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Keywords: Prostate Therapy
MO-A-BRC-3Inter-Observer variation of Target and Organ Contouring Before and After the Adoption of A deep-Learning Auto-Contouring Model for Localized Prostate Cancer
Y Wang*, S C Kamran, J A Efstathiou, Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
MO-B-BRC-4Patient-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
PO-GePV-M-110Assessing the Accuracy of Target Contours Derived From Ethos ICBCT Images for Online Adaptive Prostate SBRT
D O'Connell*, M Xiang, T Ma, S Yoon, L Valle, R Savjani, J Lamb, University of California, Los Angeles, Los Angeles, CA
PO-GePV-M-117Toward Offline Adaptive Therapy for Prostate Patients Using Velocity
E Bacon1*, S Wisnoskie2, M Hyun2, (1) Creighton University, Omaha, NE, (2) University of Nebraska Medical Center, Omaha, NE
PO-GePV-M-128Evaluation of the Clinical Impact of the Differences Between Planned and Delivered Doses in Prostate Cancer Radiotherapy Based On Daily IGRT and Patient-Reported Outcome Scores
P Mavroidis1*, J Hammers2, G Narayanasamy3, S Sud4, D Lindsay5, X Tan6, J Dooley7, S Stathakis8, L Marks9, R Chen10, S Das11, (1) University of North Carolina, Chapel Hill, NC, (2) Chapel Hill, NC, (3) University of Arkansas for Medical Sciences, Little Rock, AA, (4) University Of North Carolina At Chapel Hill, NC, (5) UNC at Chapel Hill, Chapel Hill, NC, (6) UNC at Chapel Hill, Chapel Hill, NC, (7) University of North Carolina, Chapel Hill, NC, (8) Mays Cancer Center - MD Anderson Cancer Center, San Antonio, TX, (9) University of North Carolina at Chapel Hill, Chapel Hill, NC, (10) University Of Kansas, (11) University of North Carolina, Chapel Hill, NC
PO-GePV-M-132Analysis of Intra-Fractional Motion in Prostate Stereotactic Body Radiation Therapy
R Cattell*, A Hsia, J Kim, X Qian, S Lu, A Slade, K Mani, S Ryu, Z Xu, Stony Brook University Medical Center, Stony Brook, NY
PO-GePV-M-192Predictability of Prostate Tumor Motion by Using Autoregressive Model for Real-Time Adaptive Radiation Therapy
A Hayami*, K Ichiji, N Homma, Tohoku University, Sendai, JP,
PO-GePV-T-37Are We Improving? The Learning Curve for Implementing Intraoperative Ultrasound-Guided Prostate High Dose Rate (HDR) Brachytherapy
A Besemer1*, J Wong1, S Wang1, M Hyun1, S Wisnoskie1, D Schott1, D Zheng1,2, Y Lei1,3, K Gallagher1, S Hendley1, (1) University of Nebraska Medical Center, Omaha, NE, (2) University of Rochester, Rochester, NY, (3) Barrow Neurological Institute, Phoenix, AZ
PO-GePV-T-174Evaluation of the Utility of Rescans in the Treatment of Prostate and Pelvic Nodes with Pencil Beam Scanning Protons
S Laub*, S Schmidt, L Campbell, B Hartsell, Northwestern Medicine Proton Center, Warrenville, IL
PO-GePV-T-282Evaluation of VMAT & IMRT Planning Strategies for Advanced Prostate Cancer Patients with Bilateral Hip Prostheses
J Xu*, T Cosely, T Bouton, B Zhang, D Han, J Zhou, S Chen, University of Maryland School of Medicine, Baltimore, MD
PO-GePV-T-350Variation of SpaceOAR Density and Volume Throughout the Course of Prostate Radiation Therapy Treatments
B King*, A Harpley, A Dare, D Campos, M Hwang, M Goss, J Sohn, Allegheny Health Network, Pittsburgh, PA
PO-GePV-T-426Adaptive Workflow for Prostate, Seminal Vesicle, and Nodal Volume SBRT On a CBCT Adaptive AI Driven System
E Laugeman*, A Price, L Henke, B Baumann, Washington University School of Medicine in St. Louis, St. Louis, MO
SU-E-206-2Automatic VMAT Machine Parameter Optimization Using Deep Deterministic Policy Gradients
W Hrinivich*, H Li, J Lee, Dept. of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD
SU-F-206-3Changes 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-BRB-2Automated Pipeline for Prostate Auto-Contouring and VMAT Planning
M El Basha1,2*, Q Nguyen2, D Fuentes1,2, J Pollard-Larkin1,2, F Poenisch2, Z Yu1,2, S Frank2, C Cardenas3, C Nguyen2, A Olanrewaju2, C Tang2, S Shah2, A Aggarwal4, L Court1,2, (1) University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, (2) MD Anderson Cancer Center, Houston, TX, (3) The University of Alabama at Birmingham, Birmingham, AL, (4) Guy's and St. Thomas' NHS Foundation Trust, London, UK
SU-H330-IePD-F5-3A 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-F7-4Cross Comparison and Validation of Metallic Catheter Reconstruction for Use in High-Dose-Rate Brachytherapy Utilizing Electromagnetic Tracker, Ultrasound, and Computed Tomography Information
N Hassan Rezaeian*, G Cohen, D Aramburu Nunez, J Beaudry, P McCann, A Damato, Memorial Sloan Kettering Cancer Center, New York, NY
SU-H430-IePD-F7-3Do Machine Learning-Based Models Perform Better Than Clinical Models in Predicting Biochemical Outcome for Prostate Cancer Patients?
L Sun1,2*, H Quon1,2, W Smith1,2, and C Kirkby1,3 (1) University of Calgary, Calgary, AB, CA (2) Tom Baker Cancer Centre, Calgary, AB, CA (3) Jack Ady Cancer Centre, Lethbridge, AB, CA
SU-K-207-1Comparing Spatial Accuracy of Catheter Localization Between Stepping-Transverse Mode and Twister-Sagittal Mode in Transrectal Ultrasound (TRUS) Based High-Dose-Rate (HDR) Brachytherapy for Prostate Cancer Therapy
M Keohane1*, S Dieterich1, J Matney1, P Beagen1, J Zhao1, R Valicenti1, T Liu2, S Benedict1, P Park1, (1) UC Davis Medical Center, Sacramento, CA,(2) Emory Univ, Atlanta, GA,
TU-D1000-IePD-F2-5Adaptive Radiotherapy Via Deep Learning-Based Quantitative Cone-Beam CT Imaging
L Wan1*, H Wu2, S Xu3, B Sun4, W Zhao5, (1) Beihang University, Beijing, BJ, CN (2) Beijing Cancer Hospital, Beijing, BJ, CN, (3) National Cancer Center/Cancer Hospital- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, BJ, CN, (4) Beihang University,Beijing, BJ, CN(5) Beihang University, Beijing, BJ, CN
TU-F115-IePD-F2-1Urethral 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-F6-4Dosimetric Evaluation of Stereotactic Prostate Reirradiation Using Cyberknife as An Alternative to HDR Brachytherapy for Locally Recurrent Prostate Cancer
X Zhang, S Jang*, S Lee, S Keohan, AE Hirsch, Boston Medical Center, Boston, MA
TU-J430-BReP-F2-4Dominant 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
WE-C1000-IePD-F4-3A Dosimetric Study of the Use of Hydrogel SpaceOAR™ in the Reduction of Rectal Doses for Patients Undergoing Prostate Stereotactic Body Radiotherapy
N Gross1*, R Teboh Forbang1,2, H Kadji1, G Gejerman2, B Lewis1,2, (1) Hackensack Meridian Health At Mountainside Medical Center,(2) Hackensack University Medical Center, Hackensack, NJ