Academic Appointments

All Publications

  • Characterization of 250 MeV Protons from the Varian ProBeam PBS System for FLASH Radiation Therapy INTERNATIONAL JOURNAL OF PARTICLE THERAPY Charyyev, S., Chang, C., Zhu, M., Lin, L., Langen, K., Dhabaan, A. 2023
  • An Integrated Physical Optimization Framework for Proton Stereotactic Body Radiation Therapy FLASH Treatment Planning Allows Dose, Dose Rate, and Linear Energy Transfer Optimization Using Patient-Specific Ridge Filters. International journal of radiation oncology, biology, physics Liu, R., Charyyev, S., Wahl, N., Liu, W., Kang, M., Zhou, J., Yang, X., Baltazar, F., Palkowitsch, M., Higgins, K., Dynan, W., Bradley, J., Lin, L. 2023


    Patient-specific ridge filters provide a passive means to modulate proton energy to obtain a conformal dose. Here we describe a new framework for optimization of filter design and spot maps to meet the unique demands of ultrahigh-dose-rate (FLASH) radiation therapy. We demonstrate an integrated physical optimization Intensity-modulated proton therapy (IMPT) (IPO-IMPT) approach for optimization of dose, dose-averaged dose rate (DADR), and dose-averaged linear energy transfer (LETd).We developed an inverse planning software to design patient-specific ridge filters that spread the Bragg peak from a fixed-energy, 250-MeV beam to a proximal beam-specific planning target volume. The software defines patient-specific ridge filter pin shapes and uses a Monte Carlo calculation engine, based on Geant4, to provide dose and LET influence matrices. Plan optimization, using matRAD, accommodates the IPO-IMPT objective function considering dose, dose rate, and LET simultaneously with minimum monitor unit constraints. The framework enables design of both regularly spaced and sparse-optimized ridge filters, from which some pins are omitted to allow faster delivery and selective LET optimization. To demonstrate the framework, we designed ridge filters for 3 example patients with lung cancer and optimized the plans using IPO-IMPT.The IPO-IMPT framework selectively spared the organs at risk by reducing LET and increasing dose rate, relative to IMPT planning. Sparse-optimized ridge filters were superior to regularly spaced ridge filters in dose rate. Depending on which parameter is prioritized, volume distributions and histograms for dose, DADR, and LETd, using evaluation structures specific to heart, lung, and esophagus, show high levels of FLASH dose-rate coverage and/or reduced LETd, while maintaining dose coverage within the beam specific planning target volume.This proof-of-concept study demonstrates the feasibility of using an IPO-IMPT framework to accomplish proton FLASH stereotactic body proton therapy, accounting for dose, DADR, and LETd simultaneously.

    View details for DOI 10.1016/j.ijrobp.2023.01.048

    View details for PubMedID 36736634

  • A component method to delineate surgical spine implants for proton Monte Carlo dose calculation JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Chang, C., Charyyev, S., Harms, J., Slopsema, R., Wolf, J., Refai, D., Yoon, T., McDonald, M. W., Bradley, J. D., Leng, S., Zhou, J., Yang, X., Lin, L. 2023; 24 (1): e13800


    Metallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images.The proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours.For in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm3 for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm3 , respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm3 for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt-chromium alloys by different vendors.A component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof-of-concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head-and-neck patients where tight margins are required to spare organs at risk.

    View details for DOI 10.1002/acm2.13800

    View details for Web of Science ID 000865288300001

    View details for PubMedID 36210177

    View details for PubMedCentralID PMC9859997

  • A potential revolution in cancer treatment: A topical review of FLASH radiotherapy JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Gao, Y., Liu, R., Chang, C., Charyyev, S., Zhou, J., Bradley, J. D., Liu, T., Yang, X. 2022; 23 (10): e13790


    FLASH radiotherapy (RT) is a novel technique in which the ultrahigh dose rate (UHDR) (≥40 Gy/s) is delivered to the entire treatment volume. Recent outcomes of in vivo studies show that the UHDR RT has the potential to spare normal tissue without sacrificing tumor control. There is a growing interest in the application of FLASH RT, and the ultrahigh dose irradiation delivery has been achieved by a few experimental and modified linear accelerators. The underlying mechanism of FLASH effect is yet to be fully understood, but the oxygen depletion in normal tissue providing extra protection during FLASH irradiation is a hypothesis that attracts most attention currently. Monte Carlo simulation is playing an important role in FLASH, enabling the understanding of its dosimetry calculations and hardware design. More advanced Monte Carlo simulation tools are under development to fulfill the challenge of reproducing the radiolysis and radiobiology processes in FLASH irradiation. FLASH RT may become one of standard treatment modalities for tumor treatment in the future. This paper presents the history and status of FLASH RT studies with a focus on FLASH irradiation delivery modalities, underlying mechanism of FLASH effect, in vivo and vitro experiments, and simulation studies. Existing challenges and prospects of this novel technique are discussed in this manuscript.

    View details for DOI 10.1002/acm2.13790

    View details for Web of Science ID 000860325600001

    View details for PubMedID 36168677

    View details for PubMedCentralID PMC9588273

  • A novel proton counting detector and method for the validation of tissue and implant material maps for Monte Carlo dose calculation PHYSICS IN MEDICINE AND BIOLOGY Charyyev, S., Chang, C., Harms, J., Oancea, C., Yoon, S., Yang, X., Zhang, T., Zhou, J., Lin, L. 2021; 66 (4): 045003


    The presence of artificial implants complicates the delivery of proton therapy due to inaccurate characterization of both the implant and the surrounding tissues. In this work, we describe a method to characterize implant and human tissue mimicking materials in terms of relative stopping power (RSP) using a novel proton counting detector. Each proton is tracked by directly measuring the deposited energy along the proton track using a fast, pixelated spectral detector AdvaPIX-TPX3 (TPX3). We considered three scenarios to characterize the RSPs. First, in-air measurements were made in the presence of metal rods (Al, Ti and CoCr) and bone. Then, measurements of energy perturbations in the presence of metal implants and bone in an anthropomorphic phantom were performed. Finally, sampling of cumulative stopping power (CSP) of the phantom were made at different locations of the anthropomorphic phantom. CSP and RSP information were extracted from energy spectra at each beam path. To quantify the RSP of metal rods we used the shift in the most probable energy (MPE) of CSP from the reference CSP without a rod. Overall, the RSPs were determined as 1.48, 2.06, 3.08, and 5.53 from in-air measurements; 1.44, 1.97, 2.98, and 5.44 from in-phantom measurements, for bone, Al, Ti and CoCr, respectively. Additionally, we sampled CSP for multiple paths of the anthropomorphic phantom ranging from 18.63 to 25.23 cm deriving RSP of soft tissues and bones in agreement within 1.6% of TOPAS simulations. Using minimum error of these multiple CSP, optimal mass densities were derived for soft tissue and bone and they are within 1% of vendor-provided nominal densities. The preliminary data obtained indicates the proposed novel method can be used for the validation of material and density maps, required by proton Monte Carlo Dose calculation, provided by competing multi-energy computed tomography and metal artifact reduction techniques.

    View details for DOI 10.1088/1361-6560/abd22e

    View details for Web of Science ID 000613663000001

    View details for PubMedID 33296888

  • Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy BRITISH JOURNAL OF RADIOLOGY Charyyev, S., Wang, T., Lei, Y., Ghavidel, B., Beitler, J. J., McDonald, M., Curran, W. J., Liu, T., Zhou, J., Yang, X. 2021; 95 (1129): 20210644


    Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT images and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 70 head-and-neck cancer patients whose DECT and SECT scans were acquired simultaneously. The model was trained to generate both a high and low energy DECT image based on a SECT image. The generated synthetic low and high DECT images were evaluated against the true DECT images using leave-one-out cross-validation. To evaluate our method in the context of a practical application, we generated SPR maps from synthetic DECT (sDECT) using a dual-energy based stoichiometric method and compared the SPR maps to those generated from DECT. A dosimetric comparison for dose obtained from DECT was performed against that derived from sDECT.The mean of mean absolute error, peak signal-to-noise ratio and normalized cross-correlation for the synthetic high and low energy CT images was 36.9 HU, 29.3 dB, 0.96 and 35.8 HU, 29.2 dB, and 0.96, respectively. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square deviation of about 1% with reduced noise level and artifacts than those from original DECT. Dose-volume histogram (DVH) metrics for the clinical target volume agree within 1% between the DECT and sDECT calculated dose.Our method synthesized accurate DECT images and showed a potential feasibility for proton SPR map generation.This study investigated a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.

    View details for DOI 10.1259/bjr.20210644

    View details for Web of Science ID 000731335200020

    View details for PubMedID 34709948

    View details for PubMedCentralID PMC8722254

  • Optimization of hexagonal-pattern minibeams for spatially fractionated radiotherapy using proton beam scanning MEDICAL PHYSICS Charyyev, S., Artz, M., Szalkowski, G., Chang Chih-Wei, Stanforth, A., Lin Liyong, Zhang Rongxiao, Wang, C. 2020; 47 (8): 3485-3495


    In this study, we investigated computationally and experimentally a hexagonal-pattern array of spatially fractionated proton minibeams produced by proton pencil beam scanning (PBS) technique. Spatial fractionation of dose delivery with millimeter or submillimeter beam size has proven to be a promising approach to significantly increase the normal tissue tolerance. Our goals are to obtain an optimized minibeam design and to show that it is feasible to implement the optimized minibeams at the existing proton clinics.An optimized minibeam arrangement is one that would produce high peak-to-valley dose ratios (PVDRs) in normal tissues and a PVDR approaching unity at the Bragg peak. Using Monte Carlo (MC) code TOPAS we simulated proton pencil beams that mimic those available at the existing proton therapy facilities and obtained a hexagonal-pattern array of minibeams by collimating the proton pencil beams through the 1-3 mm diameter pinholes of a collimator. We optimized the minibeam design by considering different combinations of parameters including collimator material and thickness (t), center-to-center (c-t-c) distance, and beam size. The optimized minibeam design was then evaluated for normal tissue sparing against the uniform pencil beam scanning (PBS) by calculating the therapeutic advantage (TA) in terms of cell survival fraction. Verification measurements using radiochromic films were performed at the Emory proton therapy center (EPTC).Optimized hexagonal-pattern minibeams having PVDRs of >10 at phantom surface and of >3 at depths up to 6 cm were achieved with 2 mm diameter modulated proton minibeams (with proton energies between 120 and 140 MeV) corresponding to a spread-out-Bragg-peak (SOBP) over the depth of 10-14 cm. The results of the film measurements agree with the MC results within 10%. The TA of the 2 mm minibeams against the uniform PBS is >3 from phantom surface to the depth of 5 cm and then smoothly drops to ~1.5 as it approaches the proximal edge of the SOBP. For 2 mm minibeams and 6 mm c-t-c distance, we delivered 1.72 Gy at SOBP for 7.2 × 7.2 × 4 cm3 volume in 48 s.We conclude that it is feasible to implement the optimized hexagonal-pattern 2 mm proton minibeam radiotherapy at the existing proton clinics, because desirable PVDRs and TAs are achievable and the treatment time is reasonable.

    View details for DOI 10.1002/mp.14192

    View details for Web of Science ID 000531381400001

    View details for PubMedID 32319098

  • High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study BIOMEDICAL PHYSICS & ENGINEERING EXPRESS Charyyev, S., Lei, Y., Harms, J., Eaton, B., McDonald, M., Curran, W. J., Liu, T., Zhou, J., Zhang, R., Yang, X. 2020; 6 (3): 035029


    Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-view at native gantry angles. However, PPI has poor inherent contrast and spatial resolution. To deal with this issue, we propose a deep-learning-based method to use kV digitally reconstructed radiographs (DRR) to improve PPI image quality. Method; We used a residual generative adversarial network (GAN) framework to learn the nonlinear mapping between PPIs and DRRs. Residual blocks were used to force the model to focus on the structural differences between DRR and PPI. To assess the accuracy of our method, we used 149 images for training and 30 images for testing. PPIs were acquired using a double-scattered proton beam. The DRRs acquired from CT acted as learning targets in the training process and were used to evaluate results from the proposed method using a six-fold cross-validation scheme. Results; Qualitatively, the corrected PPIs showed enhanced spatial resolution and captured fine details present in the DRRs that are missed in the PPIs. The quantitative results for corrected PPIs show average normalized mean error (NME), normalized mean absolute error (NMAE), peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) index of -0.1%, 0.3%, 39.14 dB, and 0.987, respectively. Conclusion; The results indicate the proposed method can generate high quality corrected PPIs and this work shows the potential to use a deep-learning model to make PPI available in proton radiotherapy. This will allow for beam's-eye-view (BEV) imaging with the particle used for treatment, leading to a valuable alternative to orthogonal x-rays or cone-beam CT for patient position verification.

    View details for DOI 10.1088/2057-1976/ab8a74

    View details for Web of Science ID 000530472700001

    View details for PubMedID 33438674



    New technique is trending in spatially fractionated radiotherapy with protons to utilize the spot scanning together with a physical collimator to obtain minibeams. The primary goal of this study is to quantify ambient neutron dose equivalent (${H}^{\ast }(10)$) due to the secondary neutrons when physical collimator is used to achieve desired minibeams. The ${H}^{\ast }(10)$ per treatment proton dose (D) was assessed using Monte Carlo code TOPAS and measured using WENDI-II detector at different angles (135, 180, 225 and 270 degrees) and distances (11 cm, 58 and 105 cm) from the phantom for two cases: with and without physical collimation. Without collimation $\frac{H^{\ast }(10)}{D}$ varied from 0.0013 to 0.242 mSv/Gy. With collimation $\frac{H^{\ast }(10)}{D}$ varied from 0.017 to 3.23 mSv/Gy. Results show that the secondary neutron dose will increase tenfold when the physical collimator is used. Regardless, it will be low and comparable to the neutron dose produced by conventional passive-scattered proton beams.

    View details for DOI 10.1093/rpd/ncaa030

    View details for Web of Science ID 000579855500007

    View details for PubMedID 32144416