Authors: Steven DiBiase, Gurtej S. Gill, Haohua Billy Huang, Nicholas J. Lavini, Luxshan Shanmugarajah, Salar Souri, Samantha Wong
Affiliation: Stony Brook University, Northwell Health, Cornell University, NewYork-Presbyterian, New York-Presbyterian
Abstract Preview: Purpose: Clinical applications of deep learning-based algorithms have come to the radiation oncology field as organ at risk (OAR) auto contouring programs. We evaluated two of these algorithms’ (Radfo...
Authors: Beth M. Beadle, Adrian Celaya, Laurence Edward Court, David Fuentes, Anna Lee, Tze Yee Lim, Dragan Mirkovic, Amy Moreno, Raymond Mumme, Tucker J. Netherton, Callistus M. Nguyen, Jaganathan A Parameshwaran, Jack Phan, Carlos Sjogreen, Sara L. Thrower, Congjun Wang, He C. Wang, Xin Wang
Affiliation: Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Department of Radiation Oncology, Stanford University, The University of Texas MD Anderson Cancer Center, MD Anderson Cancer Center, MD Anderson, Rice University, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Quality assurance of target volumes from radiotherapy clinical trials is a labor and resource intensive task. The purpose of this work is to quantify the accuracy of a tool that automatically...
Authors: Doris Dimitriadis/Dimitriadou, M. Saiful Huq, Ronald John Lalonde, Fang Li, Noor Mail, Adam Olson
Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, UPMC
Abstract Preview: Purpose: The objective of this study was to qualitatively evaluate Prostate Hypersight Cone-Beam CT (HSCBCT) images and assess its capability for Limbus auto-contouring. The qualitative evaluation and...
Authors: Indrin J. Chetty, Jing Cui, Mitchell Kamrava, Tiffany M. Phillips, Jennifer M. Steers, Brad Stiehl
Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center
Abstract Preview: Purpose: Auto-contouring for HDR interstitial brachytherapy can be confounded by large deformation in anatomy and image quality. Here we evaluated the performance of an AI-based auto-contouring softwa...
Authors: Mylinh Dang, Laila A Gharzai, Xinlei Mi, Poonam Yadav
Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern Medicine
Abstract Preview: Purpose: Delineation of organs at risk (OAR) in the head/neck region requires substantial physician time. Many artificial intelligence (AI) based auto-contouring software are commercially available. T...
Authors: Sven Ferguson, S. Murty Goddu, Ana Heermann, Taeho Kim, Nels C. Knutson, Hugh HC Lee, Shanti Marasini, Timothy Mitchell, Seungjong Oh, Kevin Renick
Affiliation: Washington University in St. Louis School of Medicine, Washington University School of Medicine in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis
Abstract Preview: Purpose: In the Gamma Knife stereotactic radiosurgery (GK-SRS), the delineation of organs-at-risks (OARs) was not fully automated. Due to the cumbersome nature of manual OAR contouring, dose evaluatio...
Authors: Katja M. Langen, William Andrew LePain, Robert Muiruri, Vivi Nguyen, Mosa Pasha, Roelf L. Slopsema, Alexander Stanforth, Yinan Wang, Mingyao Zhu
Affiliation: Emory Healthcare, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Intensity modulated proton therapy (IMPT) treatment planning for craniospinal irradiation (CSI) is complex and requires extensive effort from the planner. This study aims to enhance planning ...
Authors: Laurence Edward Court, Raphael Douglas, David Fuentes, Anuja Jhingran, Barbara Marquez, Raymond Mumme, Christine Peterson, Julianne M. Pollard-Larkin, Surendra Prajapati, Dong Joo Rhee, Thomas J. Whitaker
Affiliation: MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, MD Anderson, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Safe deployment of auto-contouring models requires the inclusion of automated quality assurance (QA). One approach is to use an independent auto-contouring model and compare the contours geom...
Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia
Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio
Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...
Authors: Sara Endo, Takeshi Fujisawa, Hidehiro Hojo, Masaki Nakamura, Hidenobu Tachibana
Affiliation: Department of Radiation Oncology, National Cancer Center Hospital East, Radiation Safety and Quality Assurance Division, National Cancer Center Hospital East
Abstract Preview: Purpose: To assess the clinical feasibility of deep learning (DL)-based automated contouring through qualitative and quantitative assessments.
Methods: Sixty cases were chosen, including 3 OARs...
Authors: Alexander Choi, William Ross Green, Christine Hill-Kayser, Gary D. Kao, Michael LaRiviere, Rafe A. McBeth, Steven Philbrook
Affiliation: Department of Radiation Oncology, University of Pennsylvania
Abstract Preview: Purpose: To validate the potential of clinical deployment of an in-house AI-driven auto-segmentation tool for pediatric craniospinal irradiation (CSI) in proton therapy, with goals of reducing manual ...
Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis, Hamlet Spears
Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center
Abstract Preview: Purpose: This study evaluates the range of motion of abdominal organs using 4D stack-of-stars magnetic resonance (MR) imaging and 4D computed tomography (CT), the current clinical standard. Accurate o...
Authors: Baher Elgohari, M. Saiful Huq, Ronald John Lalonde, Fang Li, Noor Mail, Jeonghoon Park, Tyler Wilhite
Affiliation: UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Department of Radiation Oncology, UPMC Hillman Cancer Center, UPMC, Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose:
To compare toxicity between consecutive-daily (QD) with every-other-day (QoD) delivery of lung stereotactic-body-radiation (SBRT) for central non-small-cell lung cancer (NSCLC).
Methods...
Authors: Gregory T. Armstrong, James E. Bates, Christine V. Chung, Lei Dong, Ralph Ermoian, Jie Fu, Christine Hill-Kayser, Rebecca M. Howell, Meena S. Khan, Sharareh Koufigar, John T. Lucas, Thomas E. Merchant, Taylor Meyers, Tucker J. Netherton, Constance A. Owens, Arnold C. Paulino, Sogand Sadeghi
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, St. Jude Children's Research Hospital, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, St. Jude Children’s Research Hospital, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, University of Washington/ Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences
Abstract Preview: Purpose: Clinical workflows often rely on auto-segmentation tools trained on adult data, which may exhibit suboptimal performance in pediatric imaging due to inherent anatomical variations and smaller...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: In an effort to improve contouring accuracy for abdominal MR guided online adaptive radiotherapy (MRgOART), patient-specific deep learning-based auto-segmentation (PS-DLAS) has been proposed....
Authors: Shatha Al Afifi, Hana Baroudi, Leonard Che Fru, Laurence Edward Court, Suzanne B. Evans, Kent A. Gifford, Adam D. Melancon, Melissa P. Mitchell, Issa Mohamad, Patricia Murina, Manickam Muruganandham, Tucker J. Netherton, Callistus M. Nguyen, Joshua S. Niedzielski, Deborah L. Schofield, Simona Shaitelman, Willie Shaw, Sanjay S. Shete, Adam Shulman, Brendon Smith, Sheeba Thengumpallil, Carlos Daniel Venencia, Conny Vrieling
Affiliation: University of Cape Town, MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, University of the Free State, UT MD Anderson Cancer Center, King Hussein Cancer Center, Instituto Zunino - Fundacion Marie Curie, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Dra., Hirslanden Clinique des Grangettes, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Therapeutic Radiology, Yale University School of Medicine, Yale University, The University of Texas, MD Anderson, Houston TX
Abstract Preview: Purpose:
Automated contouring and planning tools are usually trained on single-institution datasets, seldom tested across diverse patient populations. This introduces a risk of population bias, res...
Authors: Doris Dimitriadis/Dimitriadou, Denisa R. Goia, M. Saiful Huq, Ronald John Lalonde, Noor Mail, Adam Olson, Tyler Wilhite
Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, UPMC
Abstract Preview: Purpose: The goal of the HyperSight® offline adaptive-workflow is to create a methodical approach to adaptive-radiotherapy (ART) that considers modifications in patient setup and anatomy. Through effi...
Authors: Steve B. Jiang, Chien-Yi Liao, Dan Nguyen, Daniel Yang, Hengrui Zhao
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Post-operative radiotherapy for prostate cancer requires precise contouring of the clinical target volume (CTV) to account for microscopic disease that is invisible in the image. However, ...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose:
MR-guided adaptive radiation therapy (MRgART) is transforming clinical workflows, requiring fast, accurate organs-at-risk (OARs) contouring. While deep learning auto-segmentation (DLAS) of...
Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...
Authors: David P. Adam, William T. Hrinivich, Taoran Li, Alexander Lu, Michael Salerno, Alejandro Sisniega, Boon-Keng Kevin Teo
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, University of Pennsylvania
Abstract Preview: Purpose: Cone beam CT (CBCT)-guided online adaptive radiotherapy (ART) is of growing interest, with recent improvements in image quality provided through larger detector panels and fast gantry rotatio...
Authors: B. Gino Fallone, Gawon Han, Keith D. Wachowicz, Mark G. Wright, Eugene Yip, Jihyun Yun
Affiliation: Medical Physics Division, Department of Oncology, University of Alberta, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com
Abstract Preview: Purpose: MRI-radiotherapy hybrid systems can guide the therapeutic beam, dynamically adjusting to a moving tumor in real-time. However, there is a time delay from imaging and beam control, requiring p...
Authors: Stephanie Bennett, Ross I. Berbeco, Ning Jin, Sonal Josan, Justin Michael Sheetz, Atchar Sudhyadhom
Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Massachusetts - Lowell, Siemens Healthineers, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School,, Brigham and Women's Hospital
Abstract Preview: Purpose: AGuIX, a Gadolinium-based theranostic radiosensitizing nanoparticle, is currently under clinical evaluation in Europe and the US. Using patients from the double-blinded NanoBrainMets trial, u...
Authors: Laura Buchanan, Samantha G. Hedrick, Stephen L. Mahan, Isabella Pfeiffer, Chester R. Ramsey
Affiliation: Thompson Proton Center
Abstract Preview: Purpose: The CQ Medical kVue Pronumbra Head & Neck (HN) System is a new immobilization device for proton therapy. The mask includes 4 large knobs that attach to the board with built-in shims. These kn...
Authors: Laura I. Cervino, Sharif Elguindi, Yu-Chi Hu, Licheng Kuo, Xiaoning Liu, Jennifer Ma, Pengpeng Zhang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Radiation Oncology, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose:
Quad-shot radiotherapy (QSRT) is an emerging paradigm in palliative cancer treatment. This study aimed to streamline the QSRT workflow using automation to improve efficiency while maintain...
Authors: Avery Antes, Bulent Aydogan, Rama Chicfeh, Erik Pearson, Neslihan Sarigul
Affiliation: The University Of Chicago, The University of Chicago
Abstract Preview: Purpose: This study evaluates the performance of the Ethos Treatment Planning System (TPS) in managing oligometastatic cancer patients previously treated using multiple isocenter plans.
Methods: Th...