedID 22683930

  • Dose optimization with first-order total-variation minimization for dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) MEDICAL PHYSICS Kim, H., Li, R., Lee, R., Goldstein, T., Boyd, S., Candes, E., Xing, L. 2012; 39 (7): 4316-4327

    Abstract

    A new treatment scheme coined as dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) has recently been proposed to bridge the gap between IMRT and VMAT. By increasing the angular sampling of radiation beams while eliminating dispensable segments of the incident fields, DASSIM-RT is capable of providing improved conformity in dose distributions while maintaining high delivery efficiency. The fact that DASSIM-RT utilizes a large number of incident beams represents a major computational challenge for the clinical applications of this powerful treatment scheme. The purpose of this work is to provide a practical solution to the DASSIM-RT inverse planning problem.The inverse planning problem is formulated as a fluence-map optimization problem with total-variation (TV) minimization. A newly released L1-solver, template for first-order conic solver (TFOCS), was adopted in this work. TFOCS achieves faster convergence with less memory usage as compared with conventional quadratic programming (QP) for the TV form through the effective use of conic forms, dual-variable updates, and optimal first-order approaches. As such, it is tailored to specifically address the computational challenges of large-scale optimization in DASSIM-RT inverse planning. Two clinical cases (a prostate and a head and neck case) are used to evaluate the effectiveness and efficiency of the proposed planning technique. DASSIM-RT plans with 15 and 30 beams are compared with conventional IMRT plans with 7 beams in terms of plan quality and delivery efficiency, which are quantified by conformation number (CN), the total number of segments and modulation index, respectively. For optimization efficiency, the QP-based approach was compared with the proposed algorithm for the DASSIM-RT plans with 15 beams for both cases.Plan quality improves with an increasing number of incident beams, while the total number of segments is maintained to be about the same in both cases. For the prostate patient, the conformation number to the target was 0.7509, 0.7565, and 0.7611 with 80 segments for IMRT with 7 beams, and DASSIM-RT with 15 and 30 beams, respectively. For the head and neck (HN) patient with a complicated target shape, conformation numbers of the three treatment plans were 0.7554, 0.7758, and 0.7819 with 75 segments for all beam configurations. With respect to the dose sparing to the critical structures, the organs such as the femoral heads in the prostate case and the brainstem and spinal cord in the HN case were better protected with DASSIM-RT. For both cases, the delivery efficiency has been greatly improved as the beam angular sampling increases with the similar or better conformal dose distribution. Compared with conventional quadratic programming approaches, first-order TFOCS-based optimization achieves far faster convergence and smaller memory requirements in DASSIM-RT.The new optimization algorithm TFOCS provides a practical and timely solution to the DASSIM-RT or other inverse planning problem requiring large memory space. The new treatment scheme is shown to outperform conventional IMRT in terms of dose conformity to both the targetand the critical structures, while maintaining high delivery efficiency.

    View details for DOI 10.1118/1.4729717

    View details for Web of Science ID 000306893000029

    View details for PubMedID 22830765

  • Nonculprit Plaques in Patients With Acute Coronary Syndromes Have More Vulnerable Features Compared With Those With Non-Acute Coronary Syndromes A 3-Vessel Optical Coherence Tomography Study CIRCULATION-CARDIOVASCULAR IMAGING Kato, K., Yonetsu, T., Kim, S., Xing, L., Lee, H., McNulty, I., Yeh, R. W., Sakhuja, R., Zhang, S., Uemura, S., Yu, B., Mizuno, K., Jang, I. 2012; 5 (4): 433-440

    Abstract

    Patients with acute coronary syndrome (ACS) have a higher incidence of recurrent ischemic events. The aim of this study was to compare the plaque characteristics of nonculprit lesions between ACS and non-ACS patients using optical coherence tomography (OCT) imaging.Patients who had 3-vessel OCT imaging were selected from the Massachusetts General Hospital (MGH) OCT Registry. MGH registry is a multicenter registry of patients undergoing OCT. The prevalence and characteristics of nonculprit plaques were compared between ACS and non-ACS patients. A total of 248 nonculprit plaques were found in 104 patients: 45 plaques in 17 ACS patients and 203 plaques in 87 non-ACS patients. Compared with plaques of non-ACS patients, plaques of ACS patients had a wider lipid arc (147.3 ± 29.5° versus 116.2 ± 33.7°, P<0.001), a longer lipid length (10.7 ± 5.9 mm versus 7.0 ± 3.7 mm, P=0.002), a larger lipid volume index [averaged lipid arc×lipid length] (1605.5 ± 1013.1 versus 853.4 ± 570.8, P<0.001), and a thinner fibrous cap (70.2 ± 20.2 µm versus 103.3 ± 46.8 µm, P<0.001). Moreover, thin-cap fibroatheroma (64.7% versus 14.9%, P<0.001), macrophage (82.4% versus 37.9%, P=0.001), and thrombus (29.4% versus 1.1%, P<0.001) were more frequent in ACS patients. Although the prevalence of microchannel did not differ between the groups, the closest distance from the lumen to microchannel was shorter in ACS subjects than in non-ACS (104.6 ± 67.0 µm versus 198.3 ± 133.0 µm, P=0.027).Nonculprit lesions in patients with ACS have more vulnerable plaque characteristics compared with those with non-ACS. Neovascularization was more frequently located close to the lumen in patients with ACS.

    View details for DOI 10.1161/CIRCIMAGING.112.973701

    View details for Web of Science ID 000313573500008

    View details for PubMedID 22679059

  • Improving Respiration-Gated IMRT Delivery Efficiency by Dual-Gating at Inhale and Exhale: Treatment Planning Formalism 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Geneser, S., Fahimian, B., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3902–
  • WE-C-217BCD-07: Best in Physics (Joint Eyiaging-Therapy) - Direct Imaging of the Uptake of Platinum Anticancer Agents Using X-Ray Stimulated Fluorescence: A Proof-Of-Concept Study. Medical physics Kuang, Y., Pratx, G., Qian, J., Meng, B., Bazalova, M., Xing, L. 2012; 39 (6): 3950-3951

    Abstract

    Platinum-based (Pt) chemotherapy has greatly improved the initial response rate of different cancers. However, relapse of a drug-resistant tumor occurs with a high frequency, resulting in poor long term survival. The most common phenotype of Pt chemoresistance is decreased Pt drug accumulation in the tumor region due to either decreased influx or increased efflux, which is invisible for current imaging modalities. The inability of imaging methods to directly image the Pt drug uptake has resulted in a very unfavorable scenario for early assessment of chemotherapeutic efficacy as well as for personalized treatment planning. In this study, we investigated the feasibility of imaging the uptake and retention of Pt drugs using x-ray stimulated fluorescence CT (XSF-CT).Pt is a high atomic number element, and it emits XSF photons when excited by ionizing photons. Therefore, the alteration of spatial distribution and concentration of Pt drugs in the cancer region could be monitored with XSF-CT. In this study, a polychromatic X-ray source was used to stimulate emission of XSF photons from the Pt drugs. XSF-CT used a first-generation CT geometry. The data were collected using a cadmium telluride detector to sort out a set of spectra. The spectra were then used to generate sinogram. The bio distribution and concentration of each element were reconstructed with the ML-EM algorithm.The reconstructed images clearly identified the distributions of cisplatin. A good linearity between XSF intensities and the concentrations of cisplatin was also observed, suggesting that XSF-CT is capable of quantitative imaging. The X-ray dose for stimulating the XSF photon was 0.25 cGy per projection.XSF-CT has the potential to be a promising modality for monitoring the intervention processes within X-ray scanners. It would afford a powerful way to reliably modify an ineffective treatment regimen in nearly real time. This work was supported by NIH/NCI grants (CA133474, CA153587), an NSF grant (0854492) and a grant from the Friends for an Earlier Breast Cancer Test Foundation.

    View details for DOI 10.1118/1.4736123

    View details for PubMedID 28520005

  • Compton Scatter in X-Ray Fluorescence CT Imaging 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Bazalova, M., Kuang, Y., Pratx, G., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3986–86
  • A Binary Moving Blocker-Based Scatter Correction Technique for Cone-Beam CT with Width-Truncated Projections 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) LEE, H., Fahimian, B., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3892–92
  • Automated Data Mining of Lung SBRT Cases for Predicting Dosimetric Indices in Prospective Plans 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Atwood, T., Xing, L., Hristov, D. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3753–53
  • Single-Scan Scatter Correction in Cone Beam CT Using Stationary Boundary Blockers and Compressed Sensing 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Meng, B., Xing, L., Fahimian, B. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3891–91
  • BEST IN PHYSICS (JOINT IMAGING-THERAPY) - Direct Imaging of the Uptake of Platinum Anticancer Agents Using X-Ray Stimulated Fluorescence: A Proof-Of-Concept Study 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Kuang, Y., Pratx, G., Qian, J., Meng, B., Bazalova, M., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3950–51
  • Improving Respiration-Gated IMRT Delivery Efficiency by Dual-Gating at Inhale and Exhale: Evaluation of Planning On Eclipse and the Need for Accurate Image Registration 54th Annual Meeting and Exhibition of the American-Association-of-Physicists-in-Medicine (AAPM) Geneser, S., Fahimian, B., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2012: 3671–71
  • Radioluminescent nanophosphors enable multiplexed small-animal imaging OPTICS EXPRESS Carpenter, C. M., Sun, C., Pratx, G., Liu, H., Cheng, Z., Xing, L. 2012; 20 (11): 11598-11604

    Abstract

    We demonstrate the ability to image multiple nanoparticle-based contrast agents simultaneously using a nanophosphor platform excited by either radiopharmaceutical or X-ray irradiation. These radioluminescent nanoparticles emit optical light at unique wavelengths depending on their lanthanide dopant, enabling multiplexed imaging. This study demonstrates the separation of two distinct nanophosphor contrast agents in gelatin phantoms with a recovered phosphor separation correlation of -0.98. The ability to distinguish the two nanophosphors and a Cerenkov component is then demonstrated in a small animal phantom. Combined with the high-resolution potential of low-scattering X-ray excitation, this imaging technique may be a promising method to probe molecular processes in living organisms.

    View details for Web of Science ID 000304403100002

    View details for PubMedID 22714145

  • Evaluation of the geometric accuracy of surrogate-based gated VMAT using intrafraction kilovoltage x-ray images MEDICAL PHYSICS Li, R., Mok, E., Han, B., Koong, A., Xing, L. 2012; 39 (5): 2686-2693

    Abstract

    To evaluate the geometric accuracy of beam targeting in external surrogate-based gated volumetric modulated arc therapy (VMAT) using kilovoltage (kV) x-ray images acquired during dose delivery.Gated VMAT treatments were delivered using a Varian TrueBeam STx Linac for both physical phantoms and patients. Multiple gold fiducial markers were implanted near the target. The reference position was created for each implanted marker, representing its correct position at the gating threshold. The gating signal was generated from the RPM system. During the treatment, kV images were acquired immediately before MV beam-on at every breathing cycle, using the on-board imaging system. All implanted markers were detected and their 3D positions were estimated using in-house developed software. The positioning error of a marker is defined as the distance of the marker from its reference position for each frame of the images. The overall error of the system is defined as the average over all markers. For the phantom study, both sinusoidal motion (1D and 3D) and real human respiratory motion was simulated for the target and surrogate. In the baseline case, the two motions were synchronized for the first treatment fraction. To assess the effects of surrogate-target correlation on the geometric accuracy, a phase shift of 5% and 10% between the two motions was introduced. For the patient study, intrafraction kV images of five stereotactic body radiotherapy (SBRT) patients were acquired for one or two fractions.For the phantom study, a high geometric accuracy was achieved in the baseline case (average error: 0.8 mm in the superior-inferior or SI direction). However, the treatment delivery is prone to geometric errors if changes in the target-surrogate relation occur during the treatment: the average error was increased to 2.3 and 4.7 mm for the phase shift of 5% and 10%, respectively. Results obtained with real human respiratory curves show a similar trend. For a target with 3D motion, the technique is able to detect geometric errors in the left-right (LR) and anterior-posterior (AP) directions. For the patient study, the average intrafraction positioning errors are 0.8, 0.9, and 1.4 mm and 95th percentile errors are 1.7, 2.1, and 2.7 mm in the LR, AP, and SI directions, respectively.The correlation between external surrogate and internal target motion is crucial to ensure the geometric accuracy of surrogate-based gating. Real-time guidance based on kV x-ray images overcomes the potential issues in surrogate-based gating and can achieve accurate beam targeting in gated VMAT.

    View details for DOI 10.1118/1.4704729

    View details for Web of Science ID 000303604300039

    View details for PubMedID 22559639

    View details for PubMedCentralID PMC3344884

  • FDG-Cerenkov image guided surgical margin detection Carpenter, C., Liu, H., Sun, C., Pratx, G., Chengand, Z., Xing, L. SOC NUCLEAR MEDICINE INC. 2012
  • Development and quantification of a novel intravascular catheter-based radionuclide imaging system Zaman, R., Carpenter, C., Pratx, G., Sun, C., Xing, L., McConnell, M. SOC NUCLEAR MEDICINE INC. 2012
  • Scatter correction in cone-beam CT via a half beam blocker technique allowing simultaneous acquisition of scatter and image information MEDICAL PHYSICS Lee, H., Xing, L., Lee, R., Fahimian, B. P. 2012; 39 (5): 2386-2395

    Abstract

    X-ray scatter incurred to detectors degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. Several methods using a beam blocker for the estimation and subtraction of scatter have been proposed. However, due to missing information resulting from the obstruction of the blocker, such methods require dual scanning or dynamically moving blocker to obtain a complete volumetric image. Here, we propose a half beam blocker-based approach, in conjunction with a total variation (TV) regularized Feldkamp-Davis-Kress (FDK) algorithm, to correct scatter-induced artifacts by simultaneously acquiring image and scatter information from a single-rotation CBCT scan.A half beam blocker, comprising lead strips, is used to simultaneously acquire image data on one side of the projection data and scatter data on the other half side. One-dimensional cubic B-Spline interpolation/extrapolation is applied to derive patient specific scatter information by using the scatter distributions on strips. The estimated scatter is subtracted from the projection image acquired at the opposite view. With scatter-corrected projections where this subtraction is completed, the FDK algorithm based on a cosine weighting function is performed to reconstruct CBCT volume. To suppress the noise in the reconstructed CBCT images produced by geometric errors between two opposed projections and interpolated scatter information, total variation regularization is applied by a minimization using a steepest gradient descent optimization method. The experimental studies using Catphan504 and anthropomorphic phantoms were carried out to evaluate the performance of the proposed scheme.The scatter-induced shading artifacts were markedly suppressed in CBCT using the proposed scheme. Compared with CBCT without a blocker, the nonuniformity value was reduced from 39.3% to 3.1%. The root mean square error relative to values inside the regions of interest selected from a benchmark scatter free image was reduced from 50 to 11.3. The TV regularization also led to a better contrast-to-noise ratio.An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.

    View details for DOI 10.1118/1.3691901

    View details for Web of Science ID 000303604300008

    View details for PubMedID 22559608

  • Improved compressed sensing-based cone-beam CT reconstruction using adaptive prior image constraints PHYSICS IN MEDICINE AND BIOLOGY Lee, H., Xing, L., Davidi, R., Li, R., Qian, J., Lee, R. 2012; 57 (8): 2287-2307

    Abstract

    Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy treatment and are used as prior images. The subsequent scans are acquired using a protocol of sparse projections. In the proposed APICCS algorithm, the prior images are utilized as an initial guess and are incorporated into the objective function in the compressed sensing (CS)-based iterative reconstruction process. Furthermore, the prior information is employed to detect any possible mismatched regions between the prior and current images for improved reconstruction. For this purpose, the prior images and the reconstructed images are classified into three anatomical regions: air, soft tissue and bone. Mismatched regions are identified by local differences of the corresponding groups in the two classified sets of images. A distance transformation is then introduced to convert the information into an adaptive voxel-dependent relaxation map. In constructing the relaxation map, the matched regions (unchanged anatomy) between the prior and current images are assigned with smaller weight values, which are translated into less influence on the CS iterative reconstruction process. On the other hand, the mismatched regions (changed anatomy) are associated with larger values and the regions are updated more by the new projection data, thus avoiding any possible adverse effects of prior images. The APICCS approach was systematically assessed by using patient data acquired under standard and low-dose protocols for qualitative and quantitative comparisons. The APICCS method provides an effective way for us to enhance the image quality at the matched regions between the prior and current images compared to the existing PICCS algorithm. Compared to the current CBCT imaging protocols, the APICCS algorithm allows an imaging dose reduction of 10-40 times due to the greatly reduced number of projections and lower x-ray tube current level coming from the low-dose protocol.

    View details for DOI 10.1088/0031-9155/57/8/2287

    View details for Web of Science ID 000302567100013

    View details for PubMedID 22460008

  • Total-Variation Regularization Based Inverse Planning for Intensity Modulated Arc Therapy TECHNOLOGY IN CANCER RESEARCH & TREATMENT Zhu, L., Niu, T., Choi, K., Xing, L. 2012; 11 (2): 149-162

    Abstract

    Intensity modulated arc therapy (IMAT) delivers conformal dose distributions through continuous gantry rotation with constant or variable speed while modulating the field aperture shape and weight. The enlarged angular space and machine delivery constraints make inverse planning of IMAT more intractable as compared to its counterpart of fixed gantry IMRT. Currently, IMAT inverse planning is being done using two extreme methods: the first one computes in beamlet domain with a subsequent arc leaf sequencing, and the second proceeds in machine parameter domain with entire emphasis placed on a pre-determined delivery method without exploring potentially better alternative delivery schemes. Towards truly optimizing the IMAT treatment on a patient specific basis, in this work we propose a total-variation based inverse planning framework for IMAT, which takes advantage of the useful features of the above two existing approaches while avoiding their shortcomings. A quadratic optimization algorithm has been implemented to demonstrate the performance and advantage of the proposed approach. Applications of the technique to a prostate case and a head and neck case indicate that the algorithm is capable of generating IMAT plans with patient specific numbers of arcs efficiently. Superior dose distributions and delivery time are achieved with a maximum number of apertures of three for each field. As compared to conventional beamlet-based algorithms, our method regularizes the field modulation complexity during optimization, and permits us to obtain the best possible plan with a pre-set modulation complexity of fluences. As illustrated in both prostate and head-and-neck case studies, the proposed method produces more favorable dose distributions than the segment-based algorithms, by optimally accommodating the clinical need of intensity modulation levels for each individual field. On a more fundamental level, our formulation preserves the convexity of optimization and makes the search of the global optimal solution possible with a deterministic method.

    View details for DOI 10.7785/tcrt.2012.500244

    View details for Web of Science ID 000300869500006

    View details for PubMedID 22335409

  • Fiber-based system for imaging tumor margins with Cerenkov Luminescence Liu, H., Carpenter, C. M., Jiang, H., Pratx, G., Sun, C., Buchin, M. P., Gambhir, S. S., Xing, L., Cheng, Z. AMER CHEMICAL SOC. 2012
  • Response to "Comment on 'Bridging the gap between IMRT and VMAT: Dense angularly sampled and sparse intensity modulated radiation therapy'" [Med. Phys. 38, 4912-4919 (2011)] MEDICAL PHYSICS Li, R., Xing, L. 2012; 39 (3): 1676-1676

    View details for DOI 10.1118/1.3687906

    View details for Web of Science ID 000301503400053

    View details for PubMedID 22380399

  • An end-to-end examination of geometric accuracy of IGRT using a new digital accelerator equipped with onboard imaging system PHYSICS IN MEDICINE AND BIOLOGY Wang, L., Kielar, K. N., Mok, E., Hsu, A., Dieterich, S., Xing, L. 2012; 57 (3): 757-769

    Abstract

    The Varian's new digital linear accelerator (LINAC), TrueBeam STx, is equipped with a high dose rate flattening filter free (FFF) mode (6 MV and 10 MV), a high definition multileaf collimator (2.5 mm leaf width), as well as onboard imaging capabilities. A series of end-to-end phantom tests were performed, TrueBeam-based image guided radiation therapy (IGRT), to determine the geometric accuracy of the image-guided setup and dose delivery process for all beam modalities delivered using intensity modulated radiation therapy (IMRT) and RapidArc. In these tests, an anthropomorphic phantom with a Ball Cube II insert and the analysis software (FilmQA (3cognition)) were used to evaluate the accuracy of TrueBeam image-guided setup and dose delivery. Laser cut EBT2 films with 0.15 mm accuracy were embedded into the phantom. The phantom with the film inserted was first scanned with a GE Discovery-ST CT scanner, and the images were then imported to the planning system. Plans with steep dose fall off surrounding hypothetical targets of different sizes were created using RapidArc and IMRT with FFF and WFF (with flattening filter) beams. Four RapidArc plans (6 MV and 10 MV FFF) and five IMRT plans (6 MV and 10 MV FFF; 6 MV, 10 MV and 15 MV WFF) were studied. The RapidArc plans with 6 MV FFF were planned with target diameters of 1 cm (0.52 cc), 2 cm (4.2 cc) and 3 cm (14.1 cc), and all other plans with a target diameter of 3 cm. Both onboard planar and volumetric imaging procedures were used for phantom setup and target localization. The IMRT and RapidArc plans were then delivered, and the film measurements were compared with the original treatment plans using a gamma criteria of 3%/1 mm and 3%/2 mm. The shifts required in order to align the film measured dose with the calculated dose distributions was attributed to be the targeting error. Targeting accuracy of image-guided treatment using TrueBeam was found to be within 1 mm. For irradiation of the 3 cm target, the gammas (3%, 1 mm) were found to be above 90% in all plan deliveries. For irradiations of smaller targets (2 cm and 1 cm), similar accuracy was achieved for 6 MV and 10 MV beams. Slightly degraded accuracy was observed for irradiations with higher energy beam (15 MV). In general, gammas (3%, 2 mm) were found to be above 97% for all the plans. Our end-to-end tests showed an excellent relative dosimetric agreement and sub-millimeter targeting accuracy for 6 MV and 10 MV beams, using both FFF and WFF delivery methods. However, increased deviations in spatial and dosimetric accuracy were found when treating lesions smaller than 2 cm or with 15 MV beam.

    View details for DOI 10.1088/0031-9155/57/3/757

    View details for Web of Science ID 000299542000013

    View details for PubMedID 22252134

    View details for PubMedCentralID PMC5233463

  • Investigations on the electrochemical properties of new conjugated polymers containing benzo[c]cinnoline and oxadiazole moieties POLYMER Chen, J., Wu, H., Chiang, C., Peng, L., Chen, T., Xing, L., Liu, S. 2011; 52 (26): 6011-6019
  • Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment MEDICAL PHYSICS Meng, B., Pratx, G., Xing, L. 2011; 38 (12): 6603-6609

    Abstract

    Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT∕CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment.In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT∕CT reconstruction algorithm.Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed successfully with identical results even when half of the nodes were manually terminated in the middle of the process.An ultrafast, reliable and scalable 4D CBCT∕CT reconstruction method was developed using the MapReduce framework. Unlike other parallel computing approaches, the parallelization and speedup required little modification of the original reconstruction code. MapReduce provides an efficient and fault tolerant means of solving large-scale computing problems in a cloud computing environment.

    View details for DOI 10.1118/1.3660200

    View details for Web of Science ID 000298250100028

    View details for PubMedID 22149842

    View details for PubMedCentralID PMC3247927

  • Application reliability for communication networks and its analysis method JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS Huang, N., Chen, Y., Hou, D., Xing, L., Kang, R. 2011; 22 (6): 1030-1036
  • Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce JOURNAL OF BIOMEDICAL OPTICS Pratx, G., Xing, L. 2011; 16 (12)

    Abstract

    Monte Carlo simulation is considered the most reliable method for modeling photon migration in heterogeneous media. However, its widespread use is hindered by the high computational cost. The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. We ported the MC321 Monte Carlo package to Hadoop, an open-source MapReduce framework. In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. The simulation time was found to be linearly dependent on the number of photons and inversely proportional to the number of nodes. For a cluster size of 240 nodes, the simulation of 100 billion photon histories took 22 min, a 1258 × speed-up compared to the single-threaded Monte Carlo program. The overall computational throughput was 85,178 photon histories per node per second, with a latency of 100 s. The distributed simulation produced the same output as the original implementation and was resilient to hardware failure: the correctness of the simulation was unaffected by the shutdown of 50% of the nodes.

    View details for DOI 10.1117/1.3656964

    View details for Web of Science ID 000299490300011

    View details for PubMedID 22191916

    View details for PubMedCentralID PMC3273307

  • Continued exploration of biphenylsulfonamide scaffold as a platform for aggrecanase-1 inhibition BIOORGANIC & MEDICINAL CHEMISTRY LETTERS Hu, Y., Xing, L., Thomason, J. R., Xiang, J., Ipek, M., Guler, S., Li, H., Sabatini, J., Chockalingam, P., Reifenberg, E., Sheldon, R., Morris, E. A., Georgiadis, K. E., Tam, S. 2011; 21 (22): 6800-6803

    Abstract

    Design, synthesis and structure-activity relationship of a series of biphenylsulfonamido-3-methylbutanoic acid based aggrecanase-1 inhibitors are described. In addition to robust aggrecanase-1 inhibition, these compounds also exhibit potent MMP-13 activity. In cell-based cartilage explants assay compound 48 produced 87% inhibition of proteoglycan degradation at 10 μg/mL. Good pharmacokinetic properties were demonstrated by 46 with a half-life of 6h and bioavailability of 23%.

    View details for DOI 10.1016/j.bmcl.2011.09.036

    View details for Web of Science ID 000296423700032

    View details for PubMedID 21982494

  • Toward real-time Monte Carlo simulation using a commercial cloud computing infrastructure PHYSICS IN MEDICINE AND BIOLOGY Wang, H., Ma, Y., Pratx, G., Xing, L. 2011; 56 (17): N175-N181

    Abstract

    Monte Carlo (MC) methods are the gold standard for modeling photon and electron transport in a heterogeneous medium; however, their computational cost prohibits their routine use in the clinic. Cloud computing, wherein computing resources are allocated on-demand from a third party, is a new approach for high performance computing and is implemented to perform ultra-fast MC calculation in radiation therapy. We deployed the EGS5 MC package in a commercial cloud environment. Launched from a single local computer with Internet access, a Python script allocates a remote virtual cluster. A handshaking protocol designates master and worker nodes. The EGS5 binaries and the simulation data are initially loaded onto the master node. The simulation is then distributed among independent worker nodes via the message passing interface, and the results aggregated on the local computer for display and data analysis. The described approach is evaluated for pencil beams and broad beams of high-energy electrons and photons. The output of cloud-based MC simulation is identical to that produced by single-threaded implementation. For 1 million electrons, a simulation that takes 2.58 h on a local computer can be executed in 3.3 min on the cloud with 100 nodes, a 47× speed-up. Simulation time scales inversely with the number of parallel nodes. The parallelization overhead is also negligible for large simulations. Cloud computing represents one of the most important recent advances in supercomputing technology and provides a promising platform for substantially improved MC simulation. In addition to the significant speed up, cloud computing builds a layer of abstraction for high performance parallel computing, which may change the way dose calculations are performed and radiation treatment plans are completed.

    View details for DOI 10.1088/0031-9155/56/17/N02

    View details for PubMedID 21841211

  • Bridging the gap between IMRT and VMAT: Dense angularly sampled and sparse intensity modulated radiation therapy MEDICAL PHYSICS Li, R., Xing, L. 2011; 38 (9): 4912-4919

    Abstract

    To propose an alternative radiation therapy (RT) planning and delivery scheme with optimal angular beam sampling and intrabeam modulation for improved dose distribution while maintaining high delivery efficiency.In the proposed approach, coined as dense angularly sampled and sparse intensity modulated RT (DASSIM-RT), a large number of beam angles are used to increase the angular sampling, leading to potentially more conformal dose distributions as compared to conventional IMRT. At the same time, intensity modulation of the incident beams is simplified to eliminate the dispensable segments, compensating the increase in delivery time caused by the increased number of beams and facilitating the plan delivery. In a sense, the proposed approach shifts and transforms, in an optimal fashion, some of the beam segments in conventional IMRT to the added beams. For newly available digital accelerators, the DASSIM-RT delivery can be made very efficient by concatenating the beams so that they can be delivered sequentially without operator's intervention. Different from VMAT, the level of intensity modulation in DASSIS-RT is field specific and optimized to meet the need of each beam direction. Three clinical cases (a head and neck (HN) case, a pancreas case, and a lung case) are used to evaluate the proposed RT scheme. DASSIM-RT, VMAT, and conventional IMRT plans are compared quantitatively in terms of the conformality index (CI) and delivery efficiency.Plan quality improves generally with the number and intensity modulation of the incident beams. For a fixed number of beams or fixed level of intensity modulation, the improvement saturates after the intensity modulation or number of beams reaches to a certain level. An interplay between the two variables is observed and the saturation point depends on the values of both variables. For all the cases studied here, the CI of DASSIM-RT with 15 beams and 5 intensity levels (0.90, 0.79, and 0.84 for the HN, pancreas, and lung cases, respectively) is similar with that of conventional IMRT with seven beams and ten intensity levels (0.88, 0.79, and 0.83) and is higher than that of single-arc VMAT (0.75, 0.75, and 0.82). It is also found that the DASSIM-RT plans generally have better sparing of organs-at-risk than IMRT plans. It is estimated that the dose delivery time of DASSIM-RT with 15 beams and 5 intensity levels is about 4.5, 4.4, and 4.2 min for the HN, pancreas, and lung case, respectively, similar to that of IMRT plans with 7 beams and 10 intensity levels.DASSIS-RT bridges the gap between IMRT and VMAT and allows optimal sampling of angular space and intrabeam modulation, thus it provides improved conformity in dose distributions while maintaining high delivery efficiency.

    View details for DOI 10.1118/1.3618736

    View details for Web of Science ID 000294482900002

    View details for PubMedID 21978036

    View details for PubMedCentralID PMC3166337

  • Dose verification for respiratory-gated volumetric modulated arc therapy PHYSICS IN MEDICINE AND BIOLOGY Qian, J., Xing, L., Liu, W., Luxton, G. 2011; 56 (15): 4827-4838

    Abstract

    A novel commercial medical linac system (TrueBeam™, Varian Medical Systems, Palo Alto, CA) allows respiratory-gated volumetric modulated arc therapy (VMAT), a new modality for treating moving tumors with high precision and improved accuracy by allowing for regular motion associated with a patient's breathing during VMAT delivery. The purpose of this work is to adapt a previously-developed dose reconstruction technique to evaluate the fidelity of VMAT treatment during gated delivery under clinic-relevant periodic motion related to patient breathing. A Varian TrueBeam system was used in this study. VMAT plans were created for three patients with lung or pancreas tumors. Conventional 6 and 15 MV beams with flattening filter and high-dose-rate 10 MV beams with no flattening filter were used in these plans. Each patient plan was delivered to a phantom first without gating and then with gating for three simulated respiratory periods (3, 4.5 and 6 s). Using the adapted log-file-based dose reconstruction procedure supplemented with ion chamber array (Seven29™, PTW, Freiburg, Germany) measurements, the delivered dose was used to evaluate the fidelity of gated VMAT delivery. Comparison of Seven29 measurements with and without gating showed good agreement with gamma-index passing rates above 99% for 1%/1 mm dose accuracy/distance-to-agreement criteria. With original plans as reference, gamma-index passing rates were 100% for the reconstituted plans (1%/1 mm criteria) and 93.5-100% for gated Seven29 measurements (3%/3 mm criteria). In the presence of leaf error deliberately introduced into the gated delivery of a pancreas patient plan, both dose reconstruction and Seven29 measurement consistently indicated substantial dosimetric differences from the original plan. In summary, a dose reconstruction procedure was demonstrated for evaluating the accuracy of respiratory-gated VMAT delivery. This technique showed that under clinical operation, the TrueBeam system faithfully realized treatment plans with gated delivery. This methodology affords a useful tool for machine- and patient-specific quality assurance of the newly available respiratory-gated VMAT.

    View details for DOI 10.1088/0031-9155/56/15/013

    View details for Web of Science ID 000292885000014

    View details for PubMedID 21753232

    View details for PubMedCentralID PMC3360016

  • A Bayesian approach to real-time 3D tumor localization via monoscopic x-ray imaging during treatment delivery MEDICAL PHYSICS Li, R., Fahimian, B. P., Xing, L. 2011; 38 (7): 4205-4214

    Abstract

    Monoscopic x-ray imaging with on-board kV devices is an attractive approach for real-time image guidance in modern radiation therapy such as VMAT or IMRT, but it falls short in providing reliable information along the direction of imaging x-ray. By effectively taking consideration of projection data at prior times and/or angles through a Bayesian formalism, the authors develop an algorithm for real-time and full 3D tumor localization with a single x-ray imager during treatment delivery.First, a prior probability density function is constructed using the 2D tumor locations on the projection images acquired during patient setup. Whenever an x-ray image is acquired during the treatment delivery, the corresponding 2D tumor location on the imager is used to update the likelihood function. The unresolved third dimension is obtained by maximizing the posterior probability distribution. The algorithm can also be used in a retrospective fashion when all the projection images during the treatment delivery are used for 3D localization purposes. The algorithm does not involve complex optimization of any model parameter and therefore can be used in a "plug-and-play" fashion. The authors validated the algorithm using (1) simulated 3D linear and elliptic motion and (2) 3D tumor motion trajectories of a lung and a pancreas patient reproduced by a physical phantom. Continuous kV images were acquired over a full gantry rotation with the Varian TrueBeam on-board imaging system. Three scenarios were considered: fluoroscopic setup, cone beam CT setup, and retrospective analysis.For the simulation study, the RMS 3D localization error is 1.2 and 2.4 mm for the linear and elliptic motions, respectively. For the phantom experiments, the 3D localization error is < 1 mm on average and < 1.5 mm at 95th percentile in the lung and pancreas cases for all three scenarios. The difference in 3D localization error for different scenarios is small and is not statistically significant.The proposed algorithm eliminates the need for any population based model parameters in monoscopic image guided radiotherapy and allows accurate and real-time 3D tumor localization on current standard LINACs with a single x-ray imager.

    View details for DOI 10.1118/1.3598435

    View details for Web of Science ID 000292521100037

    View details for PubMedID 21859022

    View details for PubMedCentralID PMC3145219

  • Synthesis and Radioluminescence of PEGylated Eu3+-doped Nanophosphors as Bioimaging Probes ADVANCED MATERIALS Sun, C., Pratx, G., Carpenter, C. M., Liu, H., Cheng, Z., Gambhir, S. S., Xing, L. 2011; 23 (24): H195-H199

    View details for DOI 10.1002/adma.201100919

    View details for Web of Science ID 000293046600018

    View details for PubMedID 21557339

    View details for PubMedCentralID PMC4145869

  • Limited-angle x-ray luminescence tomography: methodology and feasibility study PHYSICS IN MEDICINE AND BIOLOGY Carpenter, C. M., Pratx, G., Sun, C., Xing, L. 2011; 56 (12): 3487-3502

    Abstract

    X-ray luminescence tomography (XLT) has recently been proposed as a new imaging modality for biological imaging applications. This modality utilizes phosphor nanoparticles which luminesce near-infrared light when excited by x-ray photons. The advantages of this modality are that it uniquely combines the high sensitivity of radioluminescent nanoparticles and the high spatial localization of collimated x-ray beams. Currently, XLT has been demonstrated using x-ray spatial encoding to resolve the imaging volume. However, there are applications where the x-ray excitation may be limited by geometry, where increased temporal resolution is desired, or where a lower dose is mandatory. This paper extends the utility of XLT to meet these requirements by incorporating a photon propagation model into the reconstruction algorithm in an x-ray limited-angle (LA) geometry. This enables such applications as image-guided surgery, where the ability to resolve lesions at depths of several centimeters can be the key to successful resection. The hybrid x-ray/diffuse optical model is first formulated and then demonstrated in a breast-sized phantom, simulating a breast lumpectomy geometry. Both numerical and experimental phantoms are tested, with lesion-simulating objects of various sizes and depths. Results show localization accuracy with median error of 2.2 mm, or 4% of object depth, for small 2-14 mm diameter lesions positioned from 1 to 4.5 cm in depth. This compares favorably with fluorescence optical imaging, which is not able to resolve such small objects at this depth. The recovered lesion size has lower size bias in the x-ray excitation direction than the optical direction, which is expected due to the increased optical scatter. However, the technique is shown to be quite invariant in recovered size with respect to depth, as the standard deviation is less than 2.5 mm. Sensitivity is a function of dose; radiological doses are found to provide sufficient recovery for µg ml(-1) concentrations, while therapy dosages provide recovery for ng ml(-1) concentrations. Experimental phantom results agree closely with the numerical results, with positional errors recovered within 8.6% of the effective depth for a 5 mm object, and within 5.2% of the depth for a 10 mm object. Object-size median error is within 2.3% and 2% for the 5 and 10 mm objects, respectively. For shallow-to-medium depth applications where optical and radio-emission imaging modalities are not ideal, such as in intra-operative procedures, LAXLT may be a useful tool to detect molecular signatures of disease.

    View details for DOI 10.1088/0031-9155/56/12/003

    View details for Web of Science ID 000291095700004

    View details for PubMedID 21606553

    View details for PubMedCentralID PMC4132056

  • In vivo MRSI of hyperpolarized [1-C-13]pyruvate metabolism in rat hepatocellular carcinoma NMR IN BIOMEDICINE Darpolor, M. M., Yen, Y., Chua, M., Xing, L., Clarke-Katzenberg, R. H., Shi, W., Mayer, D., Josan, S., Hurd, R. E., Pfefferbaum, A., Senadheera, L., So, S., Hofmann, L. V., Glazer, G. M., Spielman, D. M. 2011; 24 (5): 506-513

    Abstract

    Hepatocellular carcinoma (HCC), the primary form of human adult liver malignancy, is a highly aggressive tumor with average survival rates that are currently less than 1 year following diagnosis. Most patients with HCC are diagnosed at an advanced stage, and no efficient marker exists for the prediction of prognosis and/or response(s) to therapy. We have reported previously a high level of [1-(13)C]alanine in an orthotopic HCC using single-voxel hyperpolarized [1-(13)C]pyruvate MRS. In the present study, we implemented a three-dimensional MRSI sequence to investigate this potential hallmark of cellular metabolism in rat livers bearing HCC (n = 7 buffalo rats). In addition, quantitative real-time polymerase chain reaction was used to determine the mRNA levels of lactate dehydrogenase A, nicotinamide adenine (phosphate) dinucleotide dehydrogenase quinone 1 and alanine transaminase. The enzyme levels were significantly higher in tumor than in normal liver tissues within each rat, and were associated with the in vivo MRSI signal of [1-(13)C]alanine and [1-(13)C]lactate after a bolus intravenous injection of [1-(13)C]pyruvate. Histopathological analysis of these tumors confirmed the successful growth of HCC as a nodule in buffalo rat livers, revealing malignancy and hypervascular architecture. More importantly, the results demonstrated that the metabolic fate of [1-(13)C]pyruvate conversion to [1-(13)C]alanine significantly superseded that of [1-(13)C]pyruvate conversion to [1-(13)C]lactate, potentially serving as a marker of HCC tumors.

    View details for DOI 10.1002/nbm.1616

    View details for Web of Science ID 000291597200009

    View details for PubMedID 21674652

    View details for PubMedCentralID PMC3073155

  • GPU computing in medical physics: A review MEDICAL PHYSICS Pratx, G., Xing, L. 2011; 38 (5): 2685-2697

    Abstract

    The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

    View details for DOI 10.1118/1.3578605

    View details for PubMedID 21776805

  • Initial application of a geometric QA tool for integrated MV and kV imaging systems on three image guided radiotherapy systems MEDICAL PHYSICS Mao, W., Speiser, M., Medin, P., Papiez, L., Solberg, T., Xing, L. 2011; 38 (5): 2335-2341

    Abstract

    Several linacs with integrated kilovoltage (kV) imaging have been developed for delivery of image guided radiation therapy (IGRT). High geometric accuracy and coincidence of kV imaging systems and megavoltage (MV) beam delivery are essential for successful image guidance. A geometric QA tool has been adapted for routine QA for evaluating and characterizing the geometric accuracy of kV and MV cone-beam imaging systems. The purpose of this work is to demonstrate the application of methodology to routine QA across three IGRT-dedicated linac platforms.It has been applied to a Varian Trilogy (Varian Medical Systems, Palo Alto, CA), an Elekta SynergyS (Elekta, Stockholm, Sweden), and a Brainlab Vero (Brainlab AG, Feldkirchen, Germany). Both the Trilogy and SynergyS linacs are equipped with a retractable kV x-ray tube and a flat panel detector. The Vero utilizes a rotating, rigid ring structure integrating a MV x-ray head mounted on orthogonal gimbals, an electronic portal imaging device (EPID), two kV x-ray tubes, and two fixed flat panel detectors. This dual kV imaging system provides orthogonal radiographs, CBCT images, and real-time fluoroscopic monitoring. Two QA phantoms were built to suit different field sizes. Projection images of a QA phantom were acquired using MV and kV imaging systems at a series of gantry angles. Software developed for this study was used to analyze the projection images and calculate nine geometric parameters for each projection. The Trilogy was characterized five times over one year, while the SynergyS was characterized four times and the Vero once. Over 6500 individual projections were acquired and analyzed. Quantitative geometric parameters of both MV and kV imaging systems, as well as the isocenter consistency of the imaging systems, were successfully evaluated.A geometric tool has been successfully implemented for calibration and QA of integrated kV and MV across a variety of radiotherapy platforms. X-ray source angle deviations up to 0.8 degrees, and detector center offsets up to 3 mm, were observed for three linacs, with the exception of the Vero, for which a significant center offset of one kV detector (prior to machine commissioning) was observed. In contrast, the gimbal-based MV source positioning of the Vero demonstrated differences between observed and expected source positions of less than 0.2 mm, both with and without gimbal rotation.This initial application of this geometric QA tool shows promise as a universal, independent tool for quantitative evaluation of geometric accuracies of both MV and integrated kV imaging systems across a range of platforms. It provides nine geometric parameters of any imaging system at every gantry angle as well as the isocenter coincidence of the MV and kV image systems.

    View details for DOI 10.1118/1.3570768

    View details for Web of Science ID 000290625700006

    View details for PubMedID 21776767

  • Multisource modeling of flattening filter free (FFF) beam and the optimization of model parameters MEDICAL PHYSICS Cho, W., Kielar, K. N., Mok, E., Xing, L., Park, J., Jung, W., Suh, T. 2011; 38 (4): 1931-1942

    Abstract

    With the introduction of flattening filter free (FFF) linear accelerators to radiation oncology, new analytical source models for a FFF beam applicable to current treatment planning systems is needed. In this work, a multisource model for the FFF beam and the optimization of involved model parameters were designed.The model is based on a previous three source model proposed by Yang et al. ["A three-source model for the calculation of head scatter factors," Med. Phys. 29, 2024-2033 (2002)]. An off axis ratio (OAR) of photon fluence was introduced to the primary source term to generate cone shaped profiles. The parameters of the source model were determined from measured head scatter factors using a line search optimization technique. The OAR of the photon fluence was determined from a measured dose profile of a 40 x 40 cm2 field size with the same optimization technique, but a new method to acquire gradient terms for OARs was developed to enhance the speed of the optimization process. The improved model was validated with measured dose profiles from 3 x 3 to 40 x 40 cm2 field sizes at 6 and 10 MV from a TrueBeam STx linear accelerator. Furthermore, planar dose distributions for clinically used radiation fields were also calculated and compared to measurements using a 2D array detector using the gamma index method.All dose values for the calculated profiles agreed with the measured dose profiles within 0.5% at 6 and 10 MV beams, except for some low dose regions for larger field sizes. A slight overestimation was seen in the lower penumbra region near the field edge for the large field sizes by 1%-4%. The planar dose calculations showed comparable passing rates (> 98%) when the criterion of the gamma index method was selected to be 3%/3 mm.The developed source model showed good agreements between measured and calculated dose distributions. The model is easily applicable to any other linear accelerator using FFF beams as the required data include only the measured PDD, dose profiles, and output factors for various field sizes, which are easily acquired during conventional beam commissioning process.

    View details for DOI 10.1118/1.3560426

    View details for Web of Science ID 000289153500020

    View details for PubMedID 21626926

    View details for PubMedCentralID PMC3188653

  • Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization MEDICAL PHYSICS Zhang, X., Wang, J., Xing, L. 2011; 38 (2): 701-711

    Abstract

    The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization.After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of "metal shadows" in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective.The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images.Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general "missing data" image reconstruction problems.

    View details for DOI 10.1118/1.3533711

    View details for Web of Science ID 000286945000017

    View details for PubMedID 21452707

    View details for PubMedCentralID PMC3033877

  • Automated detection of junctions structures and tracking of their trajectories in 4D images. Information processing in medical imaging : proceedings of the ... conference Xiong, G., Xing, L. 2011; 22: 486-497

    Abstract

    Junction structures, as the natural anatomical markers, are useful to study the organ or tumor motion. However, detection and tracking of the junctions in four-dimensional (4D) images are challenging. The paper presents a novel framework to automate this task. Detection of their centers and sizes is first achieved by an analysis of local shape profiles on one segmented reference image. Junctions are then separately tracked by simultaneously using neighboring intensity features from all images. Defined by a closed B-spline space curve, the individual trajectory is assumed to be cyclic and obtained by maximizing the metric of combined correlation coefficients. Local extrema are suppressed by improving the initial conditions using random walks from pair-wise optimizations. Our approach has been applied to analyze the vessel junctions in five real 4D respiration-gated computed tomography (CT) image datasets with promising results. More than 500 junctions in the lung are detected with an average accuracy of greater than 85% and the mean error between the automated and the manual tracking is sub-voxel.

    View details for PubMedID 21761680

  • Computed Tomography as a Tool for Anatomical and Molecular Imaging NANOPLATFORM-BASED MOLECULAR IMAGING Liu, P., Zhou, H., Xing, L., Chen 2011: 107–37
  • Three- and Four-Dimensional Morphological Imaging for Adaptive Radiation Therapy Planning ADAPTIVE RADIATION THERAPY Xing, L., Qian, J., Choi, K., Suh, T., Li, X. A. 2011: 19–34
  • Facile Synthesis of Amine-Functionalized Eu3+-Doped La(OH)(3) Nanophosphors for Bioimaging NANOSCALE RESEARCH LETTERS Sun, C., Carpenter, C., Pratx, G., Xing, L. 2011; 6

    Abstract

    Here, we report a straightforward synthesis process to produce colloidal Eu(3+)-activated nanophosphors (NPs) for use as bioimaging probes. In this procedure, poly(ethylene glycol) serves as a high-boiling point solvent allowing for nanoscale particle formation as well as a convenient medium for solvent exchange and subsequent surface modification. The La(OH)3:Eu(3+) NPs produced by this process were ~3.5 nm in diameter as determined by transmission electron microscopy. The NP surface was coated with aminopropyltriethoxysilane to provide chemical functionality for attachment of biological ligands, improve chemical stability and prevent surface quenching of luminescent centers. Photoluminescence spectroscopy of the NPs displayed emission peaks at 597 and 615 nm (λex = 280 nm). The red emission, due to (5)D0 → (7)F1 and (5)D0 → (7)F2 transitions, was linear with concentration as observed by imaging with a conventional bioimaging system. To demonstrate the feasibility of these NPs to serve as optical probes in biological applications, an in vitro experiment was performed with HeLa cells. NP emission was observed in the cells by fluorescence microscopy. In addition, the NPs displayed no cytotoxicity over the course of a 48-h MTT cell viability assay. These results suggest that La(OH)3:Eu(3+) NPs possess the potential to serve as a luminescent bioimaging probe.

    View details for DOI 10.1007/s11671-010-9768-x

    View details for Web of Science ID 000289104200024

    View details for PubMedCentralID PMC3211300

  • Iterative prescription refinement in fully discretized inverse problems of radiation therapy planning INVERSE PROBLEMS IN SCIENCE AND ENGINEERING Censor, Y., Xing, L. 2011; 19 (8): 1125-1137
  • Reducing Gated IMRT Delivery Times: Dual-gated Delivery Optimization and Implementation Geneser, S., Fahimian, B., Kielar, K., Xing, L. ELSEVIER SCIENCE INC. 2011: S202–S202
  • Inverse planning for IMRT with nonuniform beam profiles using total-variation regularization (TVR) MEDICAL PHYSICS Kim, T., Zhu, L., Suh, T., Geneser, S., Meng, B., Xing, L. 2011; 38 (1): 57-66

    Abstract

    Radiation therapy with high dose rate and flattening filter-free (FFF) beams has the potential advantage of greatly reduced treatment time and out-of-field dose. Current inverse planning algorithms are, however, not customized for beams with nonuniform incident profiles and the resultant IMRT plans are often inefficient in delivery. The authors propose a total-variation regularization (TVR)-based formalism by taking the inherent shapes of incident beam profiles into account.A novel TVR-based inverse planning formalism is established for IMRT with nonuniform beam profiles. The authors introduce a TVR term into the objective function, which encourages piecewise constant fluence in the nonuniform FFF fluence domain. The proposed algorithm is applied to lung and prostate and head and neck cases and its performance is evaluated by comparing the resulting plans to those obtained using a conventional beamlet-based optimization (BBO).For the prostate case, the authors' algorithm produces acceptable dose distributions with only 21 segments, while the conventional BBO requires 114 segments. For the lung case and the head and neck case, the proposed method generates similar coverage of target volume and sparing of the organs-at-risk as compared to BBO, but with a markedly reduced segment number.TVR-based optimization in nonflat beam domain provides an effective way to maximally leverage the technical capacity of radiation therapy with FFF fields. The technique can generate effective IMRT plans with improved dose delivery efficiency without significant deterioration of the dose distribution.

    View details for DOI 10.1118/1.3521465

    View details for Web of Science ID 000285769800008

    View details for PubMedID 21361175

    View details for PubMedCentralID PMC3017580

  • Toward Truly Optimal IMRT Dose Distribution: Inverse Planning with Voxel-specific Penalty TECHNOLOGY IN CANCER RESEARCH & TREATMENT Lougovski, P., LeNoach, J., Zhu, L., Ma, Y., Censor, Y., Xing, L. 2010; 9 (6): 629-636

    Abstract

    To establish an inverse planning framework with adjustable voxel penalty for more conformal IMRT dose distribution as well as improved interactive controllability over the regional dose distribution of the resultant plan.In the proposed coarse-to-fine planning scheme, a conventional inverse planning with organ specific parameters is first performed. The voxel penalty scheme is then "switched on" by allowing the prescription dose to change on an individual voxel scale according to the deviation of the actual voxel dose from the ideally desired dose. The rationale here is intuitive: when the dose at a voxel does not meet its ideal dose, it simply implies that this voxel is not competitive enough when compared with the ones that have met their planning goal. In this case, increasing the penalty of the voxel by varying the prescription can boost its competitiveness and thus improve its dose. After the prescription adjustment, the plan is re-optimized. The dose adjustment/re-optimization procedure is repeated until the resultant dose distribution cannot be improved anymore. The prescription adjustment on a finer scale can be accomplished either automatically or manually. In the latter case, the regions/voxels where a dose improvement is needed are selected visually, unlike in the automatic case where the selection is done purely based on the difference of the actual dose at a given voxel and its ideal prescription. The performance of the proposed method is evaluated using a head and neck and a prostate case.An inverse planning framework with the voxel-specific penalty is established. By adjusting voxel prescriptions iteratively to boost the region where large mismatch between the actual calculated and desired doses occurs, substantial improvements can be achieved in the final dose distribution. The proposed method is applied to a head and neck case and a prostate case. For the former case, a significant reduction in the maximum dose to the brainstem is achieved while the PTV dose coverage is greatly improved. The doses to other organs at risk are also reduced, ranging from 10% to 30%. For the prostate case, the use of the voxel penalty scheme also results in vast improvements to the final dose distribution. The PTV experiences improved dose uniformity and the mean dose to the rectum and bladder is reduced by as much as 15%.Introduction of the spatially non-uniform and adjustable prescription provides room for further improvements of currently achievable dose distributions and equips the planner with an effective tool to modify IMRT dose distributions interactively. The technique is easily implementable in any existing inverse planning platform, which should facilitate clinical IMRT planning process and, in future, off-line/on-line adaptive IMRT.

    View details for Web of Science ID 000284971100011

    View details for PubMedID 21070085

    View details for PubMedCentralID PMC3057528

  • X-Ray Luminescence Computed Tomography via Selective Excitation: A Feasibility Study IEEE TRANSACTIONS ON MEDICAL IMAGING Pratx, G., Carpenter, C. M., Sun, C., Xing, L. 2010; 29 (12): 1992-1999

    Abstract

    X-ray luminescence computed tomography (XLCT) is proposed as a new molecular imaging modality based on the selective excitation and optical detection of X-ray-excitable phosphor nanoparticles. These nano-sized particles can be fabricated to emit near-infrared (NIR) light when excited with X-rays, and, because because both X-rays and NIR photons propagate long distances in tissue, they are particularly well suited for in vivo biomedical imaging. In XLCT, tomographic images are generated by irradiating the subject using a sequence of programmed X-ray beams, while sensitive photo-detectors measure the light diffusing out of the subject. By restricting the X-ray excitation to a single, narrow beam of radiation, the origin of the optical photons can be inferred regardless of where these photons were detected, and how many times they scattered in tissue. This study presents computer simulations exploring the feasibility of imaging small objects with XLCT, such as research animals. The accumulation of 50 nm phosphor nanoparticles in a 2-mm-diameter target can be detected and quantified with subpicomolar sensitivity using less than 1 cGy of radiation dose. Provided sufficient signal-to-noise ratio, the spatial resolution of the system can be made as high as needed by narrowing the beam aperture. In particular, 1 mm spatial resolution was achieved for a 1-mm-wide X-ray beam. By including an X-ray detector in the system, anatomical imaging is performed simultaneously with molecular imaging via standard X-ray computed tomography (CT). The molecular and anatomical images are spatially and temporally co-registered, and, if a single-pixel X-ray detector is used, they have matching spatial resolution.

    View details for DOI 10.1109/TMI.2010.2055883

    View details for Web of Science ID 000284848700004

    View details for PubMedID 20615807

  • A unified framework for 3D radiation therapy and IMRT planning: plan optimization in the beamlet domain by constraining or regularizing the fluence map variations PHYSICS IN MEDICINE AND BIOLOGY Meng, B., Zhu, L., Widrow, B., Boyd, S., Xing, L. 2010; 55 (22): N521-N531

    Abstract

    The purpose of this work is to demonstrate that physical constraints on fluence gradients in 3D radiation therapy (RT) planning can be incorporated into beamlet optimization explicitly by direct constraint on the spatial variation of the fluence maps or implicitly by using total-variation regularization (TVR). The former method forces the fluence to vary in accordance with the known form of a wedged field and latter encourages the fluence to take the known form of the wedged field by requiring the derivatives of the fluence maps to be piece-wise constant. The performances of the proposed methods are evaluated by using a brain cancer case and a head and neck case. It is found that both approaches are capable of providing clinically sensible 3D RT solutions with monotonically varying fluence maps. For currently available 3D RT delivery schemes based on the use of customized physical or dynamic wedges, constrained optimization seems to be more useful because the optimized fields are directly deliverable. Working in the beamlet domain provides a natural way to model the spatial variation of the beam fluence. The proposed methods take advantage of the fact that 3D RT is a special form of intensity-modulated radiation therapy (IMRT) and finds the optimal plan by searching for fields with a certain type of spatial variation. The approach provides a unified framework for 3D CRT and IMRT plan optimization.

    View details for DOI 10.1088/0031-9155/55/22/N01

    View details for Web of Science ID 000283789700001

    View details for PubMedID 21030744

  • A FAILURE DETECTION STRATEGY FOR INTRAFRACTION PROSTATE MOTION MONITORING WITH ON-BOARD IMAGERS FOR FIXED-GANTRY IMRT 51st Annual Meeting of the American-Association-of-Physicists-in-Medicine Liu, W., Luxton, G., Xing, L. ELSEVIER SCIENCE INC. 2010: 904–11

    Abstract

    To develop methods to monitor prostate intrafraction motion during fixed-gantry intensity-modulated radiotherapy using MV treatment beam imaging together with minimal kV imaging for a failure detection strategy that ensures prompt detection when target displacement exceeds a preset threshold.Real-time two-dimensional (2D) marker position in the MV image plane was obtained by analyzing cine-MV images. The marker's in-line movement, and thus its time-varying three-dimensional (3D) position, was estimated by combining the 2D projection data with a previously established correlative relationship between the directional components of prostate motion. A confirmation request for more accurate localization using MV-kV triangulation was triggered when the estimated prostate displacement based on the cine-MV data was greater than 3 mm. An interventional action alert followed on positive MV-kV confirmation. To demonstrate the feasibility and accuracy of the proposed method, simulation studies of conventional-fraction intensity-modulated radiotherapy sessions were done using 536 Calypso-measured prostate trajectories from 17 radiotherapy patients.A technique for intrafraction prostate motion management has been developed. The technique, using "freely available" cine-MV images and minimum on-board kV imaging (on average 2.5 images/fraction), successfully limited 3D prostate movement to within a range of 3 mm relative to the MV beam for 99.4% of the total treatment time. On average, only approximately one intervention/fraction was needed to achieve this level of accuracy.Instead of seeking to accurately and continuously localize the prostate target as existing motion tracking systems do, the present technique effectively uses cine-MV data to provide a clinically valuable way to minimize kV usage, while maintaining high targeting accuracy.

    View details for DOI 10.1016/j.ijrobp.2009.12.068

    View details for Web of Science ID 000282731300037

    View details for PubMedID 20579818

  • Sinogram preprocessing and binary reconstruction for determination of the shape and location of metal objects in computed tomography (CT) MEDICAL PHYSICS Meng, B., Wang, J., Xing, L. 2010; 37 (11): 5867-5875

    Abstract

    To develop a binary image reconstruction method for the autolocalization of metallic object(s) in CT with sparse projections.The authors divide the system into two types of contents: Metal(s) and nonmetal(s). The boundaries of metallic objects are obtained by using a penalized weighted least-squares algorithm with the adequate intensity gradient-controlled. A novel mechanism of "amplifying" the difference between metal(s) and nonmetallic substances is introduced by preprocessing the sinogram data, which is shown to be necessary in dealing with a case with sparse projection data. A series of experimental studies are performed to evaluate the proposed approach.A novel binary CT image reconstruction formalism is established for the autodetermination of the shape and location of metallic objects in the presence of limited number of projections. Experimental studies reveal that the presented algorithm works well even when the embedded metal object(s) has different shape(s). It is also shown that when the projection data are sparse, a differential manipulation of projection data can greatly facilitate the binary reconstruction process and allow the authors to obtain accurate binary CT images that would otherwise be unattainable.Binary CT reconstruction provides a viable method for determining the geometric distribution information of the implanted metal objects in CT imaging.

    View details for DOI 10.1118/1.3505294

    View details for Web of Science ID 000283747600033

    View details for PubMedID 21158299

    View details for PubMedCentralID PMC2980545

  • Inverse planning for four-dimensional (4D) volumetric modulated arc therapy MEDICAL PHYSICS Ma, Y., Chang, D., Keall, P., Xie, Y., Park, J., Suh, T., Xing, L. 2010; 37 (11): 5627-5633

    Abstract

    To develop a 4D volumetric modulated arc therapy (VMAT) inverse planning framework.4D VMAT inverse planning aims to derive an aperture and weight modulated arc therapy treatment plan that optimizes the accumulated dose distribution from all gantry angles and breathing phases. Under an assumption that the gantry rotation and patient breathing are synchronized (i.e., there is a functional relationship between the phase of the patient breathing cycle and the beam angle), the authors compute the contribution from different respiration phases through the registration of the phased CT images. The accumulative dose distribution is optimized by iteratively adjusting the aperture shape and weight of each beam through the minimization of the planning objective function. For comparison, traditional 3D VMAT plans are also performed for the two cases and the performance of the proposed technique is demonstrated.A framework for 4D VMAT inverse planning has been proposed. With the consideration of the extra dimension of time in VMAT, a tighter target margin can be achieved with a full duty cycle, which is otherwise not achievable simultaneously by either 3D VMAT optimization or gated VMAT.The 4D VMAT planning formulism proposed here provides useful insight on how the "time" dimension can be exploited in rotational arc therapy to maximally compensate for the intrafraction organ motion.

    View details for DOI 10.1118/1.3497271

    View details for PubMedID 21158274

  • Tomographic molecular imaging of x-ray-excitable nanoparticles OPTICS LETTERS Pratx, G., Carpenter, C. M., Sun, C., Rao, R. P., Xing, L. 2010; 35 (20): 3345-3347

    Abstract

    X-ray luminescence computed tomography (XLCT) is proposed as a new dual molecular/anatomical imaging modality. XLCT is based on the selective excitation and optical detection of x-ray-excitable nanoparticles. As a proof of concept, we built a prototype XLCT system and imaged near-IR-emitting Gd(2)O(2)S:Eu phosphors in various phantoms. Imaging in an optically diffusive medium shows that imaging performance is not affected by optical scatter; furthermore, the linear response of the reconstructed images suggests that XLCT is capable of quantitative imaging.

    View details for Web of Science ID 000283048100013

    View details for PubMedID 20967061

  • OPTIMIZED HYBRID MEGAVOLTAGE-KILOVOLTAGE IMAGING PROTOCOL FOR VOLUMETRIC PROSTATE ARC THERAPY 51st Annual Meeting of the American-Association-of-Physicists-in-Medicine Liu, W., Wiersma, R. D., Xing, L. ELSEVIER SCIENCE INC. 2010: 595–604

    Abstract

    To develop a real-time prostate position monitoring technique for modern arc radiotherapy through novel use of cine-megavoltage (MV) imaging, together with as-needed kilovoltage (kV) imaging.We divided the task of monitoring the intrafraction prostate motion into two steps for rotational deliveries: to detect potential target motion beyond a predefined threshold using MV images from different viewing angles by taking advantage of gantry rotation during arc therapy and to verify the displacement and determine whether intervention is needed using fiducial/tumor position information acquired from combined MV-kV imaging (by turning on the kV imager). A Varian Trilogy linear accelerator with an onboard kV imager was used to examine selected typical trajectories using a four-dimensional motion phantom. The performance of the algorithm was evaluated using phantom measurements and computer simulation for 536 Calypso-measured tracks from 17 patients.Fiducial displacement relative to the MV beam was limited to within a range of 3 mm 99.9% of the time with <1 mm accuracy. On average, only ∼0.5 intervention per arc delivery was needed to achieve this level of accuracy. Compared with other fluoroscopy-based tracking techniques, kV use was significantly reduced to an average of <15 times per arc delivery.By focusing the attention on detecting predefined abnormal motion (i.e., "failure" detection) and using the inherent mechanism of gantry rotation during arc radiotherapy, the current approach provides high confidence regarding the prostate position in real time without the unwanted overhead of continuous or periodic kV imaging.

    View details for DOI 10.1016/j.ijrobp.2009.11.056

    View details for Web of Science ID 000282147000041

    View details for PubMedID 20472354

    View details for PubMedCentralID PMC4131869

  • Clinical development of a failure detection-based online repositioning strategy for prostate IMRT-Experiments, simulation, and dosimetry study MEDICAL PHYSICS Liu, W., Qian, J., Hancock, S. L., Xing, L., Luxton, G. 2010; 37 (10): 5287-5297

    Abstract

    To implement and evaluate clinic-ready adaptive imaging protocols for online patient repositioning (motion tracking) during prostate IMRT using treatment beam imaging supplemented by minimal, as-needed use of on-board kV.The authors examine the two-step decision-making strategy: (1) Use cine-MV imaging and online-updated characterization of prostate motion to detect target motion that is potentially beyond a predefined threshold and (2) use paired MV-kV 3D localization to determine overthreshold displacement and, if needed, reposition the patient. Two levels of clinical implementation were evaluated: (1) Field-by-field based motion correction for present-day linacs and (2) instantaneous repositioning for new-generation linacs with capabilities of simultaneous MV-kV imaging and remote automatic couch control during treatment delivery. Experiments were performed on a Varian Trilogy linac in clinical mode using a 4D motion phantom programed with prostate motion trajectories taken from patient data. Dosimetric impact was examined using a 2D ion chamber array. Simulations were done for 536 trajectories from 17 patients.Despite the loss of marker detection efficiency caused by the MLC leaves sometimes obscuring the field at the marker's projected position on the MV imager, the field-by-field correction halved (from 23% to 10%) the mean percentage of time that target displacement exceeded a 3 mm threshold, as compared to no intervention. This was achieved at minimal cost in additional imaging (average of one MV-kV pair per two to three treatment fractions) and with a very small number of repositionings (once every four to five fractions). Also with low kV usage (approximation 2/fraction), the instantaneous repositioning approach reduced overthreshold time by more than 75% (23% to 5%) even with severe MLC blockage as often encountered in current IMRT and could reduce the overthreshold time tenfold (to < 2%) if the MLC blockage problem were relieved. The information acquired for repositioning using combined MV-kV images was found to have submillimeter accuracy.This work demonstrated with a current clinical setup that substantial reduction of adverse targeting effects of intrafraction prostate motion can be realized. The proposed adaptive imaging strategy incurs minimal imaging dose to the patient as compared to other stereoscopic imaging techniques.

    View details for DOI 10.1118/1.3488887

    View details for Web of Science ID 000283483700016

    View details for PubMedID 21089763

    View details for PubMedCentralID PMC2951998

  • Compressed sensing based cone-beam computed tomography reconstruction with a first-order method MEDICAL PHYSICS Choi, K., Wang, J., Zhu, L., Suh, T., Boyd, S., Xing, L. 2010; 37 (9): 5113-5125

    Abstract

    This article considers the problem of reconstructing cone-beam computed tomography (CBCT) images from a set of undersampled and potentially noisy projection measurements.The authors cast the reconstruction as a compressed sensing problem based on l1 norm minimization constrained by statistically weighted least-squares of CBCT projection data. For accurate modeling, the noise characteristics of the CBCT projection data are used to determine the relative importance of each projection measurement. To solve the compressed sensing problem, the authors employ a method minimizing total-variation norm, satisfying a prespecified level of measurement consistency using a first-order method developed by Nesterov.The method converges fast to the optimal solution without excessive memory requirement, thanks to the method of iterative forward and back-projections. The performance of the proposed algorithm is demonstrated through a series of digital and experimental phantom studies. It is found a that high quality CBCT image can be reconstructed from undersampled and potentially noisy projection data by using the proposed method. Both sparse sampling and decreasing x-ray tube current (i.e., noisy projection data) lead to the reduction of radiation dose in CBCT imaging.It is demonstrated that compressed sensing outperforms the traditional algorithm when dealing with sparse, and potentially noisy, CBCT projection views.

    View details for DOI 10.1118/1.3481510

    View details for Web of Science ID 000281906000063

    View details for PubMedID 20964231

    View details for PubMedCentralID PMC2945747

  • Hybrid x-ray/optical luminescence imaging: Characterization of experimental conditions MEDICAL PHYSICS Carpenter, C. M., Sun, C., Pratx, G., Rao, R., Xing, L. 2010; 37 (8): 4011-4018

    Abstract

    The feasibility of x-ray luminescence imaging is investigated using a dual-modality imaging system that merges x-ray and optical imaging. This modality utilizes x-ray activated nanophosphors that luminesce when excited by ionizing photons. By doping phosphors with lanthanides, which emit light in the visible and near infrared range, the luminescence is suitable for biological applications. This study examines practical aspects of this new modality including phosphor concentration, light emission linearity, detector damage, and spectral emission characteristics. Finally, the contrast produced by these phosphors is compared to that of x-ray fluoroscopy.Gadolinium and lanthanum oxysulfide phosphors doped with terbium (green emission) or europium (red emission) were studied. The light emission was imaged in a clinical x-ray scanner with a cooled CCD camera and a spectrophotometer; dose measurements were determined with a calibrated dosimeter. Using these properties, in addition to luminescence efficiency values found in the literature for a similar phosphor, minimum concentration calculations are performed. Finally, a 2.5 cm agar phantom with a 1 cm diameter cylindrical phosphor-filled inclusion (diluted at 10 mg/ml) is imaged to compare x-ray luminescence contrast with x-ray fluoroscopic contrast at a superficial location.Dose to the CCD camera in the chosen imaging geometry was measured at less than 0.02 cGy/s. Emitted light was found to be linear with dose (R(2)= 1) and concentration (R(2)= 1). Emission peaks for clinical x-ray energies are less than 3 nm full width at half maximum, as expected from lanthanide dopants. The minimum practical concentration necessary to detect luminescent phosphors is dependent on dose; it is estimated that subpicomolar concentrations are detectable at the surface of the tissue with typical mammographic doses, with the minimum detectable concentration increasing with depth and decreasing with dose. In a reflection geometry, x-ray luminescence had nearly a 430-fold greater contrast to background than x-ray fluoroscopy.X-ray luminescence has the potential to be a promising new modality for enabling molecular imaging within x-ray scanners. Although much work needs to be done to ensure biocompatibility of x-ray exciting phosphors, the benefits of this modality, highlighted in this work, encourage further study.

    View details for DOI 10.1118/1.3457332

    View details for Web of Science ID 000281112900011

    View details for PubMedID 20879562

    View details for PubMedCentralID PMC2917453

  • Dose reconstruction for volumetric modulated arc therapy (VMAT) using cone-beam CT and dynamic log files PHYSICS IN MEDICINE AND BIOLOGY Qian, J., Lee, L., Liu, W., Chu, K., Mok, E., Luxton, G., Le, Q., Xing, L. 2010; 55 (13): 3597-3610

    Abstract

    Volumetric modulated arc therapy (VMAT) has recently emerged as a new clinical modality for conformal radiation therapy. The aim of this work is to establish a methodology and procedure for retrospectively reconstructing the actual dose delivered in VMAT based on the pre-treatment cone-beam computed tomography (CBCT) and dynamic log files. CBCT was performed before the dose delivery and the system's log files were retrieved after the delivery. Actual delivery at a control point including MLC leaf positions, gantry angles and cumulative monitor units (MUs) was recorded in the log files and the information was extracted using in-house developed software. The extracted information was then embedded into the original treatment DICOM-radiation therapy (RT) file to replace the original control point parameters. This reconstituted DICOM-RT file was imported into the Eclipse treatment planning system (TPS) and dose was computed on the corresponding CBCT. A series of phantom experiments was performed to show the feasibility of dose reconstruction, validate the procedure and demonstrate the efficacy of this methodology. The resultant dose distributions and dose-volume histograms (DVHs) were compared with those of the original treatment plan. The studies indicated that CBCT-based VMAT dose reconstruction is readily achievable and provides a valuable tool for monitoring the dose actually delivered to the tumor target as well as the sensitive structures. In the absence of setup errors, the reconstructed dose shows no significant difference from the original pCT-based plan. It is also elucidated that the proposed method is capable of revealing the dosimetric changes in the presence of setup errors. The method reported here affords an objective means for dosimetric evaluation of VMAT delivery and is useful for adaptive VMAT in future.

    View details for DOI 10.1088/0031-9155/55/13/002

    View details for Web of Science ID 000279004300002

    View details for PubMedID 20526034

  • Fast and accurate marker-based projective registration method for uncalibrated transmission electron microscope tilt series PHYSICS IN MEDICINE AND BIOLOGY Lee, H., Lee, J., Shin, Y. G., Lee, R., Xing, L. 2010; 55 (12): 3417-3440

    Abstract

    This paper presents a fast and accurate marker-based automatic registration technique for aligning uncalibrated projections taken from a transmission electron microscope (TEM) with different tilt angles and orientations. Most of the existing TEM image alignment methods estimate the similarity between images using the projection model with least-squares metric and guess alignment parameters by computationally expensive nonlinear optimization schemes. Approaches based on the least-squares metric which is sensitive to outliers may cause misalignment since automatic tracking methods, though reliable, can produce a few incorrect trajectories due to a large number of marker points. To decrease the influence of outliers, we propose a robust similarity measure using the projection model with a Gaussian weighting function. This function is very effective in suppressing outliers that are far from correct trajectories and thus provides a more robust metric. In addition, we suggest a fast search strategy based on the non-gradient Powell's multidimensional optimization scheme to speed up optimization as only meaningful parameters are considered during iterative projection model estimation. Experimental results show that our method brings more accurate alignment with less computational cost compared to conventional automatic alignment methods.

    View details for DOI 10.1088/0031-9155/55/12/010

    View details for Web of Science ID 000278147800010

    View details for PubMedID 20508322

  • Image-based modeling of tumor shrinkage in head and neck radiation therapy 50th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) Chao, M., Xie, Y., Moros, E. G., Le, Q., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2010: 2351–58

    Abstract

    Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases.Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique.The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the "ground truth" with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%.An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

    View details for DOI 10.1118/1.3399872

    View details for Web of Science ID 000277242800043

    View details for PubMedID 20527569

    View details for PubMedCentralID PMC2874043

  • AMERICAN SOCIETY FOR THERAPEUTIC RADIOLOGY AND ONCOLOGY (ASTRO) AND AMERICAN COLLEGE OF RADIOLOGY (ACR) PRACTICE GUIDELINES FOR IMAGE-GUIDED RADIATION THERAPY (IGRT) INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Potters, L., Gaspar, L. E., Kavanagh, B., Galvin, J. M., Hartford, A. C., Hevezi, J. M., Kupelian, P. A., Mohiden, N., Samuels, M. A., Timmerman, R., Tripuraneni, P., Vlachaki, M. T., Xing, L., Rosenthal, S. A. 2010; 76 (2): 319-325

    View details for DOI 10.1016/j.ijrobp.2009.09.041

    View details for Web of Science ID 000274121500001

    View details for PubMedID 20117284

  • A binary image reconstruction technique for accurate determination of the shape and location of metal objects in x-ray computed tomography JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY Wang, J., Xing, L. 2010; 18 (4): 403-414

    Abstract

    The presence of metals in patients causes streaking artifacts in X-ray CT and has been recognized as a problem that limits various applications of CT imaging. Accurate localization of metals in CT images is a critical step for metal artifacts reduction in CT imaging and many practical applications of CT images. The purpose of this work is to develop a method of auto-determination of the shape and location of metallic object(s) in the image space. The proposed method is based on the fact that when a metal object is present in a patient, a CT image can be divided into two prominent components: high density metal and low density normal tissues. This prior knowledge is incorporated into an objective function as the regularization term whose role is to encourage the solution to take a form of two intensity levels. A computer simulation study and four experimental studies are performed to evaluate the proposed approach. Both simulation and experimental studies show that the presented algorithm works well even in the presence of complicated shaped metal objects. For a hexagonally shaped metal embedded in a water phantom, for example, it is found that the accuracy of metal reconstruction is within sub-millimeter.

    View details for DOI 10.3233/XST-2010-0271

    View details for Web of Science ID 000283777900006

    View details for PubMedID 21045277

  • Metal Artifact Reduction in Computed Tomography by Constrained Optimization Conference on Medical Imaging - Physics of Medical Imaging Zhang, X., Wang, J., Xing, L. SPIE-INT SOC OPTICAL ENGINEERING. 2010

    View details for DOI 10.1117/12.844646

    View details for Web of Science ID 000285047200063

  • Accurate determination of the shape and location of metal objects in x-ray computed tomography Conference on Medical Imaging - Physics of Medical Imaging Wang, J., Xing, L. SPIE-INT SOC OPTICAL ENGINEERING. 2010

    View details for DOI 10.1117/12.844294

    View details for Web of Science ID 000285047200179

  • X-ray Activated Optical Contrast Agents for Simultaneous Anatomical/Functional CT Imaging 52nd Annual Meeting of the American-Society-for-Therapeutic-Radiation-Oncology (ASTRO) Pratx, G., Carpenter, C. M., Sun, C., Rao, R., Xing, L. ELSEVIER SCIENCE INC. 2010: S641–S642
  • BEAM'S-EYE-VIEW DOSIMETRICS-GUIDED INVERSE PLANNING FOR APERTURE-MODULATED ARC THERAPY INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Ma, Y., Popple, R., Suh, T., Xing, L. 2009; 75 (5): 1587-1595

    Abstract

    To use angular beam's-eye-view dosimetrics (BEVD) information to improve the computational efficiency and plan quality of inverse planning of aperture-modulated arc therapy (AMAT).In BEVD-guided inverse planning, the angular space spanned by a rotational arc is represented by a large number of fixed-gantry beams with angular spacing of approximately 2.5 degrees. Each beam is assigned with an initial aperture shape determined by the beam's-eye-view (BEV) projection of the planning target volume (PTV) and an initial weight. Instead of setting the beam weights arbitrarily, which slows down the subsequent optimization process and may result in a suboptimal solution, a priori knowledge about the quality of the beam directions derived from a BEVD is adopted to initialize the weights. In the BEVD calculation, a higher score is assigned to directions that allow more dose to be delivered to the PTV without exceeding the dose tolerances of the organs at risk (OARs) and vice versa. Simulated annealing is then used to optimize the segment shapes and weights. The BEVD-guided inverse planning is demonstrated by using two clinical cases, and the results are compared with those of a conventional approach without BEVD guidance.An a priori knowledge-guided inverse planning scheme for AMAT is established. The inclusion of BEVD guidance significantly improves the convergence behavior of AMAT inverse planning and results in much better OAR sparing as compared with the conventional approach.BEVD-guidance facilitates AMAT treatment planning and provides a comprehensive tool to maximally use the technical capacity of the new arc therapeutic modality.

    View details for DOI 10.1016/j.ijrobp.2009.05.003

    View details for Web of Science ID 000272341800043

    View details for PubMedID 19733446

  • Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression PHYSICS IN MEDICINE AND BIOLOGY Riaz, N., Shanker, P., Wiersma, R., Gudmundsson, O., Mao, W., Widrow, B., Xing, L. 2009; 54 (19): 5735-5748

    Abstract

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

    View details for DOI 10.1088/0031-9155/54/19/005

    View details for Web of Science ID 000270051600006

    View details for PubMedID 19729711

  • IMAGE-GUIDED RADIOTHERAPY IN NEAR REAL TIME WITH INTENSITY-MODULATED RADIOTHERAPY MEGAVOLTAGE TREATMENT BEAM IMAGING INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Mao, W., Hsu, A., Riaz, N., Lee, L., Wiersma, R., Luxton, G., King, C., Xing, L., Solberg, T. 2009; 75 (2): 603-610

    Abstract

    To utilize image-guided radiotherapy (IGRT) in near real time by obtaining and evaluating the online positions of implanted fiducials from continuous electronic portal imaging device (EPID) imaging of prostate intensity-modulated radiotherapy (IMRT) delivery.Upon initial setup using two orthogonal images, the three-dimensional (3D) positions of all implanted fiducial markers are obtained, and their expected two-dimensional (2D) locations in the beam's-eye-view (BEV) projection are calculated for each treatment field. During IMRT beam delivery, EPID images of the megavoltage treatment beam are acquired in cine mode and subsequently analyzed to locate 2D locations of fiducials in the BEV. Simultaneously, 3D positions are estimated according to the current EPID image, information from the setup portal images, and images acquired at other gantry angles (the completed treatment fields). The measured 2D and 3D positions of each fiducial are compared with their expected 2D and 3D setup positions, respectively. Any displacements larger than a predefined tolerance may cause the treatment system to suspend the beam delivery and direct the therapists to reposition the patient.Phantom studies indicate that the accuracy of 2D BEV and 3D tracking are better than 1 mm and 1.4 mm, respectively. A total of 7330 images from prostate treatments were acquired and analyzed, showing a maximum 2D displacement of 6.7 mm and a maximum 3D displacement of 6.9 mm over 34 fractions.This EPID-based, real-time IGRT method can be implemented on any external beam machine with portal imaging capabilities without purchasing any additional equipment, and there is no extra dose delivered to the patient.

    View details for DOI 10.1016/j.ijrobp.2009.04.068

    View details for Web of Science ID 000269941600040

    View details for PubMedID 19735886

  • Pancreatic Tumor Motion on a Single Planning 4D-CT Does Not Correlate With Intrafraction Tumor Motion During Treatment AMERICAN JOURNAL OF CLINICAL ONCOLOGY-CANCER CLINICAL TRIALS Minn, A. Y., Schellenberg, D., Maxim, P., Suh, Y., McKenna, S., Cox, B., Dieterich, S., Xing, L., Graves, E., Goodman, K. A., Chang, D., Koong, A. C. 2009; 32 (4): 364-368

    Abstract

    To quantify pancreas tumor motion on both a planning 4D-CT and during a single fraction treatment using the CyberKnife linear accelerator and Synchrony respiratory tracking software, and to investigate whether a single 4D-CT study is reliable for determining radiation treatment margins for patients with locally advanced pancreas cancer.Twenty patients underwent fiducial placement, biphasic pancreatic protocol CT scan and 4D-CT scan in the treatment position while free-breathing. Patients were then treated with a single 25 Gy fraction of stereotactic body radiotherapy. Predicted pancreas motion in the superior-inferior (SI), left-right (LR), and anterior-posterior (AP) directions was calculated from the maximum inspiration and maximum expiration 4D-CT scan. For CyberKnife treatments, mean respiratory cycle motion and maximum respiratory cycle motion was determined in the SI, LR, and AP directions.The range of centroid movement based on 4D-CT in the SI, LR, and AP directions were 0.9 to 28.8 mm, 0.1 to 13.7 mm, and 0.2 to 7.6 mm, respectively. During CyberKnife treatment, in the SI direction, the mean motion of the centroid ranged from 0.5 to 12.7 mm. In the LR direction, the mean motion range was 0.4 to 9.4 mm. In the AP direction, the mean motion range was 0.6 to 5.5 mm. The maximum range of movement (mean) during CyberKnife treatment in the SI, LR, and AP directions were 4.5 to 48.8 mm (mean 20.8 mm), 1.5 to 41.3 mm (mean 11.3 mm), and 1.6 to 68.1 mm (mean 13.4 mm), respectively. Neither the maximum or mean motion correlated with the 4D-CT movement.There is substantial respiratory associated motion of pancreatic tumors. The 4D-CT planning scans cannot accurately predict the movement of pancreatic tumors during actual treatment on CyberKnife.

    View details for DOI 10.1097/COC.0b013e31818da9e0

    View details for PubMedID 19398901

  • TISSUE FEATURE-BASED AND SEGMENTED DEFORMABLE IMAGE REGISTRATION FOR IMPROVED MODELING OF SHEAR MOVEMENT OF LUNGS INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Xie, Y., Chao, M., Xing, L. 2009; 74 (4): 1256-1265

    Abstract

    To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures.The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different "colors" according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given "color." The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients.For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases.The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

    View details for DOI 10.1016/j.ijrobp.2009.02.023

    View details for Web of Science ID 000267505000040

    View details for PubMedID 19545792

    View details for PubMedCentralID PMC2725185

  • Four-dimensional inverse treatment planning with inclusion of implanted fiducials in IMRT segmented fields MEDICAL PHYSICS Ma, Y., Lee, L., Keshet, O., Keall, P., Xing, L. 2009; 36 (6): 2215-2221

    Abstract

    The purpose of this study is to develop a 4D inverse planning strategy capable of controlling the appearance of the implanted fiducial(s) in segmented IMRT fields for cine MV or combined MV/kV image-guided IMRT. This work is focused on enhancing the visibility of the implanted fiducial(s) in 4D IMRT inverse planning, whose goal is to derive a set of time-resolved (or phase-tagged) MLC segments to cater for the motion of the patient anatomy extracted from the emerging 4D images. The task is to optimize the shapes and weights of all the segments for each incident beam, with the fiducial(s) being forced/encouraged to be inside the segmented fields. The system is modeled by a quadratic objective function with inclusion of a hard/soft constraint characterizing the authors' level of preference for the fiducial(s) to be included in the segmented fields. A simulated annealing algorithm is employed to optimize the system. The proposed technique is demonstrated using two clinical cases. A segment-based inverse planning framework for 4D radiation therapy, capable of providing tempospatially optimized IMRT plans, has been established. Furthermore, using the described 4D optimization approach, it is demonstrated that the MLC blockage of the implanted fiducial(s) during the segmented delivery is avoided without severely compromising the final dose distribution. The visibility of implanted fiducials in 4D IMRT can be improved without significantly deteriorating final dose distribution. This is a foundation for the authors to use cine MV or combined MV/KV to effectively guide the 4D IMRT delivery.

    View details for DOI 10.1118/1.3121425

    View details for PubMedID 19610310

  • Scatter correction for cone-beam CT in radiation therapy MEDICAL PHYSICS Zhu, L., Xie, Y., Wang, J., Xing, L. 2009; 36 (6): 2258-2268

    Abstract

    Cone-beam CT (CBCT) is being increasingly used in modern radiation therapy for patient setup and adaptive replanning. However, due to the large volume of x-ray illumination, scatter becomes a rather serious problem and is considered as one of the fundamental limitations of CBCT image quality. Many scatter correction algorithms have been proposed in literature, while a standard practical solution still remains elusive. In radiation therapy, the same patient is scanned repetitively during a course of treatment, a natural question to ask is whether one can obtain the scatter distribution on the first day of treatment and then use the data for scatter correction in the subsequent scans on different days. To realize this scatter removal scheme, two technical pieces must be in place: (i) A strategy to obtain the scatter distribution in on-board CBCT imaging and (ii) a method to spatially match a prior scatter distribution with the on-treatment CBCT projection data for scatter subtraction. In this work, simple solutions to the two problems are provided. A partially blocked CBCT is used to extract the scatter distribution. The x-ray beam blocker has a strip pattern, such that partial volume can still be accurately reconstructed and the whole-field scatter distribution can be estimated from the detected signals in the shadow regions using interpolation/extrapolation. In the subsequent scans, the patient transformation is determined using a rigid registration of the conventional CBCT and the prior partial CBCT. From the derived patient transformation, the measured scatter is then modified to adapt the new on-treatment patient geometry for scatter correction. The proposed method is evaluated using physical experiments on a clinical CBCT system. On the Catphan 600 phantom, the errors in Hounsfield unit (HU) in the selected regions of interest are reduced from about 350 to below 50 HU; on an anthropomorphic phantom, the error is reduced from 15.7% to 5.4%. The proposed method is attractive in applications where a high CBCT image quality is critical, for example, dose calculation in adaptive radiation therapy.

    View details for DOI 10.1118/1.3130047

    View details for Web of Science ID 000266442000035

    View details for PubMedID 19610315

    View details for PubMedCentralID PMC2832067

  • Search for IMRT inverse plans with piecewise constant fluence maps using compressed sensing techniques MEDICAL PHYSICS Zhu, L., Xing, L. 2009; 36 (5): 1895-1905

    Abstract

    An intensity-modulated radiation therapy (IMRT) field is composed of a series of segmented beams. It is practically important to reduce the number of segments while maintaining the conformality of the final dose distribution. In this article, the authors quantify the complexity of an IMRT fluence map by introducing the concept of sparsity of fluence maps and formulate the inverse planning problem into a framework of compressing sensing. In this approach, the treatment planning is modeled as a multiobjective optimization problem, with one objective on the dose performance and the other on the sparsity of the resultant fluence maps. A Pareto frontier is calculated, and the achieved dose distributions associated with the Pareto efficient points are evaluated using clinical acceptance criteria. The clinically acceptable dose distribution with the smallest number of segments is chosen as the final solution. The method is demonstrated in the application of fixed-gantry IMRT on a prostate patient. The result shows that the total number of segments is greatly reduced while a satisfactory dose distribution is still achieved. With the focus on the sparsity of the optimal solution, the proposed method is distinct from the existing beamlet- or segment-based optimization algorithms.

    View details for DOI 10.1118/1.3110163

    View details for Web of Science ID 000265526800050

    View details for PubMedID 19544809

    View details for PubMedCentralID PMC2736710

  • Noise suppression in scatter correction for cone-beam CT MEDICAL PHYSICS Zhu, L., Wang, J., Xing, L. 2009; 36 (3): 741-752

    Abstract

    Scatter correction is crucial to the quality of reconstructed images in x-ray cone-beam computed tomography (CBCT). Most of existing scatter correction methods assume smooth scatter distributions. The high-frequency scatter noise remains in the projection images even after a perfect scatter correction. In this paper, using a clinical CBCT system and a measurement-based scatter correction, the authors show that a scatter correction alone does not provide satisfactory image quality and the loss of the contrast-to-noise ratio (CNR) of the scatter corrected image may overwrite the benefit of scatter removal. To circumvent the problem and truly gain from scatter correction, an effective scatter noise suppression method must be in place. They analyze the noise properties in the projections after scatter correction and propose to use a penalized weighted least-squares (PWLS) algorithm to reduce the noise in the reconstructed images. Experimental results on an evaluation phantom (Catphan600) show that the proposed algorithm further reduces the reconstruction error in a scatter corrected image from 10.6% to 1.7% and increases the CNR by a factor of 3.6. Significant image quality improvement is also shown in the results on an anthropomorphic phantom, in which the global noise level is reduced and the local streaking artifacts around bones are suppressed.

    View details for DOI 10.1118/1.3063001

    View details for Web of Science ID 000263718100008

    View details for PubMedID 19378735

    View details for PubMedCentralID PMC2736744

  • Use of MV and kV imager correlation for maintaining continuous real-time 3D internal marker tracking during beam interruptions PHYSICS IN MEDICINE AND BIOLOGY Wiersma, R. D., Riaz, N., Dieterich, S., Suh, Y., Xing, L. 2009; 54 (1): 89-103

    Abstract

    The integration of onboard kV imaging together with a MV electronic portal imaging device (EPID) on linear accelerators (LINAC) can provide an easy to implement real-time 3D organ position monitoring solution for treatment delivery. Currently, real-time MV-kV tracking has only been demonstrated by simultaneous imagining by both MV and kV imaging devices. However, modalities such as step-and-shoot IMRT (SS-IMRT), which inherently contain MV beam interruptions, can lead to loss of target information necessary for 3D localization. Additionally, continuous kV imaging throughout the treatment delivery can lead to high levels of imaging dose to the patient. This work demonstrates for the first time how full 3D target tracking can be maintained even in the presence of such beam interruption, or MV/kV beam interleave, by use of a relatively simple correlation model together with MV-kV tracking. A moving correlation model was constructed using both present and prior positions of the marker in the available MV or kV image to compute the position of the marker on the interrupted imager. A commercially available radiotherapy system, equipped with both MV and kV imaging devices, was used to deliver typical SS-IMRT lung treatment plans to a 4D phantom containing internally embedded metallic markers. To simulate actual lung tumor motion, previous recorded 4D lung patient motion data were used. Lung tumor motion data of five separate patients were inputted into the 4D phantom, and typical SS-IMRT lung plans were delivered to simulate actual clinical deliveries. Application of the correlation model to SS-IMRT lung treatment deliveries was found to be an effective solution for maintaining continuous 3D tracking during 'step' beam interruptions. For deliveries involving five or more gantry angles with 50 or more fields per plan, the positional errors were found to have < or =1 mm root mean squared error (RMSE) in all three spatial directions. In addition to increasing the robustness of MV-kV tracking against beam interruption, it was also found that use of correlation can be an effective way of lowering kV dose to the patient and for increasing kV image quality by reduction of MV scatter interference.

    View details for DOI 10.1088/0031-9155/54/1/006

    View details for Web of Science ID 000261597400006

    View details for PubMedID 19060356

  • Iterative image reconstruction for CBCT using edge-preserving prior MEDICAL PHYSICS Wang, J., Li, T., Xing, L. 2009; 36 (1): 252-260

    Abstract

    On-board cone-beam computed tomography (CBCT) is a new imaging technique for radiation therapy guidance, which provides volumetric information of a patient at treatment position. CBCT improves the setup accuracy and may be used for dose reconstruction. However, there is great concern that the repeated use of CBCT during a treatment course delivers too much of an extra dose to the patient. To reduce the CBCT dose, one needs to lower the total mAs of the x-ray tube current, which usually leads to reduced image quality. Our goal of this work is to develop an effective method that enables one to achieve a clinically acceptable CBCT image with as low as possible mAs without compromising quality. An iterative image reconstruction algorithm based on a penalized weighted least-squares (PWLS) principle was developed for this purpose. To preserve edges in the reconstructed images, we designed an anisotropic penalty term of a quadratic form. The algorithm was evaluated with a CT quality assurance phantom and an anthropomorphic head phantom. Compared with conventional isotropic penalty, the PWLS image reconstruction algorithm with anisotropic penalty shows better resolution preservation.

    View details for DOI 10.1118/1.3036112

    View details for Web of Science ID 000262105200028

    View details for PubMedID 19235393

    View details for PubMedCentralID PMC2739313

  • Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy MEDICAL PHYSICS Paquin, D., Levy, D., Xing, L. 2009; 36 (1): 4-11

    Abstract

    Adaptive radiation therapy (ART) is the incorporation of daily images in the radiotherapy treatment process so that the treatment plan can be evaluated and modified to maximize the amount of radiation dose to the tumor while minimizing the amount of radiation delivered to healthy tissue. Registration of planning images with daily images is thus an important component of ART. In this article, the authors report their research on multiscale registration of planning computed tomography (CT) images with daily cone beam CT (CBCT) images. The multiscale algorithm is based on the hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [Multiscale Model. Simul. 2(4), pp. 554-579 (2004)]. Registration is achieved by decomposing the images to be registered into a series of scales using the (BV, L2) decomposition and initially registering the coarsest scales of the image using a landmark-based registration algorithm. The resulting transformation is then used as a starting point to deformably register the next coarse scales with one another. This procedure is iterated at each stage using the transformation computed by the previous scale registration as the starting point for the current registration. The authors present the results of studies of rectum, head-neck, and prostate CT-CBCT registration, and validate their registration method quantitatively using synthetic results in which the exact transformations our known, and qualitatively using clinical deformations in which the exact results are not known.

    View details for DOI 10.1118/1.3026602

    View details for Web of Science ID 000262105200002

    View details for PubMedID 19235367

    View details for PubMedCentralID PMC2739311

  • Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy Xing L, Paquin D, Levy D 2009; 36: 4-11
  • Medical Physics Iterative image reconstruction for CBCT using edge-preserving prior Xing L, Wang J, Li T 2009; 34: 252-260
  • Real-time 3D internal marker tracking during arc radiotherapy by the use of combined MV-kV imaging PHYSICS IN MEDICINE AND BIOLOGY Liu, W., Wiersma, R. D., Mao, W., Luxton, G., Xing, L. 2008; 53 (24): 7197-7213

    Abstract

    To minimize the adverse dosimetric effect caused by tumor motion, it is desirable to have real-time knowledge of the tumor position throughout the beam delivery process. A promising technique to realize the real-time image guided scheme in external beam radiation therapy is through the combined use of MV and onboard kV beam imaging. The success of this MV-kV triangulation approach for fixed-gantry radiation therapy has been demonstrated. With the increasing acceptance of modern arc radiotherapy in the clinics, a timely and clinically important question is whether the image guidance strategy can be extended to arc therapy to provide the urgently needed real-time tumor motion information. While conceptually feasible, there are a number of theoretical and practical issues specific to the arc delivery that need to be resolved before clinical implementation. The purpose of this work is to establish a robust procedure of system calibration for combined MV and kV imaging for internal marker tracking during arc delivery and to demonstrate the feasibility and accuracy of the technique. A commercially available LINAC equipped with an onboard kV imager and electronic portal imaging device (EPID) was used for the study. A custom built phantom with multiple ball bearings was used to calibrate the stereoscopic MV-kV imaging system to provide the transformation parameters from imaging pixels to 3D world coordinates. The accuracy of the fiducial tracking system was examined using a 4D motion phantom capable of moving in accordance with a pre-programmed trajectory. Overall, spatial accuracy of MV-kV fiducial tracking during the arc delivery process for normal adult breathing amplitude and period was found to be better than 1 mm. For fast motion, the results depended on the imaging frame rates. The RMS error ranged from approximately 0.5 mm for the normal adult breathing pattern to approximately 1.5 mm for more extreme cases with a low imaging frame rate of 3.4 Hz. In general, highly accurate real-time tracking of implanted markers using hybrid MV-kV imaging is achievable and the technique should be useful to improve the beam targeting accuracy of arc therapy.

    View details for DOI 10.1088/0031-9155/53/24/013

    View details for Web of Science ID 000261310200013

    View details for PubMedID 19043177

  • Using total-variation regularization for intensity modulated radiation therapy inverse planning with field-specific numbers of segments PHYSICS IN MEDICINE AND BIOLOGY Zhu, L., Lee, L., Ma, Y., Ye, Y., Mazzeo, R., Xing, L. 2008; 53 (23): 6653-6672

    Abstract

    Currently, there are two types of treatment planning algorithms for intensity modulated radiation therapy (IMRT). The beamlet-based algorithm generates beamlet intensity maps with high complexity, resulting in large numbers of segments in the delivery after a leaf-sequencing algorithm is applied. The segment-based direct aperture optimization (DAO) algorithm includes the physical constraints of the deliverable apertures in the calculation, and achieves a conformal dose distribution using a small number of segments. However, the number of segments is pre-fixed in most of the DAO approaches, and the typical random search scheme in the optimization is computationally intensive. A regularization-based algorithm is proposed to overcome the drawbacks of the DAO method. Instead of smoothing the beamlet intensity maps as in many existing methods, we include a total-variation term in the optimization objective function to reduce the number of signal levels of the beam intensity maps. An aperture rectification algorithm is then applied to generate a significantly reduced number of deliverable apertures. As compared to the DAO algorithm, our method has an efficient form of quadratic optimization, with an additional advantage of optimizing field-specific numbers of segments based on the modulation complexity. The proposed approach is evaluated using two clinical cases. Under the condition that the clinical acceptance criteria of the treatment plan are satisfied, for the prostate patient, the total number of segments for five fields is reduced from 61 using the Eclipse planning system to 35 using the proposed algorithm; for the head and neck patient, the total number of segments for seven fields is reduced from 107 to 28. The head and neck result is also compared to that using an equal number of four segments for each field. The comparison shows that using field-specific numbers of segments achieves a much improved dose distribution.

    View details for DOI 10.1088/0031-9155/53/23/002

    View details for Web of Science ID 000260859000002

    View details for PubMedID 18997262

  • The use of EPID-measured leaf sequence files for IMRT dose reconstruction in adaptive radiation therapy MEDICAL PHYSICS Lee, L., Mao, W., Xing, L. 2008; 35 (11): 5019-5029

    Abstract

    For intensity modulated radiation treatment (IMRT) dose reconstruction, multileaf collimator (MLC) log files have been shown applicable for deriving delivered fluence maps. However, MLC log files are dependent on the accuracy of leaf calibration and only available from one linear accelerator manufacturer. This paper presents a proof of feasibility and principles in (1) using an amorphous silicon electronic portal imaging device (aSi-EPID) to capture the MLC segments during an IMRT delivery and (2) reconstituting a leaf sequence (LS) file based on the leaf end positions calculated from the MLC segments and their associated fractional monitor units. These EPID-measured LS files are then used to derive delivered fluence maps for dose reconstruction. The developed approach was tested on a pelvic phantom treated with a typical prostate IMRT plan. The delivered fluence maps, which were derived from the EPID-measured LS files, showed slight differences in the intensity levels compared with the corresponding planned ones. The dose distribution calculated with the delivered fluence maps showed a discernible difference in the high dose region when compared to that calculated with the planned fluence maps. The maximum dose in the former distribution was also 2.5% less than that in the latter one. The EPID-measured LS file can serve the same purpose as a MLC log files does for the derivation of the delivered fluence map and yet is independent of the leaf calibration. The approach also allows users who do not have access to MLC log files to probe the actual IMRT delivery and translate the information gained for dose reconstruction in adaptive radiation therapy.

    View details for DOI 10.1118/1.2990782

    View details for PubMedID 19070236

  • MRI-based treatment planning with electron density information mapped from CT images: A preliminary study TECHNOLOGY IN CANCER RESEARCH & TREATMENT Wang, C., Chao, M., Lee, L., Xing, L. 2008; 7 (5): 341-347

    Abstract

    Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patient's readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3-5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patient's treatment with only simulation MRI and any available diagnostic/staging CT data.

    View details for PubMedID 18783283

  • Feature-based rectal contour propagation from planning CT to cone beam CT MEDICAL PHYSICS Xie, Y., Chao, M., Lee, P., Xing, L. 2008; 35 (10): 4450-4459

    Abstract

    The purpose of this work is to develop a novel feature-based registration strategy to automatically map the rectal contours from planning computed tomography (CT) (pCT) to cone beam CT (CBCT). The rectal contours were manually outlined on the pCT. A narrow band with the outlined contour as its interior surface was then constructed, so that we can exclude the volume inside the rectum in the registration process. The corresponding contour in the CBCT was found by using a feature-based registration algorithm, which consists of two steps: (1) automatically searching for control points in the pCT and CBCT based on the features of the surrounding tissue and matching the homologous control points using the scale invariance feature transformation; and (2) using the control points for a thin plate spline transformation to warp the narrow band and mapping the corresponding contours from pCT to CBCT. The proposed contour propagation technique is applied to digital phantoms and clinical cases and, in all cases, the contour mapping results are found to be clinically acceptable. For clinical cases, the method yielded satisfactory results even when there were significant rectal content changes between the pCT and CBCT scans. As a consequence, the accordance between the rectal volumes after deformable registration and the manually segmented rectum was found to be more than 90%. The proposed technique provides a powerful tool for adaptive radiotherapy of prostate, rectal, and gynecological cancers in the future.

    View details for DOI 10.1118/1.2975230

    View details for PubMedID 18975692

  • Auto-propagation of contours for adaptive prostate radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Chao, M., Xie, Y., Xing, L. 2008; 53 (17): 4533-4542

    Abstract

    The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.

    View details for DOI 10.1088/0031-9155/53/17/005

    View details for Web of Science ID 000258537000006

    View details for PubMedID 18677041

  • Intrafractional motion of the prostate during hypofractionated radiotherapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Xie, Y., Djajaputra, D., King, C. R., Hossain, S., Ma, L., Xing, L. 2008; 72 (1): 236-246

    Abstract

    To report the characteristics of prostate motion as tracked by the stereoscopic X-ray images of the implanted fiducials during hypofractionated radiotherapy with CyberKnife.Twenty-one patients with prostate cancer who were treated with CyberKnife between January 2005 and September 2007 were selected for this retrospective study. The CyberKnife uses a stereoscopic X-ray system to obtain the position of the prostate target through the monitoring of implanted gold fiducial markers. If there is a significant deviation, the treatment is paused while the patient is repositioned by moving the couch. The deviations calculated from X-ray images acquired within the time interval between two consecutive couch motions constitute a data set.Included in the analysis were 427 data sets and 4,439 time stamps of X-ray images. The mean duration for each data set was 697 sec. At 30 sec, a motion >2 mm exists in about 5% of data sets. The percentage is increased to 8%, 11%, and 14% at 60 sec, 90 sec, and 120 sec, respectively. A similar trend exists for other values of prostate motion.With proper monitoring and intervention during treatment, the prostate shifts observed among patients can be kept within the tracking range of the CyberKnife. On average, a sampling rate of approximately 40 sec between consecutive X-rays is acceptable to ensure submillimeter tracking. However, there is significant movement variation among patients, and a higher sampling rate may be necessary in some patients.

    View details for DOI 10.1016/j.ijrobp.2008.04.051

    View details for Web of Science ID 000258741700036

    View details for PubMedID 18722274

    View details for PubMedCentralID PMC2725181

  • A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging MEDICAL PHYSICS Mao, W., Riaz, N., Lee, L., Wiersma, R., Xing, L. 2008; 35 (8): 3554-3564

    Abstract

    The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.

    View details for DOI 10.1118/1.2953563

    View details for PubMedID 18777916

  • Dose reduction for kilovotage cone-beam computed tomography in radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Wang, J., Li, T., Liang, Z., Xing, L. 2008; 53 (11): 2897-2909

    Abstract

    Kilovotage cone-beam computed tomography (kV-CBCT) has shown potentials to improve the accuracy of a patient setup in radiotherapy. However, daily and repeated use of CBCT will deliver high extra radiation doses to patients. One way to reduce the patient dose is to lower mAs when acquiring projection data. This, however, degrades the quality of low mAs CBCT images dramatically due to excessive noises. In this work, we aim to improve the CBCT image quality from low mAs scans. Based on the measured noise properties of the sinogram, a penalized weighted least-squares (PWLS) objective function was constructed, and the ideal sinogram was then estimated by minimizing the PWLS objection function. To preserve edge information in the projection data, an anisotropic penalty term was designed using the intensity difference between neighboring pixels. The effectiveness of the presented algorithm was demonstrated by two experimental phantom studies. Noise in the reconstructed CBCT image acquired with a low mAs protocol was greatly suppressed after the proposed sinogram domain image processing, without noticeable sacrifice of the spatial resolution.

    View details for DOI 10.1088/0031-9155/53/11/009

    View details for Web of Science ID 000256352000010

    View details for PubMedID 18460749

  • Fast internal marker tracking algorithm for onboard MV and kV imaging systems MEDICAL PHYSICS Mao, W., Wiersma, R. D., Xing, L. 2008; 35 (5): 1942-1949

    Abstract

    Intrafraction organ motion can limit the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT) due to target position uncertainty. To ensure high accuracy in beam targeting, real-time knowledge of the target location is highly desired throughout the beam delivery process. This knowledge can be gained through imaging of internally implanted radio-opaque markers with fluoroscopic or electronic portal imaging devices (EPID). In the case of MV based images, marker detection can be problematic due to the significantly lower contrast between different materials in comparison to their kV-based counterparts. This work presents a fully automated algorithm capable of detecting implanted metallic markers in both kV and MV images with high consistency. Using prior CT information, the algorithm predefines the volumetric search space without manual region-of-interest (ROI) selection by the user. Depending on the template selected, both spherical and cylindrical markers can be detected. Multiple markers can be simultaneously tracked without indexing confusion. Phantom studies show detection success rates of 100% for both kV and MV image data. In addition, application of the algorithm to real patient image data results in successful detection of all implanted markers for MV images. Near real-time operational speeds of approximately 10 frames/sec for the detection of five markers in a 1024 x 768 image are accomplished using an ordinary PC workstation.

    View details for DOI 10.1118/1.2905225

    View details for Web of Science ID 000255456500035

    View details for PubMedID 18561670

    View details for PubMedCentralID PMC2809731

  • Combined kV and MV imaging for real-time tracking of implanted fiducial markers MEDICAL PHYSICS Wiersma, R. D., Mao, W., Xing, L. 2008; 35 (4): 1191-1198

    Abstract

    In the presence of intrafraction organ motion, target localization uncertainty can greatly hamper the advantage of highly conformal dose techniques such as intensity modulated radiation therapy (IMRT). To minimize the adverse dosimetric effect caused by tumor motion, a real-time knowledge of the tumor position is required throughout the beam delivery process. The recent integration of onboard kV diagnostic imaging together with MV electronic portal imaging devices on linear accelerators can allow for real-time three-dimensional (3D) tumor position monitoring during a treatment delivery. The aim of this study is to demonstrate a near real-time 3D internal fiducial tracking system based on the combined use of kV and MV imaging. A commercially available radiotherapy system equipped with both kV and MV imaging systems was used in this work. A hardware video frame grabber was used to capture both kV and MV video streams simultaneously through independent video channels at 30 frames per second. The fiducial locations were extracted from the kV and MV images using a software tool. The geometric tracking capabilities of the system were evaluated using a pelvic phantom with embedded fiducials placed on a moveable stage. The maximum tracking speed of the kV/MV system is approximately 9 Hz, which is primarily limited by the frame rate of the MV imager. The geometric accuracy of the system is found to be on the order of less than 1 mm in all three spatial dimensions. The technique requires minimal hardware modification and is potentially useful for image-guided radiation therapy systems.

    View details for DOI 10.1118/1.2842072

    View details for Web of Science ID 000254510700004

    View details for PubMedID 18491510

    View details for PubMedCentralID PMC2811551

  • Development of a QA phantom and automated analysis tool for geometric quality assurance of on-board MV and kV x-ray imaging systems MEDICAL PHYSICS Mao, W., Lee, L., Xing, L. 2008; 35 (4): 1497-1506

    Abstract

    The medical linear accelerator (linac) integrated with a kilovoltage (kV) flat-panel imager has been emerging as an important piece of equipment for image-guided radiation therapy. Due to the sagging of the linac head and the flexing of the robotic arms that mount the x-ray tube and flat-panel detector, geometric nonidealities generally exist in the imaging geometry no matter whether it is for the two-dimensional projection image or three-dimensional cone-beam computed tomography. Normally, the geometric parameters are established during the commissioning and incorporated in correction software in respective image formation or reconstruction. A prudent use of an on-board imaging system necessitates a routine surveillance of the geometric accuracy of the system like the position of the x-ray source, imager position and orientation, isocenter, rotation trajectory, and source-to-imager distance. Here we describe a purposely built phantom and a data analysis software for monitoring these important parameters of the system in an efficient and automated way. The developed tool works equally well for the megavoltage (MV) electronic portal imaging device and hence allows us to measure the coincidence of the isocenters of the MV and kV beams of the linac. This QA tool can detect an angular uncertainty of 0.1 degrees of the x-ray source. For spatial uncertainties, such as the source position, the imager position, or the kV/MV isocenter misalignment, the demonstrated accuracy of this tool was better than 1.6 mm. The developed tool provides us with a simple, robust, and objective way to probe and monitor the geometric status of an imaging system in a fully automatic process and facilitate routine QA workflow in a clinic.

    View details for DOI 10.1118/1.2885719

    View details for PubMedID 18491545

  • Reducing respiratory motion artifacts in radionuclide imaging through retrospective stacking: A simulation study LINEAR ALGEBRA AND ITS APPLICATIONS Thorndyke, B., Koong, A., Xing, L. 2008; 428 (5-6): 1325-1344
  • Automated contour mapping with a regional deformable model INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Chao, M., Li, T., Schreibmann, E., Koong, A., Xing, L. 2008; 70 (2): 599-608

    Abstract

    To develop a regional narrow-band algorithm to auto-propagate the contour surface of a region of interest (ROI) from one phase to other phases of four-dimensional computed tomography (4D-CT).The ROI contours were manually delineated on a selected phase of 4D-CT. A narrow band encompassing the ROI boundary was created on the image and used as a compact representation of the ROI surface. A BSpline deformable registration was performed to map the band to other phases. A Mattes mutual information was used as the metric function, and the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm was used to optimize the function. After registration the deformation field was extracted and used to transform the manual contours to other phases. Bidirectional contour mapping was introduced to evaluate the proposed technique. The new algorithm was tested on synthetic images and applied to 4D-CT images of 4 thoracic patients and a head-and-neck Cone-beam CT case.Application of the algorithm to synthetic images and Cone-beam CT images indicates that an accuracy of 1.0 mm is achievable and that 4D-CT images show a spatial accuracy better than 1.5 mm for ROI mappings between adjacent phases, and 3 mm in opposite-phase mapping. Compared with whole image-based calculations, the computation was an order of magnitude more efficient, in addition to the much-reduced computer memory consumption.A narrow-band model is an efficient way for contour mapping and should find widespread application in future 4D treatment planning.

    View details for DOI 10.1016/j.ijrobp.2007.09.057

    View details for Web of Science ID 000252521700038

    View details for PubMedID 18207035

  • Retrospective IMRT dose reconstruction based on cone-beam CT and MLC log-file INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Lee, L., Le, Q., Xing, L. 2008; 70 (2): 634-644

    Abstract

    Head-and-neck (HN) cone-beam computed tomography (CBCT) can be exploited to probe the IMRT dose delivered to a patient taking into account the interfraction anatomic variation and any potential inaccuracy in the IMRT delivery. The aim of this work is to reconstruct the intensity-modulated radiation therapy dose delivered to an HN patient using the CBCT and multileaf collimator (MLC) log-files.A cylindrical CT phantom was used for calibrating the electron density and validating the procedures of the dose reconstruction. Five HN patients were chosen, and for each patient, CBCTs were performed on three separate fractions spaced every 2 weeks starting from the first fraction. The respective MLC log-files were retrieved and converted into fluence maps. The dose was then reconstructed on the corresponding CBCT with the regenerated fluence maps. The reconstructed dose distribution, dosimetric endpoints, and DVHs were compared with that of the treatment plan.Phantom study showed that HN CBCT can be directly used for dose reconstruction. For most treatment sessions, the CBCT-based dose reconstructions yielded DVHs of the targets close (within 3%) to that of the original treatment plans. However, dosimetric changes (within 10%) due to anatomic variations caused by setup inaccuracy, organ deformation, tumour shrinkage, or weight loss (or a combination of these) were observed for the critical organs.The methodology we established affords an objective dosimetric basis for the clinical decision on whether a replanning is necessary during the course of treatment and provides a valuable platform for adaptive therapy in future.

    View details for DOI 10.1016/j.ijrobp.2007.09.054

    View details for Web of Science ID 000252521700042

    View details for PubMedID 18207036

  • Individualized gating windows based on four-dimensional CT information for respiration-gated radiotherapy PHYSICS IN MEDICINE AND BIOLOGY Wink, N. M., Chao, M., Antony, J., Xing, L. 2008; 53 (1): 165-175

    Abstract

    The purpose of this work is to relate the gating window and displacement of a moving tumor target and develop a systematic method to individualize the gating window for respiration-gated radiation therapy (RT). As the relationship between patient anatomy and respiration phase is contained in 4D images, we aim to quantify this information and utilize the data to guide gated treatment planning. After 4D image acquisition, the target and organs at risk were delineated manually on the selected gating phase. The contours were propagated automatically onto every phase-specific image set using a control volume-based contour mapping technique. The mean and maximum distances between the contours in the gating phase and each of other phases were evaluated in three dimensions. The gating window was determined in such a way that the residual movement of the target within the window is smaller or equal to the patient's setup error. The proposed method was applied to plan the gated treatments of 12 lung cancer patients. As a result of this work, a method to calculate patient-specific gating windows has been developed. The general reference drawn from this study is that, with the aide of 4D images and automated 4D contour propagation, it is feasible to individualize the gating widow selection. As compared with the current practice, the proposed technique has a potential to eliminate the guesswork involved in choosing a gating window and avoid dosimetric error in planning gated RT. In conclusion, individualization of gating windows reduces the subjectivity in respiration-gated RT and improves the treatment of moving targets.

    View details for DOI 10.1088/0031-9155/53/1/011

    View details for Web of Science ID 000252792400011

    View details for PubMedID 18182694

  • Dose reduction in kV cone beam CT for radiation therapy Physics in Medicine and Biology Xing L, Wang J, Li T, Liang Z 2008; 53: 2897-2909
  • Medical Imaging Modalities in Radiotherapy RADIATION ONCOLOGY: AN EVIDENCE-BASED APPROACH Hristov, D., Xing, L., Lu, J. J., Brady, L. W. 2008: 625–39
  • Image guided intensity modulated radiation therapy MATHEMATICAL METHODS IN BIOMEDICAL IMAGING AND INTENSITY-MODULATED RADIATION THERAPY (IMRT) Xing, L., Lee, L., Censor, Y., Jiang, M., Louis, A. K. 2008; 7: 479–504
  • Multiscale deformable registration of noisy medical images MATHEMATICAL BIOSCIENCES AND ENGINEERING Paquin, D., Levy, D., Xing, L. 2008; 5 (1): 125-144

    Abstract

    Multiscale image registration techniques are presented for the registration of medical images using deformable registration models. The techniques are particularly effective for registration problems in which one or both of the images to be registered contains significant levels of noise. A brief overview of existing deformable registration techniques is presented, and experiments using B-spline free-form deformation registration models demonstrate that ordinary deformable registration techniques fail to produce accurate results in the presence of significant levels of noise. The hierarchical multiscale image decomposition described in E. Tadmor, S. Nezzar, and L. Vese's, "A multiscale image representation using hierarchical (BV;L2) decompositions" (Multiscale Modeling and Simulations, 2 (2004): 4, pp. 554-579) is reviewed, and multiscale image registration algorithms are developed based on the multiscale decomposition. Accurate registration of noisy images is achieved by obtaining a hierarchical multiscale decomposition of the images and iteratively registering the resulting components. This approach enables a successful regstration of images that contain noise levels well beyond the level at which ordinary deformable registration fails. Numerous image registration experiments demonstrate the accuracy and efficiency of the multiscale registration techniques.

    View details for Web of Science ID 000254377900008

    View details for PubMedID 18193935

  • Modeling the shear movement of the lungs during respiration using tissue feature-based image registration, conditionally accepted Xing L, Xie Y, Chao M 2008
  • Noise suppression in scatter correction for cone-beam CT, in press Xing L, Zhu L, Wang J 2008
  • Pancreatic tumor motion on a single planning 4D-CT dose not correlate with intrafraction tumor motion during treatment, in press Xing L, Minn Y, Schellenberg D, mazim P, Suh Y, Cox B, Dieterich S, Goodman KA, Chang D, Koong A 2008
  • Auto-mapping of rectum contour for prostate adaptive therapy inverse planning Medical Physics Xing L, Xie Y, Chao M 2008
  • Quality assurance of PET/CT for radiation therapy International Journal of Radiation Oncology, Biology and Physics Xing L 2008; 71: S38-41
  • Contour propagation from planning CT to cone beam CT (CBCT) Physics in Medicine and Biology Xing L, Chao M, Schreibmann E, Li T 2008; 53: 4533-4542
  • Design of multi-purpose phantom and automated software analysis tool for quality assurance of onboard kV/MV imaging system Medical Physics Xing L, Mao W, Lee L 2008; 35: 1497-1506
  • Quality assurance of positron emission tomography/computed tomography for radiation therapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Xing, L. 2008; 71 (1): S38-S42

    Abstract

    Recent advances in radiation delivery techniques, such as intensity-modulated radiation therapy, provide unprecedented ability to exquisitely control three-dimensional dose distribution. Development of on-board imaging and other image-guidance methods significantly improved our ability to better target a radiation beam to the tumor volume. However, in reality, accurate definition of the location and boundary of the tumor target is still problematic. Biologic and physiologic imaging promises to solve the problem in a fundamental way and has a more and more important role in patient staging, treatment planning, and therapeutic assessment in radiation therapy clinics. The last decade witnessed a dramatic increase in the use of positron emission tomography and computed tomography in radiotherapy practice. To ensure safe and effective use of nuclide imaging, a rigorous quality assurance (QA) protocol of the imaging tools and integration of the imaging data must be in place. The application of nuclide imaging in radiation oncology occurs at different levels of sophistication. Quantitative use of the imaging data in treatment planning through image registration and standardized uptake value calculation is often involved. Thus, QA should not be limited to the performance of the scanner, but should also include the process of implementing image data in treatment planning, such as data transfer, image registration, and quantitation of data for delineation of tumors and sensitive structures. This presentation discusses various aspects of nuclide imaging as applied to radiotherapy and describes the QA procedures necessary for the success of biologic image-guided radiation therapy.

    View details for DOI 10.1016/j.ijrobp.2007.05.091

    View details for Web of Science ID 000255154300008

    View details for PubMedID 18406935

    View details for PubMedCentralID PMC2600917

  • Fast fiducial detection algorithm for onboard MV and kV imaging systems Medical Physics Xing L, Mao W, Wiersma R 2008; 35: 1942-1949
  • 4D-4D Image registration for image guided radiation therapy (IGRT) International Journal of Radiation Oncology, Biology and Physics Xing L, Schreibmann E, Thorndyke B 2008; 71: 578-586
  • Objective assessment of deformable image registration in radiotherapy: Amulti-institution study Xing L, Kashani R, Hub M, Balter JM, Kessler M, dong L, Zhang L, Xie Y, Hawkes D, Schnabel JA, McClelland J, Joshi S, Chen C, Lu W 2008; 35: 5944-5953
  • Dose reduction in fluoscopic imaging, conditionally accepted Xing L, Wang J, Li T 2008
  • Reducing respiratory motion artifacts in radionuclide imaging through retrospective stacking: A simulation study Linear Algebra and its Applications Xing L, Thorndyke B, Koong A 2008; 428: 1325-1344
  • Real-time monitoring of implanted fiducials using onboard kV and treatment MV beams Medical Physics Xing L, Wiersma R 2008; 35: 1191-1198
  • Point/Counterpoint. Kilovoltage imaging is more suitable than megavoltage imaging for guiding radiation therapy. Medical physics Xing, L., Chang, J., Orton, C. G. 2007; 34 (12): 4563-4566

    View details for PubMedID 18196781

  • Automated contour mapping using sparse volume sampling for 4D radiation therapy MEDICAL PHYSICS Chao, M., Schreibmann, E., Li, T., Wink, N., Xing, L. 2007; 34 (10): 4023-4029

    Abstract

    The purpose of this work is to develop a novel strategy to automatically map organ contours from one phase of respiration to all other phases on a four-dimensional computed tomography (4D CT). A region of interest (ROI) was manually delineated by a physician on one phase specific image set of a 4D CT. A number of cubic control volumes of the size of approximately 1 cm were automatically placed along the contours. The control volumes were then collectively mapped to the next phase using a rigid transformation. To accommodate organ deformation, a model-based adaptation of the control volume positions was followed after the rigid mapping procedure. This further adjustment of control volume positions was performed by minimizing an energy function which balances the tendency for the control volumes to move to their correspondences with the desire to maintain similar image features and shape integrity of the contour. The mapped ROI surface was then constructed based on the central positions of the control volumes using a triangulated surface construction technique. The proposed technique was assessed using a digital phantom and 4D CT images of three lung patients. Our digital phantom study data indicated that a spatial accuracy better than 2.5 mm is achievable using the proposed technique. The patient study showed a similar level of accuracy. In addition, the computational speed of our algorithm was significantly improved as compared with a conventional deformable registration-based contour mapping technique. The robustness and accuracy of this approach make it a valuable tool for the efficient use of the available spatial-tempo information for 4D simulation and treatment.

    View details for DOI 10.1118/1.2780105

    View details for Web of Science ID 000250330100035

    View details for PubMedID 17985648

  • Examination of geometric and dosimetric accuracies of gated step-and-shoot intensity modulated radiation therapy MEDICAL PHYSICS Wiersma, R. D., Xing, L. 2007; 34 (10): 3962-3970

    Abstract

    Due to the complicated technical nature of gated radiation therapy, electronic and mechanical limitations may affect the precision of delivery. The purpose of this study is to investigate the geometric and dosimetric accuracies of gated step-and-shoot intensity modulated radiation treatments (SS-IMRT). Unique segmental MLC plans are designed, which allow quantitative testing of the gating process. Both ungated and gated deliveries are investigated for different dose sizes, dose rates, and gating window times using a commercial treatment system (Varian Trilogy) together with a respiratory gating system [Varian Real-Time Position Management system]. Radiographic film measurements are used to study the geometric accuracy, where it is found that with both ungated and gated SS-IMRT deliveries the MLC leaf divergence away from planned is less than or equal to the MLC specified leaf tolerance value for all leafs (leaf tolerance being settable from 0.5-5 mm). Nevertheless, due to the MLC controller design, failure to define a specific leaf tolerance value suitable to the SS-IMRT plan can lead to undesired geometric effects, such as leaf motion of up to the maximum 5 mm leaf tolerance value occurring after the beam is turned on. In this case, gating may be advantageous over the ungated case, as it allows more time for the MLC to reach the intended leaf configuration. The dosimetric precision of gated SS-IMRT is investigated using ionization chamber methods. Compared with the ungated case, it is found that gating generally leads to increased dosimetric errors due to the interruption of the "overshoot phenomena." With gating the average timing deviation for intermediate segments is found to be 27 ms, compared to 18 ms for the ungated case. For a plan delivered at 600 MU/min this would correspond to an average segment dose error of approximately 0.27 MU and approximately 0.18 MU for gated and ungated deliveries, respectively. The maximum dosimetric errors for individual intermediate segments are found to deviate by up to approximately 0.64 MU from their planned value when delivered at 600 MU/min using gating, this compares to only approximately 0.32 MU for the ungated case.

    View details for DOI 10.1118/1.2776671

    View details for Web of Science ID 000250330100028

    View details for PubMedID 17985641

  • Computational challenges for image-guided radiation therapy: Framework and current research SEMINARS IN RADIATION ONCOLOGY Xing, L., Siebers, J., Keall, P. 2007; 17 (4): 245-257

    Abstract

    It is arguable that the imaging and delivery hardware necessary for delivering real-time adaptive image-guided radiotherapy is available on high-end linear accelerators. Robust and computationally efficient software is the limiting factor in achieving highly accurate and precise radiotherapy to the constantly changing anatomy of a cancer patient. The limitations are not caused by the availability of algorithms but rather issues of reliability, integration, and calculation time. However, each of the software components is an active area of research and development at academic and commercial centers. This article describes the software solutions in 4 broad areas: deformable image registration, adaptive replanning, real-time image guidance, and dose calculation and accumulation. Given the pace of technological advancement, the integration of these software solutions to develop real-time adaptive image-guided radiotherapy and the associated challenges they bring will be implemented to varying degrees by all major manufacturers over the coming years.

    View details for DOI 10.1016/j.semradonc.2007.07.004

    View details for Web of Science ID 000250060100002

    View details for PubMedID 17903702

  • Enhanced 4D cone-beam CT with inter-phase motion model MEDICAL PHYSICS Li, T., Koong, A., Xing, L. 2007; 34 (9): 3688-3695

    Abstract

    Four-dimensional (4D) cone-beam CT (CBCT) is commonly obtained by respiratory phase binning of the projections, followed by independent reconstructions of the rebinned data in each phase bin. Due to the significantly reduced number of projections per reconstruction, the quality of the 4DCBCT images is often degraded by view-aliasing artifacts easily seen in the axial view. Acquisitions using multiple gantry rotations or slow gantry rotation can increase the number of projections and substantially improve the 4D images. However, the extra cost of the scan time may set fundamental limits to their applications in clinics. Improving the trade-off between image quality and scan time is the key to making 4D onboard imaging practical and more useful. In this article, we present a novel technique toward high-quality 4DCBCT imaging without prolonging the acquisition time, referred to as the "enhanced 4DCBCT". The method correlates the data in different phase bins and integrates the internal motion into the 4DCBCT image formulation. Several strategies of the motion derivation are discussed, and the resultant images are assessed with numerical simulations as well as a clinical case.

    View details for DOI 10.1118/1.2767144

    View details for Web of Science ID 000249547200031

    View details for PubMedID 17926972

  • CT image registration in sinograrn space MEDICAL PHYSICS Mao, W., Li, T., Wink, N., Xing, L. 2007; 34 (9): 3596-3602

    Abstract

    Object displacement in a CT scan is generally reflected in CT projection data or sinogram. In this work, the direct relationship between object motion and the change of CT projection data (sinogram) is investigated and this knowledge is applied to create a novel algorithm for sinogram registration. Calculated and experimental results demonstrate that the registration technique works well for registering rigid 2D or 3D motion in parallel and fan beam samplings. Problem and solution for 3D sinogram-based registration of metallic fiducials are also addressed. Since the motion is registered before image reconstruction, the presented algorithm is particularly useful when registering images with metal or truncation artifacts. In addition, this algorithm is valuable for dealing with situations where only limited projection data are available, making it appealing for various applications in image guided radiation therapy.

    View details for DOI 10.1118/1.2767402

    View details for Web of Science ID 000249547200022

    View details for PubMedID 17926963

  • Formulating adaptive radiation therapy (ART) treatment planning into a closed-loop control framework 48th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) de la Zerda, A., Armbruster, B., Xing, L. IOP PUBLISHING LTD. 2007: 4137–53

    Abstract

    While ART has been studied for years, the specific quantitative implementation details have not. In order for this new scheme of radiation therapy (RT) to reach its potential, an effective ART treatment planning strategy capable of taking into account the dose delivery history and the patient's on-treatment geometric model must be in place. This paper performs a theoretical study of dynamic closed-loop control algorithms for ART and compares their utility with data from phantom and clinical cases. We developed two classes of algorithms: those Adapting to Changing Geometry and those Adapting to Geometry and Delivered Dose. The former class takes into account organ deformations found just before treatment. The latter class optimizes the dose distribution accumulated over the entire course of treatment by adapting at each fraction, not only to the information just before treatment about organ deformations but also to the dose delivery history. We showcase two algorithms in the class of those Adapting to Geometry and Delivered Dose. A comparison of the approaches indicates that certain closed-loop ART algorithms may significantly improve the current practice. We anticipate that improvements in imaging, dose verification and reporting will further increase the importance of adaptive algorithms.

    View details for DOI 10.1088/0031-9155/52/14/008

    View details for Web of Science ID 000247400000008

    View details for PubMedID 17664599

  • Investigation of linac-based image-guided hypofractionated prostate radiotherapy 47th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology Pawlicki, T., Kim, G., Hsu, A., Cotrutz, C., Boyer, A. L., Xing, L., King, C. R., Luxton, G. ELSEVIER SCIENCE INC. 2007: 71–79

    Abstract

    A hypofractionation treatment protocol for prostate cancer was initiated in our department in December 2003. The treatment regimen consists of a total dose of 36.25 Gy delivered at 7.25 Gy per fraction over 10 days. We discuss the rationale for such a prostate hypofractionation protocol and the need for frequent prostate imaging during treatment. The CyberKnife (Accuray Inc., Sunnyvale, CA), a linear accelerator mounted on a robotic arm, is currently being used as the radiation delivery device for this protocol, due to its incorporation of near real-time kV imaging of the prostate via 3 gold fiducial seeds. Recently introduced conventional linac kV imaging with intensity modulated planning and delivery may add a new option for these hypofractionated treatments. The purpose of this work is to investigate the use of intensity modulated radiotherapy (IMRT) and the Varian Trilogy Accelerator with on-board kV imaging (Varian Medical Systems Inc., Palo Alto, CA) for treatment of our hypofractionated prostate patients. The dose-volume histograms and dose statistics of 2 patients previously treated on the CyberKnife were compared to 7-field IMRT plans. A process of acquiring images to observe intrafraction prostate motion was achieved in an average time of about 1 minute and 40 seconds, and IMRT beam delivery takes about 40 seconds per field. A complete 7-field IMRT plan can therefore be imaged and delivered in 10 to 17 minutes. The Varian Trilogy Accelerator with on-board imaging and IMRT is well suited for image-guided hypofractionated prostate treatments. During this study, we have also uncovered opportunities for improvement of the on-board imaging hardware/software implementation that would further enhance performance in this regard.

    View details for DOI 10.1016/j.meddos.2007.01.004

    View details for Web of Science ID 000246485600002

    View details for PubMedID 17472885

  • High-quality four-dimensional CBCT reconstruction with virtual projections 49th Annual Meeting of the American-Association-of-Physicists-in-Medicine Li, T., Papiez, L., Timmerman, R., Choy, H., Koong, A., Xing, L. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2007: 2638–39
  • In vivo bioluminescence tumor imaging of RGD peptide-modified adenoviral vector encoding firefly luciferase reporter gene MOLECULAR IMAGING AND BIOLOGY Niu, G., Xiong, Z., Cheng, Z., Cai, W., Gambhir, S. S., Xing, L., Chen, X. 2007; 9 (3): 126-134

    Abstract

    The goal of this study is to demonstrate the feasibility of chemically modified human adenovirus (Ad) vectors for tumor retargeting.E1- and E3-deleted Ad vectors carrying firefly luciferase reporter gene under cytomegalovirus promoter (AdLuc) was surface-modified with cyclic arginine-glycine-aspartic acid (RGD) peptides through a bifunctional poly(ethyleneglycol) linker (RGD-PEG-AdLuc) for integrin alpha(v)beta(3) specific delivery. The Coxsackie and adenovirus viral receptor (CAR) and integrin alpha(v)beta(3) expression in various tumor cell lines was determined by reverse transcriptase PCR and fluorescence-activated cell sorting. Bioluminescence imaging was performed in vitro and in vivo to evaluate RGD-modified AdLuc infectivity.RGD-PEG-AdLuc abrogated the native CAR tropism and exhibited significantly enhanced transduction efficiency of integrin-positive tumors than AdLuc through intravenous administration.This approach provides a robust platform for site-specific gene delivery and noninvasive monitoring of the transgene delivery efficacy and homing.

    View details for DOI 10.1007/s11307-007-0079-2

    View details for Web of Science ID 000246175500005

    View details for PubMedID 17297551

    View details for PubMedCentralID PMC4165526

  • Optimizing 4D cone-beam CT acquisition protocol for external beam radiotherapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Li, T., Xing, L. 2007; 67 (4): 1211-1219

    Abstract

    Four-dimensional cone-beam computed tomography (4D-CBCT) imaging is sensitive to parameters such as gantry rotation speed, number of gantry rotations, X-ray pulse rate, and tube current, as well as a patient's breathing pattern. The aim of this study is to optimize the image acquisition on a patient-specific basis while minimizing the scan time and the radiation dose.More than 60 sets of 4D-CBCT images, each with a temporal resolution of 10 phases, were acquired using multiple-gantry rotation and slow-gantry rotation techniques. The image quality was quantified with a relative root mean-square error (RE) and correlated with various acquisition settings; specifically, varying gantry rotation speed, varying both the rotation speed and the number of rotations, and varying both the rotation speed and tube current to keep the radiation exposure constant. These experiments were repeated for three different respiratory periods.With similar radiation dose, 4D-CBCT images acquired with low current and low rotation speed have better quality over images obtained with high current and high rotation speed. In general, a one-rotation low-speed scan is superior to a two-rotation double-speed scan, even though they provide the same number of projections. Furthermore, it is found that the image quality behaves monotonically with the relative speed as defined by the gantry rotation speed and the patient respiratory period.The RE curves established in this work can be used to predict the 4D-CBCT image quality before a scan. This allows the acquisition protocol to be optimized individually to balance the desired quality with the associated scanning time and patient radiation dose.

    View details for DOI 10.1016/j.ijrobp.2006.10.024

    View details for Web of Science ID 000245021100032

    View details for PubMedID 17197125

  • Stereotactic body radiation therapy in multiple organ sites JOURNAL OF CLINICAL ONCOLOGY Timmerman, R. D., Kavanagh, B. D., Cho, L. C., Papiez, L., Xing, L. 2007; 25 (8): 947-952

    Abstract

    Stereotactic body radiation therapy (SBRT) uses advanced technology to deliver a potent ablative dose to deep-seated tumors in the lung, liver, spine, pancreas, kidney, and prostate.SBRT involves constructing very compact high-dose volumes in and about the tumor. Tumor position must be accurately assessed throughout treatment, especially for tumors that move with respiration. Sophisticated image guidance and related treatment delivery technologies have developed to account for such motion and efficiently deliver high daily dose. All this serves to allow the delivery of ablative dose fractionation to the target capable of both disrupting tumor mitosis and cellular function.Prospective phase I dose-escalation trials have been carried out to reach potent tumoricidal dose levels capable of eradicating tumors with high likelihood. These studies indicate a clear dose-response relationship for tumor control with escalating dose of SBRT. Prospective phase II studies have been reported from several continents consistently showing very high levels of local tumor control. Although late toxicity requires further careful assessment, acute and subacute toxicities are generally acceptable. Patterns of toxicity, both clinical and radiographic, are distinct from those observed with conventionally fractionated radiotherapy as a result of the unique biologic response to ablative fractionation.Prospective trials using SBRT have confirmed the efficacy of treatment in a variety of patient populations. Although mechanisms of ablative-dose injury remain elusive, ongoing prospective trials offer the hope of finding the ideal application for SBRT in the treatment arsenal.

    View details for DOI 10.1200/JCO.2006.09.7469

    View details for Web of Science ID 000244845200005

    View details for PubMedID 17350943

  • Evaluation of patterns of failure and subjective salivary function in patients treated with intensity modulated radiotherapy for head and neck squamous cell carcinoma 45th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) Daly, M. E., Lieskovsky, Y., Pawlicki, T., Yau, J., Pinto, H., Kaplan, M., Fee, W. E., Koong, A., Goffinet, D. R., Xing, L., Le, Q. JOHN WILEY & SONS INC. 2007: 211–20

    Abstract

    Our aim was to correlate patterns of failure with target volume delineations in patients with head and neck squamous cell carcinoma (HNSCC) treated with intensity-modulated radiation therapy (IMRT) and to report subjective xerostomia outcomes after IMRT as compared with conventional radiation therapy (CRT).Between January 2000 and April 2005, 69 patients with newly diagnosed nonmetastatic HNSCC underwent curative parotid-sparing IMRT at Stanford University. Sites included were oropharynx (n = 39), oral cavity (n = 8), larynx (n = 8), hypopharynx (n = 8), and unknown primary (n = 6). Forty-six patients received definitive IMRT (66 Gy, 2.2 Gy/fraction), and 23 patients received postoperative IMRT (60.2 Gy, 2.15 Gy/fraction). Fifty-one patients also received concomitant chemotherapy. Posttreatment salivary gland function was evaluated by a validated xerostomia questionnaire in 29 IMRT and 75 matched CRT patients >6 months after completing radiation treatment.At a median follow-up of 25 months for living patients (range, 10-60), 7 locoregional failures were observed, 5 in the gross target or high-risk postoperative volume, 1 in the clinical target volume, and 1 at the junction of the IMRT and supraclavicular fields. The 2-year Kaplan-Meier estimates for locoregional control and overall survival were 92% and 74% for definitive IMRT and 87% and 87% for postoperative IMRT patients, respectively. The mean total xerostomia questionnaire score was significantly better for IMRT than for CRT patients (p = .006).The predominant pattern of failure in IMRT-treated patients is in the gross tumor volume. Parotid sparing with IMRT resulted in less subjective xerostomia and may improve quality of life in irradiated HNSCC patients.

    View details for DOI 10.1002/hed.20505

    View details for Web of Science ID 000244459100002

    View details for PubMedID 17111429

  • Evaluation of on-board kV cone beam CT (CBCT)-based dose calculation PHYSICS IN MEDICINE AND BIOLOGY Yang, Y., Schreibmann, E., Li, T., Wang, C., Xing, L. 2007; 52 (3): 685-705

    Abstract

    On-board CBCT images are used to generate patient geometric models to assist patient setup. The image data can also, potentially, be used for dose reconstruction in combination with the fluence maps from treatment plan. Here we evaluate the achievable accuracy in using a kV CBCT for dose calculation. Relative electron density as a function of HU was obtained for both planning CT (pCT) and CBCT using a Catphan-600 calibration phantom. The CBCT calibration stability was monitored weekly for 8 consecutive weeks. A clinical treatment planning system was employed for pCT- and CBCT-based dose calculations and subsequent comparisons. Phantom and patient studies were carried out. In the former study, both Catphan-600 and pelvic phantoms were employed to evaluate the dosimetric performance of the full-fan and half-fan scanning modes. To evaluate the dosimetric influence of motion artefacts commonly seen in CBCT images, the Catphan-600 phantom was scanned with and without cyclic motion using the pCT and CBCT scanners. The doses computed based on the four sets of CT images (pCT and CBCT with/without motion) were compared quantitatively. The patient studies included a lung case and three prostate cases. The lung case was employed to further assess the adverse effect of intra-scan organ motion. Unlike the phantom study, the pCT of a patient is generally acquired at the time of simulation and the anatomy may be different from that of CBCT acquired at the time of treatment delivery because of organ deformation. To tackle the problem, we introduced a set of modified CBCT images (mCBCT) for each patient, which possesses the geometric information of the CBCT but the electronic density distribution mapped from the pCT with the help of a BSpline deformable image registration software. In the patient study, the dose computed with the mCBCT was used as a surrogate of the 'ground truth'. We found that the CBCT electron density calibration curve differs moderately from that of pCT. No significant fluctuation was observed in the calibration over the period of 8 weeks. For the static phantom, the doses computed based on pCT and CBCT agreed to within 1%. A notable difference in CBCT- and pCT-based dose distributions was found for the motion phantom due to the motion artefacts which appeared in the CBCT images (the maximum discrepancy was found to be approximately 3.0% in the high dose region). The motion artefacts-induced dosimetric inaccuracy was also observed in the lung patient study. For the prostate cases, the mCBCT- and CBCT-based dose calculations yielded very close results (<2%). Coupled with the phantom data, it is concluded that the CBCT can be employed directly for dose calculation for a disease site such as the prostate, where there is little motion artefact. In the prostate case study, we also noted a large discrepancy between the original treatment plan and the CBCT (or mCBCT)-based calculation, suggesting the importance of inter-fractional organ movement and the need for adaptive therapy to compensate for the anatomical changes in the future.

    View details for DOI 10.1088/0031-9155/52/3/011

    View details for Web of Science ID 000243684600011

    View details for PubMedID 17228114

  • Hybrid Multiscale Landmark and Deformable Image Registration Mathematical Biosciences and Engineering Paqin D., Levy D, Xing L. 2007; 4: 711 ?737
  • Combination of integrin siRNA and irradiation for breast cancer therapy BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS Cao, Q., Cai, W., Li, T., Yang, Y., Chen, K., Xing, L., Chen, X. 2006; 351 (3): 726-732

    Abstract

    Up-regulation of integrin alpha(v)beta(3) has been shown to play a key role in tumor angiogenesis and metastasis. In this study, we evaluated the role of integrin alpha(v)beta(3) in breast cancer cell resistance to ionizing irradiation (IR) and tested the anti-tumor efficacy of combining integrin alpha(v) siRNA and IR. Colonogenic survival assay, cell proliferation, apoptosis, and cell cycle analysis were carried out to determine the treatment effect of siRNA, IR, or combination of both on MDA-MB-435 cells (integrin alpha(v)beta(3)-positive). Integrin alpha(v)beta(3)-negative MCF-7 cells exert more radiosensitivity than MDA-MB-435 cells. IR up-regulates integrin alpha(v)beta(3) expression in MDA-MB-435 cells and integrin alpha(v) siRNA can effectively reduce both alpha(v) and alpha(v)beta(3) integrin expression, leading to increased radiosensitivity. Integrin alpha(v) siRNA also promotes IR-induced apoptosis and enhances IR-induced G2/M arrest in cell cycle progression. This study, with further optimization, may provide a simple and highly efficient treatment strategy for breast cancer as well as other integrin alpha(v)beta(3)-positive cancer types.

    View details for DOI 10.1016/j.bbrc.2006.10.100

    View details for Web of Science ID 000242233000025

    View details for PubMedID 17087916

  • Scatter correction method for X-ray CT using primary modulation: Theory and preliminary results IEEE TRANSACTIONS ON MEDICAL IMAGING Zhu, L., Bennett, N. R., Fahrig, R. 2006; 25 (12): 1573-1587

    Abstract

    An X-ray system with a large area detector has high scatter-to-primary ratios (SPRs), which result in severe artifacts in reconstructed computed tomography (CT) images. A scatter correction algorithm is introduced that provides effective scatter correction but does not require additional patient exposure. The key hypothesis of the algorithm is that the high-frequency components of the X-ray spatial distribution do not result in strong high-frequency signals in the scatter. A calibration sheet with a checkerboard pattern of semitransparent blockers (a "primary modulator") is inserted between the X-ray source and the object. The primary distribution is partially modulated by a high-frequency function, while the scatter distribution still has dominant low-frequency components, based on the hypothesis. Filtering and demodulation techniques suffice to extract the low-frequency components of the primary and hence obtain the scatter estimation. The hypothesis was validated using Monte Carlo (MC) simulation, and the algorithm was evaluated by both MC simulations and physical experiments. Reconstructions of a software humanoid phantom suggested system parameters in the physical implementation and showed that the proposed method reduced the relative mean square error of the reconstructed image in the central region of interest from 74.2% to below 1%. In preliminary physical experiments on the standard evaluation phantom, this error was reduced from 31.8% to 2.3%, and it was also demonstrated that the algorithm has no noticeable impact on the resolution of the reconstructed image in spite of the filter-based approach. Although the proposed scatter correction technique was implemented for X-ray CT, it can also be used in other X-ray imaging applications, as long as a primary modulator can be inserted between the X-ray source and the imaged object.

    View details for DOI 10.1109/TMI.2006.884636

    View details for Web of Science ID 000242650400005

    View details for PubMedID 17167993

  • Four-dimensional cone-beam computed tomography using an on-board imager MEDICAL PHYSICS Li, T., Xing, L., Munro, P., McGuinness, C., Chao, M., Yang, Y., Loo, B., Koong, A. 2006; 33 (10): 3825-3833

    Abstract

    On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patient's respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.

    View details for DOI 10.1118/1.2349692

    View details for Web of Science ID 000241424100024

    View details for PubMedID 17089847

  • Indirect MR lymphangiography of the head and neck using conventional gadolinium contrast: A pilot study in humans 45th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) Loo, B. W., Draney, M. T., Sivanandan, R., Ruehm, S. G., Pawlicki, T., Xing, L., Herfkens, R. J., Le, Q. ELSEVIER SCIENCE INC. 2006: 462–68

    Abstract

    To evaluate indirect magnetic resonance lymphangiography (MR-LAG) using interstitial injection of conventional gadolinium contrast (gadoteridol and gadopentetate dimeglumine) for delineating the primary lymphatic drainage of head-and-neck sites.We performed head-and-neck MR-LAG in 5 healthy volunteers, with injection of dermal and mucosal sites. We evaluated the safety of the procedure, the patterns of enhancement categorized by injection site and nodal level, the time course of enhancement, the optimal concentration and volume of contrast, and the optimal imaging sequence.The worst side effects of interstitial contrast injection were brief, mild pain and swelling at the injected sites that were self-limited. MR-LAG resulted in consistent visualization of the primary lymphatic drainage pattern specific to each injected site, which was reproducible on repeated examinations. The best enhancement was obtained with injection of small volumes (0.3-0.5 mL) of either agent diluted, imaging within 5-15 min of injection, and a three-dimensional fast spoiled gradient echo sequence with magnetization transfer.We found head-and-neck MR-LAG to be a safe, convenient imaging method that provides functional information about the lymphatic drainage of injected sites. Applied to head-and-neck cancer, it has the potential to identify sites at highest risk of occult metastatic spread for radiotherapy or surgical planning, and possibly to visualize micrometastases.

    View details for DOI 10.1016/j.ijrobp.2006.05.045

    View details for Web of Science ID 000240699500024

    View details for PubMedID 16965993

  • Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking MEDICAL PHYSICS Thorndyke, B., Schreibmann, E., Koong, A., Xing, L. 2006; 33 (7): 2632-2641

    Abstract

    Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined "retrospective stacking" (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to 18FDG-PET images of a pancreatic and a liver patient. Comparisons were made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.

    View details for DOI 10.1118/1.2207367

    View details for Web of Science ID 000239173900035

    View details for PubMedID 16898467

  • Overview of image-guided radiation therapy MEDICAL DOSIMETRY Xing, L., Thorndyke, B., Schreibmann, E., Yang, Y., Li, T., Kim, G., Luxton, G., Koong, A. 2006; 31 (2): 91-112

    Abstract

    Radiation therapy has gone through a series of revolutions in the last few decades and it is now possible to produce highly conformal radiation dose distribution by using techniques such as intensity-modulated radiation therapy (IMRT). The improved dose conformity and steep dose gradients have necessitated enhanced patient localization and beam targeting techniques for radiotherapy treatments. Components affecting the reproducibility of target position during and between subsequent fractions of radiation therapy include the displacement of internal organs between fractions and internal organ motion within a fraction. Image-guided radiation therapy (IGRT) uses advanced imaging technology to better define the tumor target and is the key to reducing and ultimately eliminating the uncertainties. The purpose of this article is to summarize recent advancements in IGRT and discussed various practical issues related to the implementation of the new imaging techniques available to radiation oncology community. We introduce various new IGRT concepts and approaches, and hope to provide the reader with a comprehensive understanding of the emerging clinical IGRT technologies. Some important research topics will also be addressed.

    View details for DOI 10.1016/j.meddos.2005.12.004

    View details for Web of Science ID 000237818000002

    View details for PubMedID 16690451

  • Model-based image reconstruction for four-dimensional PET MEDICAL PHYSICS Li, T., Thorndyke, B., Schreibmann, E., Yang, Y., Xing, L. 2006; 33 (5): 1288-1298

    Abstract

    Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case.

    View details for DOI 10.1118/1.2192581

    View details for Web of Science ID 000237673600012

    View details for PubMedID 16752564

  • Image registration with auto-mapped control volumes MEDICAL PHYSICS Schreibmann, E., Xing, L. 2006; 33 (4): 1165-1179

    Abstract

    Many image registration algorithms rely on the use of homologous control points on the two input image sets to be registered. In reality, the interactive identification of the control points on both images is tedious, difficult, and often a source of error. We propose a two-step algorithm to automatically identify homologous regions that are used as a priori information during the image registration procedure. First, a number of small control volumes having distinct anatomical features are identified on the model image in a somewhat arbitrary fashion. Instead of attempting to find their correspondences in the reference image through user interaction, in the proposed method, each of the control regions is mapped to the corresponding part of the reference image by using an automated image registration algorithm. A normalized cross-correlation (NCC) function or mutual information was used as the auto-mapping metric and a limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) was employed to optimize the function to find the optimal mapping. For rigid registration, the transformation parameters of the system are obtained by averaging that derived from the individual control volumes. In our deformable calculation, the mapped control volumes are treated as the nodes or control points with known positions on the two images. If the number of control volumes is not enough to cover the whole image to be registered, additional nodes are placed on the model image and then located on the reference image in a manner similar to the conventional BSpline deformable calculation. For deformable registration, the established correspondence by the auto-mapped control volumes provides valuable guidance for the registration calculation and greatly reduces the dimensionality of the problem. The performance of the two-step registrations was applied to three rigid registration cases (two PET-CT registrations and a brain MRI-CT registration) and one deformable registration of inhale and exhale phases of a lung 4D CT. Algorithm convergence was confirmed by starting the registration calculations from a large number of initial transformation parameters. An accuracy of approximately 2 mm was achieved for both deformable and rigid registration. The proposed image registration method greatly reduces the complexity involved in the determination of homologous control points and allows us to minimize the subjectivity and uncertainty associated with the current manual interactive approach. Patient studies have indicated that the two-step registration technique is fast, reliable, and provides a valuable tool to facilitate both rigid and nonrigid image registrations.

    View details for DOI 10.1118/1.2184440

    View details for Web of Science ID 000237038300040

    View details for PubMedID 16696494

  • Combined integrin siRNA therapy and radiotherapy of breast cancer Cao, Q., Li, T., Cai, W., Zhang, X., Chen, K., Yang, Y., Xing, L., Chen, X. AMER ASSOC CANCER RESEARCH. 2006
  • Multiscale image registration MATHEMATICAL BIOSCIENCES AND ENGINEERING Paquin, D., Levy, D., Schreibmann, E., Xing, L. 2006; 3 (2): 389-418

    Abstract

    A multiscale image registration technique is presented for the registration of medical images that contain significant levels of noise. An overview of the medical image registration problem is presented, and various registration techniques are discussed. Experiments using mean squares, normalized correlation, and mutual information optimal linear registration are presented that determine the noise levels at which registration using these techniques fails. Further experiments in which classical denoising algorithms are applied prior to registration are presented, and it is shown that registration fails in this case for significantly high levels of noise, as well. The hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [20] is presented, and accurate registration of noisy images is achieved by obtaining a hierarchical multiscale decomposition of the images and registering the resulting components. This approach enables successful registration of images that contain noise levels well beyond the level at which ordinary optimal linear registration fails. Image registration experiments demonstrate the accuracy and efficiency of the multiscale registration technique, and for all noise levels, the multiscale technique is as accurate as or more accurate than ordinary registration techniques.

    View details for Web of Science ID 000235978000008

    View details for PubMedID 20361831

  • Image interpolation in 4D CT using a BSpline deformable registration model INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Schreibmann, E., Chen, G. T., Xing, L. 2006; 64 (5): 1537-1550

    Abstract

    To develop a method for deriving the phase-binned four-dimensional computed tomography (4D CT) image sets through interpolation of the images acquired at some known phases.Four-dimensional computed tomography data sets for 3 patients were acquired. For each patient, the correlation between inhale and exhale phases was studied and quantified using a BSpline deformable model. Images at an arbitrary phase were deduced by an interpolation of the deformation coefficients. The accuracy of the proposed scheme was assessed by comparing marker trajectories and by checkerboard/difference display of the interpolated and acquired images.The images at intermediate phases could be derived by an interpolation of the deformation field. An analysis of marker movements indicated that 3 mm accuracy is achievable by the interpolation. The subtraction of image analysis indicated a similar level of success. The proposed technique was useful also for automatically mapping the organ contours in a known phase to other phases, and for designing patient-specific margins in the presence of respiratory motion. Finally, the technique led to a 90% reduction in the acquired data, because in the BSpline model, a lattice of only a few thousand values is sufficient to describe a CT data set of 25 million pixels.Organ deformation can be well modeled by using a BSpline model. The proposed technique may offer useful means for radiation dose reduction, binning artifacts removal, and disk storage improvement in 4D imaging.

    View details for DOI 10.1016/j.ijrobp.2005.11.018

    View details for Web of Science ID 000236477200032

    View details for PubMedID 16503382

  • F-18-labeled bombesin analogs for targeting GRP receptor-expressing prostate cancer JOURNAL OF NUCLEAR MEDICINE Zhang, X., Cai, W., Cao, F., Schreibmann, E., Wu, Y., Wu, J. C., Xing, L., Chen, X. 2006; 47 (3): 492-501

    Abstract

    The gastrin-releasing peptide receptor (GRPR) is found to be overexpressed in a variety of human tumors. The aim of this study was to develop 18F-labeled bombesin analogs for PET of GRPR expression in prostate cancer xenograft models.[Lys3]Bombesin ([Lys3]BBN) and aminocaproic acid-bombesin(7-14) (Aca-BBN(7-14)) were labeled with 18F by coupling the Lys3 amino group and Aca amino group, respectively, with N-succinimidyl-4-18F-fluorobenzoate (18F-SFB) under slightly basic condition (pH 8.5). Receptor-binding affinity of FB-[Lys3]BBN and FB-Aca-BBN(7-14) was tested in PC-3 human prostate carcinoma cells. Internalization and efflux of both radiotracers were also evaluated. Tumor-targeting efficacy and in vivo kinetics of both radiotracers were examined in male athymic nude mice bearing subcutaneous PC-3 tumors by means of biodistribution and dynamic microPET imaging studies. 18F-FB-[Lys3]BBN was also tested for orthotopic PC-3 tumor delineation. Metabolic stability of 18F-FB-[Lys3]BBN was determined in mouse blood, urine, liver, kidney, and tumor homogenates at 1 h after injection.The typical decay-corrected radiochemical yield was about 30%-40% for both tracers, with a total reaction time of 150 +/- 20 min starting from 18F-. 18F-FB-[Lys3]BBN had moderate stability in the blood and PC-3 tumor, whereas it was degraded rapidly in the liver, kidneys, and urine. Both radiotracers exhibited rapid blood clearance. 18F-FB-[Lys3]BBN had predominant renal excretion. 18F-FB-Aca-BBN(7-14) exhibited both hepatobiliary and renal clearance. Dynamic microPET imaging studies revealed that the PC-3 tumor uptake of 18F-FB-[Lys3]BBN in PC-3 tumor was much higher than that of 18F-FB-Aca-BBN(7-14) at all time points examined (P < 0.01). The receptor specificity of 18F-FB-[Lys3]BBN in vivo was demonstrated by effective blocking of tumor uptake in the presence of [Tyr4]BBN. No obvious blockade was found in PC-3 tumor when 18F-FB-Aca-BBN(7-14) was used as radiotracer under the same condition. 18F-FB-[Lys3]BBN was also able to visualize orthotopic PC-3 tumor at early time points after tracer administration, at which time minimal urinary bladder activity was present to interfere with the receptor-mediated tumor uptake.This study demonstrates that 18F-FB-[Lys3]BBN and PET are suitable for detecting GRPR-positive prostate cancer in vivo.

    View details for Web of Science ID 000249695800020

    View details for PubMedID 16513619

  • Motion correction for improved target localization with on-board cone-beam computed tomography PHYSICS IN MEDICINE AND BIOLOGY Li, T., Schreibmann, E., Yang, Y., Xing, L. 2006; 51 (2): 253-267

    Abstract

    On-board imager (OBI) based cone-beam computed tomography (CBCT) has become available in radiotherapy clinics to accurately identify the target in the treatment position. However, due to the relatively slow gantry rotation (typically about 60 s for a full 360 degrees scan) in acquiring the CBCT projection data, the patient's respiratory motion causes serious problems such as blurring, doubling, streaking and distortion in the reconstructed images, which heavily degrade the image quality and the target localization. In this work, we present a motion compensation method for slow-rotating CBCT scans by incorporating into image reconstruction a patient-specific motion model, which is derived from previously obtained four-dimensional (4D) treatment planning CT images of the same patient via deformable registration. The registration of the 4D CT phases results in transformations representing a temporal sequence of three-dimensional (3D) deformation fields, or in other words, a 4D model of organ motion. The algorithm was developed heuristically in two-dimensional (2D) parallel-beam geometry and extended to 3D cone-beam geometry. By simulations with digital phantoms capable of translational motion and other complex motion, we demonstrated that the algorithm can reduce the motion artefacts locally, and restore the tumour size and shape, which may thereby improve the accuracy of target localization and patient positioning when CBCT is used as the treatment guidance.

    View details for DOI 10.1088/0031-9155/51/2/005

    View details for Web of Science ID 000235041000005

    View details for PubMedID 16394337

  • Multistage image registration (figures featured in the cover of the issue of the journal) Mathematical Biosciences and Engineering Paquin D, Levy D, Schreibmann E., Xing L 2006; 3 (1): 389-418
  • Radiation dose reduction in four-dimensional computed tomography MEDICAL PHYSICS Li, T., Schreibmann, E., Thorndyke, B., Tillman, G., Boyer, A., Koong, A., Goodman, K., Xing, L. 2005; 32 (12): 3650-3660

    Abstract

    Four-dimensional (4D) CT is useful in many clinical situations, where detailed abdominal and thoracic imaging is needed over the course of the respiratory cycle. However, it usually delivers a larger radiation dose than the standard three-dimensional (3D) CT, since multiple scans at each couch position are required in order to provide the temporal information. Our purpose in this work is to develop a method to perform 4D CT scans at relatively low current, hence reducing the radiation exposure of the patients. To deal with the increased statistical noise caused by the low current, we proposed a novel 4D penalized weighted least square (4D-PWLS) smoothing method, which can incorporate both spatial and phase information. The 4D images at different phases were registered to the same phase via a deformable model, thereby, a regularization term combining temporal and spatial neighbors can be designed for the 4D-PWLS objective function. The proposed method was tested with phantom experiments and a patient study, and superior noise suppression and resolution preservation were observed. A quantitative evaluation of the benefit of the proposed method to 4D radiotherapy and 4D PET/CT imaging are under investigation.

    View details for DOI 10.1118/1.2122567

    View details for Web of Science ID 000234643700016

    View details for PubMedID 16475764

  • Optimization of radiotherapy dose-time fractionation with consideration of tumor specific biology MEDICAL PHYSICS Yang, Y., Xing, L. 2005; 32 (12): 3666-3677

    Abstract

    The "four Rs" of radiobiology play an important role in the design of radiation therapy treatment protocol. The purpose of this work is to explore their influence on external beam radiotherapy for fast and slowly proliferating tumors and develop an optimization framework for tumor-biology specific dose-time-fractionation scheme. The linear quadratic model is used to describe radiation response of tumor, in which the time dependence of sublethal damage repair and the redistribution and reoxygenation effects are included. The optimum radiotherapeutic strategy is defined as the treatment scheme that maximizes tumor biologically effective dose (BED) while keeping normal tissue BED constant. The influence of different model parameters on total dose, overall treatment time, fraction size, and intervals is also studied. The results showed that, for fast proliferating tumors, the optimum overall time is similar to the assumed kickoff time T(k) and almost independent of interval patterns. Significant increase in tumor control can be achieved using accelerated schemes for the tumors with doubling time smaller than 3 days, but little is gained for those with doubling time greater than 5 days. The incomplete repair of normal tissues between two consecutive fractions in standard fractionation has almost no influence on the fractional doses, even for the hyperfractionation with an interval time of 8 h. However, when the resensitization effect is included, the fractional doses at the beginning and end of each irradiated week become obviously higher than others in the optimum scheme and the hyperfractionation scheme has little advantage over the standard or hypofractionation one. For slowly proliferating tumors, provided that the alpha/beta ratio of the tumor is comparable to that of the normal tissues, a hypofractionation is more favorable. The overall treatment time should be larger than a minimum, which is predominantly determined by the resensitization time. The proposed technique provides a useful tool to systematically optimize radiotherapy for fast and slow proliferating tumors and sheds important insight into the complex problem of dose-time fractionation.

    View details for DOI 10.1118/1.2126167

    View details for Web of Science ID 000234643700018

    View details for PubMedID 16475766

  • Dose-volume based ranking of incident beam direction and its utility in facilitating IMRT beam placement INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Schreibmann, E., Xing, L. 2005; 63 (2): 584-593

    Abstract

    Beam orientation optimization in intensity-modulated radiation therapy (IMRT) is computationally intensive, and various single beam ranking techniques have been proposed to reduce the search space. Up to this point, none of the existing ranking techniques considers the clinically important dose-volume effects of the involved structures, which may lead to clinically irrelevant angular ranking. The purpose of this work is to develop a clinically sensible angular ranking model with incorporation of dose-volume effects and to show its utility for IMRT beam placement.The general consideration in constructing this angular ranking function is that a beamlet/beam is preferable if it can deliver a higher dose to the target without exceeding the tolerance of the sensitive structures located on the path of the beamlet/beam. In the previously proposed dose-based approach, the beamlets are treated independently and, to compute the maximally deliverable dose to the target volume, the intensity of each beamlet is pushed to its maximum intensity without considering the values of other beamlets. When volumetric structures are involved, the complication arises from the fact that there are numerous dose distributions corresponding to the same dose-volume tolerance. In this situation, the beamlets are not independent and an optimization algorithm is required to find the intensity profile that delivers the maximum target dose while satisfying the volumetric constraints. In this study, the behavior of a volumetric organ was modeled by using the equivalent uniform dose (EUD). A constrained sequential quadratic programming algorithm (CFSQP) was used to find the beam profile that delivers the maximum dose to the target volume without violating the EUD constraint or constraints. To assess the utility of the proposed technique, we planned a head-and-neck and abdominal case with and without the guidance of the angular ranking information. The qualities of the two types of IMRT plans were compared quantitatively.An effective angular ranking model with consideration of volumetric effect has been developed. It is shown that the previously reported dose-based angular ranking represents a special case of the general formalism proposed here. Application of the technique to a abdominal and a head-and-neck IMRT case indicated that the proposed technique is capable of producing clinically sensible angular ranking. In both cases, we found that the IMRT plans obtained under the guidance of EUD-based angular ranking were improved in comparison with that obtained using the conventional uniformly spaced beams.The EUD-based function is a general approach for angular ranking and allows us to identify the potentially good and bad angles for clinically complicated cases. The ranking can be used either as a guidance to facilitate the manual beam placement or as prior information to speed up the computer search for the optimal beam configuration. Thus the proposed technique should have positive clinical impact in facilitating the IMRT planning process.

    View details for DOI 10.1016/j.ijrobp.2005.06.008

    View details for Web of Science ID 000232083700033

    View details for PubMedID 16168850

  • Towards biologically conformal radiation therapy (BCRT): Selective IMRT dose escalation under the guidance of spatial biology distribution MEDICAL PHYSICS Yang, Y., Xing, L. 2005; 32 (6): 1473-1484

    Abstract

    It is well known that the spatial biology distribution (e.g., clonogen density, radiosensitivity, tumor proliferation rate, functional importance) in most tumors and sensitive structures is heterogeneous. Recent progress in biological imaging is making the mapping of this distribution increasingly possible. The purpose of this work is to establish a theoretical framework to quantitatively incorporate the spatial biology data into intensity modulated radiation therapy (IMRT) inverse planning. In order to implement this, we first derive a general formula for determining the desired dose to each tumor voxel for a known biology distribution of the tumor based on a linear-quadratic model. The desired target dose distribution is then used as the prescription for inverse planning. An objective function with the voxel-dependent prescription is constructed with incorporation of the nonuniform dose prescription. The functional unit density distribution in a sensitive structure is also considered phenomenologically when constructing the objective function. Two cases with different hypothetical biology distributions are used to illustrate the new inverse planning formalism. For comparison, treatments with a few uniform dose prescriptions and a simultaneous integrated boost are also planned. The biological indices, tumor control probability (TCP) and normal tissue complication probability (NTCP), are calculated for both types of plans and the superiority of the proposed technique over the conventional dose escalation scheme is demonstrated. Our calculations revealed that it is technically feasible to produce deliberately nonuniform dose distributions with consideration of biological information. Compared with the conventional dose escalation schemes, the new technique is capable of generating biologically conformal IMRT plans that significantly improve the TCP while reducing or keeping the NTCPs at their current levels. Biologically conformal radiation therapy (BCRT) incorporates patient-specific biological information and provides an outstanding opportunity for us to truly individualize radiation treatment. The proposed formalism lays a technical foundation for BCRT and allows us to maximally exploit the technical capacity of IMRT to more intelligently escalate the radiation dose.

    View details for Web of Science ID 000229908600004

    View details for PubMedID 16013703

  • The value of PET/CT is being over-sold as a clinical tool in radiation oncology MEDICAL PHYSICS Xing, L., Wessels, B., Hendee, W. R. 2005; 32 (6): 1457-1459

    View details for DOI 10.1118/1.1924458

    View details for Web of Science ID 000229908600001

  • Narrow band deformable registration of prostate magnetic resonance imaging, magnetic resonance spectroscopic imaging, and computed tomography studies INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Schreibmann, E., Xing, L. 2005; 62 (2): 595-605

    Abstract

    Endorectal (ER) coil-based magnetic resonance imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) is often used to obtain anatomic and metabolic images of the prostate and to accurately identify and assess the intraprostatic lesions. Recent advancements in high-field (3 Tesla or above) MR techniques affords significantly enhanced signal-to-noise ratio and makes it possible to obtain high-quality MRI data. In reality, the use of rigid or inflatable endorectal probes deforms the shape of the prostate gland, and the images so obtained are not directly usable in radiation therapy planning. The purpose of this work is to apply a narrow band deformable registration model to faithfully map the acquired information from the ER-based MRI/MRSI onto treatment planning computed tomography (CT) images.A narrow band registration, which is a hybrid method combining the advantages of pixel-based and distance-based registration techniques, was used to directly register ER-based MRI/MRSI with CT. The normalized correlation between the two input images for registration was used as the metric, and the calculation was restricted to those points contained in the narrow bands around the user-delineated structures. The narrow band method is inherently efficient because of the use of a priori information of the meaningful contour data. The registration was performed in two steps. First, the two input images were grossly aligned using a rigid registration. The detailed mapping was then modeled by free form deformations based on B-spline. The limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS), which is known for its superior performance in dealing with high-dimensionality problems, was implemented to optimize the metric function. The convergence behavior of the algorithm was studied by self-registering an MR image with 100 randomly initiated relative positions. To evaluate the performance of the algorithm, an MR image was intentionally distorted, and an attempt was then made to register the distorted image with the original one. The ability of the algorithm to recover the original image was assessed using a checkerboard graph. The mapping of ER-based MRI onto treatment planning CT images was carried out for two clinical cases, and the performance of the registration was evaluated.A narrow band deformable image registration algorithm has been implemented for direct registration of ER-based prostate MRI/MRSI and CT studies. The convergence of the algorithm was confirmed by starting the registration experiment from more than 100 different initial conditions. It was shown that the technique can restore an MR image from intentionally introduced deformations with an accuracy of approximately 2 mm. Application of the technique to two clinical prostate MRI/CT registrations indicated that it is capable of producing clinically sensible mapping. The whole registration procedure for a complete three-dimensional study (containing 256 x 256 x 64 voxels) took less than 15 min on a standard personal computer, and the convergence was usually achieved in fewer than 100 iterations.A deformable image registration procedure suitable for mapping ER-based MRI data onto planning CT images was presented. Both hypothetical tests and patient studies have indicated that the registration is reliable and provides a valuable tool to integrate the ER-based MRI/MRSI information to guide prostate radiation therapy treatment.

    View details for DOI 10.1016/j.ijrobp.2005.02.001

    View details for Web of Science ID 000229082500038

    View details for PubMedID 15890605

  • Optical detection of tumors in vivo by visible light tissue oximetry TECHNOLOGY IN CANCER RESEARCH & TREATMENT Maxim, P. G., Carson, J. J., Benaron, D. A., Loo, B. W., Xing, L., Boyer, A. L., Friedland, S. 2005; 4 (3): 227-234

    Abstract

    Endoscopy is a standard procedure for identifying tumors in patients suspected of having gastrointestinal (G.I.) cancer. The early detection of G.I. neoplasms during endoscopy is currently made by a subjective visual inspection that relies to a high degree on the experience of the examiner. This process can be difficult and unreliable, as tumor lesions may be visually indistinguishable from benign inflammatory conditions and the surrounding mucosa. In this study, we evaluated the ability of local ischemia detection using visible light spectroscopy (VLS) to differentiate neoplastic from normal tissue based on capillary tissue oxygenation during endoscopy. Real-time data were collected (i) from human subjects (N = 34) monitored at various sites during endoscopy (enteric mucosa, malignant, and abnormal tissue such as polyps) and (ii) murine animal subjects with human tumor xenografts. Tissue oximetry in human subjects during endoscopy revealed a tissue oxygenation (StO2%, mean +/- SD) of 46 +/- 22% in tumors, which was significantly lower than for normal mucosal oxygenation (72 +/- 4%; P < or = 0.0001). No difference in tissue oxygenation was observed between normal and non-tumor abnormal tissues (P = N.S.). Similarly, VLS tissue oximetry for murine tumors revealed a mean local tumor oxygenation of 45% in LNCaP, 50% in M21, and 24% in SCCVII tumors, all significantly lower than normal muscle tissue (74%, P < 0.001). These results were further substantiated by positive controls, where a rapid real-time drop in tumor oxygenation was measured during local ischemia induced by clamping or epinephrine. We conclude that VLS tissue oximetry can distinguish neoplastic tissue from normal tissue with a high specificity (though a low sensitivity), potentially aiding the endoscopic detection of gastrointestinal tumors.

    View details for Web of Science ID 000229787600001

    View details for PubMedID 15896077

  • The value of PET/CT is being over-sold as a clinical tool in radiation oncology. For the proposition. Medical physics Xing, L. 2005; 32 (6): 1457-1458

    View details for PubMedID 16013699

  • In vivo prostate magnetic resonance spectroscopic imaging using two-dimensional J-resolved PRESS at 3 T MAGNETIC RESONANCE IN MEDICINE Kim, D. H., Margolis, D., Xing, L., Daniel, B., Spielman, D. 2005; 53 (5): 1177-1182

    Abstract

    In vivo magnetic resonance spectroscopic imaging of the prostate using single-voxel and multivoxel two-dimensional (2D) J-resolved sequences is investigated at a main magnetic field strength of 3 T. Citrate, an important metabolite often used to aid the detection of prostate cancer in magnetic resonance spectroscopic exams, can be reliably detected along with the other metabolites using this method. We show simulations and measurements of the citrate metabolite using 2D J-resolved spectroscopy to characterize the spectral pattern. Furthermore, using spiral readout gradients, the single-voxel 2D J-resolved method is extended to provide the spatial distribution information as well all within a reasonable scan time (17 min). Phantom and in vivo data are presented to illustrate the multivoxel 2D J-resolved spiral chemical shift imaging sequence.

    View details for DOI 10.1002/mrm.20452

    View details for Web of Science ID 000228796900026

    View details for PubMedID 15844143

  • Quantitation of the a priori dosimetric capabilities of spatial points in inverse planning and its significant implication in defining IMRT solution space 14th International Conference on the Use of Computers in Radiation Therapy Shou, Z., Yang, Y., Cotrutz, C., Levy, D., Xing, L. IOP PUBLISHING LTD. 2005: 1469–82

    Abstract

    In inverse planning, the likelihood for the points in a target or sensitive structure to meet their dosimetric goals is generally heterogeneous and represents the a priori knowledge of the system once the patient and beam configuration are chosen. Because of this intrinsic heterogeneity, in some extreme cases, a region in a target may never meet the prescribed dose without seriously deteriorating the doses in other areas. Conversely, the prescription in a region may be easily met without violating the tolerance of any sensitive structure. In this work, we introduce the concept of dosimetric capability to quantify the a priori information and develop a strategy to integrate the data into the inverse planning process. An iterative algorithm is implemented to numerically compute the capability distribution on a case specific basis. A method of incorporating the capability data into inverse planning is developed by heuristically modulating the importance of the individual voxels according to the a priori capability distribution. The formalism is applied to a few specific examples to illustrate the technical details of the new inverse planning technique. Our study indicates that the dosimetric capability is a useful concept to better understand the complex inverse planning problem and an effective use of the information allows us to construct a clinically more meaningful objective function to improve IMRT dose optimization techniques.

    View details for DOI 10.1088/0031-9155/50/7/010

    View details for Web of Science ID 000228918500010

    View details for PubMedID 15798337

  • Investigation of using a power function as a cost function in inverse planning optimization MEDICAL PHYSICS Xia, P., Yu, N. C., Xing, L., Sun, X. P., Verhey, L. J. 2005; 32 (4): 920-927

    Abstract

    The purpose of this paper is to investigate the use of a power function as a cost function in inverse planning optimization. The cost function for each structure is implemented as an exponential power function of the deviation between the resultant dose and prescribed or constrained dose. The total cost function for all structures is a summation of the cost function of every structure. When the exponents of all terms in the cost function are set to 2, the cost function becomes a classical quadratic cost function. An independent optimization module was developed and interfaced with a research treatment planning system from the University of North Carolina for dose calculation and display of results. Three clinical cases were tested for this study with various exponents set for tumor targets and sensitive structures. Treatment plans with these exponent settings were compared, using dose volume histograms. The results of our study demonstrated that using an exponent higher than 2 in the cost function for the target achieved better dose homogeneity than using an exponent of 2. An exponent higher than 2 for serial sensitive structures can effectively reduce the maximum dose. Varying the exponent from 2 to 4 resulted in the most effective changes in dose volume histograms while the change from 4 to 8 is less drastic, indicating a situation of saturation. In conclusion, using a power function with exponent greater than 2 as a cost function can effectively achieve homogeneous dose inside the target and/or minimize maximum dose to the critical structures.

    View details for DOI 10.1118/1.1872552

    View details for Web of Science ID 000228659700010

    View details for PubMedID 15895574

  • Measurement of ionizing radiation using carbon nanotube field effect transistor PHYSICS IN MEDICINE AND BIOLOGY Tang, X. W., Yang, Y., Kim, W., Wang, Q., Qi, P. F., Dai, H. J., Xing, L. 2005; 50 (3): N23-N31

    Abstract

    Single-walled carbon nanotubes (SWNTs) are a new class of highly promising nanomaterials for future nano-electronics. Here, we present an initial investigation of the feasibility of using SWNT field effect transistors (SWNT-FETs) formed on silicon-oxide substrates and suspended FETs for radiation dosimetry applications. Electrical measurements and atomic force microscopy (AFM) revealed the intactness of SWNT-FET devices after exposure to over 1 Gy of 6 MV therapeutic x-rays. The sensitivity of SWNT-FET devices to x-ray irradiation is elucidated by real-time dose monitoring experiments and accumulated dose reading based on threshold voltage shift. SWNT-FET devices exhibit sensitivities to x-rays that are at least comparable to or orders of magnitude higher than commercial MOSFET (metal-oxide semiconductor field effect transistor) dosimeters and could find applications as miniature dosimeters for microbeam profiling and implantation.

    View details for DOI 10.1088/0031-9155/50/3/N02

    View details for PubMedID 15773731

  • Clinical knowledge-based inverse treatment planning PHYSICS IN MEDICINE AND BIOLOGY Yang, Y., Xing, L. 2004; 49 (22): 5101-5117

    Abstract

    Clinical IMRT treatment plans are currently made using dose-based optimization algorithms, which do not consider the nonlinear dose-volume effects for tumours and normal structures. The choice of structure specific importance factors represents an additional degree of freedom of the system and makes rigorous optimization intractable. The purpose of this work is to circumvent the two problems by developing a biologically more sensible yet clinically practical inverse planning framework. To implement this, the dose-volume status of a structure was characterized by using the effective volume in the voxel domain. A new objective function was constructed with the incorporation of the volumetric information of the system so that the figure of merit of a given IMRT plan depends not only on the dose deviation from the desired distribution but also the dose-volume status of the involved organs. The conventional importance factor of an organ was written into a product of two components: (i) a generic importance that parametrizes the relative importance of the organs in the ideal situation when the goals for all the organs are met; (ii) a dose-dependent factor that quantifies our level of clinical/dosimetric satisfaction for a given plan. The generic importance can be determined a priori, and in most circumstances, does not need adjustment, whereas the second one, which is responsible for the intractable behaviour of the trade-off seen in conventional inverse planning, was determined automatically. An inverse planning module based on the proposed formalism was implemented and applied to a prostate case and a head-neck case. A comparison with the conventional inverse planning technique indicated that, for the same target dose coverage, the critical structure sparing was substantially improved for both cases. The incorporation of clinical knowledge allows us to obtain better IMRT plans and makes it possible to auto-select the importance factors, greatly facilitating the inverse planning process. The new formalism proposed also reveals the relationship between different inverse planning schemes and gives important insight into the problem of therapeutic plan optimization. In particular, we show that the EUD-based optimization is a special case of the general inverse planning formalism described in this paper.

    View details for DOI 10.1088/0031-9155/49/22/006

    View details for Web of Science ID 000225629200006

    View details for PubMedID 15609561

  • Mapping of the prostate in endorectal coil-based MRI/MRSI and CT: A deformable registration and validation study 45th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) Lian, J., Xing, L., Hunjan, S., Dumoulin, C., Levin, J., Lo, A., Watkins, R., Rohling, K., Giaquinto, R., Kim, D., Spielman, D., Daniel, B. AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS. 2004: 3087–94

    Abstract

    The endorectal coil is being increasingly used in magnetic resonance imaging (MRI) and MR spectroscopic imaging (MRSI) to obtain anatomic and metabolic images of the prostate with high signal-to-noise ratio (SNR). In practice, however, the use of endorectal probe inevitably distorts the prostate and other soft tissue organs, making the analysis and the use of the acquired image data in treatment planning difficult. The purpose of this work is to develop a deformable image registration algorithm to map the MRI/MRSI information obtained using an endorectal probe onto CT images and to verify the accuracy of the registration by phantom and patient studies. A mapping procedure involved using a thin plate spline (TPS) transformation was implemented to establish voxel-to-voxel correspondence between a reference image and a floating image with deformation. An elastic phantom with a number of implanted fiducial markers was designed for the validation of the quality of the registration. Radiographic images of the phantom were obtained before and after a series of intentionally introduced distortions. After mapping the distorted phantom to the original one, the displacements of the implanted markers were measured with respect to their ideal positions and the mean error was calculated. In patient studies, CT images of three prostate patients were acquired, followed by 3 Tesla (3 T) MR images with a rigid endorectal coil. Registration quality was estimated by the centroid position displacement and image coincidence index (CI). Phantom and patient studies show that TPS-based registration has achieved significantly higher accuracy than the previously reported method based on a rigid-body transformation and scaling. The technique should be useful to map the MR spectroscopic dataset acquired with ER probe onto the treatment planning CT dataset to guide radiotherapy planning.

    View details for DOI 10.1118/1.106292

    View details for Web of Science ID 000225372300019

    View details for PubMedID 15587662

  • Feasibility study of beam orientation class-solutions for prostate IMRT MEDICAL PHYSICS Schreibmann, E., Lei, X. 2004; 31 (10): 2863-2870

    Abstract

    IMRT is being increasingly used for treatment of prostate cancer. In practice, however, the beam orientations used for the treatments are still selected empirically, without any guideline. The purpose of this work was to investigate interpatient variation of the optimal beam configuration and to facilitate intensity modulated radiation therapy (IMRT) prostate treatment planning by proposing a set of beam orientation class-solutions for a range of numbers of incident beams. We used fifteen prostate cases to generate the beam orientation class-solutions. For each patient and a given number of incident beams, a multiobjective optimization engine was employed to provide optimal beam directions. For the fifteen cases considered, the gantry angle of any of the optimized plans were all distributed within a certain range The angular distributions of the optimal beams were analyzed and the most selected directions are identified as optimal directions. The optimal directions for all patients are averaged to obtain the class-solution. The class-solution gantry angles for prostate IMRT were found to be: three beams (0 degrees, 120 degrees, 240 degrees), five beams (35 degrees, 110 degrees, 180 degrees, 250 degrees, 325 degrees), six beams (0 degrees, 60 degrees, 120 degrees, 180 degrees, 240 degrees, 300 degrees), seven beams (25 degrees, 75 degrees, 130 degrees, 180 degrees, 230 degrees, 285 degrees, 335 degrees), eight beams (20 degrees, 70 degrees, 110 degrees, 150 degrees, 200 degrees, 250 degrees, 290 degrees, 340 degrees), and nine beams (20 degrees, 60 degrees, 100 degrees, 140 degrees, 180 degrees, 220 degrees, 260 degrees, 300 degrees, 340 degrees). The level of validity of the class-solutions was tested using an additional clinical prostate case by comparing with the individually optimized beam configurations. The difference between the plans obtained with class-solutions and patient-specific optimizations was found to be clinically insignificant.

    View details for DOI 10.1118/1.1797571

    View details for Web of Science ID 000224743200021

    View details for PubMedID 15543796

  • Inverse treatment planning with adaptively evolving voxel-dependent penalty scheme MEDICAL PHYSICS Yong, Y., Lei, X. 2004; 31 (10): 2839-2844

    Abstract

    In current inverse planning algorithms it is common to treat all voxels within a target or sensitive structure equally and use structure specific prescriptions and weighting factors as system parameters. In reality, the voxels within a structure are not identical in complying with their dosimetric goals and there exists strong intrastructural competition. Inverse planning objective function should not only balance the competing objectives of different structures but also that of the individual voxels in various structures. In this work we propose to model the intrastructural tradeoff through the modulation of voxel-dependent importance factors and deal with the challenging problem of how to obtain a sensible set of importance factors with a manageable amount of computing. Instead of letting the values of voxel-dependent importance to vary freely during the search process, an adaptive algorithm, in which the importance factors were tied to the local radiation doses through a heuristically constructed relation, was developed. It is shown that the approach is quite general and the EUD-based optimization is a special case of the proposed framework. The new planning tool was applied to study a hypothetical phantom case and a prostate case. Comparison of the results with that obtained using conventional inverse planning technique with structure specific importance factors indicated that the dose distributions from the conventional inverse planning are at best suboptimal and can be significantly improved with the help of the proposed nonuniform penalty scheme.

    View details for DOI 10.1118/1.1799311

    View details for Web of Science ID 000224743200017

    View details for PubMedID 15543792

  • Incorporating model parameter uncertainty into inverse treatment planning MEDICAL PHYSICS Lian, J., Xing, L. 2004; 31 (9): 2711-2720

    Abstract

    Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment.

    View details for DOI 10.1118/1.1785451

    View details for Web of Science ID 000224117400041

    View details for PubMedID 15487755

  • Quantitative measurement of MLC leaf displacements using an electronic portal image device 45th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology (ASTRO) Yang, Y., Xing, L. IOP PUBLISHING LTD. 2004: 1521–33

    Abstract

    The success of an IMRT treatment relies on the positioning accuracy of the MLC (multileaf collimator) leaves for both step-and-shoot and dynamic deliveries. In practice, however, there exists no effective and quantitative means for routine MLC QA and this has become one of the bottleneck problems in IMRT implementation. In this work we present an electronic portal image device (EPID) based method for fast and accurate measurement of MLC leaf positions at arbitrary locations within the 40 cm x 40 cm radiation field. The new technique utilizes the fact that the integral signal in a small region of interest (ROI) is a sensitive and reliable indicator of the leaf displacement. In this approach, the integral signal at a ROI was expressed as a weighted sum of the contributions from the displacements of the leaf above the point and the adjacent leaves. The weighting factors or linear coefficients of the system equations were determined by fitting the integral signal data for a group of pre-designed MLC leaf sequences to the known leaf displacements that were intentionally introduced during the creation of the leaf sequences. Once the calibration is done, the system can be used for routine MLC leaf positioning QA to detect possible leaf errors. A series of tests was carried out to examine the functionality and accuracy of the technique. Our results show that the proposed technique is potentially superior to the conventional edge-detecting approach in two aspects: (i) it deals with the problem in a systematic approach and allows us to take into account the influence of the adjacent MLC leaves effectively; and (ii) it may improve the signal-to-noise ratio and is thus capable of quantitatively measuring extremely small leaf positional displacements. Our results indicate that the technique can detect a leaf positional error as small as 0.1 mm at an arbitrary point within the field in the absence of EPID set-up error and 0.3 mm when the uncertainty is considered. Given its simplicity, efficiency and accuracy, we believe that the technique is ideally suitable for routine MLC leaf positioning QA.

    View details for DOI 10.1088/0031-9155/49/8/010

    View details for Web of Science ID 000221250800010

    View details for PubMedID 15152689

  • Multiobjective evolutionary optimization of the number of beams, their orientations and weights for intensity-modulated radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Schreibmann, E., Lahanas, M., Xing, L., Baltas, D. 2004; 49 (5): 747-770

    Abstract

    We propose a hybrid multiobjective (MO) evolutionary optimization algorithm (MOEA) for intensity-modulated radiotherapy inverse planning and apply it to optimize the number of incident beams, their orientations and intensity profiles. The algorithm produces a set of efficient solutions, which represent different clinical trade-offs and contains information such as variety of dose distributions and dose-volume histograms. No importance factors are required and solutions can be obtained in regions not accessible by conventional weighted sum approaches. The application of the algorithm using a test case, a prostate and a head and neck tumour case is shown. The results are compared with MO inverse planning using a gradient-based optimization algorithm.

    View details for DOI 10.1088/0031-9155/49/5/007

    View details for Web of Science ID 000220314800007

    View details for PubMedID 15070200

  • Quality assurance of magnetic resonance spectroscopic imaging-derived metabolic data 44th Annual Meeting of the American-Society-for-Therapeutic-Radiology-and-Oncology Hunjan, S., Adalsteinsson, E., Kim, D. H., Harsh, G. R., Boyer, A. L., Spielman, D., Xing, L. ELSEVIER SCIENCE INC. 2003: 1159–73

    Abstract

    Spatially resolved metabolite maps, as measured by magnetic resonance spectroscopic imaging (MRSI) methods, are being increasingly used to acquire metabolic information to guide therapy, with metabolite ratio maps perhaps providing the most diagnostic information. We present a quality assurance procedure for MRSI-derived metabolic data acquired ultimately for guiding conformal radiotherapy.An MRSI phantom filled with brain-mimicking solutions was custom-built with an insert holding eight vials containing calibration solutions of precisely varying metabolite concentrations that emulated increasing grade/density of brain tumor. Phantom metabolite ratios calculated from fully relaxed 1D, 2D, and 3D MRS data for each vial were compared with calibrated metabolite ratios acquired at 9.4 T. Additionally, 3D ratio maps were "discretized" to eight pseudoabnormality levels on a slice-by-slice basis and the accuracy of this procedure was verified.Regression analysis revealed expected linear relationships between experimental and calibration metabolite ratios with intercepts close to zero for the three acquisition modes. 1D MRS data agreed most with theoretical considerations (regression coefficient, b = 0.969; intercept 0.008). The 2D (b = 1.049; intercept -0.199) and 3D (correlation coefficient r(2) = 0.9978-0.7336 for five slices) MRSI indicated reduced MRS data quality in regions of degraded B(0) and B(1) homogeneity. Pseudoabnormality levels were found to be consistent with expectations within regions of adequate B(0) homogeneity.This simple phantom-based approach to generate baseline calibration curves for all MRS acquisition modes may be useful to identify temporal deviations from acceptable data quality in a routine clinical environment or for testing new MRS and MRSI acquisition software.

    View details for DOI 10.1016/S0630-3016(03)01564-5

    View details for Web of Science ID 000186293800031

    View details for PubMedID 14575849

  • Independent dosimetric calculation with inclusion of head scatter and MLC transmission for IMRT MEDICAL PHYSICS Yang, Y., Xing, L., Li, J. G., Palta, J., Chen, Y., Luxton, G., Boyer, A. 2003; 30 (11): 2937-2947

    Abstract

    Independent verification of the MU settings and dose calculation of IMRT treatment plans is an important step in the IMRT quality assurance (QA) procedure. At present, the verification is mainly based on experimental measurements, which are time consuming and labor intensive. Although a few simplified algorithms have recently been proposed for the independent dose (or MU) calculation, head scatter has not been precisely taken into account in all these investigations and the dose validation has mainly been limited to the central axis. In this work we developed an effective computer algorithm for IMRT MU and dose validation. The technique is superior to the currently available computer-based MU check systems in that (1) it takes full consideration of the head scatter and leaf transmission effects; and (2) it allows a precise dose calculation at an arbitrary spatial point instead of merely a point on the central axis. In the algorithm the dose at an arbitrary spatial point is expressed as a summation of the contributions of primary and scatter radiation from all beamlets. Each beamlet is modulated by a dynamic modulation factor (DMF), which is determined by the MLC leaf trajectories, the head scatter, the jaw positions, and the MLC leaf transmission. A three-source model was used to calculate the head scatter distribution for irregular segments shaped by MLC and the scatter dose contributions were computed using a modified Clarkson method. The system reads in MLC leaf sequence files (or RTP files) generated by the Corvus (NOMOS Corporation, Sewickley, PA) inverse planning system and then computes the doses at the desired points. The algorithm was applied to study the dose distributions of several testing intensity modulated fields and two multifield Corvus plans and the results were compared with Corvus plans and experimental measurements. The final dose calculations at most spatial points agreed with the experimental measurements to within 3% for both the specially designed testing fields and the clinical intensity modulated field. Furthermore, excellent agreement (mostly within +/- 3.0%) was also found between our independent calculation and the ion chamber measurements at both central axis and off-axis positions for the multifield Corvus IMRT plans. These results indicate that the approach is robust and valuable for routine clinical IMRT plan validation.

    View details for DOI 10.1118/1.1617391

    View details for Web of Science ID 000186596900011

    View details for PubMedID 14655941

  • Segment-based dose optimization using a genetic algorithm PHYSICS IN MEDICINE AND BIOLOGY Cotrutz, C., Xing, L. 2003; 48 (18): 2987-2998

    Abstract

    Intensity modulated radiation therapy (IMRT) inverse planning is conventionally done in two steps. Firstly, the intensity maps of the treatment beams are optimized using a dose optimization algorithm. Each of them is then decomposed into a number of segments using a leaf-sequencing algorithm for delivery. An alternative approach is to pre-assign a fixed number of field apertures and optimize directly the shapes and weights of the apertures. While the latter approach has the advantage of eliminating the leaf-sequencing step, the optimization of aperture shapes is less straightforward than that of beamlet-based optimization because of the complex dependence of the dose on the field shapes, and their weights. In this work we report a genetic algorithm for segment-based optimization. Different from a gradient iterative approach or simulated annealing, the algorithm finds the optimum solution from a population of candidate plans. In this technique, each solution is encoded using three chromosomes: one for the position of the left-bank leaves of each segment, the second for the position of the right-bank and the third for the weights of the segments defined by the first two chromosomes. The convergence towards the optimum is realized by crossover and mutation operators that ensure proper exchange of information between the three chromosomes of all the solutions in the population. The algorithm is applied to a phantom and a prostate case and the results are compared with those obtained using beamlet-based optimization. The main conclusion drawn from this study is that the genetic optimization of segment shapes and weights can produce highly conformal dose distribution. In addition, our study also confirms previous findings that fewer segments are generally needed to generate plans that are comparable with the plans obtained using beamlet-based optimization. Thus the technique may have useful applications in facilitating IMRT treatment planning.

    View details for Web of Science ID 000185973500003

    View details for PubMedID 14529206

  • Therapeutic treatment plan optimization with probability density-based dose prescription MEDICAL PHYSICS Lian, J., Cotrutz, C., Xing, L. 2003; 30 (4): 655-666

    Abstract

    The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process.

    View details for DOI 10.1118/1.1561622

    View details for Web of Science ID 000182284300020

    View details for PubMedID 12722818

  • IMRT dose shaping with regionally variable penalty scheme MEDICAL PHYSICS Cotrutz, C., Xing, L. 2003; 30 (4): 544-551

    Abstract

    A commonly known deficiency of currently available inverse planning systems is the difficulty in fine-tuning the final dose distribution. In practice, it is not uncommon that just a few unsatisfactory regions in the planning target volume or an organ at risk prevent an intensity modulated radiation therapy (IMRT) plan from being clinically acceptable. The purpose of this work is to introduce a mechanism for controlling the regional doses after a conventional IMRT plan is obtained and to demonstrate its clinical utility. Two types of importance factors are introduced in the objective function to model the tradeoffs of different clinical objectives. The first is the conventional structure-dependent importance factor, which quantifies the interstructure tradeoff. The second type is the voxel-dependent importance factor which "modulates" the importance of different voxels within a structure. The planning proceeds in two major steps. First a conventional inverse planning is performed, where the structure-dependent importance factors are determined in a trial-and-error fashion. The next level of planning involves fine-tuning the regional doses to meet specific clinical requirements. To achieve this, the voxels where doses need to be modified are identified either graphically on the isodose layouts, or on the corresponding dose-volume histogram (DVH) curves. The importance value of these voxels is then adjusted to increase/decrease the penalty at the corresponding regions. The technique is applied to two clinical cases. It was found that both tumor hot spots and critical structure maximal doses can be easily controlled by varying the regional penalty. One to three trials were sufficient for the conventionally optimized dose distributions to be adjusted to meet clinical expectation. Thus introducing the voxel-dependent penalty scheme provides an effective means for IMRT dose distributions painting and sculpting.

    View details for DOI 10.1118/1.1556610

    View details for Web of Science ID 000182284300008

    View details for PubMedID 12722806

  • Incorporating leaf transmission and head scatter corrections into step-and-shoot leaf sequences for IMRT INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Yang, Y., Xing, L. 2003; 55 (4): 1121-1134

    Abstract

    Leaf transmission and head scatter are two important factors that influence intensity-modulated radiation therapy (IMRT) delivery and should be correctly taken into account when generating multileaf collimator (MLC) sequences. Significant discrepancies between the desired and delivered intensity profiles could otherwise result. The purpose of this article is to propose a reliable algorithm to minimize the dosimetric effects caused by the two factors in step-and-shoot mode.The goal of the algorithm is to minimize the difference between the desired fluence map and the fluence map actually delivered. For this purpose, an error function, defined as the least-square difference between the desired and the delivered fluence maps, is introduced. The effects of transmission and head scatter are minimized by adjusting the fractional monitor units (MUs) in the initial MLC sequences, created by using the desired fluence map without inclusion of the contributions from the two factors. Computationally, a downhill simplex optimization method is used to minimize the error function with respect to the fractional MUs. A three-source model is used to evaluate the relative head scatter distribution for each segment at the beginning of the calculation. The algorithm has been assessed by comparing the dose distributions delivered by the corrected leaf sequence files and the theoretic predication, calculated by Monte Carlo simulation using the desired fluence maps, for an intuitive test field and several clinical IMRT cases.The deviations between the desired fluence maps and those calculated using the corrected leaf sequence files are <0.3% of the maximum MU for the test field and <1.0% for the clinical IMRT cases. The experimental data show that both absolute and relative dose distributions delivered by the corrected leaf sequences agree with the desired ones within 2.5% of the maximum dose or 2 mm in high-dose gradient regions. Compared with the results obtained by using the leaf sequences in which only the transmission or none of the two effects is corrected, significant improvements in the fluence and dose distributions have been observed.Transmission and head scatter play important roles in the dosimetric behavior of IMRT delivery. A larger error may result if only one factor is considered because of the opposite effects of the two factors. We noted that the influence of the two effects is more pronounced in absolute dose than in the relative dose. The algorithm proposed in this work accurately corrects for these two effects in step-and-shoot delivery and provides a reliable tool for clinical IMRT application.

    View details for DOI 10.1016/S0360-3016(02)04417-6

    View details for Web of Science ID 000181269600031

    View details for PubMedID 12605992

  • Using the volumetric effect of a finite-sized detector for routine quality assurance of multileaf collimator leaf positioning MEDICAL PHYSICS Yang, Y., Xing, L. 2003; 30 (3): 433-441

    Abstract

    Intensity modulated radiation therapy (IMRT) is an advanced form of radiation therapy and promises to improve dose conformation while reducing the irradiation to the sensitive structures. The modality is, however, more complicated than conventional treatment and requires much more stringent quality assurance (QA) to ensure what has been planned can be achieved accurately. One of the main QA tasks is the assurance of positioning accuracy of multileaf collimator (MLC) leaves during IMRT delivery. Currently, the routine quality assurance of MLC in most clinics isbeing done using radiographic films with specially designed MLC leaf sequences. Besides being time consuming, the results of film measurements are difficult to quantify and interpret. In this work, we propose a new and effective technique for routine MLC leaf positioning QA. The technique utilizes the fact that, when a finite-sized detector is placed under a leaf, the relative output of the detector will depend on the relative fractional volume irradiated. A small error in leaf positioning would change the fractional volume irradiated and lead to a deviation of the relative output from the normal reading. For a given MLC and detector system, the relation between the relative output and the leaf displacement can be easily established through experimental measurements and used subsequently as a quantitative means for detecting possible leaf positional errors. The method was tested using a linear accelerator with an 80-leaf MLC. Three different locations, including two locations on central plane (X1 = X2 = 0) and one point on an off-central plane location (X1 = -7.5, X = 7.5), were studied. Our results indicated that the method could accurately detect a leaf positional change of approximately 0.1 mm. The method was also used to monitor the stability of MLC leaf positioning for five consecutive weeks. In this test, we intentionally introduced two positional errors in the testing MLC leaf sequences: -0.2 mm and 1.2 mm. The technique was found to be robust and could detect the positional inaccuracy in each week's test. The influence of other possible error sources, including the ion chamber placement, jaw settings, gantry and collimator angle read-outs, and the positioning errors of the adjacent leaves, on detection accuracy were also investigated. The principle of our method is independent of the types of the MLC and the detector and may have significant practical implications in facilitating routine MLC QA for IMRT delivery.

    View details for DOI 10.1118/1.1543150

    View details for Web of Science ID 000181587500019

    View details for PubMedID 12674244

  • Incorporating prior knowledge into beam orientation optimization in IMRT. International journal of radiation oncology, biology, physics Pugachev, A., Xing, L. 2002; 54 (5): 1565-1574

    Abstract

    Selection of beam configuration in currently available intensity-modulated radiotherapy (IMRT) treatment planning systems is still based on trial-and-error search. Computer beam orientation optimization has the potential to improve the situation, but its practical implementation is hindered by the excessive computing time associated with the calculation. The purpose of this work is to provide an effective means to speed up the beam orientation optimization by incorporating a priori geometric and dosimetric knowledge of the system and to demonstrate the utility of the new algorithm for beam placement in IMRT.Beam orientation optimization was performed in two steps. First, the quality of each possible beam orientation was evaluated using beam's-eye-view dosimetrics (BEVD) developed in our previous study. A simulated annealing algorithm was then employed to search for the optimal set of beam orientations, taking into account the BEVD scores of different incident beam directions. During the calculation, sampling of gantry angles was weighted according to the BEVD score computed before the optimization. A beam direction with a higher BEVD score had a higher probability of being included in the trial configuration, and vice versa. The inclusion of the BEVD weighting in the stochastic beam angle sampling process made it possible to avoid spending valuable computing time unnecessarily at "bad" beam angles. An iterative inverse treatment planning algorithm was used for beam intensity profile optimization during the optimization process. The BEVD-guided beam orientation optimization was applied to an IMRT treatment of paraspinal tumor. The advantage of the new optimization algorithm was demonstrated by comparing the calculation with the conventional scheme without the BEVD weighting in the beam sampling.The BEVD tool provided useful guidance for the selection of the potentially good directions for the beams to incident and was used to guide the search for the optimal beam configuration. The BEVD-guided sampling improved both optimization speed and convergence of the calculation. A comparison of several five-field IMRT treatment plans obtained with and without BEVD guidance indicated that the computational efficiency was increased by a factor of approximately 10.Incorporation of BEVD information allows for development of a more robust tool for beam orientation optimization in IMRT planning. It enables us to more effectively use the angular degree of freedom in IMRT without paying the excessive computing overhead and brings us one step closer to the goal of automated selection of beam orientations in a clinical environment.

    View details for PubMedID 12459386

  • Incorporating prior knowledge into beam orientaton optimization in IMRT INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Pugachev, A., Xing, L. 2002; 54 (5): 1565-1574

    Abstract

    Selection of beam configuration in currently available intensity-modulated radiotherapy (IMRT) treatment planning systems is still based on trial-and-error search. Computer beam orientation optimization has the potential to improve the situation, but its practical implementation is hindered by the excessive computing time associated with the calculation. The purpose of this work is to provide an effective means to speed up the beam orientation optimization by incorporating a priori geometric and dosimetric knowledge of the system and to demonstrate the utility of the new algorithm for beam placement in IMRT.Beam orientation optimization was performed in two steps. First, the quality of each possible beam orientation was evaluated using beam's-eye-view dosimetrics (BEVD) developed in our previous study. A simulated annealing algorithm was then employed to search for the optimal set of beam orientations, taking into account the BEVD scores of different incident beam directions. During the calculation, sampling of gantry angles was weighted according to the BEVD score computed before the optimization. A beam direction with a higher BEVD score had a higher probability of being included in the trial configuration, and vice versa. The inclusion of the BEVD weighting in the stochastic beam angle sampling process made it possible to avoid spending valuable computing time unnecessarily at "bad" beam angles. An iterative inverse treatment planning algorithm was used for beam intensity profile optimization during the optimization process. The BEVD-guided beam orientation optimization was applied to an IMRT treatment of paraspinal tumor. The advantage of the new optimization algorithm was demonstrated by comparing the calculation with the conventional scheme without the BEVD weighting in the beam sampling.The BEVD tool provided useful guidance for the selection of the potentially good directions for the beams to incident and was used to guide the search for the optimal beam configuration. The BEVD-guided sampling improved both optimization speed and convergence of the calculation. A comparison of several five-field IMRT treatment plans obtained with and without BEVD guidance indicated that the computational efficiency was increased by a factor of approximately 10.Incorporation of BEVD information allows for development of a more robust tool for beam orientation optimization in IMRT planning. It enables us to more effectively use the angular degree of freedom in IMRT without paying the excessive computing overhead and brings us one step closer to the goal of automated selection of beam orientations in a clinical environment.

    View details for Web of Science ID 000179566100039

  • Application of constrained least-squares techniques to IMRT treatment planning INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Crooks, S. M., Xing, L. 2002; 54 (4): 1217-1224

    Abstract

    The purpose of this work was to apply the method of constrained least-squares to inverse treatment planning and to explore its potential for providing a fast interactive planning environment for intensity-modulated radiation therapy (IMRT).The description of the dose inside a patient is a linear matrix transformation of beamlet weights. The constrained least-squares method adds additional matrix operators and produces beamlet weights by a direct linear transformation. These matrix operators contain a priori knowledge about the radiation distribution. The constrained least-squares technique was applied to obtain IMRT plans for prostate and paraspinal cancer patients and compared with the corresponding plans optimized using the CORVUS inverse planning system.It was demonstrated that a constrained least-squares technique is suitable for IMRT plan optimization with significantly increased computing speed. For the two cases we have tested, the constrained least-squares method was an order of magnitude faster than conventional iterative techniques because of the avoidance of the iterative calculations. We also found that the constrained least-squares method is capable of generating clinically acceptable treatment plans with less trial-and-error adjustments of system variables, and with improved target volume coverage as well as sensitive structure sparing in comparison with that obtained using CORVUS.The constrained least-squares method has the advantage that it does not require iterative calculation and thus significantly speeds up the therapeutic plan optimization process. Besides shedding important insight into the inverse planning problem, the technique has strong potential to provide a fast and interactive environment for IMRT treatment planning.

    View details for Web of Science ID 000179122400029

    View details for PubMedID 12419451

  • Inverse planning for functional image-guided intensity-modulated radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Xing, L., Cotrutz, C., Hunjan, S., Boyer, A. L., Adalsteinsson, E., Spielman, D. 2002; 47 (20): 3567-3578

    Abstract

    Radiation therapy is an image-guided process whose success critically depends on the imaging modality used for treatment planning and the level of integration of the available imaging information. In this work, we establish a dose optimization framework for incorporating metabolic information from functional imaging modalities into the intensity-modulated radiation therapy (IMRT) inverse planning process and to demonstrate the technical feasibility of planning deliberately non-uniform dose distributions in accordance with functional imaging data. For this purpose, a metabolic map from functional images is discretized into a number of abnormality levels (ALs) and then fused with CT images. To escalate dose to the metabolically abnormal regions, we assume, for a given spatial point, a linear relation between the AL and the prescribed dose. But the formalism developed here is independent of the assumption and any other relation between AL and prescription is applicable. For a given AL and prescription relation, it is only necessary to prescribe the dose to the lowest AL in the target and the desired doses to other regions with higher AL values are scaled accordingly. To accomplish differential sparing of a sensitive structure when its functional importance (FI) distribution is known, we individualize the tolerance doses of the voxels within the structure according to their Fl levels. An iterative inverse planning algorithm in voxel domain is used to optimize the system with in homogeneous dose prescription. To model intra-structural trade-off, a mechanism is introduced through the use of voxel-dependent weighting factors, in addition to the conventional structure specific weighting factors which model the inter-structural trade-off. The system is used to plan a phantom case with a few hypothetical functional distributions and a brain tumour treatment with incorporation of magnetic resonance spectroscopic imaging data. The results indicated that it is technically feasible to produce deliberately non-uniform dose distributions according to the functional imaging requirements. Integration of functional imaging information into radiation therapy dose optimization allows for consideration of patient-specific biologic information and provides a significant opportunity to truly individualize radiation treatment. This should enhance our capability to safely and intelligently escalate dose and lays the technical foundation for future clinical studies of the efficacy of functional imaging-guided IMRT.

    View details for Web of Science ID 000179171900003

    View details for PubMedID 12433120

  • Examination of the effect of increasing the number of radiation beams on a radiation treatment plan PHYSICS IN MEDICINE AND BIOLOGY Crooks, S. M., Pugachev, A., King, C., Xing, L. 2002; 47 (19): 3485-3501

    Abstract

    Within the confines of least-squares operations, it is possible to quantify the effect of the addition of treatment fields or beamlets to a treatment plan. Using linear algebra and eigenvalue perturbation theory, the effect of the increase in number of treatments is shown to be equivalent to adding a perturbation operator. The effect of adding additional fields will be negligible if the perturbation operator is small. The correspondence of this approach to an earlier work in beam-orientation optimization is also demonstrated. Results are presented for prostate, spinal and head and neck cases, and the connection to beam-orientation optimization is examined.

    View details for Web of Science ID 000178847300004

    View details for PubMedID 12408477

  • Minimizing delivery time and monitor units in static IMRT by leaf-sequencing PHYSICS IN MEDICINE AND BIOLOGY Crooks, S. M., McAven, L. F., Robinson, D. F., Xing, L. 2002; 47 (17): 3105-3116

    Abstract

    Intensity-modulated radiation therapy (IMRT) requires the determination of the appropriate multileaf collimator settings to deliver an intensity map. The purpose of this work was to attempt to reduce the number of segments required for IMRT delivery and the number of monitor units required to deliver an intensity map. An intensity map may be written as a matrix. Leaf sequencing was formulated as a problem of decomposing the matrix into a series of sub-matrices. Sets of random intensity matrices were created and the segmentations produced by applying different algorithms were compared. The number of segments, important if verification and record (VR) overhead is significant, and beam on times were examined. It is shown that reducing the value of the matrix entries by the maximum amount at each stage results in the smallest number of steps. Reducing the 2-norm (sum of the squares) of the matrix entries by the maximum amount at each step results in the smallest beam on time. Three new algorithms are introduced, two of which produce results that are superior to those generated by the algorithms of other researchers. The resulting methods can be expanded upon to include tongue and groove effects and leaf inter-digitization. With square random matrices of the order 15, the reduction in beam time and segmentation is up to 30-40%. Compared to previous algorithms, those presented here have demonstrated a reduction in the beam on time required to deliver an intensity map by 30-40%. Similarly, the number of segments needed to deliver an intensity map is also reduced.

    View details for Web of Science ID 000178231900005

    View details for PubMedID 12361213

  • A three-source model for the calculation of head scatter factors MEDICAL PHYSICS Yang, Y., Xing, L., Boyer, A. L., Song, Y. X., Hu, Y. M. 2002; 29 (9): 2024-2033

    Abstract

    Accurate determination of the head scatter factor Sc is an important issue, especially for intensity modulated radiation therapy, where the segmented fields are often very irregular and much less than the collimator jaw settings. In this work, we report an Sc calculation algorithm for symmetric, asymmetric, and irregular open fields shaped by the tertiary collimator (a multileaf collimator or blocks) at different source-to-chamber distance. The algorithm was based on a three-source model, in which the photon radiation to the point of calculation was treated as if it originated from three effective sources: one source for the primary photons from the target and two extra-focal photon sources for the scattered photons from the primary collimator and the flattening filter, respectively. The field mapping method proposed by Kim et al. [Phys. Med. Biol. 43, 1593-1604 (1998)] was extended to two extra-focal source planes and the scatter contributions were integrated over the projected areas (determined by the detector's eye view) in the three source planes considering the source intensity distributions. The algorithm was implemented using Microsoft Visual C/C++ in the MS Windows environment. The only input data required were head scatter factors for symmetric square fields, which are normally acquired during machine commissioning. A large number of different fields were used to evaluate the algorithm and the results were compared with measurements. We found that most of the calculated Sc's agreed with the measured values to within 0.4%. The algorithm can also be easily applied to deal with irregular fields shaped by a multileaf collimator that replaces the upper or lower collimator jaws.

    View details for DOI 10.1118/1.1500767

    View details for Web of Science ID 000178093000010

    View details for PubMedID 12349923

  • Independent monitor unit calculation for intensity modulated radiotherapy using the MIMIC multileaf collimator MEDICAL PHYSICS Chen, Z., Xing, L., Nath, R. 2002; 29 (9): 2041-2051

    Abstract

    A self-consistent monitor unit (MU) and isocenter point-dose calculation method has been developed that provides an independent verification of the MU for intensity modulated radiotherapy (IMRT) using the MIMiC (Nomos Corporation) multileaf collimator. The method takes into account two unique features of IMRT using the MIMiC: namely the gantry-dynamic arc delivery of intensity modulated photon beams and the slice-by-slice dose delivery for large tumor volumes. The method converts the nonuniform beam intensity planned at discrete gantry angles of 5 degrees or 10 degrees into conventional nonmodulated beam intensity apertures of elemental arc segments of 1 degree. This approach more closely simulates the actual gantry-dynamic arc delivery by MIMiC. Because each elemental arc segment is of uniform intensity, the MU calculation for an IMRT arc is made equivalent to a conventional arc with gantry-angle dependent beam apertures. The dose to the isocenter from each 1 degree elemental arc segment is calculated by using the Clarkson scatter summation technique based on measured tissue-maximum-ratio and output factors, independent of the dose calculation model used in the IMRT planning system. For treatments requiring multiple treatment slices, the MU for the arc at each treatment slice takes into account the MU, leakage and scatter doses from other slices. This is achieved by solving a set of coupled linear equations for the MUs of all involved treatment slices. All input dosimetry data for the independent MU/isocenter point-dose calculation are measured directly. Comparison of the MU and isocenter point dose calculated by the independent program to those calculated by the Corvus planning system and to direct measurements has shown good agreement with relative difference less than +/-3%. The program can be used as an independent initial MU verification for IMRT plans using the MIMiC multileaf collimators.

    View details for DOI 10.1118/1.1500397

    View details for Web of Science ID 000178093000012

    View details for PubMedID 12349925

  • Using voxel-dependent importance factors for interactive DVH-based dose optimization PHYSICS IN MEDICINE AND BIOLOGY Cotrutz, C., Xing, L. 2002; 47 (10): 1659-1669

    Abstract

    Intensity modulated radiation therapy (IMRT) inverse planning is usually performed by pre-selecting parameters such as beam modality, beam configuration and importance factors and then optimizing the fluence profiles or beamlet weights. In reality, the IMRT dose optimization problem may be ill-conditioned and there may not be a physical solution to account for the chosen parameters and constraints. Planner intervention is often required to conduct a multiple trial-and-error process where several parameters are sequentially varied until an acceptable compromise is achieved. The resulting solution reflects a balance between the conflicting requirements of the target and the sensitive structures. A major problem of the conventional inverse planning formalism is that there exists no effective mechanism for a planner to fine-tune the dose distribution on a local level or to differentially modify the dose-volume histograms (DVHs) of the involved structures. In this paper we introduce a new inverse planning scheme with voxel-dependent importance factors and demonstrate that it provides us with an effective link between the system parameters and the dosimetric behaviour at a local level. The planning proceeds in two steps. After a conventional trial-and-error inverse planning procedure is completed, we identify the dose interval at which the fractional volume on the DVH curve needs to be changed. The voxels that receive dose in the selected range are then located and their voxel-dependent importance factors are adjusted accordingly. The fine-tuning of the DVHs is iterative in nature and, using widely available computer graphic software tools, the process can be made graphically interactive. The new IMRT planning scheme is applied to two test cases and the results indicate that our control over the differential shapes of the DVHs of the involved structures is,greatly enhanced. Thus the technique may have significant practical implications in facilitating the IMRT treatment planning process.

    View details for Web of Science ID 000176029200004

    View details for PubMedID 12069085

  • Inverse planning for functional image-guided IMRT Physics in Medicine and Biology L. Xing, Cotrutz C, Hunjun S, Boyer AL, Adalsteinsson E, Spielman D 2002; 47: 3567-3578
  • Pseudo beam's-eye-view as applied to beam orientation selection in intensity-modulated radiation therapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Pugachev, A., Lei, X. 2001; 51 (5): 1361-1370

    Abstract

    To introduce the concept of pseudo beam's-eye-view (pBEV), to establish a framework for computer-assisted beam orientation selection in intensity-modulated radiation therapy (IMRT), and to evaluate the utility of the proposed technique.To facilitate the selection of beam orientations for IMRT treatment planning, a scoring of beam direction was introduced. The score function was based on the maximum target dose deliverable by the beam without exceeding the tolerance doses of the critical structures. For the score function calculation, the beam portal at given gantry and couch angles was divided into a grid of beamlets. Each beamlet crossing the target was assigned the maximum intensity that could be used without exceeding the dose tolerances of the organs at risk (OARs) and normal tissue. Thereafter, a score was assigned to the beam according to the target dose delivered. The beams for the treatment were selected among those with the highest scores. In a sense, this technique is similar to the beam's-eye-view approach used in conventional radiation therapy, except that the evaluation by a human is replaced by a score function, and beam modulation is taken into account.The pBEV technique was tested on two clinical cases: a paraspinal treatment and a nasopharyngeal cancer with both coplanar and noncoplanar beam configurations. The plans generated under the guidance of pBEV for the paraspinal treatment offered superior target dose uniformity and reduced OAR doses. For the nasopharyngeal cancer case, it was also found that the pBEV-selected coplanar and noncoplanar beams significantly improved the target coverage without compromising the sparing of the OARs.The pBEV technique developed in this work provides a comprehensive tool for beam orientation selection in IMRT. It is especially valuable for complicated cases, where the target is surrounded by several sensitive structures and where it is difficult to select a set of good beam orientations. The pBEV technique has considerable potential for simplifying the IMRT treatment planning process and for maximizing the technical capacity of IMRT.

    View details for Web of Science ID 000172495200024

    View details for PubMedID 11728698

  • Linear algebraic methods applied to intensity modulated radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Crooks, S. M., Xing, L. 2001; 46 (10): 2587-2606

    Abstract

    Methods of linear algebra are applied to the choice of beam weights for intensity modulated radiation therapy (IMRT). It is shown that the physical interpretation of the beam weights, target homogeneity and ratios of deposited energy can be given in terms of matrix equations and quadratic forms. The methodology of fitting using linear algebra as applied to IMRT is examined. Results are compared with IMRT plans that had been prepared using a commercially available IMRT treatment planning system and previously delivered to cancer patients.

    View details for Web of Science ID 000171866700006

    View details for PubMedID 11686277

  • Computer-assisted selection of coplanar beam orientations in intensity-modulated radiation therapy PHYSICS IN MEDICINE AND BIOLOGY Pugachev, A., Xing, L. 2001; 46 (9): 2467-2476

    Abstract

    In intensity-modulated radiation therapy (IMRT), the incident beam orientations are often determined by a trial and error search. The conventional beam's-eye view (BEV) tool becomes less helpful in IMRT because it is frequently required that beams go through organs at risk (OARs) in order to achieve a compromise between the dosimetric objectives of the planning target volume (PTV) and the OARs. In this paper, we report a beam's-eye view dosimetrics (BEVD) technique to assist in the selection of beam orientations in IMRT. In our method, each beam portal is divided into a grid of beamlets. A score function is introduced to measure the 'goodness' of each beamlet at a given gantry angle. The score is determined by the maximum PTV dose deliverable by the beamlet without exceeding the tolerance doses of the OARs and normal tissue located in the path of the beamlet. The overall score of the gantry angle is given by a sum of the scores of all beamlets. For a given patient. the score function is evaluated for each possible beam orientation. The directions with the highest scores are then selected as the candidates for beam placement. This procedure is similar to the BEV approach used in conventional radiation therapy, except that the evaluation by a human is replaced by a score function to take into account the intensity modulation. This technique allows one to select beam orientations without the excessive computing overhead of computer optimization of beam orientation. It also provides useful insight into the problem of selection of beam orientation and is especially valuable for complicated cases where the PTV is surrounded by several sensitive structures and where it is difficult to select a set of 'good' beam orientations. Several two-dimensional (2D) model cases were used to test the proposed technique. The plans obtained using the BEVD-selected beam orientations were compared with the plans obtained using equiangular spaced beams. For all the model cases investigated, the use of BEVD-selected beam orientations improved the dose distributions significantly. These examples indicate that the technique has considerable potential for simplifying the IMRT treatment planning process and allows for better utilization of the technical capacity of IMRT.

    View details for Web of Science ID 000171558300016

    View details for PubMedID 11580182

  • Role of beam orientation optimization in intensity-modulated radiation therapy INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS Pugachev, A., Li, J. G., Boyer, A. L., Hancock, S. L., Le, Q. T., Donaldson, S. S., Xing, L. 2001; 50 (2): 551-560

    Abstract

    To investigate the role of beam orientation optimization in intensity-modulated radiation therapy (IMRT) and to examine the potential benefits of noncoplanar intensity-modulated beams.A beam orientation optimization algorithm was implemented. For this purpose, system variables were divided into two groups: beam position (gantry and table angles) and beam profile (beamlet weights). Simulated annealing was used for beam orientation optimization and the simultaneous iterative inverse treatment planning algorithm (SIITP) for beam intensity profile optimization. Three clinical cases were studied: a localized prostate cancer, a nasopharyngeal cancer, and a paraspinal tumor. Nine fields were used for all treatments. For each case, 3 types of treatment plan optimization were performed: (1) beam intensity profiles were optimized for 9 equiangular spaced coplanar beams; (2) orientations and intensity profiles were optimized for 9 coplanar beams; (3) orientations and intensity profiles were optimized for 9 noncoplanar beams.For the localized prostate case, all 3 types of optimization described above resulted in dose distributions of a similar quality. For the nasopharynx case, optimized noncoplanar beams provided a significant gain in the gross tumor volume coverage. For the paraspinal case, orientation optimization using noncoplanar beams resulted in better kidney sparing and improved gross tumor volume coverage.The sensitivity of an IMRT treatment plan with respect to the selection of beam orientations varies from site to site. For some cases, the choice of beam orientations is important even when the number of beams is as large as 9. Noncoplanar beams provide an additional degree of freedom for IMRT treatment optimization and may allow for notable improvement in the quality of some complicated plans.

    View details for Web of Science ID 000168781000033

    View details for PubMedID 11380245

  • A dose-volume histogram based optimization algorithm for ultrasound guided prostate implants MEDICAL PHYSICS Chen, Y., Boyer, A. L., Xing, L. 2000; 27 (10): 2286-2292

    Abstract

    The task of treatment planning for prostate implants is to find an optimal seed configuration, comprising the target coverage and dosimetric consideration of critical structures such as the rectum and urethra. An efficient method to accomplish this is to use an inverse planning technique that derives the optimized solution from a prescribed treatment goal. The goal can be specified in the voxel domain as the desired doses to the voxels of the target and critical structures, or in the dose volume representation as the desired dose volume histograms (DVHs) of the target and critical structures. The DVH based optimization has been successfully used in plan optimization for intensity-modulated radiation therapy (IMRT) but little attention has been paid to its application in prostate implants. Clinically, it has long been known that some normal structure tolerances are more accurately assessed by volumetric information. Dose-volume histograms are also widely used for plan evaluation. When working in the DVH domain for optimization one has more control over the final DVHs. We have constructed an objective function sensitive to the DVHs of the target and critical structures. The objective function is minimized using an iterative algorithm, starting from a randomly selected initial seed configuration. At each iteration step, a trial position is given to a randomly selected source and the trial position is accepted if the objective function is decreased. To avoid being trapped in a less optimal local minimum, the optimization process is repeated. The final plan is selected from a pool of optimized plans obtained from a series of randomized initial seed configurations.

    View details for Web of Science ID 000090089500011

    View details for PubMedID 11099195

  • Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system PHYSICS IN MEDICINE AND BIOLOGY Ma, C. M., Pawlicki, T., Jiang, S. B., Li, J. S., Deng, J., Mok, E., Kapur, A., Xing, L., Ma, L., Boyer, A. L. 2000; 45 (9): 2483-2495

    Abstract

    The purpose of this work was to use Monte Carlo simulations to verify the accuracy of the dose distributions from a commercial treatment planning optimization system (Corvus, Nomos Corp., Sewickley, PA) for intensity-modulated radiotherapy (IMRT). A Monte Carlo treatment planning system has been implemented clinically to improve and verify the accuracy of radiotherapy dose calculations. Further modifications to the system were made to compute the dose in a patient for multiple fixed-gantry IMRT fields. The dose distributions in the experimental phantoms and in the patients were calculated and used to verify the optimized treatment plans generated by the Corvus system. The Monte Carlo calculated IMRT dose distributions agreed with the measurements to within 2% of the maximum dose for all the beam energies and field sizes for both the homogeneous and heterogeneous phantoms. The dose distributions predicted by the Corvus system, which employs a finite-size pencil beam (FSPB) algorithm, agreed with the Monte Carlo simulations and measurements to within 4% in a cylindrical water phantom with various hypothetical target shapes. Discrepancies of more than 5% (relative to the prescribed target dose) in the target region and over 20% in the critical structures were found in some IMRT patient calculations. The FSPB algorithm as implemented in the Corvus system is adequate for homogeneous phantoms (such as prostate) but may result in significant under or over-estimation of the dose in some cases involving heterogeneities such as the air-tissue, lung-tissue and tissue-bone interfaces.

    View details for Web of Science ID 000089438900007

    View details for PubMedID 11008950

  • Computer verification of fluence map for intensity modulated radiation therapy MEDICAL PHYSICS Xing, L., Li, J. G. 2000; 27 (9): 2084-2092

    Abstract

    In a treatment planning system for intensity modulated radiation therapy (IMRT), the time sequence of multileaf collimator (MLC) settings are derived from an optimal fluence map as a postoptimization process using a software module called a "leaf sequencer." The dosimetric accuracy of the dynamic delivery depends on the functionality of the module and it is important to verify independently the correctness of the leaf sequences for each field of a patient treatment. This verification is unique to the IMRT treatment and has been done using radiographic film, electronic portal imaging device (EPID) or electronic imaging system (BIS). The measurement tests both the leaf sequencer and the dynamic multileaf collimator (MLC) delivery system, providing a reliable assurance of clinical IMRT treatment. However, this process is labor intensive and time consuming. In this paper, we propose to separate quality assurance (QA) of the leaf sequencer from the dynamic MLC delivery system. We describe a simple computer algorithm for the verification of the leaf sequences. The software reads in the leaf sequences and simulates the motion of the MLC leaves. The generated fluence map is then compared quantitatively with the reference map from the treatment planning system. A set of pre-defined QA indices is introduced to measure the "closeness" between the computed and the reference maps. The approach has been used to validate the CORVUS (NOMOS Co., Sewickley, PA) treatment plans. The results indicate that the proposed approach is robust and suitable to support the complex IMRT QA process.

    View details for Web of Science ID 000089410200011

    View details for PubMedID 11011737

  • Dosimetric effects of patient displacement and collimator and gantry angle misalignment on intensity modulated radiation therapy RADIOTHERAPY AND ONCOLOGY Xing, L., Lin, Z. X., Donaldson, S. S., Le, Q. T., Tate, D., Goffinet, D. R., Wolden, S., Ma, L. J., Boyer, A. L. 2000; 56 (1): 97-108

    Abstract

    The primary goal of this study was to examine systematically the dosimetric effect of small patient movements and linear accelerator angular setting misalignments in the delivery of intensity modulated radiation therapy. We will also provide a method for estimating dosimetric errors for an arbitrary combination of these uncertainties.Sites in two patients (lumbar-vertebra and nasopharynx) were studied. Optimized intensity modulated radiation therapy treatment plans were computed for each patient using a commercially available inverse planning system (CORVUS, NOMOS Corporation, Sewickley, PA). The plans used nine coplanar beams. For each patient the dose distributions and relevant dosimetric quantities were calculated, including the maximum, minimum, and average doses in targets and sensitive structures. The corresponding dose volumetric information was recalculated by purposely varying the collimator angle or gantry angle of an incident beam while keeping other beams unchanged. Similar calculations were carried out by varying the couch indices in either horizontal or vertical directions. The intensity maps of all the beams were kept the same as those in the optimized plan. The change of a dosimetric quantity, Q, for a combination of collimator and gantry angle misalignments and patient displacements was estimated using Delta=Sigma(DeltaQ/Deltax(i))Deltax(i). Here DeltaQ is the variation of Q due to Deltax(i), which is the change of the i-th variable (collimator angle, gantry angle, or couch indices), and DeltaQ/Deltax(i) is a quantity equivalent to the partial derivative of the dosimetric quantity Q with respect to x(i).While the change in dosimetric quantities was case dependent, it was found that the results were much more sensitive to small changes in the couch indices than to changes in the accelerator angular setting. For instance, in the first example in the paper, a 3-mm movement of the couch in the anterior-posterior direction can cause a 38% decrease in the minimum target dose or a 41% increase in the maximum cord dose, whereas a 5 degrees change in the θ(1)=20 degrees beam only gave rise to a 1.5% decrease in the target minimum or 5.1% in the cord maximum. The effect of systematic positioning uncertainties of the machine settings was more serious than random uncertainties, which tended to smear out the errors in dose distributions.The dose distribution of an intensity modulated radiation therapy (IMRT) plan changes with patient displacement and angular misalignment in a complex way. A method was proposed to estimate dosimetric errors for an arbitrary combination of uncertainties in these quantities. While it is important to eliminate the angular misalignment, it was found that the couch indices (or patient positioning) played a much more important role. Accurate patient set-up and patient immobilization is crucial in order to take advantage fully of the technological advances of IMRT. In practice, a sensitivity check should be useful to foresee potential IMRT treatment complications and a warning should be given if the sensitivity exceeds an empirical value. Quality assurance action levels for a given plan can be established out of the sensitivity calculation.

    View details for Web of Science ID 000088159100013

    View details for PubMedID 10869760

  • Breast-conserving radiation therapy using combined electron and intensity-modulated radiotherapy technique RADIOTHERAPY AND ONCOLOGY Li, J. G., Williams, S. S., Goffinet, D. R., Boyer, A. L., Xing, L. 2000; 56 (1): 65-71

    Abstract

    To explore the feasibility of a multi-modality breast-conserving radiation therapy treatment technique to reduce high dose to the ipsilateral lung and the heart when compared with the conventional treatment technique using two tangential fields.An electron beam with appropriate energy was combined with four intensity modulated photon beams. The direction of the electron beam was chosen to be tilted 10-20 degrees laterally from the anteroposterior direction. Two of the intensity-modulated photon beams had the same gantry angles as the conventional tangential fields, whereas the other two beams were rotated 15-25 degrees toward the anteroposterior directions from the first two photon beams. An iterative algorithm was developed which optimizes the weight of the electron beam as well as the fluence profiles of the photon beams for a given patient. Two breast cancer patients with early-stage breast tumors were planned with the new technique and the results were compared with those from 3D planning using tangential fields as well as 9-field intensity-modulated radiotherapy (IMRT) techniques.The combined electron and IMRT plans showed better dose conformity to the target with significantly reduced dose to the ipsilateral lung and, in the case of the left-breast patient, reduced dose to the heart, than the tangential field plans. In both the right-sided and left-sided breast plans, the dose to other normal structures was similar to that from conventional plans and was much smaller than that from the 9-field IMRT plans. The optimized electron beam provided between 70 to 80% of the prescribed dose at the depth of maximum dose of the electron beam.The combined electron and IMRT technique showed improvement over the conventional treatment technique using tangential fields with reduced dose to the ipsilateral lung and the heart. The customized beam directions of the four IMRT fields also kept the dose to other critical structures to a minimum.

    View details for Web of Science ID 000088159100010

    View details for PubMedID 10869757

  • Inverse planning incorporating organ motion MEDICAL PHYSICS Li, J. G., Xing, L. 2000; 27 (7): 1573-1578

    Abstract

    Accurate targeting is important in intensity-modulated radiation therapy (IMRT). The positional uncertainties of structures with respect to the external beams arise in part from random organ motion and patient setup errors. While it is important to improve immobilization and reduce the influence of organ motion, the residual effects should be included in the IMRT plan design. Current inverse planning algorithms follow the conventional approach and include uncertainties by assuming population-based margins to the target and sensitive structures. Margin around a structure represents a "hard boundary" and the fact that a structure has a spatial probability distribution has been completely ignored. With increasing understanding of spatial uncertainties of structures and the technical capability of fine-tuning the dose distribution on an individual beamlet level in IMRT, it seems timely and important to fully utilize the information in the planning process. This will reduce the "effective" margins of the structures and facilitate dose escalation. Instead of specifying a "hard margin," we describe an inverse planning algorithm which takes into consideration positional uncertainty in terms of spatial probability distribution. The algorithm was demonstrated by assuming that the random organ motion can be represented by a three-dimensional Gaussian distribution function. Other probability distributions can be dealt with similarly. In particular, the commonly used "hard margin" is a special case of the current approach with a uniform probability distribution within a specified range. The algorithm was applied to plan treatment for a prostate case and a pancreatic case. The results were compared with those obtained by adding a margin to the clinical target volume. Better sparing of the sensitive structures were obtained in both cases using the proposed method for approximately the same target coverage.

    View details for Web of Science ID 000088372700010

    View details for PubMedID 10947260

  • Beam orientation optimization in intensity-modulated radiation treatment planning MEDICAL PHYSICS Pugachev, A. B., Boyer, A. L., Xing, L. 2000; 27 (6): 1238-1245

    Abstract

    Beam direction optimization is an important problem in radiation therapy. In intensity modulated radiation therapy (IMRT), the difficulty for computer optimization of the beam directions arises from the fact that they are coupled with the intensity profiles of the incident beams. In order to obtain the optimal incident beam directions using iterative or stochastic methods, the beam profiles ought to be optimized after every change of beam configuration. In this paper we report an effective algorithm to optimize gantry angles for IMRT. In our calculation the gantry angles and the beam profiles (beamlet weights) were treated as two separate groups of variables. The gantry angles were sampled according to a simulated annealing algorithm. For each sampled beam configuration, beam profile calculation was done using a fast filtered backprojection (FBP) method. Simulated annealing was also used for beam profile optimization to examine the performance of the FBP for beam orientation optimization. Relative importance factors were incorporated into the objective function to control the relative importance of the target and the sensitive structures. Minimization of the objective function resulted in the best possible beam orientations and beam profiles judged by the given objective function. The algorithm was applied to several model problems and the results showed that the approach has potential for IMRT applications.

    View details for Web of Science ID 000087765000005

    View details for PubMedID 10902552

  • Monitor unit calculation for an intensity modulated photon held by a simple scatter-summation algorithm PHYSICS IN MEDICINE AND BIOLOGY Xing, L., Chen, Y., Luxton, G., Li, J. G., Boyer, A. L. 2000; 45 (3): N1-N7

    Abstract

    An important issue in intensity modulated radiation therapy (IMRT) is the verification of the monitor unit (MU) calculation of the planning system using an independent procedure. Because of the intensity modulation and the dynamic nature of the delivery process, the problem becomes much more involved than that in conventional radiation therapy. In this work, a closed formula for MU calculation is derived. The approach is independent of the specific form of leaf sequence algorithms. It is straightforward to implement the procedure using a simple computer program. The approach is illustrated by a simplified example and is demonstrated by a few CORVUS (NOMOS Corporation, Sewickley, PA) treatment plans. The results indicate that it is robust and suitable for IMRT MU verification.

    View details for Web of Science ID 000085887000017

    View details for PubMedID 10730973

  • Clinical implementation of wedge filter optimization in three-dimensional radiotherapy treatment planning RADIOTHERAPY AND ONCOLOGY Li, J. G., Boyer, A. L., Xing, L. 1999; 53 (3): 257-264

    Abstract

    To describe a wedge filter optimization technique which automatically chooses the beam weights and wedge filters and to demonstrate the implementation of the algorithm in clinical three-dimensional (3D) radiotherapy treatment planning.Given the incident directions and beam energies of J beams, the dose distribution is a function of the beam weights, wedge angles, and wedge orientations. Instead of decomposing an incident field into a superposition of an open and two nominal wedged fields and then optimizing their weights, the algorithm optimizes the objective function with respect to the beam weights, wedge angles and wedge orientations directly. A salient feature of the algorithm is that no planner intervention was required in the selection of wedge filters during the optimization process. A dose-based objective function which incorporated the relative importance of structures was adopted in this work. The objective function was minimized by the method of simulated annealing. The technique was demonstrated by using a phantom study and two clinical cases.For the phantom case, the classical wedge pair result was obtained, providing a useful test of the algorithm. Dose distributions and dose volume histograms for the target and surrounding organs were presented for the two clinical cases. It was also shown that dose homogeneity to the target could be compromised by increasing the relative importance factors to the surrounding organs.A 3D wedge filter optimization algorithm has been developed. The technique has the potential to fully automate the 3D radiotherapy treatment planning process. In addition, treatment planning time and efforts were significantly reduced.

    View details for Web of Science ID 000084709600012

    View details for PubMedID 10660206

  • Estimation theory and model parameter selection for therapeutic treatment plan optimization MEDICAL PHYSICS Xing, L., Li, J. G., Pugachev, A., Le, Q. T., Boyer, A. L. 1999; 26 (11): 2348-2358

    Abstract

    Treatment optimization is usually formulated as an inverse problem, which starts with a prescribed dose distribution and obtains an optimized solution under the guidance of an objective function. The solution is a compromise between the conflicting requirements of the target and sensitive structures. In this paper, the treatment plan optimization is formulated as an estimation problem of a discrete and possibly nonconvex system. The concept of preference function is introduced. Instead of prescribing a dose to a structure (or a set of voxels), the approach prioritizes the doses with different preference levels and reduces the problem into selecting a solution with a suitable estimator. The preference function provides a foundation for statistical analysis of the system and allows us to apply various techniques developed in statistical analysis to plan optimization. It is shown that an optimization based on a quadratic objective function is a special case of the formalism. A general two-step method for using a computer to determine the values of the model parameters is proposed. The approach provides an efficient way to include prior knowledge into the optimization process. The method is illustrated using a simplified two-pixel system as well as two clinical cases. The generality of the approach, coupled with promising demonstrations, indicates that the method has broad implications for radiotherapy treatment plan optimization.