Authors: Chuan He, Anh H. Le, Iris Z. Wang
Affiliation: Roswell Park Comprehensive Cancer Center, Cedars-Sinai
Abstract Preview: Purpose: To develop a non-measured and DVH-based (NMDB) IMRT QA framework integrating machine learning (ML) to classify lung SBRT VMAT plans prone to delivery errors
Methods: 560 Eclipse AcurosXB l...
Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jing Sun, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Xiaojing Zhu
Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Shanghai University of Electric Power, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Accurate prediction of patient response to radiotherapy plays a crucial role in monitoring disease progression and assessing treatment efficacy, enabling clinicians to develop personalized th...
Authors: Zachary Carr, Katie W. Hulme, Zaiyang Long, Nathan A. Quails, Ashley Tao
Affiliation: Gundersen Health System, Ohio State University Wexner Medical Center, Mayo Clinic, Ohio State Wexner Medical Center, The Cleveland Clinic
Abstract Preview: Purpose: Meaningful interpretation of deviation index (DI) in clinical practice relies on appropriately set target exposure indices (EIT). EIT values for a given exam-view can be derived from the medi...
Authors: Wilfred R Furtado, Gary Y. Ge, Jie Zhang
Affiliation: Department of Radiology, University of Kentucky, University of Kentucky
Abstract Preview: Purpose: The United Kingdom and several other countries already have well-established diagnostic reference levels (DRLs) for gastrointestinal fluoroscopic procedures, whereas the United States does no...
Authors: David Ayala Alvarez, Facundo Ballester, Luc Beaulieu, Francisco Berumen-Murillo, Jean-Simon Cote, Ernesto Mainegra-Hing, Iymad Mansour, Gaël Ndoutoume-Paquet, Jan P. Seuntjens, Rowan M. Thomson, Christian Valdes, Javier Vijande, Peter G. Watson
Affiliation: Département de physique, de génie physique et d'optique, Université Laval, Princess Margaret Cancer Centre & University of Toronto, McGill University, Department of Physics and Medical Physics Unit, McGill University, IFIC-UV, University of Valencia, National Research Council Canada, Carleton University, 5Service de Physique Médicale et de Radioprotection, Centre Intégré de Cancérologie, CHU de Québec- Université Laval et Centre de recherche du CHU de Québec, Nuclear Medicine Department, Hospital Regional de Antofagasta, Université Laval, Carleton Laboratory for Radiotherapy Physics, Department of Physics, Carleton University
Abstract Preview: Purpose: Low-energy X-ray beams used in electronic brachytherapy (eBT) pose unique dosimetric challenges due to high depth-dose gradients, material-dependent detector responses, and the absence of sta...
Authors: David Ayala Alvarez, Facundo Ballester, Luc Beaulieu, Francisco Berumen-Murillo, Jean-Simon Cote, Ernesto Mainegra-Hing, Iymad Mansour, Gaël Ndoutoume-Paquet, Rowan M. Thomson, Christian Valdes, Javier Vijande, Peter G. Watson
Affiliation: Département de physique, de génie physique et d'optique, Université Laval, Laval University, Princess Margaret Cancer Centre, McGill University, Department of Physics and Medical Physics Unit, McGill University, IFIC-UV, University of Valencia, National Research Council Canada, Carleton University, 5Service de Physique Médicale et de Radioprotection, Centre Intégré de Cancérologie, CHU de Québec- Université Laval et Centre de recherche du CHU de Québec, Nuclear Medicine Department, Hospital Regional de Antofagasta
Abstract Preview: Purpose: Modelling electronic brachytherapy (eBT) sources is difficult because of the high-dose gradients and challenges associated with low-energy modelling. This study examines the accuracy of avail...
Authors: Rita Buono, Elisabetta Cagni, Roberta Castriconi, Surendra Bahadur Chand, Marco Esposito, Claudio Fiorino, Valeria Landoni, Aldo Mazzilli, Eugenia Moretti, Lorenzo Placidi, Giulia Rambaldi Guidasci, Alessia Tudda
Affiliation: IRCCS San Raffaele Scientific Institute, Department of Advanced Technology, IRCCS Regina Elena National Cancer Institute, ASU FC Medical Physics, University Hospital of Parma AOUP, ICTP, B.P. Koirala Memorial Cancer Hospital, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Fatebenefratelli Isola Tiberina – Gemelli Isola
Abstract Preview: Purpose: To explore the feasibility and educational impact of transferring knowledge-based planning (KBP) models—developed using Italian breast radiotherapy data—to a Nepalese hospital, thereby demons...
Authors: Kevin M Brom, Jaydev K. Dave, Chunming Gu, Nicholas J. Hangiandreou, Zaiyang Long, Donald J Tradup
Affiliation: Mayo Clinic
Abstract Preview: Purpose: Ultrasound scanner onboard quality checks for shear wave elastography (SWE) rely on operator judgement and are insufficient. This study aims to establish a protocol for quality assessment and...
Authors: Thomas I. Banks, Bin Cai, Andrew R. Godley, Yang Kyun Park, Hao Peng, Rameshwar Prasad, Chenyang Shen, Shunyu Yan, Haozhao Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, University of Texas Southwestern Medical Center
Abstract Preview: Purpose:
The RefleXion® X1 (RefleXion Medical, Inc., Hayward, CA) uniquely integrates KVCT and PET as on-board image guidance for radiotherapy. It has been installed and commissioned for clinical u...
Authors: Samuel L. Brady, Shruti Hegde, Alexander Knapp, Usman Mahmood, Joseph G. Meier, Elanchezhian Somasundaram, Zachary Taylor
Affiliation: Cincinnati Children's Hospital Medical Ctr, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Cincinnati Children's Hospital Medical Center, Cincinnati Childrens Hospital Med Ctr
Abstract Preview: Purpose:
To assess how two benchmark multi-organ CT segmentation models respond to varying image noise levels.
Methods:
This study utilized the pediatric CT dataset from The Cancer Imaging Ar...
Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Richard A. Popple, Wenyin Shi, Rodney J. Sullivan, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao
Affiliation: Thomas Jefferson University, The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: Objectively evaluating brain sparing as a plan-quality indicator for patients receiving stereotactic radiosurgery (SRS) to multiple metastases (multi-met) is complicated by variability in tar...
Authors: Hyejoo Kang, Andrew Keeler, Mathias Lehmann, Jason Patrick Luce, Ha Nguyen, John C. Roeske
Affiliation: Varian Imaging Laboratory, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago
Abstract Preview: Purpose: Markerless tumor tracking (MTT) using dual-energy (DE) subtraction imaging is being considered as a non-invasive method to track tumors during lung cancer treatment. Prior to clinical impleme...
Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang
Affiliation: Duke University Medical Center
Abstract Preview: Purpose: Gradient-based optimization is the standard approach for IMRT fluence map optimization (FMO). Recently, a machine learning (ML)-assisted framework using a one-layer neural network was propose...
Authors: David P. Adam, Xun Jia, Youfang Lai, Yuncheng Zhong
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University
Abstract Preview: Purpose: Radiopharmaceutical therapy is experiencing a resurgence in interest due to its potential of treating widespread metastatic disease in a patient-specific manner. Accurately measuring and desc...
Authors: Lando S. Bosma, Victoria Brennan, Nicolas Cote, ChengCheng Gui, Nima Hassan Rezaeian, Jue Jiang, Sudharsan Madhavan, Josiah Simeth, Neelam Tyagi, Harini Veeraraghavan, Michael J Zelefsky
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, NYU Langone Health, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Deep learning-based deformable image registration (DIR) models often lack robustness when applied to datasets with differing imaging characteristics. We aimed to (1) improve registration netw...