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Keywords: MR
| MO-B-BRC-2 | Comprehensive Evaluation of a Real-Time 3D MR Imaging Technique Using a Deformation-Driven Deep Convolutional Neural Network (KS-RegNet) H Shao1*, T Li2, M Dohopolski1, J Wang1, J Cai2, J Tan1, K Wang1, Y Zhang1, (1) The University of Texas Southwestern Medical Center, Dallas, TX, (2) The Hong Kong Polytechnic University, Hong Kong, HK |
| MO-B-BRC-4 | Patient-Specific Transfer Learning to Enhance the Performance of Deep Learning Auto-Segmentation in 0.35 T MRgRT for Prostate Cancer M Kawula1*, I Hadi1, L Nierer1, M Vagni2, D Cusumano2, L Boldrini2, L Placidi2, S Corradini1, C Belka1,3, G Landry1, C Kurz1, (1) Department of Radiation Oncology, University Hospital, LMU Munich, Germany, (2) Fondazione Policlinico Universitario Agostino Gemelli, Rome, Italy, (3) German Cancer Consortium (DKTK), Munich, Germany |
| MO-C930-IePD-F9-1 | Can Abnormal Pudendal Nerve Be Detected and Evaluated Using MR DWI ADC Values - A Preliminary Study J James*, PhD, A Jawahar, MD, Department of Radiology, Loyola University Medical Center, Maywood, IL |
| MO-C930-IePD-F9-2 | Comparison of Effective Connectivity and Functional Connectivity for Brain Health in Middle-Aged Adults K Chuang1,2*, S Ramakrishnapillai2, K Madden2, J St Amant2, K Gwizdala 2, R Dhullipudi2, L Bazzano3, O Carmichael2, (1) Louisiana State University, Baton Rouge, LA, (2) Pennington Biomedical Research Center, Baton Rouge, LA, (3) Tulane School of Public Health and Tropical Medicine, New Orleans, LA |
| MO-C930-IePD-F9-3 | Automatic Organ Contouring for Head and Neck MR-Guided Online Adaptive Radiotherapy Using Neural Networks V Koteva1, D Mcquaid2, A Dunlop3, B Eiben4, E Persson5*, U Oelfke6, (1) The Institute of Cancer Research, Iver, BKM, GB, (2) Royal Marsden Hospital, ,,(3) Royal Marsden Hospital, ,,(4) The Institute Of Cancer Research, (5) Sutton, GB, (6) The Institute of Cancer Research, Sutton |
| MO-C930-IePD-F9-5 | Reducing Bias and Noise in T2* Measurements for Low-SNR Data: A Phantom Study G Anthony1,2*, X Zhang1,3, X Guan1, R Dharmakumar1,2,3, (1) Krannert Cardiovascular Research Center, Indiana University School of Medicine/IU Health Cardiovascular Institute, Indianapolis, IN 46202, (2) Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202, (3) Department of Bioengineering, University of California in Los Angeles, Los Angeles, CA 90095 |
| MO-C930-IePD-F9-6 | In-Vivo Assessments of Creatine-Kinase-Based ATP Buffering in Human Skeletal Muscle Following Isotonic and Isometric Exercise Using 31P-MRS N Sanchez1*, A Moody1, G Clarke1, (1)University of Texas Health Science Center - San Antonio, San Antonio, TX |
| MO-E115-IePD-F2-3 | Daily 4DMRI Assessed Motion and Its Impact On ITV for Non-Gated MRI-Guided Adaptive Radiation Therapy of Liver Cancer E Omari*, H Jassar, M Straza, E Paulson, X Chen, E Ahunbay, W Hall, X Li, Medical College of Wisconsin, Milwaukee, WI |
| MO-E115-IePD-F2-4 | Low-Dose Contrast-Enhancement MRI Using Deep Learning with Patient-Specific Image Prior for Liver Cancer Adaptive Radiotherapy Y Gao, J Deng, X Jia*, The University of Texas Southwestern Medical Ctr, Garland, TX |
| MO-E115-IePD-F6-1 | Experimental Validation of the Dosimetric Impact of a Gadolinium-Based Contrast Agent On a Photon Beam in the Presence of 1.5 T Magnetic Field K Hall1*, L Kim1, G Ibbott2, F Riaz4, M Reyhan3,4, (1) MD Anderson Cancer Center at Cooper, Camden, NJ, (2) The American Board of Radiology, Tucson, AZ, (3) Robert Wood Johnson University Hospital, Hamilton, NJ,(4) Rutgers Cancer Institute of New Jersey, New Brunswick, NJ |
| MO-E115-IePD-F6-3 | Retrospective Cardio-Respiratory Motion Corrected Dose Evaluation for the Left Ventricle and Left Ventricle Myocardium From Lung Radiation Therapy Treatments A Omidi1*, E Weiss2, J Wilson1,3, M Rosu-Bubulac2, (1) Department of Biomedical Engineering, School of Engineering, Virginia Commonwealth University, Richmond, VA, (2) Department of Radiation Oncology, School of Medicine, Virginia Commonwealth University, Richmond, VA, (3) Pauley Heart Center, School of medicine, Virginia Commonwealth University, Richmond, VA, |
| MO-E115-IePD-F6-4 | 4D-THRIVE MRI for Internal Target Volume Estimation in Abdominal and Lung Radiation Therapy J Deng, T Aguilera, R Hannan, A Godley*, University of Texas Southwestern Medical Ctr, Dallas, Texas |
| MO-E115-IePD-F6-5 | Real Time Volumetric MRI From Ultra-Sparse Samples Via Implicit Neural Representation Learning R Yesiloglu1*, L Shen2, A Johansson3, Y Cao4, J Balter5, L Xing6, L Liu7, (1) Stanford University, Stanford, CA, (2)Stanford University,Palo Alto, CA, (3) Uppsala University, Sweden, (4) University of Michigan, Ann Arbor, MI, (5) University of Michigan, Ann Arbor, MI, (6) Stanford University School of Medicine, Stanford, CA, (7) Stanford University, Palo Alto, CA |
| MO-E115-IePD-F6-6 | A Hybrid Model Derived From Multi-Parametric MRIs for Predicting Neoadjuvant Chemoradiation Response in Locally Advanced Rectal Cancer Hao CHEN1*, Xing Li2, X. Sharon Qi3, (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 |
| MO-FG-BRB-2 | A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI Based Glioma Segmentation Z Yang1*, Z Hu2, H Ji3, K Lafata1, S Floyd1, F Yin1, C Wang1, (1) Duke University, Durham, NC, (2) Duke Kunshan university, Kunshan, Jingsu, China, (3) North Carolina State University, Raleigh, NC |
| MO-FG-BRB-9 | MRI Detection of Iron Metabolism to Predict GBM Outcomes M Petronek*, C Lee, V Monga, J Buatti, J St-Aubin, D Spitz, V Magnotta, B Allen, University of Iowa Carver College of Medicine, Iowa City, IA |
| MO-G-BRA-0 | Recent Task Group Reports On Brachytherapy: TG-222 and TG-303 H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-1 | Introduction H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-2 | Mesh Brachytherapy Planning Techniques and Dosimetric Parameters H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-3 | Mesh Brachytherapy Quality Management and Medical Event Definition H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-4 | Protocol Development and MRI Basics for the Implementation of MRI in High Dose Rate Brachytherapy H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-5 | Applicator Commissioning and Workflow Development for the Implementation of MRI in High Dose Rate Brachytherapy H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRA-6 | Q & A H Zhang1*, W Feng2*, K Hwang3*, J Zoberi4*, (1) Northwestern Memorial Hospital, Chicago, IL, (2) Saint Barnabas Medical Center, Tenafly, NJ, (3) UT MD Anderson Cancer Center, Sugar Land, TX, (4) Washington University School of Medicine, Saint Louis, MO |
| MO-G-BRC-6 | Technical Feasibility of Real-Time Cardiorespiratory Motion Mitigation Using MRI-Guided MLC-Tracking On the Unity MR-Linac P Borman*, P Uijtewaal, O Akdag, P Woodhead, B Raaymakers, M Fast, University Medical Center Utrecht, Utrecht, NL |
| MO-H345-IePD-F1-4 | Define Target Volume for Cardiac Radioablation Surgery Using Integration of Endoventricle Electroanatomic Mapping and Coherent Point Drift T Chen*, H Wang, Y Yuan, C Barbhaiya, D Barbee, New York University, New York, NY |
| MO-H345-IePD-F6-6 | Evaluation of Striatal Functional Connectivity Changes Across Heavy and Non-Heavy Alcohol Drinking Rhesus Macaques with Resting State FMRI K Ruano Espinoza1, 2*, K Grant 2* C Kroenke 3,2*, (1) Oregon Health and Science University (OHSU), Beaverton, OR (2) Oregon National Primate Research Center, Division of Neuroscience, Hillsboro, OR (3) Advanced Imaging Research Center, Portland, OR |
| MO-I430-BReP-F2-5 | Development and Validation of Strong Tesla Electron Return Effect Reduction (STEER) Planning Technique for Centrally Located Lung Radiotherapy with MR-Linac System J Visak*, B Cai, M Lin, A Pompos, A Godley, P Iyengar, C Park, K Westover, University of Texas Southwestern Medical Center, Dallas, TX |
| PO-GePV-I-24 | The ACR MRI QC Low-Contrast Detectability Test and the Rose Model H Gach1*, (1) Washington University School of Medicine in St. Louis, St. Louis, MO |
| PO-GePV-I-25 | Real-Time Quality Control of RF Coils Using Clinical MRI Data T McKeown1*, S Robertson2*, E Samei2, (1) Duke University, Durham, NC, (2) Duke University Health System, Durham, NC |
| PO-GePV-I-26 | Comparison Between EPI DWI and PROPELLER DWI in MR Brain Imaging P Mavroidis1*, E Giankou2, M Papaioannou3, V Roka4, A Tsikrika5, S Kostopoulos6, D Glotsos7, G Sakkas8, E Dardiotis9, D Chaniotis10, S Stathakis11, E Kapsalaki12, E Lavdas13, (1) University of North Carolina, Chapel Hill, NC, (2) ,,,(3) Animus Kyanoys Stavros, Larissa, ,GR, (4) Health Center of Farkadona, Trikala, ,GR, (5) General University Hospital of Larissa, Larissa, ,GR, (6) University of West Attica, Athens, ,GR, (7) ,,,(8) University of Thessaly, Trikala, ,GR, (9) ,,,(10) ,,,(11) Mays Cancer Center - MD Anderson Cancer Center, San Antonio, TX, (12) ,,,(13) University of West Attica, Athens, ,GR |
| PO-GePV-I-27 | Implementation and Testing of Intermolecular Multiple Quantum Coherence MRI On Clinical 3T MRI for Brown Adipose Tissue Detection R Dugan1*, K Kirby2, O Carmichael3, (1) Louisiana State University, Baton Rouge, LA, (2) Mayo Clinic, Rochester, MN, (3) Pennington Biomedical Research Center, Baton Rouge, LA |
| PO-GePV-I-30 | Pharmacokinetic Modeling for Hyperpolarized MRI of 13C Urea K Michel1*, C Walker1, S Lai1, M Merritt2, J Bankson1, (1) The University of Texas MD Anderson Cancer Center, Houston, TX, (2) The University of Florida, Gainesville, FL |
| PO-GePV-I-31 | Quantifying the Influence of a Vendor DL Reconstruction Algorithm On MR Image Quality J Sanders, RJ Stafford*, C Walker, UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-I-33 | The 'BEST' Method of Measuring SNR of MRI QA Images M NessAiver1*, E Nessaiver2, S Nessaiver3, A NessAiver4 (1) Simply Physics, Baltimore, MD, (2) Johns Hopkins University, ,,(3) Simply Physics Inc,(4) Simply Physics Inc |
| PO-GePV-I-35 | MRS and Diffusion MRI in a Maternal Obesity Model of Developmental Programming in Baboon Offspring J Vasquez1*, H Huber2, L Cox3, P Nathanielsz4, Geoffrey Clarke1, (1) University of Texas Health Science Center at San Antonio, San Antonio, TX, (2) Texas Biomedical Research Institute, San Antonio, TX, (3) Wake Forest School of Medicine, Winston-Salem, NC, (4) University of Wyoming, Laramie, Wyoming |
| PO-GePV-I-41 | 3D Super-Resolution Reconstruction for Hippocampus Sparing in Brain Radiotherapy (in Silico Study) Juyoung Lee1,2*, Jaehee Chun2,3, Jin Sung Kim2,3, Taeho Kim1, (1) Washington University School of Medicine in St. Louis, St. Louis, MO, (2) Yonsei University College of Medicine, Seoul, KR, (3) Oncosoft Inc., Seoul, KR |
| PO-GePV-I-42 | Importance of Determining the Maximum Magnetic Displacement Forces for Implanted Devices Everywhere Within the Magnet Bore: A 3T-7T Comparison Study L Bardwell Speltz*, K Kirby, P Trester, I Langenfeld, M Bernstein, A Fagan, Mayo Clinic, Rochester, MN |
| PO-GePV-I-44 | Gd-Doped Gel Phantom Recipe Calculator for 3T MRI Z Razi1*, A Bumin1, H Gao1, Z Zhang2, M Arreola1, (1) University of Florida, Gainesville, FL (2) Washington University School of Medicine, Saint Louis, MO |
| PO-GePV-I-89 | Preclinical Tumor Growth Delay Is More Reliably Derived From Imaging-Based Volume Measurements Than Manual Caliper Measurements M Shotbolt*, J Castro, B Spieler, S Welford, I Mihaylov, University of Miami, Miami, FL |
| PO-GePV-M-28 | Determination of Optimal MR Scheduled Exam Slot Time by Retrospective Analysis of Performed Exam Durations C MacLellan1,2*, S Berkowitz1,2, B Scherrer3, R MacDougall3, S Dahlstedt1, I Cabral-goncalves1, L Tsai1,2, (1) Beth Israel Deaconess Medical Center, Boston, MA, (2) Harvard Medical School, Boston, MA, (3) Quantivly, Somerville, MA |
| PO-GePV-M-45 | Reference-Guided Contrastive Learning for Overall Survival Prediction in Glioma Patients Using Pre-Operative MRIs Z Yang1*, M Chen1, S Stojadinovic1, Z Wardak1, R Timmerman1, T Dan1, W Lu1, X Gu1,2, (1) UT Southwestern Medical Center, Dallas, TX, (2) Stanford University, Palo Alto, CA |
| PO-GePV-M-64 | Investigating Disease-Stage Dependence of MR-Based Radiomic Feature Reproducibility Against Image Perturbations in Nasopharyngeal Carcinoma T Cheung, S Lam, J Zhang*, J Cai, Hong Kong Polytechnic University, Hong Kong, CN |
| PO-GePV-M-83 | MRI-Based Synthetic CT Images Generated Using 3D Conditional GAN for IMPT Treatment Planning S Chen*, A Qin, R Deraniyagala, X Ding, William Beaumont Hospital, Royal Oak, MI Y Peng, Y Liu, C Zhao, X Deng, Sun Yat-sen University, Guangzhou, Guangdong, China |
| PO-GePV-M-102 | MR-Guided Stereotactic Body Radiation Therapy for Unresectable Primary Liver Cancer: A Six-Year Experience R Chin1*, J Schiff1, A Bommireddy2, K Kang1, N Andruska1, A Price1, O Green1, Y Huang1, K Korenblat1, P Parikh3, J Olsen4, P Samson1, L Henke1, H Kim1, S Badiyan1, (1) Washington University School of Medicine, Saint Louis, MO, (2) Saint Louis University School of Medicine, Saint Louis, MO, (3) Henry Ford Cancer Institute, Detroit, MI (4) University of Colorado School of Medicine, Aurora, CO |
| PO-GePV-M-114 | A Dosimetric Comparison for Adaptive Cone-Beam CT and MRI Based Radiotherapy for Stereotactic Partial Breast Irradiation D Parsons*, L Chen, H Lee, Y Zhang, B Cai, T Zhuang, B Hrycushko, C Park, Y Gonzalez, X Zhong, J Visak, C Nwachukwu, N Kim, P Alluri, A Rahimi, M Lin, University of Texas Southwestern Medical Center, Dallas, TX |
| PO-GePV-M-181 | MR-CT Image Registration by Using Unsupervised Deep Learning Model M Tavakoli1*, S Abbasi2, H Hamid Reza Boveiri3, M Mosleh-Shirazi4, A Mehdizadeh5, (1) University of Pittsburgh School of Medicine and UPMC Hillman Cancer Center, Pittsburgh, PA, USA, PA, (2) Shiraz University of Medical Sciences, Shiraz, IR, (3) Sama College, Iau, Shoushtar Branch, (4) Shiraz University of Medical Sciences, Shiraz, IR, (5) Shiraz University Of Medical Sciences, |
| PO-GePV-M-182 | Automated Multimodality Image Registration for Application in Brachytherapy Using U-Net Based Organ Segmentation K Qing1*, X Feng2, 3, S Glaser1, W Watkins1, D Du1, Y Chen1, C Han1, J Liang1, J Liu1, B Liu1, Q Chen1, A Liu1, (1) City of Hope National Medical Center, Duarte, CA, (2) University of Virginia, Charlottesville, VA, (3) Carina Medical LLC, Lexington, KY |
| PO-GePV-M-194 | Feasibility of PTV Margin Reduction for Pelvic Oligometastatic Disease Treated Using MRI-Guided Adaptive Radiotherapy J Snyder1*, J St. Aubin1, D Dunkerley1, D Hyer1, (1) University of Iowa Hospitals and Clinics, Iowa City, IA |
| PO-GePV-M-201 | Automatic Segmentation of Rectal Tumor On Magnetic Resonance Images Via A Deep Discriminative Model Consisting of U-Net and Conditional Random Field Based Post-Processing Hao CHEN1*, Xing Li2, X. Sharon Qi3, (1) Xi'an University of Posts and telecommunications, Xian, ,CN, (2) Xi'an University of Posts and Telecommunications, Xian, Shaanxi Province, CN, (3) UCLA School of Medicine, Los Angeles, CA |
| PO-GePV-M-203 | Automated Segmentation of Vestibular Schwannomas From MRI with Deep Neural Network H Wang*, T Qu, K Bernstein, D Barbee, D Kondziolka, NYU Langone Medical Center, New York, NY |
| PO-GePV-M-204 | Integration of Color Diffusion Tensor Tractography Images Into Contouring Workflows with Commercial Software Z Grelewicz*, K Tatebe, Rush University Medical Center, Chicago, IL |
| PO-GePV-M-224 | A Two-Step Deep Learning Method for Accurate Synthetic CT From Abdominal MRI E Ahunbay1*, J Xu2, A Parchur1, D Thill2, E Paulson1, X Chen1, E Omari1, X Li1, (1) Medical College of Wisconsin, Milwaukee, WI, (2) Elekta, Inc., Atlanta, GA |
| PO-GePV-M-226 | Characterization of Image Quality During MR-Guided Radiotherapy (MRgRT) Localization: Impact of Coil Sensitivity Mapping R Herrera1, J McCulloch1,2, P Shipman2, A Gutierrez1,2, T Romaguera1,2, D Alvarez1,2, I Aizpurua3, M Chuong1,2, M Mehta1,2, J Bayouth4, K Mittauer1,2*, (1) Miami Cancer Institute, Miami, FL (2) Florida International University, Miami, FL (3) ViewRay Inc, Oakwood, OH (4) University of Wisconsin-Madison, Madison, WI |
| PO-GePV-M-227 | Evaluation of Delivered Dose Using Synthetic CT for MR-Guided and CT-Guided Radiotherapy H Wang1*, (1) UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-M-229 | Cross-Validation of MRI Distortion Assessment Using Fiducial and Harmonic Analysis Phantoms P Yan1*, C Velten1,2, Y Alvarado1, J Anias1, Q Peng1,2, W Tome1,2, (1) Montefiore Medical Center, Bronx, NY, (2) Albert Einstein College of Medicine, Bronx, NY |
| PO-GePV-M-231 | A Novel 3D Water Phantom System Designed for Measurements in MR Linear Accelerators T Lee1*, M Yu2, J Wu3, Y Wang4, (1) Department of Nuclear Medicine, National Taiwan University Hospital, Taipei, Taiwan, (2) Department of Radiation Oncology Taipei Medical University Hospital, Taipei, Taiwan, (3) Division of Radiation Oncology, Departments of Oncology, National Taiwan University Hospital, Taipei, Taiwan, (4) Department of Radiation Oncology, Fu Jen Catholic University Hospital, New Taipei City, Taiwan |
| PO-GePV-M-232 | Microstructure Analysis and Dosimetry with EBT Film in MR-Linac P Yadav1*, C Corbella2, M Keidar3, I Das4, (1) Northwestern University Feinberg School of Medicine, Chicago, IL, (2) George Washington University, ,,(3) ,,,(4) Northwestern University Feinberg School of Medicine, Chicago, IL |
| PO-GePV-M-233 | Impact of 0.35 T Magnetic Field On Surface Dose I Das1*, P Yadav2, (1) Northwestern University Feinberg School of Medicine, Chicago, IL, (2) Northwestern University Feinberg School of Medicine, Chicago, IL |
| PO-GePV-M-235 | Correcting Geometric Image Distortion and Isocenter-Shift at Various Gantry Angles On a 0.35T MRgRT S Marasini1*, B Quinn2, M Cole2, R Flores2, T Kim1, (1) Washington University in St. Louis, Saint Louis, MO, (2) Modus Medical Devices, London, ,CA |
| PO-GePV-M-239 | Dosimetric Feasibility of Craniopharyngioma Radiation Therapy Using An MR-Guided Linac K Mooney*1, M Mistro2, C Ainsley1, A Harrison3, A Kubli1, H Liu1, H Nourzadeh1, W Shi1, 1Thomas Jefferson University Hospital, Philadelphia, PA 2University of Virginia, Charlottesville, VA 3ChristianaCare Health System, Newark DE |
| PO-GePV-M-240 | Deep Learning-Based Synthetic CT Generation for MR-Only Adaptive Radiation Therapy On MR-Linacs B Hunt1, B Zaki2, G Russo3, G Asher4*, G Gill5, C Thomas6, T Prioleau7, D Gladstone8, B Pogue9, R Zhang10, (1) Dartmouth College, Hanover, NH, (2) Dartmouth-hitchcock Medical Center, ,,(3) Dartmouth-hitchcock Medical Center, ,,(4) Dartmouth College, ,,(5) Dartmouth-hitchcock Medical Center, ,,(6) Dartmouth-Hitchcock Medical Center, ,,(7) Dartmouth College, ,,(8) Dartmouth College, Hanover, New Hampshire, (9) University of Wisconsin-Madison, Madison, WI, (10) Dartmouth-Hitchcock Med. Ctr., Lebanon, NH |
| PO-GePV-M-241 | A Fast 3D Contour Editing Tool with 3D paintbrush and Edge Detection for MRI-Guided Adaptive Radiation Therapy A Amjad1*, M Moreau2, A Parchur1, E Ahunbay1, D Cooper2, X Li1, (1) Medical College of Wisconsin, Milwaukee, WI, (2) Elekta, Inc, MO |
| PO-GePV-M-242 | MRI-Guided Adaptive Head and Neck Radiotherapy On a 1.5T MR Linac System E Aliotta, J Hesse, E Subashi, P Godoy Scripes, M Aristophanous*, J Mechalakos, L Cervino, N Tyagi, K Zakeri, N Lee, Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GePV-M-246 | Feasibility of Stereotactic Radiotherapy for Base of Tongue Cancers On the MR-Linac H Wang1*, (1) UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-M-248 | Automatic Segmentation of Salivary Glands and Skeletal Muscles for MR-Based Daily Adapted Head and Neck Cancer Radiotherapy C Cardenas1*, T Ermongkonchai2, D Xing3, Z Iqbal1, A Mcdonald1, A Mohamed4, B Harris3, R Khor3, H Bahig5, C Fuller4, S Ng3, (1) The University of Alabama at Birmingham, Birmingham, AL, (2) University Of Melbourne, Melbourne, Australia,(3) Austin Health, Melbourne, Australia, (4) UT MD Anderson Cancer Center, Houston, TX, (5) CHUM |
| PO-GePV-M-249 | Improving Target Dose Coverage with Patient’s Comfort Arms-Down Planning in 0.35T MRgRT S Marasini1*, D Holloway2, J Park3, T Kim1, (1) Washington University in St. Louis, Saint Louis, MO, (2) Viewray (3) University of Texas Southwestern, Dallas, TX, |
| PO-GePV-M-253 | MR-Based Treatment Planning and Plan Adaptation for Treating Cardiac Metastases with MR-Linac J Yang*, P Castillo, A Sobremonte, B Lee, M Pham, N Hughes, M Mohammadsaid, X Wang, P Lee, UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-M-255 | Feasibility of Using AI Generated Synthetic CT Images From a Commercially Available MRI Simulator for Proton Therapy Planning in the Prostate M Saki1*, P Johnson1,2, C Liu2, (1) University of Florida Health Proton Therapy Institute, Jacksonville, FL, (2) University of Florida, Gainesville, FL |
| PO-GePV-M-258 | Inter-Observer and Intra-Observer Variability of Pelvic Organs at Risk Delineation in Multiple Magnetic Resonance Imaging Sequences W Zheng1,2, S Huang1, E Li1,3, J Lian1,4, X Yang1*, (1) Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong province, 510060, China, (2) Department of Radiation Oncology, Southern Theater Air Force Hospital of the People's Liberation Army, Guangzhou, Guangdong province, 510050, China, (3) Guangzhou Xinhua College, Guangzhou, Guangdong, 510520, China,(4) Department of Radiation Oncology, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong province, 510405, China |
| PO-GePV-M-259 | Commissioning Elekta Unity MR Imaging Sequences for MRI-Guided Brachytherapy W Massock*, Y Kim, J St-Aubin, University of Iowa, College of Medicine, Iowa City, IA |
| PO-GePV-M-263 | Feasibility study: Polymer Gel Dosimetry On 0.35T MR-Linac System L Marage*, J Boudet, L Aubignac, I Bessieres, A Petitfils, Centre Georges-Francois Leclerc, Dijon, 21, FR |
| PO-GePV-M-268 | Gating Parameters for MR-Guided Radiotherapy: When One Tracks Not What One Treats C Ainsley*, Thomas Jefferson University, Philadelphia, PA |
| PO-GePV-M-341 | Mapping Tissue Oxygenation in Vivo with MRI Z Zhang*, Washington University School of Medicine, Saint Louis, MO |
| PO-GePV-T-23 | A Novel Quality Assurance System to Evaluate MR-Only Workflow for Interstitial and Intracavitary Gynecological HDR Brachytherapy S Aldelaijan1,2*, H Alsaleh1, C Constantinescu1, S Devic2, I Buzurovic3, B Moftah1,2, (1) King Faisal Hospital & Research Centre, Riyadh, SA, (2) Gerald Bronfman Department of Oncology, McGill University, Montreal, QC, CA, (3) Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, MA |
| PO-GePV-T-34 | Evaluation of the Dosimetric Quality of MRI-Only HDR Brachytherapy Planning with Titanium Ring-And-Tandem Applicators I Veltchev*, T Lin, X Chen, R Price, K Howell, C Ma, Fox Chase Cancer Center, Philadelphia, PA |
| PO-GePV-T-47 | Evaluate Atlas-Based Auto-Segmentation in MR Images for Liver Yttrium-90 Selective Internal Radiation Therapy J Li*, R Anne, Thomas Jefferson University, Philadelphia, PA |
| PO-GePV-T-49 | Radiobiological Comparison of Prostate LDR Brachytherapy with and Without Simultaneously Integrated Boost to the Dominant Intra-Prostatic Lesion Defined by 68Ga-PSMA PET / MpMRI R Holden*, J Lian, S To, T Royce, P Mavroidis, University of North Carolina, Chapel Hill, NC |
| PO-GePV-T-273 | Evaluation of a Novel Plastic Scintillation Detector Performance in MR-LINAC K Yun1*, M Hwang1, D Lee1, S Oh1, M Feijoo2, S Beron2, D Pavord1, (1) Allegheny Health Network, Pittsburgh, PA, (2) Blue Physics LLC, Tampa, FL |
| PO-GePV-T-323 | Open Source Tool to Compare MR-Linac Logfiles with Monaco RT Plans M Kusters1*,J Kaas1, P de Graaf1,S Biggs2 (1) Radboudumc, Nijmegen, NL (2) Radiotherapy AI, AUS |
| PO-GePV-T-332 | Role of MR-Scanning Water Tank in Commissioning of MR-Linac Unit P Yadav1*, I Das2, (1) Northwestern University Feinberg School of Medicine, Chicago, IL, (2) Northwestern University Feinberg School of Medicine, Chicago, IL |
| SU-E-207-2 | Optimizing the Performance of Bloch Fitting for the Analysis of AcidoCEST MRI T Li*, K Jones, FW Schuler, J De La Cerda, A Kotrotsou, S Zhang, M Pagel, UT MD Anderson Cancer Center, Houston, TX |
| SU-E-207-4 | A Ratiometric Method for Assessing Multi-Modal Breast MRI Image Quality B Byrd1,2*, V Krishnaswamy2, J Gui3, M Fox2,4, K Paulsen1,2, R Barth2,4, T Rooney2,5, (1) Thayer School of Engineering at Dartmouth College, Hanover, NH, (2) CairnSurgical, LLC, Lebanon, NH, (3) Geisel School Of Medicine, Hanover, NH (4) Dartmouth-Hitchcock Medical Center, Lebanon, NH (5) University of Virginia Health, Charlottesville, VA |
| SU-E-207-5 | Cross-Site Generalizability of the Optimal Machine Learning Method for Prostate Cancer Diagnosis S Hu1, J Zhang2, X Teng2*, J Cai2, (1) Basis Scottsdale, Scottsdale, AZ, USA, (2) The Hong Kong Polytechnic University, Hong Kong, CN |
| SU-E-207-6 | A Method to Extract the Cardiac Cycle Signal Directly for 2D Cine MR and CBCT Projection Images X Wu1*, H Yao1, G Hugo1, C Eldeniz1, H An1, H Gach1, D Yang2, (1) Washington University in Saint Louis, St. Louis, MO, (2) Duke University, Chapel Hill, NC |
| SU-E-207-7 | Using Radiomic Study Design Recommendations to Optimize Classification Performance in Brain Metastases D Mitchell*, S Buszek, B Tran, H Liu, C Chung, UT MD Anderson Cancer Center, Houston, TX |
| SU-E-BRA-8 | Validity of Definition of the Sclin in Small Fields Used in MR-Linac I Das*, P Yadav, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL |
| SU-F-206-3 | Changes of Magnetic Resonance Radiomics in Response to Radium-223 Dichloride in Combination with Androgen Deprivation Therapy (ADT) and Stereotactic Body Radiation Therapy (SBRT) for Patients with Oligometastatic Castration Sensitive Prostate Cancer K Qing1*, T Ketcherside1, A Liu1, B Liu1, C Han1, W Watkins1, X Feng2,3, L Zhao4, Q Chen1, J Liu1, S Dandapani1, (1) City of Hope National Medical Center, Duarte, CA, (2) University of Virginia, Charlottesville, VA, (3) Carina Medical LLC, Lexington, KY, (4) Zhejiang University, Hangzhou, China |
| SU-F-207-1 | A Multi-Parametric Quantitative MR Protocol for Pre-Operative Radiotherapy Response Assessment in Soft-Tissue Sarcomas I Thrussell1,2*, J Winfield1,2, C Messiou1,3, S Usman2, J Newman2, R Simoes1,4, G Hopkinson2, S Zaidi1,4, A Miah1,4, M BLACKLEDGE1,2, (1) Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK, (2) MRI, The Royal Marsden NHS Foundation Trust, London, UK,(3) Department of Radiology, The Royal Marsden NHS Foundation Trust, London, UK,(4) Sarcoma Unit, The Royal Marsden NHS Foundation Trust, London, UK |
| SU-F-207-2 | Fast High-Resolution 3D Magnetization-Prepared GRE with Complementary Phase-Cycling Acquisitions Q Peng1*, Y Zhao2, C Wu3, N Kirby4, (1) Montefiore Medical Center, Bronx, NY, (2) Philips Healthcare, ,,(3) Memorial Sloan Kettering Cancer Center, New York, NY, (4) University of Texas HSC SA, San Antonio, TX |
| SU-F-207-4 | Accelerated MRI Reconstruction Using Variational Feedback U-NET with Transfer Learning Y Zhou1*, R Paul2, P Ding2, R Battle1, A Patel1, B Li2, (1) Mayo Clinic Arizona, Phoenix, AZ, (2) CIDAS, Arizona State University, Tempe, Az, United States |
| SU-F-207-5 | Association Between Liver Tumor and Surface Motion From Cine MR Images On An MRI-Linac W Mao*, J Kim, I Chetty, Henry Ford Health System, Detroit, MI |
| SU-F-207-6 | Breast Lesion Characterization Using Kinetic Features Measured On Ultrafast DCE-MRI F Pineda*, Z Ren, K Kulkarni, H Abe, G Karczmar, University of Chicago, Chicago, IL |
| SU-F-207-7 | Investigation of the RF Heating Risk From Gas Supply Line During MR Guided Cryoablation L Ren*, C Favazza, J Felmlee, D Woodrum, S Thompson, D Adamo, A Lu, Mayo Clinic, Rochester, MN |
| SU-F-BRB-3 | Automatic Image and Contour Augmentation for Deep Learning Auto-Segmentation of Complex Anatomy N Dang*, Y Zhang, A Amjad, J Ding, C Sarosiek, X Li, Medical College of Wisconsin, Milwaukee, WI |
| SU-F-BRC-4 | Ultra-Quality Multi-Parametric 4D-MRI for Real-Time Tumor Tracking in Liver Radiation Therapy Using A Dual-Supervised Downsampling-Invariant Deformable Registration Model H Xiao1*, X Han1, S Zhi1, Y Wong1, C Liu1, W Li1, W Liu2, W Wang2, Y Zhang2, H Wu2, H Lee3, A Cheung4, H Chang3, T Li1, J Cai1, (1) The Hong Kong Polytechnic University, Hong Kong, 91, CN, (2) Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, 11, CN, (3) The University Of Hong Kong, ,,(4) Queen Mary Hospital, ,, |
| SU-F-BRC-6 | Patient-Specific Synthetic MRI Generation From CBCT for Image Guidance in Liver SBRT Z Zhang1*, Z Jiang2, K Lu3, F Yin4, L Ren5, (1) Duke University, Durham, NC, (2) Duke University, Durham, NC, (3) Duke University, Chapel Hill, NC, (4) Duke University Medical Center, Chapel Hill, NC, (5) University of Maryland, Baltimore, MD |
| SU-F-BRC-8 | Development and Validation of a Novel Multi-Modal (MRI and KVCT) Method to Determine Proton Stopping Power Ratio R Marants1*, J Scholey2, E Kaza1, X Miao3, T Benkert4, A Sudhyadhom1, (1) Brigham and Women's Hospital | Dana-Farber Cancer Institute | Harvard Medical School, Boston, MA, (2) University of California San Francisco, San Francisco, CA, (3) Siemens Medical Solutions USA Inc., Malvern, PA, (4) Siemens Healthcare GmbH, Erlangen, Germany |
| SU-H300-IePD-F9-1 | Nonlinear Conditional Time-Varying Granger Causality of Task FMRI Data Via Deep Stacking Networks K Chuang1,2*, S Ramakrishnapillai2, L Bazzano3, O Carmichael4, (1) Louisiana State University, Baton Rouge, LA, (2) Pennington Biomedical Research Center, Baton Rouge, LA, (3) Tulane School Of Public Health And Tropical Medicine, New Orleans, LA |
| SU-H300-IePD-F9-2 | Developing Phenotypic-Specific Brain Templates for DTI-Based Analysis L LeMerise1*, J Guerrero2, S Hartley3, A Alexander4, B Christian5, (1) University of Wisconsin-Madison, Madison, WI, (2) University of Wisconsin Madison, Madison, WI, (3) University Of Wisconsin-Madison, Madison, WI,(4) University of Wisconsin - ADCL, Madison, WI, (5) University of Wisconsin, Madison, WI |
| SU-H300-IePD-F9-4 | An In-Vivo Evaluation of MRI Sequences for Online Adaptive Cardiac Radioablation in the Presence of Cardiac Implantable Devices On a 1.5 T MR-Linac O Akdag1*, ALH Van Lier1, S Mandija1, R Keesman1,2, PTS Borman1, SMG Van De Pol1, JJC Verhoeff1, FAA Mohamed Hoesein1, RJ Hassink1, BW Raaymakers1, MF Fast1, (1) University Medical Center Utrecht, Utrecht, NL, (2) Radboud University Medical Center, Nijmegen, NL |
| SU-H300-IePD-F9-5 | Synthesizing High-Resolution 4D Cine MR Images for Mobile Tumor Motion Assessment J Lee1,2*, H Gach1, E Laugeman1, J Chun2,3, J Kim2,3, T Kim1, (1) Washington University School of Medicine in St. Louis, St. Louis, MO, (2) Yonsei University College of Medicine, Seoul, KR, (3) Oncofost Inc., Seoul, KR |
| SU-H330-IePD-F5-1 | Dosimetric and Image Quality Assessment of a Novel Deep Learning-Based Framework for MRI Synthesis From CT for Prostate High Dose-Rate Brachytherapy A Podgorsak1,2*, B Venkatesulu1,2, M Abuhamad3, M Harkenrider1,2, A Solanki1,2, J Roeske1,2, H Kang1,2, (1) Department of Radiation Oncology, Stritch School of Medicine, Cardinal Bernadin Cancer Center, Loyola University Chicago, Maywood, IL, (2) Loyola University Medical Center, Maywood, IL, (3) Department of Computer Science, Loyola University Chicago, Chicago, IL |
| SU-H330-IePD-F5-3 | A Deep Learning Method to Improve the Quality for High-Speed Imaging in a 1.5 T MRI Radiotherapy System J Zhu*, X Chen, B Yang, R Wei, S Qin, Z Yang, Z Hu, J Dai, K Men, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Beijing, 11CN, |
| SU-H330-IePD-F6-1 | Improvement of Online Treatment Planning with the MR-Linac Using Fat-Suppressed MRI T Salzillo1*, A Dresner2, A Way1, K Wahid1, S Mulder1, A Yoder1, S Ahmed1, K Corrigan1, G Manzar1, L Andring1, C Pinnix1, R Stafford3, A Mohamed1, J Wang4, C Fuller1, (1) Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX (2) Philips Healthcare (3) Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX (4) Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX |
| SU-H330-IePD-F6-3 | Towards Automated QA Using the Electronic Portal Imaging Device in a High-Field MR-Linac J Liang1*, S Lim2, N Tyagi3, X Gonzalez Souto4, J Moran5, E Subashi6, (1, 2, 3, 5, 6) Memorial Sloan-Kettering Cancer Center, New York, NY, (4) Elekta, Atlanta, GA |
| SU-H330-IePD-F6-4 | Fabrication of a Novel Device Insert to Assess Feasibility of Manually Gated Treatments On MR Linac J Visak, D Parsons, T Chiu, A Godley, J Deng*, University of Texas Southwestern Medical Center, Dallas, TX |
| SU-H330-IePD-F6-5 | Real-Time Motion Monitoring Under Deep Inspiration Breath Hold Using Orthogonal Cine MRI for Abdominal Targets On MR-Linac H Jassar1*, A Tai1, X Chen1, E Paulson1, F Lathuiliere2, S Beriault2, F Hebert2, L Savard2, D Cooper2, S Cloake2, X Li1, (1) Medical College of Wisconsin, Milwaukee, WI, USA,(2) Elekta, Stockholm, Sweden |
| SU-H330-IePD-F6-6 | Pancreatic Tumor Motion Correlation with Common Motion Surrogates On Cine MRI Acquired with a MR-Linac System B Lewis1,2*, A Guta1, J Shin1,3, Z Ji1, J Kim3, T Kim1, (1) Washington University in St. Louis, St. Louis, MO, (2) UT MD Anderson Cancer Center, Houston, TX, (3) Yonsei University College of Medicine, Seoul, ,KR |
| SU-H400-IePD-F8-1 | Dense UNet for Automatic Contour Correction On Abdominal MRI for MR-Guided Adaptive Radiation Therapy C Sarosiek*, J Ding, A Amjad, Y Zhang, N Dang, X Li, Medical College of Wisconsin, Milwaukee, WI |
| SU-H400-IePD-F8-2 | Feasibility of Predicting Deliverable Daily Plans Using Deep Learning for MR-Guided Adaptive Radiation Therapy S Hamdan1*, H Nasief1, L Buchanan2, Y Zhang1, E Omari1, X Li1, (1) Medical College of Wisconsin, Milwaukee, WI, (2) Brown University, Providence, RI |
| SU-H400-IePD-F8-4 | On-Line Adaptive and Real-Time Intrafraction Motion Management of Spine-SBRT On An MR-Linac J Cunningham*, K Snyder, J Kim, S Siddiqui, P Parikh, I Chetty, J Dolan, Henry Ford Cancer Institute, Detroit, MI |
| SU-H400-IePD-F8-5 | Automated Deformable Registration Using Patch-Based ViT-Morph for MR-Guided Adaptive Radiotherapy Y Zhao*, X Chen, C Yu, L Court, B McDonald, T Pan, H Wang, X Wang, J Phan, J Yang, UT MD Anderson Cancer Center, Houston, TX |
| SU-H400-IePD-F8-6 | Improving Structural Similarity Based Indication for MR-Guided Online Adaptation Replanning Abdul K. Parchur*, Haidy Nasief, Sara Lim, Eenas Omari, Ying Zhang, X. Allen Li, Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, 53226 USA |
| SU-H430-IePD-F4-6 | Small Field Output Factor (FOF) Measurements During Commissioning of a 0.35T MR-Linac System M Alghamwa1*, J Sohn1,2, R Hawranko1, S Kim1, P Yadav2, I Das2, W Song1, (1) Virginia Commonwealth University, Richmond, VA, (2) Northwestern University Feinberg School of Medicine, Chicago, IL |
| SU-H430-IePD-F5-2 | Automated Brain Metastases Segmentation with a Deep Dive Into False Positives Detection H Ziyaee1*, C Cardenas2, D Yeboa1, j Li1, J Johnson1, Z Zhou1, J Sanders1, R Mumme1, L Court1, T Briere1, J Yang1, (1) UT MD Anderson Cancer Center, Houston, TX, (2) The University of Alabama at Birmingham, Birmingham, AL |
| SU-I400-BReP-F1-2 | Improving Image Quality of Framed Gamma Knife Treatment Planning MRI with Flexible Array Coils J Sanders, H Liu, S Krafft, D Mackin, RJ Stafford, C Walker, T Briere, P Hou*, UT MD Anderson Cancer Center, Houston, TX |
| SU-I400-BReP-F1-3 | Reducing Parametric Maps’ Error by Sliding Window Reconstruction and Inter-Phase Data Sharing in Low-Rank Four-Dimensional Magnetic Resonance Fingerprinting (4D-MRF) Y Wong1*, C Liu2, T Li3, J Cai4, (1) The Hong Kong Polytechnic University, ,,(2) The Hong Kong Polytechnic University, Hong Kong, Hong Kong, (3) The Hong Kong Polytechnic University, Hong Kong, ,HK, (4) The Hong Kong Polytechnic University, Hong Kong, ,CN |
| SU-I400-BReP-F2-3 | Patient-Specific Image Prior Assisted Fast MR Imaging for Online Adaptive Radiotherapy Y Gao*, C Shen, Y Gonzalez, J Deng, X Jia, University of Texas Southwestern Medical Center, Dallas, TX |
| SU-J-202-2 | Accurate HU Generation for MR-LINAC Using MV-CBCT Y Hu1,2, C Williams1,2, R Berbeco1,2, M Myronakis*, (1) Brigham & Women's Hospital, Harvard Medical School, Jamaica Plain, MA, (2) Dana Farber Cancer Institute, Boston, MA |
| SU-K-202-3 | Efficacy and Photon Energy Dependency of In-Vivo Radiodynamic Therapy (RDT) with 5-Aminolevulinic Acid (5-ALA) D Yang*, D Cvetkovic, T Dos Santos, L Chen, C Ma, Fox Chase Cancer Center, Philadelphia, PA |
| SU-K-206-7 | Targeted MR Contrast Nanoparticles for Programmed Death Ligand-1 Expression N Brown1,2*, G Bort3,4, P Rocchi3,4, L Carmes3,4, M Iyer1,2, T Doussineau3, F Lux3,4, J Schoenfeld2, M Dougan5, O Tillement3,4,6, R Berbeco2, (1) Northeastern University, Department of Physics Boston, MA, (2) Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Department of Radiation Oncology, Boston, MA,(3) NHTherAguix, Lyon, France, (4) Universite Claude Bernard, Lyon, France, (5) Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA,(6) Institut Lumie`re-Matie`re, UMR 5306, Universite Lyon1-CNRS, Universite de Lyon, Villeurbanne Cedex, France |
| SU-K-BRC-1 | Implementation of Primary and Secondary Methods for Automatically Determining Necessity of Online Adaptive Replanning During MRI-Guided Adaptive Radiation Therapy H Nasief*, A Parchur, E Omari, Y Zhang, X Chen, X Li, Medical College of Wisconsin, Milwaukee, WI |
| SU-K-BRC-5 | Integration of 3D Geometric Distortion Assessment Into An Automated Daily End-To-End MRL QC Tool D Mateescu, V Malkov*, A Damyanovich, S Jelveh, J Winter, D Letourneau, Princess Margaret Hospital, Toronto, ON |
| SU-K-BRC-6 | High-Resolution Ultrashort Echo Time (UTE) 4D MRI with Camera-Based Respiratory Motion Sensing for Lung Cancer Radiotherapy Treatment Planning and Monitoring C Wu1*, G Krishnamoorthy2, V Yu3, E Subashi4, A Rimner5, R Otazo6, (1) Memorial Sloan Kettering Cancer Center, New York, NY, (2) Philips Healthcare, MR R&D, Rochester, MN, (3) Memorial Sloan Kettering Cancer Center, New York, NY, (4) Memorial Sloan Kettering Cancer Center, New York, NY, (5) Memorial Sloan-Kettering Cancer Center, New York, NY, (6) Memorial Sloan Kettering Cancer Center, New York, NY |
| SU-K-BRC-7 | Impact of Visual Biofeedback On Breathing Regularity During 4D-MRI Acquisition On the MR-Linac K Keijnemans*, P Borman, B Raaymakers, M Fast, Department of Radiotherapy, University Medical Center Utrecht, NL |
| TH-A-206-1 | JACK FOWLER EARLY-CAREER INVESTIGATOR COMPETITION WINNER: A Method for Clinical Gadolinium-Based Nanoparticle Quantification Using MRI S Bennett1*, C Verry2, E Kaza1, X Miao3, R Berbeco1, A Sudhyadhom1, (1) Brigham and Women's Hospital | Dana-Farber Cancer Institute | Harvard Medical School, Boston, MA, (2) Grenoble Alpes University Hospital, (3) Siemens Medical Solutions Usa Inc. |
| TH-A-206-2 | Effect of Various DCE-MRI Image Parameters On AI Assessment of Breast Parenchymal Enhancement L Douglas*, A Edwards, H Abe, M Giger, University of Chicago, Chicago, IL |
| TH-B-206-3 | Integrated Multi-Task MR for Abdominal Radiation Therapy: Towards Adaptive Planning and Treatment Monitoring J Chen1,2*, P Han2,3, Y Tian1, W Yang1, Y Yang2, D Li3, A Christodoulou3, K Nayak1, Z Fan1, (1) University of Southern California, Los Angeles, CA, (2) UCLA, Los Angeles, CA, (3) Cedars-sinai Medical Center, Los Angeles, CA, |
| TH-B-206-5 | Technical Results for the First Multi-Institutional Sterotactic MR-Guided Adaptive Radiation Therapy (SMART) Trial in Pancreas Cancer J Kim1*, P Parikh1, P Lee2, MD Chuong3, M Fuss4, D Low5, (1) Henry Ford Health System, Detroit, MI, (2) MD Anderson Cancer Center, (3) MCI, Miami, FL, (4) Viewray, (5) UCLA, Los Angeles, CA |
| TH-C-202-5 | Voxel-Based Estimation of Microstructure Characteristics of Head and Neck Cancers Using Time-Dependent MR Diffusion Weighted Imaging and a Random Walk with Barriers Model S Nejad-Davarani1*, M Mierzwa1, T Feiweier2, K Casper1, Y Cao1, (1) University of Michigan, Ann Arbor, MI, (2) Siemens Healthcare GmbH, Erlangen, Germany |
| TH-C-202-6 | Streamlined MR-Linac Daily QA Using Cherenkov Imaging: Longitudinal Performance Assessment After 16 Months of Clinical Use D Alexander1*, R Zhang1,2, J Mayer2, P Bruza1, B Pogue1,5, D Gladstone1, (1) Thayer School of Engineering, Dartmouth College, Hanover, NH, (2) Dartmouth-Hitchcock Medical Center, Lebanon, NH (3) University of Wisconsin-Madison, Madison, WI |
| TH-E-BRC-4 | MRIGRT - 4D Motion Modeling and Real-Time Online 3D Motion Tracking y zhang1, X Wu1*, H Gach1, J Ginn2, D Yang2, (1) Washington University, Saint Louis, MO, (2) Duke University, Chapel Hill, NC |
| TH-F-BRC-3 | BEST IN PHYSICS (MULTI-DISCIPLINARY): Motion-Corrected Image Reconstruction with Unrolling Networks On An MRI-Linac S Shan1,2, Y Gao3, P Liu1,2, T Reynolds1*, B Dong2, H Sun3, M Li3, G Liney2, F Liu3, P Keall1,2, D Waddington1,2, (1) ACRF ImageX Institute, University of Sydney, Sydney, NSW 2015, Australia (2) Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia(3)School of Information Technology & Electrical Engineering, University of Queensland, Brisbane, QLD 4067, Australia |
| TH-F-BRC-4 | MRI Wavelet-Based Machine Learning Classifier to Automatically Determine OLAR Necessity During MRgART H Nasief*, E Omari, A Parchur, Y Zhang, X Chen, E Paulson, W Hall, B Erickson, X Li, Medical College of Wisconsin, Milwaukee, WI |
| TU-AB-207-0 | Advanced MR in the Clinic Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-1 | T1/T2/T2* Mapping Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-2 | Diffusion MRI Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-3 | Perfusion MRI Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-4 | Functional MRI Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-5 | MR Elastography Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-6 | MR Spectroscopy Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-AB-207-7 | Q & A Q Yuan1*, X Zhou2*, Y Jung3*, H Liu4*, C Lin5*, S Einstein6*, (1) UT Southwestern Medical Center, Dallas, TX, (2) University of Illinois College of Medicine at Chicago, Chicago, IL, (3) University of California, Davis, Sacramento, CA, (4) UT MD Anderson Cancer Center, Houston, TX, (5) Mayo Clinic, Jacksonville, FL, (6) Penn State Hershey Medical Center, Hershey, PA |
| TU-D1000-IePD-F6-2 | An Application for the Collection Of Weekly MRI QC Across the Emory Campus A Salazar, P Sharma, M Goette*, H Kitajima, J Nye, Emory Univ, Atlanta, GA |
| TU-D1000-IePD-F6-3 | A System-Wide Magnetic Resonance Safety Program as a Value Add Proposition R Parker1, B Betz2, Y Zhou1, D Buer1, A Gray1, E Boote1*, (1) Spectrum Health, Grand Rapids, MI,(2) Advanced Radiology Services, Grand Rapids, MI |
| TU-D1000-IePD-F7-1 | Deep Learning-Based Automatic Segmentation Framework for Targets and OARs in Cervical High Dose Rate (HDR) Brachytherapy R Ni1*, S Kim1, B Haibe-kains1, A Rink1,2, (1) University of Toronto, Toronto, ON, CA, (2) Princess Margaret Hospital, Toronto, ON, CA |
| TU-D1030-IePD-F2-4 | Deep Learning Based Automatic Contour Quality Assurance for Auto-Segmentation of Abdominal Organ N Dang*, Y Zhang, A Amjad, J Ding, C Sarosiek, X Li, Medical College of Wisconsin, Milwaukee, WI |
| TU-D930-IePD-F2-4 | A Deep Learning Model with Radiomics Analysis Integration for Glioblastoma Post-Resection Survival Prediction Z Hu1*, Z Yang2, J Zhao1, H Zhang1, E Vaios2, K Lafata2, F Yin2, C Wang2, (1) Duke Kunshan University, Kunshan, Jiangsu, China (2) Duke University, Durham, NC |
| TU-D930-IePD-F9-1 | Patient Fine-Tuning of NnUnet for MRI Organ Autosegmentation J Hogan1, D Yang2*, B Baumann3, Y Duan4, C Zhao4, (1) Washington University In St. Louis School of Medicine, St. Louis, MO, (2) Duke University, Department of Radiation Oncology, Chapel Hill, NC, (3) Washington University In St. Louis School Of Medicine, Department of Radiation Oncology, St. Louis, MO, (4) University Of Missouri, EECS Department, Columbia, MO |
| TU-D930-IePD-F9-2 | Weakly Supervised Convolutional Neural Networks for Segmentation of Diffusely Abnormal White Matter in Multiple Sclerosis B Musall1*, A Kamali1, J Lincoln1, V Ly2, X Luo2, P Narayana1, R Gabr1, (1) University of Texas McGovern Medical School, Houston, TX, (2) University of Texas School of Public Health, Houston, TX |
| TU-D930-IePD-F9-5 | Effects of DWI Pulse Sequence Parameters and Type On ADC Map Calculation at 3T in a Quantitative MRI Phantom J Yu*, A Silva, Y Zhou, A Panda, Mayo Clinic Arizona, Scottsdale, AZ |
| TU-F115-IePD-F2-1 | Urethral Inter-Fractional Geometric and Dosimetric Variations of Prostate Cancer Patients: A Study Using An On-Board MRI J Pham*, R Savjani, S Yoon, T Yang, Y Gao, M Cao, P Hu, K Sheng, D Low, M Steinberg, A Kishan, Y Yang, University of California, Los Angeles, Los Angeles, CA |
| TU-F115-IePD-F2-2 | Synthetic CT Generation From Truncated MRI Using a Modified CycleGAN Model X Chen*, Y Zhao, L Court, H Wang, T Pan, J Phan, X Wang, J Yang, UT MD Anderson Cancer Center, Houston, TX |
| TU-F115-IePD-F2-5 | Ferumoxytol Relaxivity and Signal Enhancement for MR-Guided Radiation Therapy (MRgRT) at 0.35T: A Feasibility Study J Pham*, C Colbert, M Cao, K Nguyen, Y Yang, University of California, Los Angeles, Los Angeles, CA |
| TU-J430-BReP-F2-4 | Dominant Index Prostatic Lesions Segmentation Using Deep Learning for MR-Guided Radiative Ablation J Simeth*, J Jiang, A Nosov, A Wimber, M Zelefsky, N Tyagi, H Veeraraghavan, MSKCC, New York, NY |
| TU-J430-BReP-F2-5 | Implementation of Super-Resolution Imaging On An MRI-Linac J Grover1, P Liu1,2, B Dong2, S Shan1,2, B Whelan1,2, P Keall1,2*, D Waddington1,2, (1) ACRF Image X Institute, Faculty of Medicine and Health, The University of Sydney, NSW, AU, (2) Department of Medical Physics, Ingham Institute for Applied Medical Research, NSW, AU. |
| WE-A-201-3 | In Vivo MR Elastography of Aortic Stiffness Using Multi-Slice Spin-Echo Echo Planar Imaging Sequence: A Comparison to Gradient Recalled Echo Sequence H Dong1,3*, N Jin2,3, R White3, A Kolipaka3, (1) University of California, San Francisco, San Francisco, CA, (2) Siemens Healthcare, Columbus, OH, (3) The Ohio State University Wexner Medical Center, Columbus, OH |
| WE-A-201-6 | BEST IN PHYSICS (IMAGING): Respiratory Motion Detection and Reconstruction Using CAPTURE and Deep Learning Phase2Phase Network for a 0.35 T MRI-LINAC System S Chen1*, C Eldeniz2, T Fraum3, D Ludwig4, W Gan5, U Kamilov6, D Yang7, Gach8, H An9, (1) Washington University in St. Louis, Saint Louis, MO, (2) Washington University in St. Louis, Saint Louis, MO, (3) Washington University in St. Louis, Saint Louis, MO, (4) Washington University in St. Louis, Saint Louis, MO, (5) Washington University in St. Louis, Saint Louis, MO, (6) Washington University in St. Louis, St. Louis, MO, (7) Duke University, Chapel Hill, NC, (8) Washington University in St Louis, Saint Louis, MO, (9) Washington University in St. Louis, Saint Louis, MO |
| WE-A-202-5 | BEST IN PHYSICS (MULTI-DISCIPLINARY): MRI of Radiation Effects: First Images and An Investigation of a Potential Hydroxyl Radical Mechanism J Wancura1,2*, J Egan2, E Sajo2, A Sudhyadhom1, (1) Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, (2) University of Massachusetts Lowell, Lowell, MA |
| WE-B-201-1 | Deep-Learning Based Rectal Tumor Localization and Segmentation On Multi-Parametric MRI Y Zhang1*, S Hu1, L Shi2, X Sun2, N Yue1, K Nie1, (1) Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, (2) Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang Univ., Hangzhou, CN |
| WE-B-201-2 | Development and Validation of a Radiomics Model to Predict Pathological Complete Response to Neoadjuvant Chemoradiation (nCRT) in Locally Advanced Rectal Cancer: A Perspective Observational Study Y Zhang1*, S Hu1, L Shi2, X Sun2, N Yue1, K Nie1, (1) Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, (2) Department of Radiation Oncology, Sir Run Run Shaw Hospital, Zhejiang Univ., Hangzhou, ,CN |
| WE-B-201-3 | Fully Automated Segmentation of Prostatic Urethra for MR-Guided Radiation Therapy (MRgRT) D XU1,2*, T Ma2, R Savjani2, M Cao2, Y Yang2, A Kishan2, F Scalzo3, K Sheng2, (1)Computer Science, University of California, Los Angeles, CA 90095, USA (2) Radiation Oncology, University of California, Los Angeles, CA 90095, USA (3)Computer Science, Pepperdine University, 24255 Pacific Coast Hwy, Los Angeles, CA 90263, USA |
| WE-B-201-5 | Model Based Real-Time Prediction of Gastric Contractile Motion Y Zhang*, Y Cao, J Balter, University of Michigan, Ann Arbor, MI |
| WE-B-201-6 | Radiomics of Tuberous Sclerosis Complex for Precision Diagnosis F Tixier1*, D Rodriguez1, J Jones1, M Islam2,3, M Hester4,5,6, M Ho1, (1) Department of Radiology, Nationwide Children's Hospital, Columbus, Ohio, USA (2) Division of Neurology, Nationwide Children's Hospital, Columbus, OH, USA (3) Department of Clinical Pediatrics, Section of Neurology, The Ohio State University College of Medicine, Columbus, OH, USA (4) Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio, USA (5) The Steve and Cindy Rasmussen Institute for Genomic Medicine, Columbus, Ohio, USA (6) Department of Neuroscience, College of Medicine, Ohio State University, Columbus, OH, USA |
| WE-B-202-2 | MRI Simulation Protocol Optimization for Ocular Melanoma Proton Therapy Treatment Planning M Goette1*, R Slopsema2, A Dhabaan2, L Qiu2, D Qian2, H Shu2, (1) Emory Healthcare, Atlanta, GA, (2) Emory University, Atlanta, GA |
| WE-B-BRC-5 | Second-Generation Bismuth Gadolinium Theranostic Nanoparticles for MR Guidance and Radiation Dose Amplification N Brown1, 2*, P Rocchi3,4, L Carmes3,4, R Guthier2, M Iyer1,2, T Morris2,5, S Bennett2, M Lavelle2,5, T Doussineau3, C Williams2, E Huynh2, Z Han2, E Kaza2, G Bort3,4, F Lux3,4, O Tillement3,4,6, R Berbeco2, (1) Northeastern University, Department of Physics Boston, MA, (2) Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Department of Radiation Oncology, Boston, MA,(3) NHTherAguix, Lyon, France, (4) Universite Claude Bernard, Lyon, France, (5) University of Massachusetts Lowell, Department of Physics and Applied Physics, Lowell, MA, (6) Institut Lumie`re-Matie`re, UMR 5306, Universite Lyon1-CNRS, Universite de Lyon, Villeurbanne Cedex, France |
| WE-C1000-IePD-F2-2 | Enhancing Image Quality of 3D View-Sharing Sequence Acquired Abdominal Free-Breathing 4D-MRI by Retrospective Motion Artifacts Suppression by Synthetic Radial K-Space (R-MASSK) Y Wong1*, H Chang2, W Liu3, W Wang4, Y Zhang5, H Wu6, H Lee7, A Cheung8, T Li9, J Cai10, (1) The Hong Kong Polytechnic University, ,,(2) The University Of Hong Kong, ,,(3) ,,,(4) ,,,(5) Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, 11, CN, (6) Beijing Cancer Hospital, Beijing, ,CN, (7) The University Of Hong Kong, ,,(8) ,,,(9) The Hong Kong Polytechnic University, Hong Kong, ,HK, (10) Hong Kong Polytechnic University, Hong Kong, ,CN |
| WE-C1000-IePD-F2-3 | Developing In-Situ QA Tools for MRI-MV Isocenter Coincidence Check in 0.35T MRgRT T Kim1*, H Zhang1, S Marasini1, M Cole2, G Koenig2, R Flores2, (1) Washington University in St. Louis, Saint Louis, MO, (2) Modus Medical Devices, Inc., London, ON, CA |
| WE-C1000-IePD-F2-4 | Dynamic 2D Cine From Beam Eye’s View (BEV) with Projected Tumor Volume for MR-Guided Radiotherapy X Nie1, G Li2, J Jeong2*, (1) University of Kentucky, Lexington, KY, (2) Memorial Sloan Kettering Cancer Center, New York, NY |
| WE-C1000-IePD-F5-2 | Developing a Pneumatic-Driven, Dual-Modal (MR/CT) and Anthropomorphic Breathing Phantom for Image-Guided Radiotherapy T Chiu1*, S Ho2, J Visak1, M Willis1, Y Zhang1, (1) UT Southwestern Medical Center, Dallas, TX, (2) Texas A&M University |
| WE-C930-IePD-F5-2 | Improving Tumor Tracking Accuracy During MR-Guided Radiotherapy Using Pre-Trained Super-Resolution Neural Networks P Liu1,2*, D Waddington1,2, J Grover1, P Keall1,2 (1) ACRF Image X Institute, Faculty of Medicine and Health, The University of Sydney, NSW, AU (2) Department of Medical Physics, Ingham Institute of Applied Medical Research, NSW, AU |
| WE-C930-IePD-F5-3 | Deep Learning Based Cine-MR Image Prediction and Analysis for Abdominal Motion J Weng1*, S Bhupathiraju2, T Samant3, A Dresner4, J Wu1, S Samant1, (1) Department of Radiation Oncology,University of Florida, Gainesville, FL (2) Department of Computer & Information Science & Engineering, University of Florida, Gainesville, FL (3) UF Research Computing, University of Florida, Gainesville, FL (4) Philips Healthcare |
| WE-E-BRA-4 | MRI-Only Treatment Planning (MRTP) for Interstitial Gynecologic HDR Brachytherapy C Lee*, E Kaza, T Harris, D O'Farrell, R Cormack, I Buzurovic, Department of Radiation Oncology, Dana-Farber/Brigham and Womens Cancer Center, Harvard Medical School, Boston, MA |
| WE-G-BRC-6 | A Deep Learning U-Net Based Model to Automatically Correct Inaccurate Auto-Segmentation for MR-Guided Adaptive Radiotherapy J Ding*, Y Zhang, A Amjad, C Sarosiek, N Dang, X Li, Medical College of Wisconsin, Milwaukee, WI |