Authors: Yufeng Cao, Arun Gopal, Kai Huang, Kai Wang
Affiliation: Department of Radiation Oncology, University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland Medical Center, University of Maryland, Baltimore
Abstract Preview: Purpose: The treatment of left-sided breast tumors poses significant concerns regarding the risk of radiation-induced damage to nearby organs, particularly the heart. In clinical practice, breath-hold...
Authors: Zhenzhen Dai, Anthony J. Doemer, Ryan Hall, Kenneth Levin, Bing Luo, Benjamin Movsas, Karen C. Snyder, Kundan S Thind, Eleanor Walker
Affiliation: Henry Ford Health, HFHS
Abstract Preview: Purpose: To investigate the feasibility of a predictive tool for efficient allocation of hypofractionated whole-breast irradiation patients between Varian Truebeam and Ethos systems.
Methods: A ful...
Authors: Hui-Shan Jian, Yu-Ying Lin
Affiliation: Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou
Abstract Preview: Purpose: The image quality assurance of mammographic images is crucial for correct diagnosis. To develop and validate an explainable deep-learning classifier for phantom image quality assessment of di...
Authors: Amy Tien Yee Chang, Chi Wai Cheung, Tin Lok Chiu, Chen-Yu Huang, Chi Wa Kong, Pei-Xiong Li, Pak Hang Nam, Bin Yang, Siu Ki Yu
Affiliation: Comprehensive Oncology Centre, Hong Kong Sanatorium and Hospital, Medical Physics Department, Hong Kong Sanatorium and Hospital
Abstract Preview: Purpose: This study introduces BrachyPlanCheck, an independent Monte Carlo (MC)-based dose calculation tool for 192Ir brachytherapy retrospective study or algorithm commissioning.
Methods: BrachyPl...
Authors: Ryan Clark, Anthony Magliari, Luis Felipe Oliveira E Silva, Yang Sheng, Jason R Vickress, Qingrong Jackie Wu, Giulianne Rivelli Rodrigues Zaratim
Affiliation: Verspeeten Family Cancer Center, Office of Medical Affairs, Varian, A Siemens Healthineers Company, Confiar Radioterapia, Duke University Medical Center
Abstract Preview: Purpose: Develop a toolset to replace several of the tedious steps required to manually generate 3D breast treatment plans using static gantry forward planned tangent beams.
Methods: Eclipse Sc...
Authors: Michael Dohopolski, Xuejun Gu, Hao Jiang, Steve B. Jiang, Christopher Kabat, Jingying Lin, Weiguo Lu, Michael Tang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Neuralrad LLC, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose: To streamline access to clinical data stored in Oncology Information Systems such as MOSAIQ or ARIA, we developed an AI-powered chatbot capable of querying, summarizing, and interactively ans...
Authors: David Alcorta, Lindsay Bolino, Olivia Canter, Seifallah Emam, Joseph Farina, Timothy Haystead, Philip Hughes, Keshav Jha, David Loiselle, Mark Oldham, Victoria J. P. Radosova
Affiliation: Duke University Department of Pharmacology and Cancer Biology, Medical Physics Graduate Program, Duke University, Duke University Department of Medicine, Duke University, Duke University Pharmacology and Cancer Biology, Duke Univerity, Department of Radiation Oncology, Duke University Medical Center
Abstract Preview: Purpose: To simulate how Cherenkov light (CL) produced during radiation therapy can activate targeted photodynamic molecules. To experimentally determine dose and concentration thresholds for biologic...
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: Stephen R. Bowen, Richard Cheng, Kylie Kang, Janice Kim, Ana Paula Santos Lima, Dominic A. Maes, Juergen Meyer, Karen Ordovas, Kerry Reding
Affiliation: Department of Radiation Oncology, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiology, University of Washington, Division of Cardiology, University of Washington, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington
Abstract Preview: Purpose: Artificial intelligence (AI)-based auto-segmentation tools can increase the efficacy and reproducibility of radiotherapy (RT) treatment planning. This study evaluates the quality of AI-genera...
Authors: Elizabeth L. Covington, Robert T. Dess, Charles S. Mayo, Michelle L. Mierzwa, Dan Polan, Jennifer Shah, Claire Zhang
Affiliation: University of Michigan, Department of Radiation Oncology, University of Michigan
Abstract Preview: Purpose: Auto-segmentation improves contour consistency and standardization in radiation therapy but may introduce variations from current practices, potentially impacting treatment outcomes and toxic...
Authors: Jianrong Dai, Jun Dang, Enzhuo Quan, Yong Sang, Jianan Wu
Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, National Cancer Center / National Clinical Research Center for Cancer / Cancer Hospital & Shenzhen Hospital / Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Abstract Preview: Purpose: The current conformity index (CI) formula is distorted for radiotherapy plans with multiple, non-enclosing targets. We redefined the volume of reference isodose (VTV) parameter in the CI form...
Authors: Rodrigo T Massera, Sofia Giaccone Thomaz, Alessandra Tomal, Giovanna Tramontin
Affiliation: Universidade Estadual de Campinas. Instituto de Física Gleb Wataghin, Department of Imaging & Pathology, unit of Medical Physics & Quality Assessment, KU Leuven
Abstract Preview: Purpose: Monte Carlo simulations are increasingly used in breast dosimetry for their precision in estimating difficult-to-measure quantities, such as glandular dose. With ionizing radiation in breast ...
Authors: Chia-Lung Chien, Wen C. Hsi, Faraz Kalantari, Pouya Sabouri, Man Yam
Affiliation: Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)
Abstract Preview: Purpose:
Reducing treatment delivery time is critical to improving patient throughput and minimizing the risk of intrafraction motion, which can compromise treatment accuracy. This study identifies...
Authors: Zahra Bagherpour, Manijeh Beigi, Pedram Fadavi, Faraz Kalantari, Moghadaseh Khaleghibizaki, Hengameh Nazari, Mojtaba Safari, Sepideh Soltani
Affiliation: Department of Radiation Oncology, School of Medicine, Iran University of Medical Sciences, Department of Radiation Oncology, School of Medicine, Emory University and Winship Cancer Institute, Department of Radiation Oncology, Iran University of Medical Sciences, University of Arkansas for medical sciences, Department of Radiation physics, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences
Abstract Preview: Purpose: This study aims to evaluate whether readily available mammographic and sonographic data, combined with machine learning (ML) models, can predict critical molecular factors (ER, PR, HER2) in b...
Authors: Bowen Jing, Jing Wang
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
Abstract Preview: Purpose: Medical images acquired at multiple time points during neoadjuvant chemotherapy allow physicians to assess patients’ responses and personalize treatment plans accordingly. Studies from the I-...
Authors: Rafe A. McBeth, Kuancheng Wang, Ledi Wang
Affiliation: Department of Radiation Oncology, University of Pennsylvania, Georgia Institute of Technology, University of Pennsylvania
Abstract Preview: Purpose:
The integration of AI in clinical workflows presents unprecedented opportunities to enhance treatment quality in radiation oncology, yet it also demands innovative approaches to address th...
Authors: Kyle J Myers
Affiliation: Puente Solutions LLC
Abstract Preview: N/A...
Authors: Ryan Burri, Nazanin Hoshyar, Jerry W. McCoy, Yulin Song, Huma Syed
Affiliation: Bay Pines VA Medical Center
Abstract Preview: Purpose: The study aimed to streamline traditionally manual, iterative, and time-consuming VMAT commissioning process. The goal was to identify an optimal set of MLC dosimetric parameters that minimiz...
Authors: Klaus Bacher, Louise D'hondt, Jeff Rutten, Gwenny Verfaillie
Affiliation: Ghent University
Abstract Preview: Purpose: Manual organ segmentation is a very time-consuming but necessary process in personalized dosimetry. Automatic segmentation tools may alleviate this task. In this study the impact of automatic...