We develop quantitative imaging methods to characterize the tumor microenvironment, and to subsequently relate these imaging parameters to biomarkers that can be used for cancer surveillance, diagnosis and treatment monitoring/characterization. The focus is on 1) developing new acquisition methods and protocols to enhance quantification, 2) designing new image processing algorithms, analysis parameters and statistical models to quantitatively characterize imaging data, and 3) using advanced AI methods to further refine quantification or classification. While our methods can be used for other imaging modalities, we primarily focus on Ultrasound imaging modes such as contrast, molecular, elastography and spectroscopic ultrasound. Disease focus include liver cancer and liver metastasis, liver fibrosis/cirrhosis, and tumor blood flow characterization.
PhD, University of Toronto/Sunnybrook Research Institute, Medical Biophysics - Imaging Physics and Radiation Oncology (2014)
MSc, Ryerson University, Physics (2008)
BEng, Ryerson University, Electrical and Computer Engineering (2005)
Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response.
2020; 10 (1): 6996
There is a need for noninvasive repeatable biomarkers to detect early cancer treatment response and spare non-responders unnecessary morbidities and costs. Here, we introduce three-dimensional (3D) dynamic contrast enhanced ultrasound (DCE-US) perfusion map characterization as inexpensive, bedside and longitudinal indicator of tumor perfusion for prediction of vascular changes and therapy response. More specifically, we developed computational tools to generate perfusion maps in 3D of tumor blood flow, and identified repeatable quantitative features to use in machine-learning models to capture subtle multi-parametric perfusion properties, including heterogeneity. Models were developed and trained in mice data and tested in a separate mouse cohort, as well as early validation clinical data consisting of patients receiving therapy for liver metastases. Models had excellent (ROC-AUC > 0.9) prediction of response in pre-clinical data, as well as proof-of-concept clinical data. Significant correlations with histological assessments of tumor vasculature were noted (Spearman R > 0.70) in pre-clinical data. Our approach can identify responders based on early perfusion changes, using perfusion properties correlated to gold-standard vascular properties.
View details for DOI 10.1038/s41598-020-63810-1
View details for PubMedID 32332790
View details for PubMedCentralID PMC7181711
Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease.
2020; 10 (9): 4277–89
Nonalcoholic fatty liver disease is a major global health concern with increasing prevalence, associated with obesity and metabolic syndrome. Recently, quantitative ultrasound-based imaging techniques have dramatically improved the ability of ultrasound to detect and quantify hepatic steatosis. These newer ultrasound techniques possess many inherent advantages similar to conventional ultrasound such as universal availability, real-time capability, and relatively low cost along with quantitative rather than a qualitative assessment of liver fat. In addition, quantitative ultrasound-based imaging techniques are less operator dependent than traditional ultrasound. Here we review several different emerging quantitative ultrasound-based approaches used for detection and quantification of hepatic steatosis in patients at risk for nonalcoholic fatty liver disease. We also briefly summarize other clinically available imaging modalities for evaluating hepatic steatosis such as MRI, CT, and serum analysis.
View details for DOI 10.7150/thno.40249
View details for PubMedID 32226553
View details for PubMedCentralID PMC7086372
- Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease THERANOSTICS 2020; 10 (9): 4277–89
- A multi-model framework to estimate perfusion parameters using contrast-enhanced ultrasound imaging MEDICAL PHYSICS 2019; 46 (2): 590–600
Quantitative Ultrasound Spectroscopy for Differentiation of Hepatocellular Carcinoma from At-risk and Normal Liver Parenchyma.
Clinical cancer research : an official journal of the American Association for Cancer Research
Quantitative ultrasound approaches can capture tissue morphological properties to augment clinical diagnostics. This study aims to assess whether quantitative ultrasound spectroscopy (QUS) parameters measured in HCC tissues can be differentiated from those measured in at risk or healthy liver parenchyma.This prospective HIPAA-compliant study was approved by the IRB. Fifteen HCC patients, 15 non-HCC patients with chronic liver disease and 15 healthy volunteers were included (31.1% women; 68.9% men). Ultrasound radiofrequency (RF) data were acquired in each patient in both liver lobes at 2 focal depths. Region of interests (ROI) were drawn on HCC and liver parenchyma. The average normalized power spectrum for each ROI was extracted and a linear regression was fit within the -6dB bandwidth, from which the mid-band fit (MBF), spectral intercept (SI) and spectral slope (SS) were extracted. Differences in QUS parameters between the ROIs were tested by a mixed-effects regression.There was a significant intra-individual difference in MBF, SS and SI between HCC and adjacent liver parenchyma (P<0.001), and a significant inter-individual difference between HCC and at-risk and healthy non-HCC parenchyma (P<0.001). In HCC patients, cirrhosis (n=13) did not significantly change any of the three parameters (P>0.8) in differentiating HCC from non-HCC parenchyma. MBF (P=0.12), SI (P=0.33), and SS (P=0.57) were not significantly different in non-HCC tissue among the groups.The QUS parameters are significantly different in HCC vs. non-HCC liver parenchyma, independent of underlying cirrhosis. This could be leveraged for improved HCC detection with ultrasound in the future.
View details for DOI 10.1158/1078-0432.CCR-19-1030
View details for PubMedID 31444249
A Multi-Model Framework to Estimate Perfusion Parameters Using Contrast-Enhanced Ultrasound Imaging.
PURPOSE: Contrast-enhanced ultrasound imaging (CEUS) has expanded the diagnostic potential of ultrasound by enabling real-time imaging and quantification of tissue perfusion. Several perfusion models and curve fitting methods have been developed to quantify the temporal behavior of tracer signal and standardize perfusion quantification. While the least-squares approach has traditionally been applied for curve-fitting, it can be inadequate for noisy and complex data. Moreover, previous research suggests that certain perfusion models may be more relevant depending on the organ or tissue imaged. We propose a multi-model framework to select the most appropriate perfusion model and curve fitting method for each diagnostic application.METHODS: Our multi-model approach uses a system identification method, which estimates perfusion parameters from the model with the best fit to a given time-intensity curve (TIC). We compared current perfusion quantification methods that use a single perfusion model and curve fitting method and our proposed multi-model framework on bolus 3D dynamic contrast-enhanced ultrasound (DCE-US) in vivo images obtained in mice implanted with a colon cancer, as well as on simulation data. The quality of fit in estimating perfusion parameters was evaluated using the Spearman correlation coefficient, the coefficient of determination (R2 ), and the normalized root mean square error (NRMSE) to ensure that the multi-model framework finds the best perfusion model and curve fitting algorithm.RESULTS: Our multi-model framework outperforms conventional single perfusion model approaches with least squares optimization, providing more robust perfusion parameter estimation. R2 and NRMSE are 0.98 and 0.18 respectively for our proposed method. By comparison, the performance of the traditional approach is much more dependent upon the selection of the appropriate model. The R2 and NRMSE are 0.91 and 0.31, respectively.CONCLUSIONS: The proposed multi-model framework for perfusion-modeling outperforms the current approach of single perfusion modeling using least-squares optimization and more robustly estimates perfusion parameters when using empiric data labelled by an expert as the gold standard. Our technique is minimally sensitive to issues affecting the accuracy of perfusion parameter estimation, including rise time, noise, ROI size, and frame rate. This framework could be of key utility in modeling different perfusion systems in different tissues and organs. This article is protected by copyright. All rights reserved.
View details for PubMedID 30554408
Pharmacokinetic Modeling of Targeted Ultrasound Contrast Agents for Quantitative Assessment of Anti-Angiogenic Therapy: a Longitudinal Case-Control Study in Colon Cancer.
Molecular imaging and biology : MIB : the official publication of the Academy of Molecular Imaging
PURPOSE: To evaluate quantitative and semi-quantitative ultrasound molecular imaging (USMI) for antiangiogenic therapy monitoring in human colon cancer xenografts in mice.PROCEDURES: Colon cancer was established in 17 mice by injection of LS174T (Nr=9) or CT26 (Nn=8) cancer cells to simulate clinical responders and non-responders, respectively. Antiangiogenic treatment (bevacizumab; Nrt=Nnt=5) or control treatment (saline; Nrc=4, Nnc=3) was administered at days 0, 3, and 7. Three-dimensional USMI was performed by injection at days 0, 1, 3, 7, and 10 of microbubbles targeted to the vascular endothelial growth factor receptor 2 (VEGFR2). Microbubble binding rate (kb), estimated by first-pass binding model fitting, and semi-quantitative parameters late enhancement (LE) and differential targeted enhancement (dTE) were compared at each day to evaluate their ability to assess and predict the response to therapy. Correlation analysis with the ex-vivo immunohistological quantification of VEGFR2 expression and the percentage blood vessel area was also performed.RESULTS: Significant changes in the USMI parameters during treatment were observed only in the responders treated with bevacizumab (p-value <0.05). Prediction of the response to therapy as early as 1day after treatment was achieved by the quantitative parameter kb (p-value <0.01), earlier than possible by tumor volume quantification. USMI parameters could significantly distinguish between clinical responders and non-responders (p-value <<0.01) and correlated well with the ex-vivo quantification of VEGFR2 expression and the percentage blood vessels area (p-value <<0.01).CONCLUSION: USMI (semi)quantitative parameters provide earlier assessment of the response to therapy compared to tumor volume, permit early prediction of non-responders, and correlate well with ex-vivo angiogenesis biomarkers.
View details for DOI 10.1007/s11307-018-1274-z
View details for PubMedID 30225758
Role of Acid Sphingomyelinase and Ceramide in Mechano-Acoustic Enhancement of Tumor Radiation Responses
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE
2018; 110 (9): 1009–18
High-dose radiotherapy (>8-10 Gy) causes rapid endothelial cell death via acid sphingomyelinase (ASMase)-induced ceramide production, resulting in biologically significant enhancement of tumor responses. To further augment or solicit similar effects at low radiation doses, we used genetic and chemical approaches to evaluate mechano-acoustic activation of the ASMase-ceramide pathway by ultrasound-stimulated microbubbles (USMB).Experiments were carried out in wild-type and acid sphingomyelinase (asmase) knockout mice implanted with fibrosarcoma xenografts. A cohort of wild-type mice received the ASMase-ceramide pathway inhibitor sphingosine-1-phosphate (S1P). Mice were treated with varying radiation doses, with or without a priori USMB exposure at different microbubble concentrations. Treatment response was assessed with quantitative 3D Doppler ultrasound and immunohistochemistry at baseline, and at three, 24, and 72 hours after treatment, with three to five mice per treatment group at each time point. All statistical tests were two-sided.Results confirmed an interaction between USMB and ionizing radiation at 24 hours (P < .001), with a decrease in tumor perfusion of up to 46.5% by three hours following radiation and USMB. This peaked at 24 hours, persisting for up to 72 hours, and was accompanied by extensive tumor cell death. In contrast, statistically nonsignificant and minimal tumor responses were noted in S1P-treated and asmase knockout mice for all treatments.This work is the first to confirm the involvement of the ASMase-ceramide pathway in mechanotransductive vascular targeting using USMB. Results also confirm that an acute vascular effect is driving this form of enhanced radiation response, and that it can be elicited at low radiation doses (<8-10 Gy) by a priori USMB exposure.
View details for PubMedID 29506145
View details for PubMedCentralID PMC6136928
Tumour Vascular Shutdown and Cell Death Following Ultrasound-Microbubble Enhanced Radiation Therapy
2018; 8 (2): 314–27
High-dose radiotherapy effects are regulated by acute tumour endothelial cell death followed by rapid tumour cell death instead of canonical DNA break damage. Pre-treatment with ultrasound-stimulated microbubbles (USMB) has enabled higher-dose radiation effects with conventional radiation doses. This study aimed to confirm acute and longitudinal relationships between vascular shutdown and tumour cell death following radiation and USMB in a wild type murine fibrosarcoma model using in vivo imaging. Methods: Tumour xenografts were treated with single radiation doses of 2 or 8 Gy alone, or in combination with low-/high-concentration USMB. Vascular changes and tumour cell death were evaluated at 3, 24 and 72 h following therapy, using high-frequency 3D power Doppler and quantitative ultrasound spectroscopy (QUS) methods, respectively. Staining using in situ end labelling (ISEL) and cluster of differentiation 31 (CD31) of tumour sections were used to assess cell death and vascular distributions, respectively, as gold standard histological methods. Results: Results indicated a decrease in the power Doppler signal of up to 50%, and an increase of more than 5 dBr in cell-death linked QUS parameters at 24 h for tumours treated with combined USMB and radiotherapy. Power Doppler and quantitative ultrasound results were significantly correlated with CD31 and ISEL staining results (p < 0.05), respectively. Moreover, a relationship was found between ultrasound power Doppler and QUS results, as well as between micro-vascular densities (CD31) and the percentage of cell death (ISEL) (R2 0.5-0.9). Conclusions: This study demonstrated, for the first time, the link between acute vascular shutdown and acute tumour cell death using in vivo longitudinal imaging, contributing to the development of theoretical models that incorporate vascular effects in radiation therapy. Overall, this study paves the way for theranostic use of ultrasound in radiation oncology as a diagnostic modality to characterize vascular and tumour response effects simultaneously, as well as a therapeutic modality to complement radiation therapy.
View details for PubMedID 29290810
INTRA-INDIVIDUAL COMPARISON BETWEEN 2-D SHEAR WAVE ELASTOGRAPHY (GE SYSTEM) AND VIRTUAL TOUCH TISSUE QUANTIFICATION (SIEMENS SYSTEM) IN GRADING LIVER FIBROSIS
ULTRASOUND IN MEDICINE AND BIOLOGY
2017; 43 (12): 2774–82
Ultrasound-based shear wave elastography (SWE) has recently gained substantial attention for non-invasive assessment of liver fibrosis. The purpose of this study was to perform an intra-individual comparison between 2-D shear wave elastography (2-D-SWE with a GE system) and Virtual Touch Tissue Quantification (VTTQ with a Siemens system) to assess whether these can be used interchangeably to grade fibrosis. Ninety-three patients (51 men, 42 women; mean age, 54 y) with liver disease of various etiologies (hepatitis B virus = 47, hepatitis C virus = 22; alcohol = 6, non-alcoholic steatohepatitis = 5, other = 13) were included. Using published system-specific shear wave speed cutoff values, liver fibrosis was classified into clinically non-significant (F0/F1) and significant (≥F2) fibrosis. Results indicated that intra-modality repeatability was excellent for both techniques (GE 2-D-SWE: intra-class correlation coefficient = 0.89 [0.84-0.93]; VTTQ: intra-class correlation coefficient = 0.90 [0.86-0.93]). Intra-modality classification agreement for fibrosis grading was good to excellent (GE 2-D-SWE: κ = 0.65, VTTQ: κ = 0.82). However, inter-modality agreement for fibrosis grading was only fair (κ = 0.31) using published system-specific shear wave speed cutoff values of fibrosis. In conclusion, although both GE 2-D-SWE and Siemens VTTQ exhibit good to excellent intra-modality repeatability, inter-modality agreement is only fair, suggesting that these should not be used interchangeably.
View details for PubMedID 28967501
Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
2017; 20 (4): 547–55
Due to spatial tumor heterogeneity and consecutive sampling errors, it is critically important to assess treatment response following antiangiogenic therapy in three dimensions as two-dimensional assessment has been shown to substantially over- and underestimate treatment response. In this study, we evaluated whether three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) imaging allows assessing early changes in tumor perfusion following antiangiogenic treatment (bevacizumab administered at a dose of 10 mg/kg b.w.), and whether these changes could predict treatment response in colon cancer tumors that either are responsive (LS174T tumors) or none responsive (CT26) to the proposed treatment. Our results showed that the perfusion parameters of 3D DCE-US including peak enhancement (PE) and area under curve (AUC) significantly decreased by up to 69 and 77%, respectively, in LS174T tumors within 1 day after antiangiogenic treatment (P = 0.005), but not in CT26 tumors (P > 0.05). Similarly, the percentage area of neovasculature significantly decreased in treated versus control LS174T tumors (P < 0.001), but not in treated versus control CT26 tumors (P = 0.796). Early decrease in both PE and AUC by 45-50% was predictive of treatment response in 100% (95% CI 69.2, 100%) of responding tumors, and in 100% (95% CI 88.4, 100%) and 86.7% (95% CI 69.3, 96.2%), respectively, of nonresponding tumors. In conclusion, 3D DCE-US provides clinically relevant information on the variability of tumor response to antiangiogenic therapy and may be further developed as biomarker for predicting treatment outcomes.
View details for PubMedID 28721500
View details for PubMedCentralID PMC5660665
Molecular Contrast-Enhanced Ultrasound Imaging of Radiation-Induced P-Selectin Expression in Healthy Mice Colon.
International journal of radiation oncology, biology, physics
2017; 97 (3): 581-585
To evaluate the feasibility of using molecular contrast-enhanced ultrasound (mCEUS) to image radiation (XRT)-induced expression of cell adhesion molecules that mediate inflammatory response to XRT in healthy mouse colon tissue.The colons of male BALB/c mice (aged 6-8 weeks, n=9) were irradiated with 14 Gy using a Kimtron IC-225 x-ray irradiator operating at 225 kV/13.0 mA at a dose rate of 0.985 Gy/min. The head and thorax regions were shielded during irradiation. A second control cohort of mice was left untreated (n=6). Molecular CEUS was carried out before and 24 hours after irradiation using a VEVO2100 system and MS250 21-MHz center frequency transducer. Each imaging session comprised mCEUS imaging with P-selectin targeted microbubbles and control microbubbles targeted with an isotype control IgG. Quantification of mCEUS was carried out by measuring the differential targeted enhancement (dTE) parameter. The perfusion parameters peak enhancement and area under the curve were also extracted from the initial injection bolus. Animals were sacrificed at 24 hours and the colon was resected for immunohistochemistry analysis (P-selectin/CD31-stained vessel).For P-selectin targeted microbubble, a significant increase (40 a.u.; P=.013) in dTE (P-dTE) was observed in irradiated mice over 24 hours. In contrast, a nonsignificant change in P-selectin dTE was observed in control mice. For control microbubbles, no significant difference in the IgG dTE parameter was noted in treated and control animals over 24 hours. A nonsignificant increase in the peak enhancement and area under the curve perfusion parameters associated with blood volume was noted in animals treated with radiation. Quantitative histology indicated significantly elevated P-selectin expression per blood vessel (36% in treated; 14% in control).Our results confirm the feasibility of using mCEUS for imaging of XRT-induced expression of P-selectin as a potential approach to monitoring healthy tissue inflammatory damage during radiation therapy.
View details for DOI 10.1016/j.ijrobp.2016.10.037
View details for PubMedID 28126307
Ultrasound Elastography: Review of Techniques and Clinical Applications
2017; 7 (5): 1303-1329
Elastography-based imaging techniques have received substantial attention in recent years for non-invasive assessment of tissue mechanical properties. These techniques take advantage of changed soft tissue elasticity in various pathologies to yield qualitative and quantitative information that can be used for diagnostic purposes. Measurements are acquired in specialized imaging modes that can detect tissue stiffness in response to an applied mechanical force (compression or shear wave). Ultrasound-based methods are of particular interest due to its many inherent advantages, such as wide availability including at the bedside and relatively low cost. Several ultrasound elastography techniques using different excitation methods have been developed. In general, these can be classified into strain imaging methods that use internal or external compression stimuli, and shear wave imaging that use ultrasound-generated traveling shear wave stimuli. While ultrasound elastography has shown promising results for non-invasive assessment of liver fibrosis, new applications in breast, thyroid, prostate, kidney and lymph node imaging are emerging. Here, we review the basic principles, foundation physics, and limitations of ultrasound elastography and summarize its current clinical use and ongoing developments in various clinical applications.
View details for DOI 10.7150/thno.18650
View details for Web of Science ID 000396574200021
View details for PubMedID 28435467
Quantitative Three-Dimensional Dynamic Contrast-Enhanced Ultrasound Imaging: First-In-Human Pilot Study in Patients with Liver Metastases
2017; 7 (15): 3745–58
Purpose: To perform a clinical assessment of quantitative three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) feasibility and repeatability in patients with liver metastasis, and to evaluate the extent of quantitative perfusion parameter sampling errors in 2D compared to 3D DCE-US imaging. Materials and Methods: Twenty consecutive 3D DCE-US scans of liver metastases were performed in 11 patients (45% women; mean age, 54.5 years; range, 48-60 years; 55% men; mean age, 57.6 years; range, 47-68 years). Pairs of repeated disruption-replenishment and bolus DCE-US images were acquired to determine repeatability of parameters. Disruption-replenishment was carried out by infusing 0.9 mL of microbubbles (Definity; Latheus Medical Imaging) diluted in 35.1 mL of saline over 8 min. Bolus consisted of intravenous injection of 0.2 mL microbubbles. Volumes-of-interest (VOI) and regions-or-interest (ROI) were segmented by two different readers in images to extract 3D and 2D perfusion parameters, respectively. Disruption-replenishment parameters were: relative blood volume (rBV), relative blood flow (rBF). Bolus parameters included: time-to-peak (TP), peak enhancement (PE), area-under-the-curve (AUC), and mean-transit-time (MTT). Results: Clinical feasibility and repeatability of 3D DCE-US using both the destruction-replenishment and bolus technique was demonstrated. The repeatability of 3D measurements between pairs of repeated acquisitions was assessed with the concordance correlation coefficient (CCC), and found to be excellent for all parameters (CCC > 0.80), except for the TP (0.74) and MTT (0.30) parameters. The CCC between readers was found to be excellent (CCC > 0.80) for all parameters except for TP (0.71) and MTT (0.52). There was a large Coefficient of Variation (COV) in intra-tumor measurements for 2D parameters (0.18-0.52). Same-tumor measurements made in 3D were significantly different (P = 0.001) than measurements made in 2D; a percent difference of up to 86% was observed between measurements made in 2D compared to 3D in the same tumor. Conclusions: 3D DCE-US imaging of liver metastases with a matrix array transducer is feasible and repeatable in the clinic. Results support 3D instead of 2D DCE US imaging to minimize sampling errors due to tumor heterogeneity.
View details for PubMedID 29109773