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Results for "optimization framework": 51 found

A Deep Learning-Based Method for Rapid Generation of Spot Weights in Single Field Optimization for Proton Therapy in Prostate Cancer

Authors: Yu Chang, Mei Chen

Affiliation: Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine

Abstract Preview: Purpose: Spot weights optimization, as a critical step in the proton therapy, is often time-consuming and labor-intensive. Deep learning, with its powerful learning and computational efficiency, can e...

A Hybrid Population-Based and Patient-Specific Framework for 2Dโ€“3D Deformable Registration-Driven Limited-Angle Cone-Beam CT Estimation

Authors: Xiaoxue Qian, Hua-Chieh Shao, You Zhang

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:
Limited-angle CBCT (LA-CBCT) reduces imaging time and dose but suffers from under-sampling artifacts. 2Dโ€“3D deformable registration addresses this problem by estimating LA-CBCTs from defor...

A Novel Margin-Based Focal Distance Loss for Lesion Segmentation in Medical Imaging

Authors: Weiguo Lu, Hua-Chieh Shao, Guoping Xu, You Zhang

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:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...

A Novel Non-Measured and DVH-Based IMRT QA Framework with Machine Learning for Instant Classification of Susceptible Lung SBRT VMAT Plans

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...

A Radiomic Quantification Framework for Hyperparameter Optimization in Texture Characterization

Authors: Yuli Lu, Chendong Ni, Cheng Qian, Kun Qian, Weiwei Sang, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Haiming Zhu

Affiliation: Jiahui International Hospital, Radiation Oncology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: To develop a radiomic quantification framework to evaluate the effects of radiomic image preprocessing hyperparameters (i.e., image resampling and discretization) on texture characterization ...

AI-Assisted Algorithm to Generate Patient Postures for Tset Dose Evaluation

Authors: Kostas Danniidis, Agelos Kratimenos, Yufu Wang, Timothy C. Zhu, Yifeng Zhu

Affiliation: University of Pennsylvania

Abstract Preview: Purpose: This study aims to develop software and algorithms utilizing artificial intelligence (AI) to seamlessly create 3D patient postures during Total Skin Electron Therapy (TSET). The resulting mes...

Advanced Modeling of Singlet Oxygen Distribution in Pleural Cavity Photodynamic Therapy Using Validated Geometric Standardization

Authors: Hongjing Sun, Timothy C. Zhu

Affiliation: University of Pennsylvania

Abstract Preview: Purpose: This study aims to develop a model of singlet oxygen distribution in pleural photodynamic therapy (PDT) by combining standardized anatomical coordinates with CT-validated geometry reconstruct...

An FMEA-Based Approach to Improve the Process and Quality Control on MR Imaging from Outside Diagnostic Imaging Centers to be Used for Radiation Treatment Planning

Authors: Olivier Blasi, Eric Cameron, Brad K. Lofton

Affiliation: CAMP, Colorado Assn in Medical Phys (CAMP)

Abstract Preview: Purpose:
Magnetic Resonance (MR) imaging obtained from external centers for radiation therapy (RT) planning can suffer from suboptimal protocols and geometric distortions. These issues can require ...

An Integrated Optimization Method for Joint Lattice Positioning and Dose Planning in Lattice Therapy

Authors: Hao Gao, Xue Hong, Harold Li, Yuting Lin, Jufri Setianegara, Xin Tong, Chao Wang, Weijie Zhang, Ya-Nan Zhu

Affiliation: Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Lattice radiotherapy (LATTICE) is a form of spatially fractionated radiation therapy (SFRT) designed to deliver high radiation doses to specific tumor regions (vertices) while sparing surroun...

An Ultra-High Parallel Performance (UHPP) Framework for Highly Complex Radiotherapy Planning

Authors: Lu Jiang, Shusen Jing, Qihui Lyu, Dan Ruan, Ke Sheng, Qifan Xu

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: In radiotherapy, the conformity and compactness of dose distribution are vital to patient outcomes. The introduction of highly complex planning, such as 4ฯ€ radiotherapy, has provided a system...

Automated Treatment Planning Script for Bone Metastases Using Eclipse TPS

Authors: Maria Jose Almada, Bruno Forti, Andres Lima, Carlos Daniel Venencia

Affiliation: Instituto Zunino - Fundacion Marie Curie

Abstract Preview: Purpose:
To automate the planning of radiotherapy treatments for bone metastases using a script in the ECLIPSE planning system version 15.6 with a graphical interface.
Methods:
A script was d...

BEST IN PHYSICS IMAGING: Revolutionizing Neurocognitive Dynamic Pattern Discovery with Self-Supervised AI in Functional Brain Imaging

Authors: Lei Xing, Zixia Zhou

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University, Stanford

Abstract Preview: Purpose: Functional brain imaging techniques, such as functional magnetic resonance imaging (fMRI), generate high-dimensional, dynamic data reflecting complex neural processes. However, extracting rob...

Beam Orientation Optimization in IMRT Using Sparse Mixed Integer Programming and Non-Convex IMRT Fluence Map Optimization

Authors: Yabo Fu, Yang Lei, Yu Lei, Haibo Lin, Ruirui Liu, Tian Liu, Kenneth Rosenzweig, Charles B. Simone, Shouyi Wei, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York Proton Center

Abstract Preview: Purpose: Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is traditionally a complex, non-convex problem tackled with heuristic methods. This study benchmarks global...

Combining Proton Flash and Spatially Fractionated Radiotherapy โ€“ Experimental and Simulation Based Dosimetric Characterization

Authors: Gulakhshan M Hamad, Sina Mossahebi, Yannick P. Poirier, Amit Sawant

Affiliation: University of Maryland School of Medicine, Maryland University Baltimore

Abstract Preview: Purpose:
The combination of ultra-high dose rate (UHDR) proton therapy, known for normal tissue sparing, with spatially-fractionated radiotherapy (SFRT), promising enhanced tumor control and tissue...

Convergence Speed Advantages of a Machine Learning Assisted Framework in IMRT Fluence Map Optimization โ€“ a Comparison Study Using Multiple Convergence Criteria

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose: Convergence speed is crucial for an optimizer. Faster convergence leads to better solutions with fewer iterations and less time. Recently, a machine learning (ML)-assisted framework employing...

Deep Learning-Based Segmentation for Precision Radiation Therapy in Breast Cancertreatment

Authors: Hamdah Alanazi, Silvia Pella

Affiliation: FAU, Florida Atlantic University

Abstract Preview: Purpose: The appearance of breast cancer in the global list of most common cancers worldwide requires
research for ultimate treatment approaches including radiation therapy to reduce deaths from br...

Development of an Inverse Treatment Planning System for Precision Small Animal Radiotherapy

Authors: Zihao Liu, Qiwei Wu, Yanfei Xiong, Yidong Yang, Ning Zhao

Affiliation: Department of Engineering and Applied Physics, School of Physical Sciences, University of Science and Technology of China, Department of Engineering and Applied Physics, University of Science and Technology of China, University of Science and Technology of China

Abstract Preview: Purpose: To develop an inverse planning framework that optimizes beam angles and intensities for small animal radiotherapy and to validate its accuracy and effectiveness.
Methods: The inverse plann...

Development of an Orthogonal X-Ray Projections-Guided Cascading Volumetric Reconstruction and Tumor-Tracking Model for Adaptive Radiotherapy

Authors: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu

Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences

Abstract Preview: Purpose: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...

Dosimetric Assessment of Simultaneous Multi-Energy and Fluence Optimization for IMRT and VMAT

Authors: Aliasghar Rohani, Rui Zhang

Affiliation: Louisiana State University, Baton Rouge, Louisiana, Department of Radiation Oncology, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: This study aimed to evaluate the impact of simultaneous optimization of multi-photon beam energy and fluence on IMRT and VMAT treatment planning.
Methods: An Elekta linear accelerator (lin...

Efficient Denoising of Low-Statistic Influence Matrices Using a Diffusion Transformer-Based Framework for Adaptive Proton Therapy

Authors: Yuzhen Ding, Hongying Feng, Jason Michael Holmes, Baoxin Li, Wei Liu, Daniel Ma, Lisa McGee, Samir H. Patel, Jean Claude M. Rwigema, Sujay A. Vora

Affiliation: Arizona State University, Department of Radiation Oncology, Mayo Clinic, Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Purpose:
Intensity-modulated proton therapy (IMPT) is a preferred treatment modality for head and neck (H&N) cancer patients, offering precise tumor targeting while sparing surrounding organs at ri...

Film-Based Method for Accurate Radiation Isocenter Determination in Linear Accelerators Using 3D Starshot

Authors: Robert A. Corns, Mohammad Kanber

Affiliation: East Carolina University, East Carolina University Brody School of Medicine

Abstract Preview: Purpose:
Accurate determination of the radiation isocenter is crucial for precise radiotherapy treatments, directly impacting patient safety and treatment quality. This study presents a computation...

First Demonstration of Prostate Radiotherapy Plan Optimization on an IBM Quantum Computer

Authors: Keisuke Fujii, Masahiro Kitagawa, Arezoo Modiri, Yuichiro Nakano, Ken N. Okada, Robabeh Rahimi, Akira SaiToh, Amit Sawant, Satoyuki Tsukano, Baoshe Zhang

Affiliation: University of Maryland, University of Maryland in Baltimore, Department of Computer and Information Sciences, Sojo University, Center for Quantum Information and Quantum Biology, Osaka University, Maryland University Baltimore, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Fully personalized radiotherapy requires computational resources far exceeding those of conventional CPU/GPU systems. This study explores the use of quantum computing (QC) in radiotherapy pla...

Geant4-DNA Simulation of Human Breast Cancer Cells Line MCF7 Irradiation with 213bi As Targeted Radionuclides

Authors: Hamid Abdollahi Nasehabad, Mehrangiz Amiri, Mohammad Reza Deevband, Faraz Kalantari, Milad Peer-Firozjaei, Ali Shabestani Monfared, Ehsan Tajikmansoury

Affiliation: Biomedical Engineering and Medical Physics Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Department of Radiology, University of British Columbia, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiobiology and Medical Physics, Babol University of Medical Sciences, 1. Department of Radiobiology and Medical Physics, Babol University of Medical Sciences, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine

Abstract Preview: Purpose:
Targeted radionuclide therapy (TRNT) with 213Bi- labeled radiopharmaceuticals is a promising approach in targeted alpha and beta therapy for cancer. This study aims to assess double-strand...

Generation of Patient-Specific Phantom for Head & Neck Proton Therapy Based on Xcat

Authors: Cheng-En Hsieh, Shen-Hao Li, Hsin-Hon Lin, Shu-Wei Wu, An-Ci Yang

Affiliation: Department of Medical Imaging and Radiological Sciences, Chang Gung University, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital Linkou

Abstract Preview: Purpose:
The aim of this study is to develop a framework of generating patient-specific phantom tailored for head and neck proton therapy. From these phantoms, digital reference objects based on th...

High-Resolution Limited-Angle CBCT Image Reconstruction for Non-Coplanar Radiation Therapy Via Dual-Domain Ordered-Subset Neural Representation with Prior Embedding (DDOS-NeRP)

Authors: Yu Gao, Lei Xing, Siqi Ye

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
Limited-angle CBCT (LA-CBCT) scans are often the only option for non-coplanar radiation therapy to prevent potential mechanical collisions. However, the consecutive angular occlusion of pr...

Implementation of Radiochemotherapy Applied to Virtual Spheroids Using an Open-Source Multiscale Computational Framework

Authors: Ignacio Espinoza, Ignacio Narea, Beatriz Sanchez-Nieto

Affiliation: Institute of Physics, Pontificia Universidad Catรณlica de Chile

Abstract Preview: Purpose: This study aims to evaluate the tumor response to combined radiochemotherapy on MCF7 spheroids using an open-source multiscale computational framework. The model provides a platform to simula...

Implementing a Learning-to-Optimize Machine Learning Framework to Accelerate VMAT Treatment Planning Optimization for Prostate Cancer

Authors: Ara Alexandrian, Sadiki Daniel

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: To develop a learning-to-optimize machine learning model that accelerates optimization in VMAT treatment planning by training on prostate patient data.
Methods: A treatment plan dataset of...

Incorporating Cyclic Group Equivariance into Deep Learning for Reliable Reconstruction of Rotationally Symmetric Tomography Systems

Authors: Fang-Fang Yin, Lei Zhang, Yaogong Zhang

Affiliation: Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Rotational symmetry is an inherent property of many tomography systems (e.g., CT, PET, SPECT), arising from the circular arrangement or rotation of detectors. This study revisits the image re...

Memory-Efficient Deep Learning for Volumetric Cone-Beam CT Image Reconstruction

Authors: Ziqi Gao, Lei Xing, Siqi Ye, S. Kevin Zhou

Affiliation: Department of Radiation Oncology, Stanford University, University of Science and Technology of China (USTC)

Abstract Preview: Purpose: To address the challenge of high memory usage in volumetric cone-beam CT (CBCT) imaging, we propose a method that combines joint reconstruction and super-resolution for sparsely sampled CBCT ...

Monte Carlo Simulation of a Prototype Fluence Field Modulated Cone Beam CT System

Authors: Gregory J Bootsma, Tunok Mondol

Affiliation: University Health Network, Princess Margaret Cancer Center

Abstract Preview: Purpose:
To evaluate the impact of prototype fluence field modulation (FFM) cone-beam CT (CBCT) on dose reduction and image quality using Monte Carlo simulations. This study particularly looks at t...

Multi-Scale, Multi-Task Framework with Jacobian Descent for Multi-Plan Dose Prediction in Sequential Boost Radiotherapy

Authors: Steve B. Jiang, Mu-Han Lin, Yu-Chen Lin, Austen Matthew Maniscalco, Dan Nguyen, David Sher, Xinran Zhong

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, UT Dallas

Abstract Preview: Purpose:
Sequential boost radiotherapy (RT) poses a challenge in allocating dose across multiple plans while protecting organs at risk (OARs). Clinicians must decide whether OAR sparing should occu...

Multi-Sid Optimization for 4 Pi Robotic Radiotherapy

Authors: Qihui Lyu, Dan Ruan, Ke Sheng, Jingjie Yu

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California, San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: The robotic arm radiotherapy platform enables flexible delivery of non-coplanar and non-isocentric radiotherapy with variable Source-to-Isocenter Distances (SIDs). However, the high degrees o...

Multi-Variat, Multi-Model, and Multi-Patient: From Pure Feasibility to Generalizability in Machine Learning Outcome Prediction Model-Based Treatment Plan Optimization

Authors: Martin Frank, Oliver Jรคkel, Niklas Wahl

Affiliation: Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Karlsruhe Institute of Technology (KIT)

Abstract Preview: Purpose: Machine learning (ML) models on normal tissue complication and tumor control probability ((N)TCP) exploiting e.g. dosiomic and radiomic features are playing an increasingly important role in ...

Neural Network Based Differentiable Optimization for Volumetric Modulated Arc Therapy (VMAT)

Authors: Peng Dong, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Stanford University

Abstract Preview: Purpose: Volumetric Modulated Arc Therapy (VMAT) optimization is a complex, non-convex problem with numerous variables and intricate constraints. Traditional optimization methods often lack efficiency...

Optimization of Impulsed Acquisition Protocols on 1.5T MRI Using Simulation-Based Bayesian Experimental Design for Cell Size Imaging

Authors: Yan Dai, Jie Deng, Xun Jia, Wen Li, Junzhong Xu

Affiliation: Johns Hopkins University, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiology, Vanderbilt University Medical Center, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Cell size is a vital parameter in evaluating the tumor microenvironment, including cell apoptosis and radiotherapy(RT)-induced immune cell infiltration. The IMPULSED(Imaging Microstructural P...

Patient-Specific Deep Reinforcement Learning Framework for Automatic Replanning in Proton Therapy for Head-and-Neck Cancer

Authors: Malvern Madondo, Mark McDonald, Zhen Tian, Christopher Valdes, Ralph Weichselbaum, Xiaofeng Yang, David Yu, Jun Zhou

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Emory University, Department of Radiology, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Head-and-neck (HN) cancer patients often experience significant anatomical changes during treatment course. Proton therapy, particularly intensity-modulated proton therapy (IMPT), is sensitiv...

Patient-Specific Treatment Plan Optimization through Intentional Deep Overfit Learning As a Warm Start for Longitudinal Adaptive Radiotherapy

Authors: Wouter Crijns, Frederik Maes, Loes Vandenbroucke, Liesbeth Vandewinckele

Affiliation: Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven; Department of Radiation Oncology, UZ Leuven, Department ESAT/PSI, KU Leuven; Medical Imaging Research Center, UZ Leuven, Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven

Abstract Preview: Purpose: To explore intentional deep overfit learning (IDOL) to exploit the initial treatment plan to predict an adaptive radiotherapy plan.
Methods: A conditional generative adversarial network is...

Quality and Performance Advantages of a Machine Learning-Assisted Framework for IMRT Fluence Map Optimization

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...

Quantifying Uncertainties in Radiation Risk and Performance-Based Clinical Risk Assessment in Clinical Computed Tomography

Authors: Em Harkness, Francesco Ria, Ehsan Samei

Affiliation: Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose:
A recently introduced mathematical method quantifies performance-based clinical risk to create a risk-to-risk assessment with radiation risk, rendering the so-called total risk. However, t...

Real-Time Automatic Treatment Planning System (RT-AutoTPS) for Volumetric Modulated Arc Radiotherapy (VMAT)

Authors: Steve B. Jiang, Austen Matthew Maniscalco, Dan Nguyen, Chenyang Shen, Jiacheng Xie, Shunyu Yan, Ying Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, 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, The University of Texas at Dallas

Abstract Preview: Purpose: Although treatment planning systems (TPSs) can handle dose calculation and plan optimization automatically, planning for radiotherapy still requires extensive efforts and expertise from a mul...

Real-Time Fully Automated IMRT Planning without Optimization Process Using a Two-Step AI Framework

Authors: Daisuke Kawahara, Takaaki Matsuura, Yuji Murakami, Ryunosuke Yanagida

Affiliation: Hiroshima High-Precision Radiotherapy Cancer Center, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima

Abstract Preview: Purpose: In recent years, automation in radiation therapy planning using AI has gained significant attention to reduce the workload of treatment planners. Adaptive Radiation Therapy (ART), as a new fo...

Rectangular Aperture-Based Beam Orientation Optimization for 4ฯ€ Non-Coplanar Small Animal IMRT Delivery

Authors: Dante PI Capaldi, Lu Jiang, Qihui Lyu, Ke Sheng

Affiliation: Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose:
Preclinical small animal studies help understand radiation-induced biological responses, toxicities, and mechanisms, facilitating the translation of new therapies to patient treatment. Int...

Reinforcement Learning Based Machine Parameter Optimization for Two-Arc Prostate VMAT Planning

Authors: William T. Hrinivich, Junghoon Lee, Lina Mekki

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins University

Abstract Preview: Purpose: Volumetric modulated arc therapy (VMAT) planning is a computationally expensive process. In this work, we propose a reinforcement learning (RL) framework to automatically optimize dose rate a...

Standardized MRI-CT Hybrid Workflow for High-Dose-Rate Image-Guided Adaptive Brachytherapy in Cervical Cancer: Aapm TG-303 Implementation

Authors: Kim Creach, Kim Howard, Julius G. Ojwang, Richard A. Shaw, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: To present a standardized MRI-CT hybrid workflow for High-Dose-Rate (HDR) Image-Guided Adaptive Brachytherapy (IGBT) in cervical cancer, aligned with AAPM TG-303, as a model to assist with im...

Standardizing Hybrid Angio-CT Procedure Terminology: Mapping to Acr Common Lexicon for Future Drl Establishmen

Authors: Manuel M. Arreola, Hugh Davis, Daniella Fabri, Emily L. Marshall, BC Schwarz

Affiliation: University of Florida

Abstract Preview: Purpose:
This study aims to map procedure names, descriptions, and CPT codes from a Hybrid Angio-CT room to the American College of Radiology (ACR) Common Lexicon. This mapping will support expedit...

Streamlining Hippocampal-Sparing Whole-Brain VMAT Planning: Enhancing Efficiency and Plan Quality with an Automated Workflow

Authors: Eric C. Ford, Yulun He, Minsun Kim, Dustin Melancon, Juergen Meyer, Dong Joo Rhee, Yinghua Tao

Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, MD Anderson Cancer Center, University of Washington

Abstract Preview: Purpose: To develop and evaluate an automated-planning technique capable of generating high-quality treatment plans for hippocampal-sparing-whole-brain radiation therapy.
Methods: An auto-planning ...

The Impact of a Probabilistic Definition of the Target Volume and Radiobiological Optimization on Complication Probabilities in Proton Therapy

Authors: Ana Maria Barragan Montero, John A. Lee, Eliot Peeters, Romain Schyns, Edmond S. Sterpin, Sophie Wuyckens

Affiliation: UCLouvain, Universite Catholique de Louvain

Abstract Preview: Purpose:
Although the likelihood of a point being tumorous decreases with distance from the GTV, CTVs are still defined as binary masks. Recently, the concept of clinical target distribution (CTD),...

Transforming CT Technologist Training: Real-Time Feedback, Gamification, and Phantom-Based Education for Accurate Patient Positioning

Authors: Rebecca Lamoureux, Zahra (Zara) Razi, Zachary Whipps

Affiliation: University of New Mexico Hospital

Abstract Preview: Purpose: Patient mispositioning in CT imaging contributes to inconsistent radiation dose delivery and suboptimal image quality, impacting patient safety and diagnostic outcomes. This study evaluates a...

Two's Company, Three's a Crowd? a Bayesian Approach to Optimizing the Number of Measurement Readings in Radiation Therapy QA

Authors: Siyong Kim, Ava Paek, Joseph B. Schulz, James J. Sohn, Eric D. Stolen, Ethan D. Stolen

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Central Florida, Virginia Commonwealth University, Department of Radiation and Cellular Oncology, University of Chicago, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: The American Association of Physicists in Medicine Task Group 142 (AAPM TG-142) guidelines recommend three measurements during monthly quality assurance to keep results within two standard de...

Unidose: A Universal Framework for IMRT Dose Prediction

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, Kangning Zhang

Affiliation: 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: Dose prediction (DP) is essential in guiding radiotherapy planning. However, current DP models for intensity-modulated radiation therapy (IMRT) primarily rely on fixed-beam orientations and a...

Universal Range Modulators for Flash Proton Therapy: 3D Printing of Stackable Variable Density Units

Authors: Eric S. Diffenderfer, Lei Dong, Alejandro Garcia, Wenbo Gu, Michele M. Kim, Alexander Lin, Kai Mei, Peter B. Noรซl, Boon-Keng Kevin Teo, Lingshu Yin, Jennifer Wei Zou

Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania

Abstract Preview: Purpose: We present a novel 3D-printed range-modulating devices with spatially modulated density for FLASH particle therapy. By varying density distributions, spread-out Bragg peaks(SOBPs) can be gene...