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Keywords: quantitative imaging
MO-B-TRACK 6-1A Quantitative Analysis of Lung Elastography Performance Using Large-Deformation CT Scans Acquired at Residual Volume (RV) and Total Lung Capacity (TLC)
B Stiehl1*, M Lauria1, L Naumann1, K Singhrao1, I Barjaktarevic2, J Goldin2, M McNitt-Gray3, D Low1, A Santhanam1, (1) Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA, (2) Division of Pulmonary and Critical Care, University of California, Los Angeles, Los Angeles, CA, (3) Department of Radiology, University of California, Los Angeles, Los Angeles, CA
MO-B-TRACK 6-4Principal Component Analysis of Quantitative Computed Tomography Features and Visual Emphysema Scores: Association with Lung Function Decline
M Koo1*, W Tan2, J Hogg2, J Bourbeau3, C Hague2, J Leipsic2, and M Kirby1,2 for the CanCOLD Collaborative Research Group and The Canadian Respiratory Research Network, (1) Ryerson University, Toronto, ON, CA, (2) Centre For Heart Lung Innovation, St. Paul's Hospital, Vancouver, BC, CA, (3) McGill University Health Centre Research Institute, McGill University, Montreal, QC, CA
MO-B-TRACK 6-5Quantitative Relaxometry for Ultra-Hypofractionated MR-Guided Radiotherapy to the Prostate and DIL: A Feasibility Study
E Subashi*, E LoCastro, V Brennan, A Apte, M Zelefsky, N Tyagi, Memorial Sloan-Kettering Cancer Center, New York, NY
MO-B-TRACK 6-7Use of Short Duration Dynamic [18F]DCFPyL PET and CT Perfusion Imaging to Localize Dominant Intraprostatic Lesions in Prostate Cancer: Validation Against Digital Histopathology
D Yang1,2,3*, R Alfano4, G Bauman3,4, J Chin3,4, S Pautler3,4, K Chung2,3, A Ward4, T Lee2,3, (1) Fox Chase Cancer Center, Philadelphia, PA, (2) Robarts Research Institute, University of Western Ontario, London, ON, CA, (3) Lawson Imaging Research Program, Lawson Health Research Institute, London Health Science Centre, London, ON, CA, (4) London Regional Cancer Program, London Health Science Centre, London, ON, CA
MO-IePD-TRACK 4-1Evaluation of Cone-Beam Computed Tomography-Based Radiomic Features Reproducibility: A Phantom Study
T Adachi1,2*, M Nakamura1,2, H Iramina2, T Mizowaki2, (1) Division of Medical Physics, Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan, (2) Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
MO-IePD-TRACK 5-6Association Between Dosiomics-Based Index with Radiation Pneumonitis Induced by Radiation Therapy of Breast Cancers
Z Yang1, 2*, X Chen2, M Chen3, C Wang1, F Yin1, 2, (1) Duke University Medical Center, Durham, NC (2) Duke Kunshan University, Kunshan, Jiangsu, China (3) Kunshan First People Hospital, Kunshan, Jiangsu, China
PO-GePV-I-9Commissioning of Commercial Quantitative R2* Mapping Software for Clinical Use
B Taylor*, H Chen, H Liu, J Yung, P Hou, K Brock, RJ Stafford, Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX
PO-GePV-I-18CT Image Standardization for Radiomic Feature Enhancement in Non-Small Cell Lung Cancer
M Selim1*, J Chen2, B Fei3, G Zhang4, J Zhang5, (1) University Of Kentucky, ,,(2) University Of Kentucky, ,,(3) University of Texas (UT) at Dallas and UT Southwestern Medical Center, Richardson, TX, (4) Uthealth, ,,(5) University of Kentucky, Lexington, KY
PO-GePV-M-26A Multiple Modality Comparison of Radiomic Features for Prostate Cancer
R Delgadillo*, B Spieler, J Ford, D Kwon, F Yang, M Studenski, K Padgett, M Abramowitz, A Dal Pra, N Dogan, University of Miami, Miami, FL
PO-GePV-M-38What's Behind Auto-Segmentation Models: An Interpretability Analysis of Calculation Logic of Segmentation Model for Brain Tumor
H Chen1*, D Ban2, X Qi3, (1) Xi'an University of Posts and telecommunications, Xi'an, 61, CN, (2) Xi'an University of Posts and telecommunications, Xi'an, 61, CN, (3) UCLA School of Medicine, Los Angeles, CA
PO-GePV-M-40Radiomics Analysis Improves Machine Learning Models Assessing Chronic Obstructive Pulmonary Disease
R Au1*, K Makimoto1, W Tan2, J Bourbeau3, J Hogg2, M Kirby1, (1) Ryerson University, Toronto, ON, CA, (2) Centre For Heart Lung Innovation, University Of British Columbia, Vancouver, BC, CA, (3) McGill University, Montreal, QC, CA
PO-GePV-M-42A Machine Learning Classifier for Predicting Recurrence in Oropharyngeal Cancer
T Chinnery*, P Lang, A Nichols, S Mattonen, Western University, London, ON
PO-GePV-M-44Classification of Anatomic Structures by CT-Based Radiomics for Head-Neck Radiotherapy
Y Watanabe1*, N Gopishankar2, A Biswas2, K Rangarajan2, G Rath2, (1) University of Minnesota, Minneapolis, MN, (2) All India Institute Of Medical Sciences
PO-GePV-M-50Predicting Overall Survival of Patients with Glioma Via A Novel Framework Consisting of Two-Phase Feature Selection and Fused Regression Forest
H Chen1*, Y Liu2, X Qi3, (1) Xi'an University of Posts and telecommunications, Xi'an, 61, CN, (2) Xi'an University of Posts & Telecommunications, Xi'an, 61, CN, (3) UCLA School of Medicine, Los Angeles, CA
SU-C-TRACK 6-1A Robust Method to Quantitate Tracer Activity in Organs and Lesions with Clinical SPECT/CT Systems
J James*, J Bian, J Halama, Loyola University Medical Center, Maywood, IL
SU-C-TRACK 6-4Longitudinal PET/CT Imaging of 64Cu for Radiopharmaceutical Therapy Dosimetry
M Merrick*, L Dunnwald, A Tiwari, J Sunderland, S Graves, University Of Iowa, Iowa City, IA
SU-E-TRACK 6-1A Multi-Modality Radiomics-Based Model for Recurrence Risk Stratification in Non-Small Cell Lung Cancer
J Christie1*, O Daher1, M Abdelrazek1, P Lang1, V Nair2, S Mattonen1, (1) Western University, London, ON, CA, (2) University of Washington School of Medicine, Seattle, WA
SU-IePD-TRACK 1-2Liver Delineation Using the Weighted A-Star Pathfinding Algorithm and Deep Learning On Ultrasound B-Mode Images for Cirrhosis Assessment Using Liver Biopsy as the ‘Gold Standard’
I Gatos1, P Drazinos2, S Tsantis1, P Zoumpoulis2, I Theotokas2, D Mihailidis3, G Kagadis1*, (1) University of Patras, Rion, GR, (2) Diagnostic Echotomography SA ,Athens, GR, (3) University of Pennsylvania, Philadelphia, PA
SU-IePD-TRACK 1-3Quantitative Image Guidance In Vivo: Dual-Energy CT for Thermochemical Ablation
E Thompson*, M Jacobsen, R Layman, E Cressman, UT MD Anderson Cancer Center, Houston, TX
SU-IePD-TRACK 1-6Uniqueness of Radiomic Features in NSCLC: BeyondReproducibility/Repeatability
G Ge*, J Zhang, University of Kentucky, Lexington, KY
SU-IePD-TRACK 1-7Patient-Specific Deep Learning Model for Enhancing 4D-CBCT Image for Radiomic Analysis
Z Zhang*, M Huang, Z Jiang, Y Chang, K Lu, F Yin, L Ren, Duke University Medical Center, Durham, NC
SU-IePD-TRACK 1-7Investigation of Bias-Voltage Dependent Operational Characteristics of An Energy-Resolving Pixelated Cadmium Telluride Detector System Within An Experimental Benchtop X-Ray Fluorescence Imaging System
H Moktan*, R K Panta, S H Cho, UT MD Anderson Cancer Center, Houston, TX
SU-IePD-TRACK 2-6Development of Machine Learning Based Algorithm for Prediction of Invasiveness of Early-Lung Adenocarcinoma by Using Chest Computed Tomography
Juyoung Lee1,2*, Seong Yong Park, M.D., Ph.D.3, Jin Sung Kim, Ph.D.1, (1) Department of Radiation Oncology, Yonsei University College of Medicine, Seodaemun-gu, Seoul, KR, (2) Department of Integrative Medicine, Yonsei University College of Medicine, Seoul, KR, (3) Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, KR
TH-C-TRACK 3-5Novel Sampling Strategy for Improved Reproducibility in Quantitative T1rho Mapping
C Wu1*, Q Peng2, (1) Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA (2) Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA
TH-E-TRACK 3-1Characterization and Optimization of Quantitative Greyscale Images From Photon Counting CT
D Byrd1*, M Wu2, P Edic2, P Kinahan1, (1) University of Washington, Seattle, WA, (2) GE Research, Niskayuna NY
TH-IePD-TRACK 2-1Comparative Analysis of T2W Contrast for Clinical Prostate Protocols Using a Dedicated MR System Phantom
K Hwang*, J Yung, A Venkatesan, R Stafford, UT MD Anderson Cancer Center, Houston, TX
TH-IePD-TRACK 2-2Analysis of Diffusion and Microstructure Properties in Brain Tumors Using a Random Walk with Barriers Model
Y Li1*, M Kim2, T Lawrence3, T Feiweier4, Y Cao5, (1) University of Michigan, Ann Arbor, MI (2) University Of Michigan, Ann Arbor, MI (3) University of Michigan, Ann Arbor, MI (4) Siemens Healthineers (5) The University of Michigan, Ann Arbor, MI
TH-IePD-TRACK 2-4Obtaining New Contrasts From a Single T1-Weighted Image                                                
Y Wu1, Y Ma2, N Kovalchuk1, J Du2, L Xing1*, (1) Stanford University, Palo Alto, CA, (2) University of California San Diego, San Diego, CA
TH-IePD-TRACK 2-5Deep Learning Based T2* Mapping From MRI Images with Different Types of Weighting
Y Wu1, Y Ma2, N Kovalchuk1, J Du2, L Xing1*, (1) Stanford University, Palo Alto, CA, (2) University of California San Diego, San Diego, CA
TH-IePD-TRACK 2-6Quantitative Inter-Vendor Evaluation of PDFF and R2* Mapping Accuracy for 3T MRI Scanners
J Yu*, A Panda, Mayo Clinic, Arizona, Scottsdale, AZ
TH-IePD-TRACK 3-7Motion-Robust Free-Breathing Abdominal MR Fingerprinting (MRF) Using Radial Acquisition and Temporal Compressed Sensing Reconstruction: Initial Results
E Subashi1*, V Yu2, C Wu3, P Koken4, M Doneva5, R Otazo6, O Cohen7, (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) Memorial Sloan Kettering Cancer Center, New York, NY, (3) Memorial Sloan Kettering Cancer Center, New York, NY, (4) Philips Medical Systems,(5) Philips Medical Systems, (6) Memorial Sloan Kettering Cancer Center, New York, NY, (7) Memorial Sloan Kettering Cancer Center, New York, NY
TU-A-TRACK 2-7Single-Shot Quantitative X-Ray Imaging Using Primary Modulation and Dual-Layer Detector: A Simulation Study
L Shi*, N Bennett, A Wang, Stanford University, Stanford, CA
TU-B-TRACK 2-3Quantification of Tumor Location and Growth for Orthotopic Pancreatic Cancer Model Using Bioluminescence Tomography-Guided System
Z Deng1*, X Xu1, H Dehghani2, J Reyes3, J Wong3, P Tran3, K Wang1, (1) University of Texas Southwestern Medical Center, Dallas, TX, (2) University of Birmingham, Birmingham, UK, (3) Johns Hopkins University, Baltimore, MD
TU-D-TRACK 3-7Evaluation of Image-Domain Training Frameworks for Deep Learning Based Denoising and Deconvolution
P VanMeter1*, S Hsieh1, J Marsh1, N Huber1, A Ferrero1, C McCollough1, (1) Department of Radiology, Mayo Clinic, Rochester, MN
TU-D-TRACK 4-0The Anne and Donald Herbert Distinguished Lectureship in Modern Statistical Modeling
N Obuchowski1*, (1) Cleveland Clinic Foundation, Cleveland, OH
TU-E-TRACK 3-0Quantitative SPECT for Radionuclide and External Beam Treatment Planning
J Dickson1*, S Kappadath2*, S Kappadath3*, (1) University College London, London, UK,(2) UT MD Anderson Cancer Center, Houston, TX, (3) UT MD Anderson Cancer Center, Houston, TX
WE-IePD-TRACK 2-1High Spatial Resolution Simultaneous Quantitative T1rho and T2 Mapping at 3T
Q Peng1*, C Wu2, (1) Department of Radiology, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, USA, (2) Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
WE-IePD-TRACK 4-3Overall Survival Prediction Via An Interpretable Machine Learning Model for Patients with Oropharyngeal Cancer
X Pan1*, T Feng2, X Qi3, C Liu4, (1) Xi'an University of Posts and Telecommunications, Xi'an,shaanxi, ,CN, (2) Xi'an University of Posts and Telecommunications, Xi'an,shaanxi, ,CN (3) UCLA School of Medicine, Los Angeles, CA, (4) Xi'an University of Posts and Telecommunications, Xi'an,shaanxi, ,CN
WE-IePD-TRACK 4-6Ultrasound Histogram Assessment of Radiation-Induced Breast Toxicity in Breast Cancer Radiotherapy: A Longitudinal Study of Acute Toxicity
b zhou*, X Yang, J Lin, S Kahn, K Godette, M Torres, T Liu, Emory Univ, Atlanta, GA

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