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MO-C930-GePD-F5-3 | Improving Differentiation of Tumor and Surrounding Tissues for Tumor Delineation in Pancreas Using Image Textures From Dual-Energy CT D Schott1*, G Noid1 , P Knechtges1 , W Hall1 , B Erickson1 , T Schmidt2 , X Li1 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Marquette University, Whitefish Bay, WI |
MO-J430-CAMPUS-F1-2 | CT Radiomics Texture Features Indicate Radiation Induced Pneumonitis T Bejarano*, D Kwon , M De Ornelas , R Yechieli , H Perlow , L Freedman , I Mihaylov , Univ Miami, Miami, FL |
MO-K-SAN2-2 | BEST IN PHYSICS (MULTI-DISCIPLINARY): Predictive Capability of 18F-FDG PET/CT Imaging On Tumor Voxel Dose Response S Chen*, D Krauss , D Yan , William Beaumont Hospital, Royal Oak, MI |
PO-GePV-E-8 | Application of Ultrasound Full-Waveform Inversion in Bone Quantitative Measurement M Suo , D Zhang* , Wuhan University, Wuhan, Hubei |
PO-GePV-I-14 | Early Detection of Radiation-Induced Myocardial Injury Using 18F-FDG PET Imaging in Patients with Esophageal Cancer During Radiotherapy X Sha*, G Gong , Q Qiu , Y Yin , shandong cancer hospital, Jinan, 250117 |
PO-GePV-P-32 | Quantification and Impact Analysis of Planar MV Portal Images Cumulative Absorbed Dose On Head and Neck Radiotherapy Treatments P Iwai*, C Marmitt , G Simonetti , Uniao Oeste Paranaense de Estudos e Combate ao Cancer, Parana, Brazil |
PO-GePV-T-265 | Scintillator Optical Imaging for Co-60 Irradiator Quality Assurance Testing I Tendler1*, J Bredfeldt2, R Zhang3 , P Bruza1 , M Jermyn1, B Pogue1,4,5 , D Gladstone1,5,6, (1) Thayer School of Engineering, Dartmouth College, Hanover, NH, (2) Brigham and Women's Hospital, Boston, MA (3) Emory Proton Therapy Center, Johns Creek, GA, (4) DoseOptics LLC, Lebanon, NH, (5) Dept. of Medicine, Geisel School of Medicine, Dartmouth College, Hanover, NH (6) Norris Cotton Cancer Center, Dartmouth-Hitchcock Med. Ctr., Lebanon, NH, |
SU-E-221CD-4 | Comparison of Vendor Provided Analysis Vs Computational Sequence Modeling for T2 Mapping K McPhee*, A Wilman, Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta |
SU-E-221CD-5 | Neural Networks for Quantifying Gadoxetate Uptake From Short Or Temporally Sparse DCE MRI Acquisitions J Simeth*, Y Cao , Univ Michigan, Ann Arbor, MI |
SU-E-221CD-7 | Correcting T2 Maps Calculated From Dual-Echo Fast Spin Echo MRI for the Effects of K-Space Profile Order and Stimulated Echoes R Gabr1*, (1) University of Texas Health Science Center at Houston, Houston, TX |
SU-E-303-7 | Kinetic Analysis of 18F-FAZA Uptake Versus Time in Pancreatic Tumors F Li1*, E Taylor2 , I Yeung3 , D Jaffray4 , D Hedley5 , T Lee6 , (1) Western University, London, ON, (2) University of Toronto, Toronto, ON, (3) The Princess Margaret Cancer Centre - UHN, Toronto, ON, (4) University Health Network, Toronto, ON, (5) University Health Network, Toronto, ,(6) Robarts Research Institute, London, |
SU-E-SAN2-2 | Comparison in Classification Performance of Radiation Pneumonitis Between Two Delta Radiomics Logistic Regression Models J Foy*, H Al-Hallaq , S Armato , The University of Chicago, Chicago, IL |
SU-E-SAN2-6 | Variations in Feature Combinations Correlated with Radiation Pneumonitis Among Radiomics Software Packages J Foy*, S Armato , H Al-Hallaq , The University of Chicago, Chicago, IL |
SU-I300-GePD-F5-4 | SUVmax Assessment in 68Ga-PSMA PET/CT Scan M Fallahpoor1 , N Vahidfar2 , F Kalantari3*, (1) Department of Nuclear Medicine, Vali-Asr Hospital, Tehran University of Medical Sciences, Tehran (2) Department of Nuclear Medicine, VAli-Asr Hospital, Tehran University of Medical Sciences, Tehran (3) UT Southwestern Medical Center, Dallas, TX |
SU-I300-GePD-F5-6 | Lesion-Level Response Prediction From 18F-FDG PET/CT in Metastatic Melanoma Patients Treated with Immune Checkpoint Blockade D Huff1*, R Shah2 , A Weisman1 , L Zurbriggen3 , M Albertini3 , R Jeraj1,4 , (1) University of Wisconsin-Madison, Madison, WI, (2) North Memorial Healthcare, Robbinsdale, MN, (3) University of Wisconsin Carbone Cancer Center, Madison, WI, (4) University of Ljubljana, Ljubljana, Slovenia |
SU-I300-GePD-F8-1 | A Deep Learning Approach On Non Alcoholic Fatty Liver Disease Diagnosis Utilizing Ultrasound B-Mode Images and Liver Biopsy as Gold Standard I Gatos1 , S Tsantis1 , P Drazinos2 , P Zoumpoulis2 , I Theotokas2 , P Katsakiori1 , D Mihailidis3 , J Hazle4 , G C Kagadis1, 3*, (1) University of Patras, Rion, Greece, (2) Diagnostic Echotomography, Athens, Greece, (3) University of Pennsylvania, Philadelphia, PA, USA, (4) UT MD Anderson Cancer Center, Houston, TX, USA |
SU-I400-GePD-F8-2 | Derivation of a Quantitative Relaxation Map From a Single MR Image Using Deep Learning Y Wu1*, Y Ma2 , J Du2 , N Kovalchuk1 , L Xing1 , (1) Stanford Univ School of Medicine, Stanford, CA, (2) University of California San Diego, San Diego, CA |
SU-I430-GePD-F8-2 | Lumbar Spine Imaging-Sagittal Plane: T1 FLAIR BLADE with and Without Parallel Imaging Is Superior Than T1 Turbo Spin Echo E Lavdas1*, M Papaioannou2 , A Tsikrika3 , E Pappas4 , G Sakkas5 , V Roka6 , S Kostopoulos7 , S Stathakis8 , N Papanikolaou9 , P Mavroidis10 , (1) University of West Attica, Athens, ,(2) Animus Kyanoys Stavros, Larissa, ,(3) General University Hospital of Larissa, Larissa, ,(4) Animus Kyanoys Stavros, Larissa, ,(5) University of Thessaly, Trikala, ,(6) Health Center of Farkadona, Trikala, ,(7) University of West Attica, Athens, ,(8) University Of Texas Health, San Antonio, TX, (9) University of Texas HSC SA, San Antonio, TX, (10) Univ North Carolina, Chapel Hill, NC |
SU-I430-GePD-F9-1 | CT Textures in Selection Optimization of HPV-Associated Oropharynx Cancer Patients for Transoral Robotic Surgery T Bejarano*, M Samuels , G Thomas , F Civantos , J Leibowitz , L Freedman , S Samuels , I Mihaylov , Univ Miami, Miami, FL |
SU-I430-GePD-F9-5 | Step-Wise Solution to Evaluate CT Radiomic Feature Variability Due to Correlated Noise Texture M Shafiq ul Hassan1*, F Guo1 , H Chen1 , G Zhang2 , E Moros2 , Z Chen1 , (1) Yale New Haven Hospital, New Haven, CT, (2) Moffitt Cancer Center, Tampa, FL, |
SU-I430-GePD-F9-6 | Subset of Reproducible Radiomic Features as a Function of Multiple CT Imaging Parameters M Shafiq ul Hassan1*, F Guo1 , H Chen3 , G Zhang4 , E Moros5 , Z Chen6 , (1) Yale New Haven Hospital, New Haven, CT, (2) Yale New Haven Hospital, New Haven, CT, (3) Yale New Haven Hospital, New Haven, CT, (4) H. Lee Moffitt Cancer Center, Tampa, FL, (5) H. Lee Moffitt Cancer Center, Tampa, FL, (6) Yale Univ. School of Medicine & YNHH, New Haven, CT |
SU-J400-CAMPUS-F1-2 | Combined Use of Gray Matter Volume and Quantitative Susceptibility Mapping to Predict Early Alzheimers Disease Using a Machine Learning-Based Optimized Combination-Feature Set HK Kim1 , HY Rhee2 , CW Ryu3 ,GH Jahng3*, (1) Radiology, Kyung Hee University Hospital, Seoul,Korea ,(2) Neurology, Kyung Hee University Hospital at Gangdong, Seoul,Korea ,(3) Radiology, Kyung Hee University Hospital at Gangdong, Seoul,Korea |
SU-KL-304-3 | A New Methodology for Reconstruction of 4D-PET Images H Zhong*, X Li , Medical College of Wisconsin, Milwaukee, WI |
SU-KL-304-5 | Automated Assessment of 68Ga-PSMA PET/CT Images of Metastatic Prostate Cancer Using Quantitative Total Bone Imaging T Perk1*, G Liu1, G Starbuck1, R Francis2, M Ebert2, R Jeraj1,3, (1) University of Wisconsin-Madison, Madison, WI, (2) The University of Western Australia, Nedlands, (3) University of Ljubljana, Ljubljana, Slovenia |
SU-L-221AB-1 | Effect of Uncertainties in 18F-FDG PET/CT Imaging Feedback On Treatment Response Assessment and Dose Painting S Chen*, J Liang , A Qin , D Krauss , D Yan , William Beaumont Hospital, Royal Oak, MI |
SU-L-221AB-3 | High-Resolution Inhale/Exhale CT Parametric Response Mapping for Assessment of Pulmonary Dysfunction in Non-Small Cell Lung Cancer Patients Undergoing Radiation Treatment D Owen*, A Fortuna , B Hoff , S Jolly , R Ten Haken , C Galban , M Matuszak , University of Michigan, Ann Arbor, MI |
TH-A-SAN2-12 | A Framework of Automatic Contour Quality Validation for MRI-Guided Online Adaptive Radiation Therapy Y Zhang*, F Ceballos , E Ahunbay , X Li , Medical College of Wisconsin, Milwaukee, WI |
TH-C-SAN2-1 | Harmonizing Imaging Protocols: Impact On Radiomics Survival Prediction in Large Patient Cohorts R Ger*, S Zhou , D Mackin , H Elhalawani , B Elgohari , J Meier , C Fuller , R Howell , R Layman , H Li , O Mawlawi , R Stafford , L Court , UT MD Anderson Cancer Center, Houston, TX |
TU-AB-225BCD-6 | Molecular Image-Directed Bone Biopsies in Metastatic Prostate Cancer Patients A Roth1*, S Harmon1 , T Perk1 , M Tuite1 , S Tomlins2 , G Liu1 , R Jeraj1,3 , (1) University of Wisconsin-Madison, Madison, WI, (2) University of Michigan, Ann Arbor, MI, (3) University of Ljubljana, Ljubljana, Slovenia |
TU-AB-225BCD-9 | Quantitative Magnetic Resonance Fingerprinting (MRF) Has Lower Intra-/Inter-Scanner Variability and Higher Contrast-To-Noise-Ratio Vs. Conventional Contrast-Weighted MRI: Implications for Radiomics and Machine-Learning Applications L Lu1*, Y Chen2 , J Lian1 , D Fried1 , S Das1 , L Marks1 , W Lin2 , T Zhu1 , (1) Dept. Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA (2) Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA |
TU-AB-SAN2-8 | Intratumoral and Peritumoral CT Radiomic Modeling to Predict Treatment Failure of Early Stage Non-Small Cell Lung Cancers K Lafata1*, Y Gao2 , Y Chang3 , C Wang4 , C Kelsey5 , F Yin6 , (1) Duke University Medical Center, Durham, NC, (2) Duke University Medical Physics Graduate Program, Durham, NC, (3) Duke University Medical Center, Durham, NC, (4) Duke University Medical Center, Durham, NC, (5) Duke University, Durham, ,(6) Duke University Medical Center, Durham, NC |
TU-AB-SAN2-11 | ComBat Harmonization for Radiomcs Studies with CT Images R N Mahon1*, M Ghita1 , G D Hugo2 , E Weiss1 , (1) Virginia Commonwealth University, Richmond, VA, (2) Washington University School of Medicine, St. Louis, MO |
TU-C1030-GePD-F6-2 | Differentiation Among Non-Small Cell Lung Cancer Subtypes Using Quantitative Radiomic Features of 18F-FDG PET/CT X Sha1*, G Gong2 , Q Qiu3 , Y Yin4 , (1) shandong cancer hospital, Jinan, 250117, (2) ,Jinan, ,(3) ,Jinan, ,(4) shandong cancer hospital, Jinan, |
TU-C930-GePD-F9-5 | Transfer Learning of a Convolutional Neural Network for CBCT Projection-Domain Scatter Correction with Different Scan Conditions Y Nomura1*, Q Xu2,3 , H Shirato2,4 , S Shimizu2,5 , L Xing2,6 , (1) Department of Radiation Oncology, Graduate School of Medicine, Hokkaido University, Sapporo, Japan, (2) Global Station for Quantum Medical Science and Engineering, Global Institution for Collaborative Research and Education (GI-CoRE), Hokkaido University, Sapporo, Japan, (3) Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China, (4) Department of Radiation Medicine, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan, (5) Department of Radiation Medical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Japan, (6) Department of Radiation Oncology, Stanford University, Stanford, CA |
TU-F115-GePD-F6-4 | Dependence of Radiomics Features On CT Image Acquisition and Reconstruction Parameters Using a Cadaveric Human Liver I Gertsenshteyn1*, J Foy1 , A Crofton2 , V Grekoski3 , T Tran3 , K Guruvadoo3 , H Al-Hallaq1 , S Armato1 , W Sensakovic3 , (1) The University of Chicago, Chicago, IL, (2) Adventist University of Health Sciences, Orlando, FL, (3) Florida Hospital, Orlando, FL |
TU-F115-GePD-F9-3 | Fat Fraction Based Segmentation of CT Image Based On Surfactant-Free Microemulsion Reference Phantom: A Feasibility Study H Cho1, C Lee1 , B Ahn1 , C Hong2* , (1) Korea Research Institute of Standards and Science,Daejeon, Korea (2) Daegu Catholic University, Daegu,Korea |
TU-HI-221AB-0 | Biomedical Modeling Using Imaging Data P Boyle1*, D Tward2*, D Holdsworth3*, C Grassberger4*, (1) University of Washington, Seattle, WA, (2) The Johns Hopkins University, Baltimore, MD, (3) John P. Robarts Research Instit., London, ON, (4) Massachusetts General Hospital, Boston, MA |
TU-HI-SAN2-12 | Sub-Region Based Radiomics Analysis for Survival Prediction in Esophageal Tumors Treated by Radiotherapy P Yang1*, L Xu1 , Z Cao1 , Y Jiang1 , Y Xue1 , C Luo1 , S Wu2 ,Y Kuang3 , T Niu1 , (1) Zhejiang University, Hangzhou, Zhejiang, Peoples R China,(2) Hangzhou Cancer Hospital, Hangzhou, Zhejiang, Peoples R China,(3) University of Nevada, Las Vegas, Las Vegas, NV |
TU-J345-GePD-F4-6 | A Pre-Clinical Bioluminescence Tomography-Guided Radiation Research Platform for Pancreatic Cancer Z Deng1*, X Xu1 , H Dehghani2 , A Klose3 , P Tran1 , K Wang1 , (1) Johns Hopkins University School of Medicine, Baltimore, MD, (2) School of Computer Science, University of Birmingham, Edgbaston, Birmingham, UK, (3) InVivo Analytics, New York, NY |
TU-J345-GePD-F8-3 | Fast Distortion-Free T2 Imaging Using DIADEM Combined with Tilted-CAIPI On a Compact 3T Scanner with High-Performance Gradients MH In*, D Kang, U Yarach, Y Shu, JD Trzasko, J Huston, MA Bernstein, Mayo Clinic, Rochester, MN |
TU-L-304-2 | Cone-Beam CT of Load-Bearing Surgical Hardware Using a Mechanical Model of Implant Deformation Q Cao*, S Liu , G Osgood , S Demehri , J Siewerdsen , J Stayman , W Zbijewski , Johns Hopkins University, Baltimore, MD |
TU-L-304-3 | A Novel Contrast CT Based Quantitative Characterization of Surgical Resectability in Pancreatic Cancer Y Lao1*, J David2 , Z Fan2 , K Sheng1 , A Shiu3 , E Chang3 , R Tuli4 , W Yang3 , (1) UCLA School of Medicine, Los Angeles, CA, (2) Cedars Sinai Medical Center, Los Angeles, CA, (3) University of Southern California, Los Angeles, CA, (4) MSKCC,New York, NY |
TU-L-304-6 | Understanding Reproducibility of Radiomic Features of Lung Nodules Under Heterogenous CT Acquisition and Reconstruction Conditions N Emaminejad*, M Wahi-Anwar , G Kim , M Brown , M McNitt-Gray , David Geffen School of Medicine at UCLA, Los Angeles, CA |
TU-L-304-7 | Standardization in Quantitative Imaging: A Comparison of Radiomics Feature Values Obtained by Different Software Packages On a Set of Digital Reference Objects M McNitt-Gray1*, S Napel2 , J Kalpathy-Cramer3 , A Jaggi2 , D Cherezov4 , D Goldgof4 , H Yang5 , E Jones6 , M Muzi7 , N Emaminejad1 , M Wahi-Anwar1 , Y Balagurunathan8 , M Abdalah8 , B Zhao5 , L Hadjiiski9 , L Pierce7 , K Farahani10 , (1) David Geffen School of Medicine at UCLA, Los Angeles, CA, (2) Stanford Univ School of Medicine, Stanford, CA, (3) Massachusetts General Hospital, Boston, MA, (4) University of South Florida, Tampa, FL, (5) Columbia University, New York, NY, (6) UCSF, San Francisco, CA, (7) University of Washington, Seattle, WA (8) Moffitt Cancer Center, Tampa, FL, (9) University of Michigan, Ann Arbor, MI, (10) National Cancer Institute, Bethesda, MD |
WE-C930-GePD-F6-1 | A 2-Hydroxyglutarate(2HG) MRS Phantom for Periodic Quality Control Testing P Hou1*, H Liu2 , T Salzillo3 , J Johnson4 , C Choi5 , R Stafford6 , (1) UT MD Anderson Cancer Center, Houston, TX, (2) UT MD Anderson Cancer Center, Houston, TX, (3) UT MD Anderson Cancer Center, Houston, TX, (4) UT MD Anderson Cancer Center, Houston, TX, (5) UT southwestern, Medical Center, Dallas, TX, (6) UT MD Anderson Cancer Center, Houston, TX |
WE-F-SAN4-0 | EPID Machine QA Implementation and Automation, Are We There Yet? C Shi1*, M Barnes2*, B Sun3*, (1) Memorial Sloan Kettering Cancer Center, Marlboro, NJ, (2) Calvary Mater Hospital Newcastle, Newcastle, Australia, (3) Washington Univ. in St. Louis, St. Louis, MO |
WE-F-SAN4-1 | Role of EPID in new linac commission and the SSIM concept for evaluation C Shi1*, M Barnes2*, B Sun3*, (1) Memorial Sloan Kettering Cancer Center, Marlboro, NJ, (2) Calvary Mater Hospital Newcastle, Newcastle, Australia, (3) Washington Univ. in St. Louis, St. Louis, MO |
WE-F-SAN4-2 | Improving MPC and aligning better with TG-142 C Shi1*, M Barnes2*, B Sun3*, (1) Memorial Sloan Kettering Cancer Center, Marlboro, NJ, (2) Calvary Mater Hospital Newcastle, Newcastle, Australia, (3) Washington Univ. in St. Louis, St. Louis, MO |
WE-F-SAN4-3 | Practical implementation of EPID-based QA for linac C Shi1*, M Barnes2*, B Sun3*, (1) Memorial Sloan Kettering Cancer Center, Marlboro, NJ, (2) Calvary Mater Hospital Newcastle, Newcastle, Australia, (3) Washington Univ. in St. Louis, St. Louis, MO |
WE-FG-303-5 | Evaluation of Sensitivity of Ultrasound Imaging Biomarkers of Cervical Viscosity Based On Shear Wave Elasticity Imaging: A Simulation Study A Torres1*, M Palmeri2 , H Feltovich3 , T Hall4 , I Rosado-Mendez1 , (1) Universidad Nacional Autonoma de Mexico, Mexico City, MEX,(2) Duke University, Durham, NC, (3) Intermountain Healthcare, Provo, UT, (4) University of Wisconsin-Madison, Madison, WI |
WE-FG-303-6 | Evaluation of Cancer Microarchitecture and Microenvironment by Photoacoustic Imaging Technologies X Wang*, G Xu , J Jo , C Lee , R Kopelman , University of Michigan, Ann Arbor, MI |
WE-FG-304-7 | Automated Quantification of Lymphoma On FDG PET/CT Images Using Cascaded Convolutional Neural Networks A Weisman1*, M Kieler1 , S Perlman1 , R Jeraj1,2 , M Hutchings3 , L Kostakoglu4 , T Bradshaw1 , (1) University of Wisconsin-Madison, Madison, WI, (2) Faculty of Mathematics and Physics, Ljubljana, Slovenia, (3) Rigshospitalet, Copenhagen, Denmark, (4) Mount Sinai Medical Center, New York, NY |
WE-HI-303-6 | Integrated Backscatter Computation for Quantitative Ultrasound Evaluation of Carotid Atherosclerotic Plaque In-Vivo C Steffel*, S Wilbrand, S Salamat, R Dempsey, C Mitchell, T Varghese, University of Wisconsin-Madison School of Medicine & Public Health, Madison, WI |
WE-J-303-0 | AI and Quantitative Ultrasound Imaging F Forsberg1*, X Yang2*, (1) Thomas Jefferson University, Philadelphia, PA, (2) Emory University, Atlanta, GA |
WE-J-303-6 | In-Vivo Quantitative Ultrasound Evaluation of Carotid Atherosclerotic Plaque with Attenuation Coefficient C Steffel*, S Wilbrand, S Salamat, R Dempsey, C Mitchell, T Varghese, University of Wisconsin-Madison School of Medicine & Public Health, Madison, WI |
WE-J-304-5 | Characterization of Bioluminescence Tomography-Guided System (MuriGlo) for Pre-Clinical Radiation Research X Xu1*, Z Deng1 , P Tsouchlos2 , T Kanesalingam2 , H Dehghani3 , J Wong1 , K Wang1 , (1) Johns Hopkins School of Medicine, Baltimore, MD, (2)Xstrahl Inc. ,Suwanee,Georgia, (3) School of Computer Science, University of Birmingham, West midlands, UK |