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Taxonomy: Education: Analysis
| BReP-SNAP-I-19 | Estimation of Tumor Tracer Kinetics Employing a Novel Cross Voxel Exchange Model N Sinno1*, E Taylor1, M Milosevic1, D Jaffray2, C Coolens1 (1) Princess Margaret Cancer Centre, Toronto, ON, (2) UT MD Anderson Cancer Center, Houston, TX |
| BReP-SNAP-I-41 | Preoperative Non-Invasive Grading of Parotid Gland Cancer Malignancy Using Radiomic MR Features H Kamezawa1*, H Arimura2, R Yasumatsu2, K Ninomiya2, (1) Teikyo University, Omuta, JP, (2) Kyushu University, Fukuoka, JP |
| BReP-SNAP-M-3 | A Comparison of Convolutional Neural Networks and Logistic Regression for the Detection of Vertebral Body Misalignments During Radiation Therapy R Petragallo*, J Lamb, University of California, Los Angeles, Los Angeles, CA |
| BReP-SNAP-M-4 | A Comprehensive Framework for Radiotherapy Treatment Plan Quality Evaluation in Large Multiple Institution Dataset L Yuan*, R Kapoor, W Sleeman, M Hagan, J Palta, M Rosu-Bubulac, Virginia Commonwealth University, Richmond, VA |
| BReP-SNAP-M-6 | A Deep Learning Model to Predict a Diagnosis of MCI by Using Static and Dynamic Brain Connectomics D Cui1,2, J Jin2, Z Liu2, T Yin2*, (1) Shandong First Medical University, Taian, 37, CN, (2) Institute Of Biomedical Engineering, Chinese Academy Of Medical Sciences, Tianjin, CN |
| BReP-SNAP-M-17 | Assessing Longitudinal CT Perfusion Changes in Pancreas and Pelvic Node Tumors Treated with SBRT On Prospective Phase I Dose Escalation Trials T Patton1*, A Santoso1, T Reinicke1, Y Vinogradskiy1, Q Diot1, C Fisher1, K Goodman2, B Jones1, (1) University of Colorado Anschutz Medical Campus, Aurora, CO, (2) Mount Sinai, New York, NY |
| BReP-SNAP-M-18 | Assessment of Texture Feature Robustness Using a Novel 3D-Printed Phantom K Spuhler*, J Teruel, P Galavis, NYU Langone Health, New York, NY |
| BReP-SNAP-M-19 | Association of Lung CT Voxel-Based Radiomics Feature Map with Galligas PET Lung Ventilation Imaging Z Yang*, K Lafata, X Chen, Y Chang, F Yin, Duke University, Durham, NC |
| BReP-SNAP-M-39 | Combining Radiomics and Convolutional Neural Network to Predict Tumor Growth of Vestibular Schwannoma K Wang*, L Chen, N George-jones, J Hunter, J Wang, UT Southwestern Medical Center, Dallas, TX |
| BReP-SNAP-M-52 | Deep Neural Network for Survival Analysis Using Intratumoral Radiomics and Dosiomics in the RTOG 0617 Clinical Trial S Lee*, H Geng, H Zhong, Y Fan, M Rosen, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| BReP-SNAP-M-55 | Detecting Pathological Complete Response in Esophageal Cancer After Neoadjuvant Therapy Based On Survival-Weighted Deep Learning: A Pilot Study S Cheng1*, W Yap2, E Tu3, (1) Taiwan AI Labs, ,,(2) Chang Gung Memorial Hospital, ,,(3) Taiwan Ai Labs, |
| BReP-SNAP-M-75 | Forecasting Individual Patient Response to Radiotherapy with a Dynamic Carrying Capacity Model M Zahid*1, N Mohsin1, A Mohamed2, J Caudell1, L Harrison1, C Fuller2, E Moros1, H Enderling1, (1) H. Lee Moffitt Cancer Center, Tampa, FL, (2) UT M.D. Anderson Cancer Center, Houston, TX |
| BReP-SNAP-M-84 | Image Processing System by Super-Resolution Using Deep Learning Leading to Exposure Dose Reduction H Miyauchi1,2*, Y Tanaka1, K Takahashi1, M Nakano2, T Hasegawa3, M Hashimoto3, (1) Kitasato University Graduate School of Medical Sciences, Sagamihara, Kanagawa, JP, (2) Cancer Institute Hospital of JFCR, Koto-ku, Tokyo, JP, (3) Faculty of Allied Health Sciences, Kitasato university, Sagamihara, Kanagawa, JP |
| BReP-SNAP-M-102 | Moving From Geometric-Based to Risk-Based Adaptive Re-Planning in Head and Neck Radiotherapy K Brock1*, S Gryshkevych2, B Rigaud1, A Ohrt1, S Svensson2, C Fuller1, (1) UT MD Anderson Cancer Center, Houston, TX, (2) RaySearch Laboratories AB, Stockholm,SE |
| BReP-SNAP-M-113 | Predicting Glioblastoma Cell Motility with Radiomics K Mulford*, M McMahon, D Odde, C Wilke, University of Minnesota, Minneapolis, Minnesota |
| BReP-SNAP-M-115 | Prediction of Radiation Pneumonitis After Lung Stereotactic Body Radiation Therapy Using Dosiomics Features: A Retrospective Multi-Institutional Study T Adachi1,2*, M Nakamura1,2, T Shintani2, T Mitsuyoshi2,3, R Kakino1,2, T Ogata3, H Tanabe3, T Ono2, H Hirashima2, T Sakamoto4, M Kokubo3, Y Matsuo2, T Mizowaki2, (1) 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, (3) Department of Radiation Oncology, Kobe City Medical Center General Hospital, Hyogo, Japan(4) Department of Radiation Oncology, Kyoto Katsura Hospital, Kyoto, Japan |
| BReP-SNAP-M-119 | Quantification of Lung Ventilation Using Voxel-Based Delta Radiomics Extracted From Thoracic 4DCT X Chen1*, K Lafata2, Z Yang3, F Yin4, (1) ,Durham, NC, (2) Duke University, Durham, NC, (3) Duke University, Durham, NC, (4) Duke University, Durham, NC |
| BReP-SNAP-M-120 | Quantum-Inspired Approach to Predicting Geometric Changes in Head and Neck Cancer J Pakela*, R Ten Haken, D McShan, M Matuszak, I El Naqa, University of Michigan, Ann Arbor, MI |
| BReP-SNAP-M-135 | Simplification of Transmission Factor Determination for I-131 Gamma Camera Based Internal Dosimetry with Co-57 Solid Flood Source Q Liang1*, L Chen2, R Klein3, J Halama4, R Harvey5, J Schwartz6, D Fisher7, (1) Actinium Pharmaceuticals, New York, NY, (2) Banner MD Anderson Cancer Center, Gilbert, AZ, (3) The Ottawa Hospital, Ottawa, ON, Canada, (4) Loyola Univ Medical Center, Maywood, IL, (5) Roswell Park Cancer Institute, Buffalo, NY, (6) Memorial Sloan Kettering Cancer Center, New York, NY, (7) Versant Medical Physics And Radiation Safety, Richland, WA |
| BReP-SNAP-T-79 | Impact of Patient-Specific Factors On Implant Uncertainty in Permanent Breast Seed Implant Brachytherapy C Zhang1,2*, M Hilts1,2, D Batchelar1,2, J Andrews2, C Hvingelby2, E Watt3, J Crook1, (1) BC Cancer - Kelowna, Kelowna, BC, CA, (2) The University Of British Columbia Okanagan, Kelowna, BC, CA, (3) Okolo Health, Calgary, AB, CA |
| BReP-SNAP-T-101 | Measurements of LET, Nuclear Halo, Energy and Angular Spectra of a Proton Spot Scanning Beam with a Hybrid Semiconductor Detector S Charyyev1*, C Chang2, A Stanforth3,4, J Harms5, C Oancea6, L Lin7, (1) Emory University, Atlanta, GA, (2) Emory University, Atlanta, GA, (3) Emory University, Atlanta, GA, (4) Georgia Institute of Technology, Atlanta, GA, (5) Emory University, Atlanta, GA, (6) ADVACAM, Prague, CZ, (7) Emory Proton Therapy Center, Atlanta, GA |
| BReP-SNAP-T-102 | Measurements, Simulation, and Analytical Model of Stray Photon and Neutron Absorbed Dose From MV External Beam Radiation Therapy C Schneider1,2*, W Newhauser2, (1) Mary Bird Perkins Cancer Center, Baton Rouge, LA, (2) Louisiana State University, Baton Rouge, LA |
| BReP-SNAP-T-107 | Multivariable Dosimetric Models for Urinary and Rectal Toxicity Prediction Assessed From Patient Reported Outcome After Prostate Stereotactic Body Radiotherapy X Pan1*, J Huang2, R Levin-epstein3, Z Wang4, D Low5, X Qi6, (1) Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing,, Xi'an, ,CN, (2) ,Xi'an, 61, CN, (3) ,,,(4) ,,,(5) UCLA, Los Angeles, CA, (6) UCLA School of Medicine, Los Angeles, CA |
| BReP-SNAP-T-136 | Using a Novel Hybrid Computational Phantom to Calculate Out-Of-Field Dose and Equivalent Dose in Proton Therapy E Kollitz1*, H Han2, C Kim2, M Riboldi1, F Kamp3, W Newhauser4, G Dedes1, K Parodi1, (1) Ludwig Maximilian University of Munich, Munich, DE, (2) Hanyang University, Seoul,KR, (3) Hospital of the Ludwig Maximilian University of Munich, Munich, DE,(4) Louisiana State University, Baton Rouge, LA, |
| MO-F-TRACK 1-6 | Automated Quantification of Spatially Abnormal 129-Xe MRI Ventilation and Perfusion: Implications for Lung Cancer, Asthma, and COPD Interventions M Mcintosh*, R Eddy, J Macneil, A Matheson, G Parraga, Robarts Research Institute, Western University, London, ON, CA |
| PO-GeP-I-69 | CT-Derived Pulmonary Perfusion E Castillo1*, R Castillo2, Y Vinogradskiy3, G Nair1, I Grills1, T Guerrero1, C Stevens1, (1) William Beaumont Hospital, Royal Oak, MI, (2) Emory Univ, Atlanta, GA, (3) University of Colorado Denver, Aurora, CO |
| PO-GeP-I-73 | Deep-Learning-Based CT ImageStandardization to Improve Stability of Radiomics Features in Non-Small CellLung Cancer J Zhang1*, M Selim2, M Brooks3, B Fei4, G Zhang5, J Chen6, (1) University of Kentucky, Lexington, KY, (2) University Of Kentucky, ,,(3) University Of Kentucky, ,,(4) University of Texas (UT) at Dallas and UT Southwestern Medical Center, Richardson, TX, (5) Uthealth, ,,(6) University Of Kentucky, |
| PO-GeP-I-79 | Developing a Novel Approach for ECG Classification Using Modified Local Binary Patterns e zeraatkar1*, M Gholamian2, N Jahani3, M Yazdi4, (1) Shiraz Urban Railway Organozation,Shiraz,IR (2) Shiraz University, Shiraz Iran,(3) Green Land Shiraz Eksir Chemical and Agricultural Industries Cimpant,Shiraz,Iran(4)Shiraz University,Shoraz Iran |
| PO-GeP-I-118 | Evaluation of Radiomic Feature Stability for CT Imaging Parameters in Lung Nodules S Koizumi1*, (1) Komazawa University, Setagaya, 13, JP |
| PO-GeP-I-184 | Radiomic Analysis Performed Preoperatively of Radical Prostatectomy to Predict Lymph Node Metastases of High-Grade Prostate Cancers D LeBlanc*, F Rasekh, G Couture, P Despres, J Beauregard, F Pouliot, L Archambault, CHUQ Pavillon Hotel-Dieu de Quebec, Quebec, QCCA, |
| PO-GeP-I-231 | Validation of Robust CT-Ventilation Methods E Castillo1*, R Castillo2, Y Vinogradskiy3, G Nair1, I Grills1, T Guerrero1, C Stevens1, (1) Beaumont Health System, Royal Oak, MI, (2) Emory Univ, Atlanta, GA, (3) University of Colorado Denver, Aurora, CO |
| PO-GeP-M-9 | A Deep Learning Method for Prediction of 3D Dose Distribution in Clinical Case S Ahn1*, E Kim2, K Kim3, C Kim4, S Lee5, Y Lim6, H Kim7, D Shin8, J Jeong9, (1) National Cancer Center, Goyang-si Gyeonggi-do,KR |
| PO-GeP-M-35 | A Patient-Specific Model for Tracking Lung Tumor During Radiotherapy Using Surrogate Signal S Fakhraei*, D Sterling, E Ehler, P Alaei, University of Minnesota, Minneapolis, MN |
| PO-GeP-M-63 | Application of Kilovoltage Cone-Beam CT Images in Extracting Radiomics Signature for Predicting Radiation-Induced Pneumonitis Y Huang*, H Liu, R Yu, Y Pu, Y Zhang#, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, BeijingCN, #corresponding author: Yibao Zhang; email: zhangyibao@pku.edu.cn |
| PO-GeP-M-68 | Assessing the Dosimetric Links Between Organ-At-Risk Delineation Variability and Treatment Planning Variability W Choi1,2, V Leandro Alves2*, E Aliotta2, H Nourzadeh2, J Siebers2, (1) Virginia State University, Petersburg, VA, (2) University of Virginia, Charlottesville, VA |
| PO-GeP-M-85 | Benchmarking the Plan Review Performance of a Commercial Automation Tool and a Dynamic Checklist Technology Using TG-275 High Risk Failure Modes J Hoisak*, R Manger, G Kim, I Dragojevic, University of California, San Diego, La Jolla, CA |
| PO-GeP-M-93 | Characterization of CT Hounsfield Units Uniformity of 3D-Printed Materials for Proton Therapy E Orton1*, C Engelberts1, R Orbovic1, M Crocker1,2, B Basaric1, D Sobczak3, L Zhao3, (1) Adaptiiv Medical Technologies, Halifax, NS, CA, (2) Dalhousie University, Halifax, NS, CA, (3) St. Jude Children's Research Hospital, Memphis, TN |
| PO-GeP-M-94 | Characterization of Patient Shifts From Ct Simulation to First Fraction to Improve Tumor Localization S Drehmel1*, J Lawrence2, C Ferreira3, E Ehler3 (1) University of Minnesota, Minneapolis, MN, (2) University of Minnesota, Saint Paul, MN, (3) University of Minnesota, Minneapolis, MN |
| PO-GeP-M-119 | Compton Camera Event Classification Using Artificial Neural Networks P Maggi1*, C Barajas2, G Kroiz2, J Basalyga2, S Peterson3, D Mackin4, R Panthi4, S Beddar4, M Gobbert2, J Polf1, (1) University of Maryland, Baltimore, Baltimore, MD, (2) University Of Maryland, Baltimore County, Baltimore, MD, (3) University of Cape Town, Rondebosch, ZA, (4) The University of Texas M.D. Anderson Cancer Center, Houston, TX |
| PO-GeP-M-136 | Deep Learning Prediction of Radiotherapy Treatment Machine Parameters L Hibbard1*, (1) Elekta, Inc, St. Charles, MO |
| PO-GeP-M-138 | Deep Learning-Based Auto-Segmentation of OARs in Head and Neck CT Images Z Shen1*, A Garsa1, S Sun2, N Bai2, C Zhang2, A Shiu1, E Chang1, W Yang1, (1) University of Southern California, Los Angeles, CA, (2) DeepVoxel Inc., Irvine, CA |
| PO-GeP-M-139 | Deep Proton DoseNet: A Deep Neural Network for Proton Dose Distribution Image Super-Resolution Y Nomura1*, T Matsuura1, H Shirato1, S Shimizu1, L Xing1,2, (1) Hokkaido University, Sapporo, Hokkaido, Japan, (2) Stanford University, Palo Alto, CA |
| PO-GeP-M-150 | Development and Validation of a Web-Crawler-Based Medical Records Information Aggregation Tool H Liu*, Y Huang, Y Pu, H Wu, Y Zhang#, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, BeijingCN,#corresponding author: Yibao Zhang; email: zhangyibao@pku.edu.cn |
| PO-GeP-M-151 | Development of 4DCT-MR Based Numerical Lung Phantoms for 4D Radiotherapy and Imaging Investigations A Duetschler1,2*, M Krieger1,2, D C Weber1,3,4, A J Lomax1,2, Y Zhang1, (1) Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, CH (2) ETH Zurich, Zurich, CH (3) University Hospital of Zurich, Zurich, CH (4) Inselspital, Bern, CH |
| PO-GeP-M-165 | Dose Prediction and Customized Optimization Settings by Learning From Previous Cases: Application to SBRT Treatment Planning E Schreibmann*, Department of Radiation Oncology and Winship Cancer Institute of Emory University |
| PO-GeP-M-166 | Dose to Circulating Blood in VMAT TBI Using a Dynamic Whole Body Blood Model B Guo*, Cleveland Clinic Foundation, Cleveland, OH |
| PO-GeP-M-180 | Effect of Using Harmonized Radiomic Features On Predicting Volume of Radiographic Changes Following Stereotactic Body Radiotherapy in Lung R N Mahon1*, M Ghita1, G D Hugo2, N Kalman3, N Mukhopadhyay1, E Weiss1, (1) Virginia Commonwealth University, Richmond, VA, (2) Washington University School of Medicine, St. Louis, MO, (3) Miami Cancer Institute, Miami, FL. |
| PO-GeP-M-195 | Evaluating the Efficacy of Regression Models in Radiomics: A Study with NSCLC Patients HHF Choi1*, (1) ,Vancouver, BC, CA |
| PO-GeP-M-202 | Evaluation of Machine Learning Algorithms for Treatment Planning Parameter Calculation J Chow1*, R Jiang2, F Ng3, (1) Princess Margaret Cancer Centre, Toronto, ON, CA, (2) Grand River Hospital, Kitchener, ON, CA, (3) Ryerson University, Toronto, ON, CA |
| PO-GeP-M-208 | Evaluation of Surface Registration Accuracy for Patient Positioning in Head and Neck Radiotherapy Using Normal Distribution Transform Algorithm S Fakhraei*, C Wilke, P Alaei, University of Minnesota, Minneapolis,MN |
| PO-GeP-M-215 | Evaluation of the Stability of Radiomics Features Using 4D-CT and Across Radiomics Platforms for Lung and Liver Tumors X Wang1*, C Ma1, H Wang2, Y Zhang1, N Yue1, K Nie1, (1) Rutgers-Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, (2) Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China |
| PO-GeP-M-232 | Generating Synthetic CT From Daily Cone Beam CT Using Machine Learning Models SA Yoganathan, S Paloor*, R Hammoud, N Hammadi, National Centre for Cancer Care & Research, HMC, Doha, QATAR. |
| PO-GeP-M-233 | Generation of Pseudo MR From CT for Soft-Tissue Sarcoma Using SRCycle GAN X Meng1*, C Wang2, X Wu1, X Xu1,3 X Pei1, (1) University of Science and Technology of China, Hefei, Anhui, CN, (2) The First Affiliated Hospital Of University Of Science And Technology Of China, Hefei, Anhui, CN, (3) Rensselaer Polytechnic Institute, Troy, NY |
| PO-GeP-M-235 | Head Neck Cancer Locoregional Recurrence Prediction Using Delta-Radiomics Feature K Wang1*, Z Zhou2, L Chen3, R Wang4, D Sher5, J Wang6, (1) UT Southwestern Medical Center, Dallas, TX, (2) University Of Central Missouri, Warrensburg, MO, (3) UT Southwestern Medical Center, Dallas, TX, (4) UT Southwestern Medical Center, Dallas, TX, (5) UT Southwestern Medical Center, Dallas, TX, (6) UT Southwestern Medical Center, Dallas, TX |
| PO-GeP-M-240 | Impact of Changes in Body Shapes On Radiation Therapy Dose Distribution After Uterine Cervical Cancer Surgery M Sasaki1*, H Ikushima2, K Kitagawa3, Y Kano4, M Tominaga5, H Honda6, W Sugimoto7, M Oita8, (1) Institute of Biomedical Sciences, Tokushima University Graduate School,Tokushima, JP, (2) Institute of Biomedical Sciences, Tokushima University Graduate School,Tokushima, JP, (3)Graduate School of Health Sciences, Tokushima University,Tokushima,JP(4)Graduate School of Health Sciences, Tokushima University,Tokushima,JP(5) Institute of Biomedical Sciences, Tokushima University Graduate School,Tokushima, JP, (6) Ehime University Hospital, Ehime, JP, (7) Tokushima Prefectural Central Hospital, Tokushima, JP, (8) Okayama University Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama, 33, JP |
| PO-GeP-M-257 | Independent Feature Selection in Radiomics Cross-Validation Is Essential to Estimate the True Model Performance J Du*, X Qi, R Chin, K Sheng, UCLA School of Medicine, Los Angeles, CA |
| PO-GeP-M-259 | Individuals in the Prediabetes Stage Exhibit Reduced Hippocampus and Amygdala Subregion Volumes D CUI, W Cao, Q Jiao, J Qiu, Y Guo*, Shandong First Medical University, Taian, 37CN, |
| PO-GeP-M-261 | Initial Experience in MRI-Based Brain Metastases Detection Using Deep Learning J Teruel1*, K Bernstein1, P Galavis1, K Spuhler1, J Silverman1, D Kondziolka1,2, K Osterman1, (1) Department of Radiation Oncology, NYU Langone Health, New York, NY, (2) Center for Advanced Radiosurgery, NYU Langone Health, New York, NY |
| PO-GeP-M-269 | Investigating Internal-External Motion Correlation Using Fast Helical Free-Breathing CT and Simultaneous Respiratory Bellows M Lauria1*, R Navaratna2, D O'Connell1, P Lee3, D Low1, (1) UCLA, Los Angeles, CA, (2) University of Wisconsin, Madison, WI, (3) The University of Texas M.D. Anderson Cancer Center, Houston, TX |
| PO-GeP-M-286 | Longitudinal Analysis of Parotid Gland Anatomical Changes During Radiotherapy by Recurrent Convolutional Neural Networks D Lee*, P Zhang, S Alam, J Jiang, S Nadeem, A Caringi, N Allgood, Y Hu, Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GeP-M-300 | MRI Radiomic Analysis for Survival Prediction in Diffuse Midline Glioma L Tam1, M Han1, D Yecies1, K Yeom1, S Mattonen2*, (1) Stanford University, Stanford, CA, USA (2) Western University, London, ON, CA |
| PO-GeP-M-319 | Optimizing Treatment Plan Selection of HPV-Associated OPSCC Patients Using Artificial Intelligence On Electronic Medical Records and Radiomics T Bejarano*, I Mihaylov, M Samuels, University of Miami, Miami, FL |
| PO-GeP-M-329 | Predicting Prognosis of Posterior Fossa Ependymoma Using MRI Radiomics L Tam1, D Yecies1, M Han1, K Yeom1, S Mattonen2*, (1) Stanford University, Stanford, CA, USA (2) Western University, London, ON, CA |
| PO-GeP-M-331 | Predicting Treatment Outcome After Immunotherapy Based On Delta-Radiomic Model in Metastatic Melanoma X Chen1*, M Zhou1, K Wang2, Z Wang4, Z Zhou4, (1) Xi'an Jiaotong University, Xi'an, Shaanxi, CN, (2) UT Southwestern Medical Center, Dallas, TX, (3) Peking University Cancer Hospital, Beijing, CN, (4) University Of Central Missouri, Warrensburg, Missouri |
| PO-GeP-M-332 | Predicting Tumor Control Using Geometric Features of Hypoxia Measured with EPRI H Smith1*, I Gertsenshteyn2,3, B Epel2,3, E Barth2,3, M Maggio3, S Sundramoorthy2,3, H Halpern2,3, (1) Department of Radiology, University of Chicago (2) Department of Radiation and Cellular Oncology, University of Chicago (3) National Institutes of Health Center for EPR Imaging In Vivo Physiology, University of Chicago, Chicago,IL |
| PO-GeP-M-337 | Prognostic Prediction for Lung Stereotactic Body Radiotherapy Using Breath-Hold CT-Based Radiomic Features with Random Survival Forest: A Multi-Institutional Study R Kakino1,2,3*, M Nakamura1,2, T Mitsuyoshi2,4, T Shintani2, M Kokubo4, Y Negoro5, M Fushiki6, M Ogura7, S Itasaka8, C Yamauchi9, S Otsu10, T Sakamoto11, M Sakamoto12, N Araki13, H Hirashima2, T Adachi1,2, Y Matsuo2, T Mizowaki2, (1) Division of Medical Physics, Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, (2) Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, (3) Research Fellow at Japan Society for the Promotion of Science, (4) Department of Radiation Oncology, Kobe City Medical Center General Hospital, (5) Department of Radiology, Tenri Hospital, (6) Department of Radiation Oncology, Nagahama City Hospital, Nagahama, (7) Department of Radiation Oncology, Kishiwada City Hospital, Kishiwada , (8) Department of Radiation Oncology, Kurashiki Central Hospital, (9) Department of Radiation Oncology, Shiga General Hospital, (10) Department of Radiation Oncology, Kyoto City Hospital, (11) Department of Radiation Oncology, Kyoto-Katsura Hospital, (12) Department of Radiology, Japanese Red Cross Fukui Hospital, (13) Department of Radiation Oncology, National Hospital Organization Kyoto Medical Center |
| PO-GeP-M-338 | Prognostic Value of Imaging-Based Estimates of Glioma Pathology Pre- and Post-Surgery E Gates*, D Suki, J Weinberg, S Prabhu, D Fuentes, D Schellingerhout, UT MD Anderson Cancer Center, Houston, TX |
| PO-GeP-M-341 | Prostate Motion When Patient Coughs and Its Dosimetric Impact B Guo, R Tendulkar, P Xia*, Cleveland Clinic Foundation, Cleveland, OH |
| PO-GeP-M-355 | Race-Telltales From Blinded Notes? Clinical Evidence Or Implicit Bias H Zhou1, D Ruan12*, (1) Dept. of Bioengineering, UCLA, Los Angeles, CA, (2) Dept. of Radiation Oncology, UCLA, Los Angeles, CA |
| PO-GeP-M-360 | Real-Time Long Range Respiratory Prediction J Prinable*, R O'Brien, ACRF Image X Institute, University of Sydney Central Clinical School, Sydney, AU |
| PO-GeP-M-366 | Reducing IMRT QA Workload by 95% and Keeping the Same Level of Quality Control T Nano1*, M Descovich1, E Hirata1, Y Interian2, G Valdes1, (1) University of California, San Franisco, San Francisco, CA, (2) USF, San Francisco, CA |
| PO-GeP-M-389 | Surveillance of Conventionally Fractionated Lung Radiotherapy Using a CBCT Dose Calculation Framework - a Preliminary Study G Lasio*, B Zhang, S Lee, A Gopal, B Yi, Univ. of Maryland School Of Medicine, Baltimore, MD |
| PO-GeP-M-392 | Target Tracking in Kilovoltage Images Using Templates of Fiducial Constellations G Angelis1*, B Zwan1,2, A Briggs1, D Nguyen3, P Keall3, J Booth1,4, (1) Northern Sydney Cancer Centre, Royal North Shore Hospital, Sydney, Australia, (2) School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, Australia, (3) ACRF Image X Institute, The University of Sydney, Sydney, NSW, Australia, (4) School of Physics, University of Sydney, Sydney, Australia |
| PO-GeP-M-396 | The Correction Term of a Three-Pool Kinetic Model for In Vitro Anaerobic Glycolysis Under MRI C Hsieh1,2*, K Lu2,3, G Lin2,3, C Wu4, F Chen4,5, (1) Institute for Radiological Research, Chang Gung University, Taoyuan, TW, ROC, (2) Imaging Core Lab, Chang Gung Memorial Hospital, Linkou, Taoyuan, TW, ROC (3) Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou, Taoyuan, TW, ROC (4) Radiation Biology Core Lab., Chang Gung Memorial Hospital, Linkou, Taoyuan, TW, ROC (5) Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, TW, ROC |
| PO-GeP-M-398 | The Feasibility of Using Radiomics to Detect T-Spine Lytic Bone Metastases in Simulation-CT Images H Naseri*, J Kildea, McGill University, Montreal, QC, CA, |
| PO-GeP-M-399 | The Impact of 5D Accumulated Dose On Toxicity Predictions Compared to Planned Dose for Non-Small Cell Lung Cancer Treated with IMRT and PSPT Y He*, U Titt, Z Liao, J Pollard-Larkin, P Balter, R Mohan, K Brock, UT MD Anderson Cancer Center, Houston, TX |
| PO-GeP-M-410 | Treatment of Oligoresistant and Oligoprogressive Disease in Metastatic Prostate Cancer Patients with Radiation Therapy A Roth1*, G Cooley1, J Smilowitz1, P Ferjancic1, G Liu1, R Jeraj1,2, (1) University of Wisconsin, Madison, WI, (2) University of Ljubljana, SI |
| PO-GeP-M-415 | Using Radiomics to Study Statin Use and Omega-3 Use in Prostate Cancer Patients D Zheng1*, Y Shi2, E Wahle1, L Krajewski1, X Liang3, Q Du2, C Zhang2, S Zhou1, M Baine1, (1) University of Nebraska Medical Center, Omaha, NE, (2)University of Nebraska Lincoln, Lincoln, NE,(3)University of Florida, Jacksonville, FL |
| PO-GeP-M-425 | Validation of Four-Dimensional Computed Tomography Without An External Respiratory Signals Device for the Radiotherapy Planning of Lung Cancer Patients Y Shimohigashi1*, Y Doi1, Y Kono1, M Maruyama1, Y Kai1, R Toya2, (1) Department of Radiological Technology, Kumamoto University Hospital, Kumamoto, Japan,(2) Department of Radiation Oncology, Kumamoto University Hospital, Kumamoto, Japan, |
| PO-GeP-M-431 | Voxel Forecast Classifier to Predict Spatially Variant Binary Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients S Bowen1*, D Hippe1, W Chaovalitwongse2, P Thammasorn2, X Liu2, R Iranzad2, R Miyaoka1, H Vesselle1, P Kinahan1, R Rengan1, J Zeng1, (1) University of Washington, School of Medicine, Seattle, WA, (2) University of Arkansas, Fayetteville, AR |
| PO-GeP-P-11 | Luminance and Non-Uniformity Changes in Primary Monitors Over the 4-Year Period of QA Measurements A Ruuge*, Y Erdi, Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GeP-P-56 | Gender Distribution of Invited Speakers and Moderators at the 59th AAPM Annual Meeting A Roso-Mares1*, S St. James2, A Cetnar3, J Pollard-Larkin4, R Jagsi5, S Evans6, J Moran7, L Cervino8, (1)UCSD,San Diego, CA, (2) UCSF, San Francisco, CA, (3) Ohio State University - James Cancer Hospital, Grove City, OH, (4) The University of Texas MD Anderson Cancer Center, Houston, TX, (5) University Of Michigan, Medical Center, Ann Arbor, MI(6) Yale University, New Haven, CT, (7) University of Michigan Medical Center, Ann Arbor, MI, (8) Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GeP-T-10 | A Comparison of Prediction Models in Autocorrelated Processes for Quality Assurance j Lah1*, G Kim2, D Shin3, (1) Myongji Hospital, Hanyang University College of Medicine, Goyang-si, KR, (2) University of California, San Diego, La Jolla, CA,(3) National Cancer Center, Goyang-si, KR |
| PO-GeP-T-239 | Comprehensive Peripheral Dosimetry for Estimation of Fetal Dose in the Setting of Intracranial Radiation Therapy A Rodrigues*, E Cullom, K Pant, W Giles, Duke University Medical Center, Durham, NC |
| PO-GeP-T-254 | Data-Driven Dose Volume Histogram Prediction M Polizzi1*, R Watkins2, W Watkins3, (1) Virginia Commonwealth University, Richmond, VA, (2) Virginia Polytechnic Institute and State University, Department of Computational Modeling and Data Analytics, (3) University of Virginia, Charlottesville, VA |
| PO-GeP-T-409 | Evaluation of PET/clinical Parameters to Predict Toxicity in Chimeric Antigen Receptor T-Cell Therapy Patients with Relapsed/refractory Non-Hodgkin Lymphoma C Uche*, C Wright, J Baron, M Lariviere, A Barsky, D Miller, A Maity, J Plastaras, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| PO-GeP-T-442 | Failure Mode and Effects Analysis for PET Applications in Radiation Therapy Quality Management A Rodrigues*, J O'Daniel, Y Mowery, F Yin, Y Cui, Duke University Medical Center, Durham, NC |
| PO-GeP-T-531 | Investigating How Various Parameters Influence Secondary Neutron Spectra Produced During High-Energy Electron-Beam Treatments F Mathew1*, G Al Makdessi2, L Montgomery1, J Kildea1, (1) McGill University, Montreal, QC, CA, (2) McGill University Health Centre, Montreal, QC, CA |
| PO-GeP-T-560 | Lens Dose to Standing Patients Treated With Electrons to the Hand J Van Schelt*, Rush University Medical Center, Chicago, IL |
| PO-GeP-T-593 | Monte Carlo-Based Organ Dose Reconstruction for Wilms Tumor Patients During Cobalt-60 External Beam Therapy J Dempsey1*, M Pauliah2, M Mille3, M Gopalakrishnan2, J Jung1, J Kalapurakal2, C Lee3, (1) East Carolina University, Greenville, NC, (2) Northwestern University, Chicago, IL, (3) National Cancer Institute, Rockville, MD |
| PO-GeP-T-700 | Reduction of Interobserver Contouring Variations Through a Retrospective, Evidence-Based Intervention H Patrick1*, L Souhami2, J Kildea1,2, (1) McGill University, Montreal, QC, CA, (2) McGill University Health Centre, Montreal, QC, CA, |
| PO-GeP-T-736 | Standardization of CSI Treatment Planning and Its Evaluation Using a DVH Registry E Sepulveda, MSc*, H Patrick, MSc, J Kildea, PhD, McGill University, Montreal, QCCA, |
| PO-GeP-T-819 | Update On a Dose Reconstruction Effort for a Large-Scale Retrospective Epidemiological Study of Late Health Effects Following Radiotherapy Within the National Wilms Tumor Study M Mille1*, M Pauliah2, J Jung3, M Gopalakrishnan2, J Kalapurakal2, C Lee1, (1) National Cancer Institute, Rockville, MD, (2) Northwestern University, Chicago, IL, (3) East Carolina Univ, Greenville, NC |
| PO-GeP-T-856 | Workflow Analysis for Framed Gamma Knife Treatments J Liu*, E Calugaru, J Chang, Northwell Health, Lake Success, NY |
| PO-GeP-T-857 | Workflow Analysis of Frameless Gamma Knife Treatments J Liu*, E Calugaru, J Chang, Northwell Health, Lake Success, NY |
| SU-CD-TRACK 2-8 | Multi-Block Discriminant Analysis of Integrative 18F-FDG-PET/CT Radiomics for Predicting Circulating Tumor Cells in Early Stage Non-Small Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy S Lee*, G Kao, S Feigenberg, J Dorsey, M Frick, S Jean-baptiste, C Uche, Y Fan, Y Xiao, University of Pennsylvania, Philadelphia, PA |
| SU-E-TRACK 1-3 | Machine Learning and Texture Analysis of Thoracic X-Ray Computed Tomography to Reveal Subclinical Emphysema M Sharma1,2*, AR Westcott1,2, JL MacNeil1,3, DG McCormack4 and G Parraga1-4, (1) Robarts Research Institute, (2) Department of Medical Biophysics, (3) School of Biomedical Engineering, (4) Department of Medicine, Western University, London, ON, Canada |
| SU-E-TRACK 3-4 | Multi-Institutional Data Mining of IMRT QA Results and Control Charts Per TG-218 Using the Open-Source Software IQDM J George1*, S Kucuker Dogan2, M Chamberland3, D Cutright1, (1) University of Chicago Medicine, Chicago, IL, (2) Northwestern Memorial Hospital, Chicago, IL, (3) The University of Vermont Medical Center, Burlington, VT |
| SU-F-TRACK 1-7 | The Application of Partial Domain Adaptation Transfer Learning in the Classification of Retinopathy Using OCT Images From Different Datasets J Wu1*, D Li1, YM Yang2, (1) Shandong Normal University, Jinan, Shandong, CN, (2) UCLA, Los Angeles, CA |
| SU-F-TRACK 2-2 | Automatic On-Board Liver Tumor Localization by Cone-Beam Projections and a Deformation-Driven Technique (U-Net-Bio) Y Zhang*, J Wang, X Huang, Y Zhang, UT Southwestern Medical Center, Dallas, TX |
| SU-F-TRACK 2-5 | Progressively Grown GAN with Learned Fusion Operation for Hetero-Modal Synthesis of MRI Sequences D Gourdeau1*, S Duchesne2, L Archambault3, (1) Universite Laval, Quebec, QC, CA, (2) Centre de recherche CERVO, Quebec, QC, CA (3) CHUQ Pavillon Hotel-Dieu de Quebec, Quebec, QC, CA |
| TH-A-TRACK 5-6 | Practical Treatment Techniques for Fetal Dose Reduction in Intracranial Stereotactic Radiation Therapy W Giles*, F Yin, J Torok, A Rodrigues, Duke University Medical Center, Durham, NC |
| TH-AB-TRACK 4-8 | Dosimetric Validation of An Artificial Intelligence Encapsulated Knowledge Transfer Across Medical Domains Applied to Heart Contouring for Treatment Planning C V Guthier1*, R Zeleznik1, J Weiss1, J Taron2, C Hancox1, D Bitterman1, D Kim1, R Punglia1, B Foldyna2, M Lu2, B Kann1, J Bredfeldt1, U Hoffmann2, H Aerts1, R Mak1, (1) Dana-Farber/Brigham and Women's Cancer Center and Harvard Medical School, Boston, MA, (2) Massachusetts General Hospital and Harvard Medical School, Boston, MA, |
| TH-AB-TRACK 4-10 | Lung Functional Avoidance Radiotherapy: Characterizing Spatial Differences Between Ventilation and Perfusion F Forghani1*, T Patton1, D Thomas1, Q Diot1, C Rusthoven1, R Castillo2, E Castillo3, I Grills3, T Guerrero3, M Miften1, Y Vinogradskiy1, (1) University of Colorado Anschutz Medical Campus, Aurora, CO (2) Emory Univ, Atlanta, GA, (3) Beaumont, Royal Oak, MI |
| TH-AB-TRACK 4-13 | Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer L Chen1*, M Dohopolski1, Z Zhou2, K Wang1, R Wang1, D Sher1, J Wang1, (1) UT Southwestern Medical Center, Dallas, TX, (2) University Of Central Missouri, Warrensburg, MO |
| TU-CD-TRACK 2-15 | Effect of Deformable PET/CT Image Registration Uncertainty On Intratumoral Dose Response Assessment S Chen*, A Qin, D Krauss, D Yan, William Beaumont Hospital, Royal Oak, MI |
| WE-D-TRACK 1-6 | Comparison of Automated Methods for Detection and Prognostication in Metastatic Prostate Cancer Using 18F-NaF PET/CT Images B Schott*1, A J Weisman1, T G Perk1, A R Roth1, S Yip2, G Liu1, R Jeraj13, (1) University of Wisconsin, Madison, WI, (2) AIQ Solutions, Madison, WI, (3) University of Ljubljana, Slovenia |
| WE-E-TRACK 2-4 | Classification of LGG Tumor IDH1 Gene Mutation Status Using T2/FLAIR MRI Texture Information M Safari1, 2*, L Archambault1, 2, A Ameri3, A Fatemi4, M Beigi5, (1) Department of Physics, Universite Laval, Quebec, QC, CA, (2) CHU de Quebec - Universite Laval, Quebec, QC, CA, (3) Department Of Clinical Oncology, Shahidbeheshti University, (4) University of Mississippi Med. Center, Jackson, MS, (5) Novin Medical Radiation Institute, Haft Tir Martyrs Hospital, Tehran, Iran. |
| WE-E-TRACK 2-6 | Deciphering Metabolic Features to Target Neuroblastoma Using Machine Learning R Wang1,2,3*, Y Zhang1,4, P Pachnis4, H Vu4, K Wang1,3, R Deberardinis4, J Wang1,3, (1) Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX. (2) School of Artificial Intelligence, Xidian University, Xi'an, People's Republic of China. (3) Medical Artificial Intelligence and Automation (MAIA) Lab, University of Texas Southwestern Medical Center, Dallas, TX. (4) Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, TX. |
| WE-E-TRACK 2-7 | Phenotyping Potential of Topologically Invariant Betti Numbers for Epidermal Growth Factor Receptor Mutations in Non-Small Cell Lung Cancer Patients K Ninomiya1*, H Arimura1, W Chan2, K Tanaka3, S Mizuno1, N Muhammad Gowdh2, N Yaakup2, C Liam2, C Chai4, K Ng2, (1)Kyushu University, (2)University Of Malaya, (3)Kyushu University Hospital, (4) University Malaysia Sarawak |
| WE-F-TRACK 1-4 | Deep-Learning for Differentiation of Benign From Malignant Parotid Lesions On MR Image B Feng1,2*, X Xia3, L Xu4, C Hu1,2, J Wang1,2, Z Zhang1,2, W Hu1,2, (1) Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, CN (2) Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, CN (3) Department of Radiology, Municipal Hospital Affiliated to Medical School of Taizhou University, Taizhou, CN (4) Department of Radiology, the Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, CN |
| WE-F-TRACK 1-5 | Prediction of Gleason Grade Group of Prostate Cancer On Multiparametric MRI Using Deep Learning, Transfer Learning, Representation Learning and Prototype Network W Zong*, M Pantelic, E Mohamed, N Wen, Henry Ford Health System, Detroit, MI |