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Results for "set errors": 137 found

A Comprehensive TG 263 Toolkit for Generating, Validating, and Parsing Radiation Therapy Target Names

Authors: Rex A. Cardan, Richard A. Popple

Affiliation: University of Alabama at Birmingham

Abstract Preview: Purpose:
Compliance with TG 263 naming conventions for target structures in radiation oncology remains a challenging task due to the complexity and variability of the protocol. Traditional validati...

A Deep Learning Method for Direct Vmi Inference Using a Dual-Layer Radiotherapy Kv-CBCT Imager

Authors: Ross I. Berbeco, Vera Birrer, Raphael Bruegger, Pablo Corral Arroyo, Roshanak Etemadpour, Dianne M. Ferguson, Rony Fueglistaller, Thomas C. Harris, Yue-Houng Hu, Matthew W. Jacobson, Mathias Lehmann, Nicholas Lowther, Daniel Morf, Marios Myronakis

Affiliation: Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology, Dana Farber/Brigham and Women's Cancer Center, Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Womens Hospital, Dana Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Varian Imaging Laboratory, Dana-Farber Cancer Institute

Abstract Preview: Purpose: A challenge for dual energy CBCT is that noise and residual errors in material decomposition steps can become amplified when forming low energy, high contrast virtual mono-energetic images (V...

A Deep Learning-Based Approach for Rapid Prediction of IMRT/VMAT Patient-Specific Quality Assurance for Online Adaptive Plans Generated with a 0.35T MR-Linac

Authors: Suman Gautam, Tianjun Ma, William Song

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: We propose an artificial intelligence (AI)-based method to rapidly predict the patient-speciïŹc quality assurance (PSQA) results for magnetic resonance (MR)-guided online adaptive radiation th...

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 Diffusion-Based AI Framework for Continuous Deformable Image Registration and Time-Resolved Dynamic CT Generation

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Gregory Szalkowski, Qingying Wang, 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: Respiratory motion management is crucial for accurate radiation delivery to moving targets while protecting healthy tissue, relying on time-resolved volumetric imaging and continuous deformab...

A Dosimetric Study of Range-Compensated Proton Arc Therapy

Authors: Alonso N. Gutierrez, Daniel E. Hyer, Blake R. Smith

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Iowa Health Care, University of Iowa

Abstract Preview: Purpose: To perform a feasibility study of optimizing and producing a compact range compensator to deliver single-energy pencil beam scanning (PBS) proton arc therapy treatments. Omitting energy chang...

A Ground Truth Label-Mediated Method for Improved Bone and Gas Cavity Definition for MRI-Guided Online Adaptive Radiotherapy Workflows Using Synthetic CT Images.

Authors: Benito De Celis Alonso, Braian Adair Maldonado Luna, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, Kamal Singhrao

Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla

Abstract Preview: Purpose: Artificial Intelligence (AI)-generated synthetic CT (sCT) images can be used to provide electron densities for dose calculation for online adaptive MRI-guided stereotactic body radiotherapy (...

A Hybrid 4π-Proton Arc Robust Optimization

Authors: Wenhua Cao, Xianjin Dai, PhD, Hadis Moazami Goudarzi, Gino Lim, Miaolan Xie, Lei Xing, Lewei Zhao

Affiliation: University of Chicago Booth School of Business, Department of Radiation Oncology, Stanford University, Department of Industrial Engineering, University of Houston, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Proton Arc Therapy (PAT) delivers a continuous dose of radiation during gantry rotation. 4π is a non-coplanar technique used for advanced proton therapy delivery. This work proposes a hybrid ...

A Mechatronic Biopsy Guidance System for an Integrated 3D TRUS with Prostate-Specific PET System

Authors: Jeffrey Bax, Ian A. Cunningham, Aaron Fenster, Lori Gardi, Sule Karagulleoglu Kunduraci, Alla Reznik, David Tessier

Affiliation: Robarts Research Institute, Imaging Research Laboratories, Robarts Research Institute, Lakehead University

Abstract Preview: Purpose: Image-guided biopsy is critical for early diagnosis of prostate cancer (PCa), the most common cancer in men worldwide. While the prostate-specific PET (P-PET) system offers enhanced sensitivi...

A Monte Carlo Dosimetry-Based Cell Survival Model Incorporating Spatial and Temporal Heterogeneity for Rpt Preclinical Studies

Authors: Alejandro Bertolet, Michael D. Farwell, Sarah Gitto, Victor V. Onecha, Daniel Pryma, Aladdin Riad

Affiliation: Department of Pathology and Laboratory Medicine, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Department of Radiology, Perelman School of Medicine, Perelman School of Medicine at the University of Pennsylvania, Massachusetts General Hospital and Harvard Medical School

Abstract Preview: Purpose: Responses to ionizing radiation (IR) strongly correlate with the absorbed dose. At the cellular level, this is typically described by a linear-quadratic relationship provided the cell populat...

A Multi-Regional and Multi-Omics Approach to Predict Penumonitis in Patients with Locally Advanced Non-Small Cell Lung Cancer in Nrg Oncology Trial RTOG 0617

Authors: Katelyn M. Atkins, Indrin J. Chetty, Elizabeth M. McKenzie, Taman Upadhaya, Samuel C. Zhang

Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center

Abstract Preview: Purpose:
We explored a multi-regional and multi-omics approach to extract CT-based radiomics and 3D dosiomics features to predict radiation pneumonitis (RP) in patients with locally advanced Non-Sm...

A Novel 2D Scintillation Dosimeter Using Long Scintillating Fibers.

Authors: Louis Archambault, Luc Beaulieu, Alexis Horik, Sajjad Ahmad Khan

Affiliation: Département de Physique, de Génie Physique et D'optique, et Centre de Recherche sur le Cancer, Université Laval, Département de physique, de génie physique et d'optique, Université Laval

Abstract Preview: Purpose: This study presents a novel 2D scintillation dosimeter leveraging long scintillating fibers for quality assurance (QA) in radiotherapy. The primary goal is to optimize critical parameters suc...

A Novel Group-Wise Non-Rigid Iterative Closest Point Shape Registration Algorithm with Temporal Smoothness Regularizations for Computing the Respiratory Motion of the Heart in Respiratory 4DCTs and Avoiding Random Cardiac Motion Artifacts

Authors: Hongyu An, Phillip Cuculich, H Michael Gach, Yao Hao, Trevor McKeown, Clifford Robinson, Yuhao Wang, Deshan Yang

Affiliation: Washington University School of Medicine in St. Louis, Washington University School of Medicine, Duke University, Department of Radiation Oncology, Duke University, Washington University in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis

Abstract Preview: Purpose: Cardiorespiratory motion management is crucial in stereotactic arrhythmia radiotherapy to define target margins and minimize cardiac toxicity. While respiratory 4DCT (r4DCT) images can infer ...

A Single-View-Based Electroacoustic Tomography Imaging Using Deep Learning for Electroporation Monitoring

Authors: Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu, Jie Zhang

Affiliation: University of Maryland School of Medicine, University of California, Irvine

Abstract Preview: Purpose: To achieve the full-view image from a single-view sinogram using a two-stage deep learning model for electroacoustic-tomography (EAT), which is an emerging imaging technique with significant ...

A Topological Technique to Unify Image Texture and Morphology to Enhance Radiomic Feature Representations

Authors: David Brizel, Kyle J. Lafata, Jian-Guo Liu, Yvonne M Mowery, Yvonne M Mowery, William Paul Segars, Jack B Stevens

Affiliation: Department of Physics, Duke University, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh

Abstract Preview: Purpose: To develop a technique to quantify tumor topology using a unifying mathematical framework that integrates texture and morphology and to evaluate its feasibility as a prognostic biomarker for ...

A Tumor Tracking Method in Surface-Guided Radiotherapy

Authors: Penghao Gao, Zejun Jiang

Affiliation: 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: Real-time tumor tracking can effectively compensate for the impact of respiratory motion on dose distribution. We propose a patient-specific external-internal correlation model driven by opti...

A Two-Layer, Two-Task Prediction Model Based on 3D Imaging and Residual Networks for Mid-Chemoradiation Tumor Response Prediction on FDG PET for La-NSCLC

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...

A Two-Marker Method for Calculating the Radiological Magnification of the Hip in Standing Pelvic Radiography

Authors: Walaa Abdelfadeel, Reagan Thomas Dugan, Tiffany Kinsey, Cameron Kofler, Zheng Feng Lu, Ingrid S. Reiser, Gregory Stacy, Sara Wallace

Affiliation: University of Chicago Medicine, University of Chicago

Abstract Preview: Purpose: To develop an accurate, vendor-neutral method for estimating geometric magnification at the plane of the hip joint on standing anterior-posterior (AP) radiographs for digital templating of to...

A Vision-Language Model for T1-Contrast Enhanced MRI Generation for Glioma Patients

Authors: Zachary Buchwald, Zach Eidex, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu

Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Gadolinium-based contrast agents (GBCA) are commonly used for patients with gliomas to delineate and characterize the brain tumors using T1-weighted (T1W) MRI. However, there is a rising conc...

A Vqvae-Based Framework with Embedded Kullback-Leibler Divergence for Stochastic and Diverse Dose Prediction

Authors: Weigang Hu

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose: The purpose of this study is to introduce a VQVAE-based framework that addresses the limitations of conventional dose prediction methods, which rely on fixed deep learning models that produce...

AI-Assisted 3D Microscale Mesh Models of Human Lungs from Iodine-Stained Serial-Sectioned Histology Images and Their Dosimetry Applications

Authors: John P. Aris, Wesley E. Bolch, Robert Joseph Dawson, Bonnie N. C. President, Yitian Wang

Affiliation: Johns Hopkins University, University of Florida

Abstract Preview: Purpose: Generation of a mesh-based microscale lung model is essential for accurate dosimetry analysis. Lungs exchange air with the environment and may be exposed to alpha-particle-emitting radionucli...

AI-Driven Troubleshooting for Truebeam Systems: Development and Testing of a Gpt-4o Chatbot

Authors: Sean P. Devan, Cory S. Knill, Charles K. Matrosic, Zheng Zhang

Affiliation: University of Michigan

Abstract Preview: Purpose: Physicists troubleshooting machine issues during patient treatments often face high-pressure situations, balancing error codes, resource constraints, and time-sensitive decisions. To streamli...

Abdomen CT Multi-Organ Segmentation Using Multi-Granularity Feature Extraction

Authors: Zilei Fu, Yi Guo, Wanli Huo, Hongdong Liu, Laishui Lyu, Zhao Peng, Yaping Qi, Senting Wang

Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University

Abstract Preview: Purpose: Medical image boundaries are commonly characterized by smooth gray-level transitions, resulting in pixel-level segmentation errors near these blurred boundaries. To address this, we developed...

Adaptive Proton Flash Therapy through Iterative Modular Pin Recycling

Authors: Zachary Diamond, Pretesh Patel, Sibo Tian, Xiaofeng Yang, David Yu, Ahmal Jawad Zafar, Jun Zhou

Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose:
We propose a method to optimize adaptive proton FLASH therapy (ADP-FLASH) using modularized pin-ridge filters (pRFs) by recycling module pins from the initial plan, reducing pRF adjustment...

Advancing Ionizing Radiation Acoustic Imaging: A Deep Learning Approach for Denoising and Quantitative Reconstruction

Authors: Kyle Cuneo, Issam M. El Naqa, Dale W. Litzenberg, Yiming Liu, Xueding Wang, Lise Wei, Wei Zhang, Jiaren Zou

Affiliation: University of Michigan, H. Lee Moffitt Cancer Center

Abstract Preview: Purpose: To quantitatively map 3D dose deposition during radiotherapy, empowering real-time adaptive radiation treatment.

Methods: The research features reconstructing dose deposition from acou...

Adversarial Diffusion-Based Self-Supervised Learning for High-Resolution MR Imaging

Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Richard L.J. Qiu, Mojtaba Safari, Shansong Wang, Xiaofeng Yang, David Yu

Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: MRI offers excellent soft tissue contrast for diagnosis and treatment but suffers from long acquisition times, causing patient discomfort and motion artifacts. To accelerate MRI, supervised d...

An Initial Simulation Study Towards the Patient-Specific Estimation of Stopping Power Ratio and Sound Velocity Using Protoacoustics: A Sensitivity Matrix Method

Authors: Ye Chen, Koki Kasamatsu, Taeko Matsuura, Taichi Murakami

Affiliation: Hokkaido University, National Institutes for Quantum Science and Technology (QST)

Abstract Preview: Purpose: In proton therapy, CT-based estimation of the stopping power ratio (SPR) is a significant source of range uncertainty. Protoacoustics have been developed to estimate the range in vivo, but fe...

An Integrated, Web-Based Tool for Automated Treatment Time Calculations, Data Visualization, and Documentation for Superficial Radiotherapy Using an SRT-100 Vision

Authors: Stephen D. Davis, Alonso N. Gutierrez, Noah S. Kalman, Yongsook C. Lee, Michael Leyva, Alejandro Rene Llanes Lopez, Carlos M. Rivera, Ranjini P. Tolakanahalli

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Miami Cancer Institute, Miami Cancer Institute, Baptist Health

Abstract Preview: Purpose: Accurate treatment time calculation is a critical component of superficial radiotherapy (SRT), particularly for the SRT-100 Vision, where dose delivery depends on applicator geometry, treatme...

Analysis of Structure Errors in Region of Interest Contouring for Radiotherapy Planning: A Study Using the RT-Contour QA Platform

Authors: Sijuan Huang, Zi LIU, Jing MA, Xin Yang

Affiliation: Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China

Abstract Preview: Purpose: To reduce the pressure of manual review of abnormal situations in manually/automatically delineated regions of interest (ROI), improve its accuracy and basis.
Methods: 220 radiotherapy pat...

Analyzer-Less X-Ray Interferometry with Super-Resolution Methods

Authors: Joyoni Dey, Hunter Cole Meyer, Murtuza Taqi

Affiliation: Louisiana State University

Abstract Preview: Purpose: We propose using super-resolution methods for X-ray grating interferometry without an analyzer with detectors that fail to meet the Nyquist sampling rate needed for traditional image recovery...

Assessment of Practice Consistency for Management of Target Exposure Indices in Digital Radiography

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...

Automated Multimodal Image Registration for Prostate Bed Radiation Treatment

Authors: Quan Chen, Xue Feng, Chunhui Han, Gaofeng Huang, Trevor Ketcherside, Yi Lao, Yun Rose Li, An Liu, Bo Liu, Kun Qing, William T. Watkins

Affiliation: Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, City of Hope National Medical Center, Mayo Clinic Arizona, Carina Medical LLC

Abstract Preview: Purpose: New treatment platforms such as Ethos (Varian Medical Systems) allow the introduction of multi-modal imaging into adaptive radiotherapy workflow to facilitate an up-to-date view of patients’ ...

Automated Review of Radiation Treatment Delivery Reports Using Openai

Authors: Ramesh Boggula, Nikhil Jordan Shad

Affiliation: Wayne State University

Abstract Preview: Purpose: To evaluate the effectiveness of OpenAI in reviewing large volumes of radiation delivery reports from Mobius3D/FX. The goal was to assess whether automating this process could identify potent...

Automated Tool for Radiotherapy Initial Patient Setup: A Robust Approach Based on Vertebral Identification

Authors: Hailun Pan, Yingli Yang, Jie Zhang, Yibin Zhang

Affiliation: Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital, Department of Radiation Oncology, Ruijin Hospital, , Shanghai Jiaotong University School Of Medicine, Shanghai United imaging Healthcare Advanced Technology Research Institute

Abstract Preview: Purpose: Accurate patient positioning is critical in radiotherapy (RT) to ensure effective treatment delivery and minimize harming surrounding healthy tissues. Vertebral misalignment during RT setup h...

Automatic Contour Quality Assurance Using Deep-Learning Based Contours

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...

Automatic Tumor Segmentation and Catheter Detection from MRI for Cervical Cancer Brachytherapy Using Uncertainty-Aware Dual Convolution-Transformer Unet

Authors: Majd Antaki, Rohini Bhatia, Gayoung Kim, Yosef Landman, Junghoon Lee, Akila N. Viswanathan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Physics and Advanced Development Elekta

Abstract Preview: Purpose: Brachytherapy is a standard radiation therapy approach for cervical cancer, which directly delivers radiation source to the tumor using catheters. Treatment planning requires identification o...

BEST IN PHYSICS MULTI-DISCIPLINARY: Motion-Resolved Dynamic CBCT Reconstruction Using Prior-Model-Free Spatiotemporal Gaussian Representation (PMF-STGR)

Authors: Hua-Chieh Shao, Chenyang Shen, Jiacheng Xie, Shunyu Yan, 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) Laboratory, 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: Motion-resolved CBCT imaging, which reconstructs a dynamic sequence of CBCTs reflecting intra-scan motion (one CBCT per x-ray projection), is highly desired for regular/irregular motion chara...

Big Data in-Vivo Epid Image Prediction for VMAT Radiotherapy

Authors: Casey E. Bojechko, Lance C Moore

Affiliation: University of California, San Diego, University of California San Diego

Abstract Preview: Purpose: EPID images collected during treatment can serve as an in-vivo error detection mechanism. Previous works have shown that comparing in-vivo EPID images to AI-predicted EPID images for IMRT pla...

Black Bone MRI As a Surrogate for CT to Detect Intensity Differences in Mandible Sub-Volumes

Authors: Cem Dede, Clifton David Fuller, Renjie He, Laia Humbert Vidan, Stephen Y. Lai, Amy Moreno, Mohamed Naser, Kareem Abdul Wahid, Natalie A West

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, The University of Texas MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Head and neck cancers (HNC) treated with radiation therapy can result in radiation-induced bone injury. In CT, changes in radiodensity correlate to changes in bone integrity. Most studies use...

CNN-Based Reconstruction for 3D Scintillation Dosimetry of Proton Pencil Beams

Authors: Sam Beddar, Jason Michael Holmes, Daniel G. Robertson, James J. Sohn, Ethan D. Stolen

Affiliation: Department of Radiation Oncology, Mayo Clinic, MD Anderson Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago

Abstract Preview: Purpose: Camera-based scintillation dosimetry incorporating large volumes have shown promise for fast and comprehensive evaluation of external beam treatment fields. While some efforts have been made ...

Characterization of a Novel Large-Sized Epid System from the Newly Released Ring Shape Radiation Therapy Halos Tx

Authors: Sen Bai, Guyu Dai, Dong Gao, Lecheng Jia, Guangjun Li, Yanfang Liu, Ying Song, Qing Xiao, Wei Zhang

Affiliation: United Imaging Healthcare, West China Hospital of Sichuan University, Shenzhen United Imaging Research Institute of Innovative Medical Equipment

Abstract Preview: Purpose:
Electronic portal imaging device (EPID) is currently the most widely used in-vivo dosimetry (IVD) device. However, the effective detector area shortage hinders further applications. This s...

Clinical Assessment of Synthetic CT in MR-Only Brain Radiotherapy

Authors: Ergun E. Ahunbay, Colette Gage, Abdul Kareem Parchur, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: AI-generated synthetic CT (sCT) images address challenges with prior sCT approaches, including atlas- and threshold-based methods. Commercial AI-based sCT tools have been introduced. This wor...

Clinical Implementation of Automated Contour Quality Assurance in Head and Neck Radiotherapy

Authors: Sam Armstrong, Jamison Louis Brooks, Nicole Johnson, Douglas John Moseley, Cassie Sonnicksen, Erik J. Tryggestad

Affiliation: Mayo Clinic

Abstract Preview: Purpose: To evaluate the feasibility of a shallow learning-based quality assurance (QA) tool designed to assist human reviewers in assessing organ-at-risk (OAR) contours for head and neck radiotherapy...

Comparative Evaluation of Nn-Unet Models for Radiotherapy Dose Prediction Using the Head and Neck Cancer Patients

Authors: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price

Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering

Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...

Comparison of Clinical Virtual Unenhanced and True Unenhanced Images on a Prototype Deep Silicon Photon-Counting Detector CT

Authors: Meghan Lubner, Krista McClure, Aria M. Salyapongse, Timothy P. Szczykutowicz, Giuseppe Toia, Ming Yan, Zhye Yin, Meghan Yue

Affiliation: GE HealthCare, Departments of Radiology and Medical Physics, University Wisconsin-Madison, GE Healthcare, University of Wisconsin-Madison, UW-Madison, University of Wisconsin Madison, Department of Radiology

Abstract Preview: Purpose: To evaluate virtual unenhanced (VUE) and true unenhanced (TUE) human subject images on a prototype deep silicon photon-counting detector (PCD) CT with prototype algorithms.
Methods: 5 subj...

Compressed Sensing Enhanced Radiomic Feature Selection for Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR)

Authors: Hao Peng, Yajun Yu

Affiliation: 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: Personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is a new treatment paradigm pioneered by our institution. But the early decision-making process in PULSAR is challe...

Construction and Application Study of a Deep Learning-Based Iscout-Guided Precision Radiotherapy Positioning Error Prediction Model for Breast Cancer

Authors: Fangfen Dong, Jiaming Li, Xiaobo Li, Weipei Wang, Zhixin Wang, Bing Wu, Benhua Xu, Yong Yang, Yifa Zhao

Affiliation: Department of Radiation Oncology, Fujian Medical University Union Hospital/Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors/Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematologi, Zhangpu County Hospital, School of Medical Imaging, Fujian Medical University

Abstract Preview: Purpose: To explore the construction and clinical application value of a deep learning-based positioning error prediction model, providing a reference for optimizing iSCOUT system-guided precision rad...

Cross-Slice Attention for Unsupervised 3D Pelvic CBCT to CT Translation

Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap

Affiliation: University of North Carolina at Chapel Hill, Huaqiao University

Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...

Cycle-Consistent Multi-Task Automated Segmentation and Synthetic CT Generation Model for Adaptive Proton Therapy

Authors: Derek Tang, Susu Yan

Affiliation: Massachusetts General Hospital

Abstract Preview: Purpose: To evaluate the performance of a multi-task automated-segmentation and synthetic CT generation model (sCT) and investigate its application in an adaptive proton therapy workflow.
Methods: ...

Data-Driven Forward Projector for Optimization of the Proton Stopping Power Calibration in Treatment Planning Based on Sparse Proton Radiographies

Authors: Hector Andrade-Loarca, Ines Butz, Chiara Gianoli, Prof. Gitta Kutyniok, Jianfei Li, Katia Parodi, Prof. Vincenzo Patera, Angelo Schiavi, Prof. Ozan Öktem

Affiliation: Sapienza University of Rome, Department of Mathematics, Royal Institute of Technology, School of Computation, Information and Technology, Technische Universitaet Muenchen, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t MĂŒnchen (LMU Munich), Department of Mathematics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen

Abstract Preview: Purpose: To explore and demonstrate the feasibility of accurate and fast prediction of the water equivalent thickness (WET) distribution of tissue traversed by a proton imaging pencil beam, aiming at ...

Deep Learning-Based Auto-Segmentation in Cervical High-Dose-Rate Brachytherapy with Clinical Considerations

Authors: Benjamin Haibe-Kains, Ruiyan Ni, Alexandra Rink

Affiliation: Department of Medical Biophysics, University of Toronto, University Health Network

Abstract Preview: Purpose: Accurate auto-segmentation for targets and organs-at-risk (OARs) using deep learning reduces the delineating time in radiotherapy. In high-dose-rate brachytherapy, specific clinical criteria ...

Deep Learning-Based Segmentation Using Cine Epid Images for Real-Time Tumor Monitoring

Authors: Fumiaki Komatsu, Shunsuke Moriya, Ryosuke Nakamura, Takeji Sakae, Toshiyuki Terunuma, Tetsuya Tomita

Affiliation: Graduate School of Comprehensive Human Sciences, University of Tsukuba, Institute of Medicine, University of Tsukuba, Proton Medical Research Center, University of Tsukuba, Department of Radiology, University of Tsukuba Hospital

Abstract Preview: Purpose: To develop a deep learning (DL) model capable of accurately tracking lung tumors independent of beam angle variations.
Methods: A thoracic dynamic phantom simulating lung motion in the sup...

Deep-Learning Convolutional Neural Network-Based Breast Cancer Localization for Mammographic Images: A Study on Simulated and Clinical Images

Authors: Xiaoyu Duan, Xiang Li, Wenbo Wan, Lei Zhang, Yiwen Zhang

Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Breast screening has been proved to reduce breast cancer mortality by early detection and treatment for patients. Mammography is the most common and widely used technique for breast cancer sc...

Deformable Scintillator Array Dosimetry for In Vivo Volumetric Dose and Dose-Rate Validation of Uhdr Proton Therapy

Authors: Petr Bruza, Megan Clark, David J. Gladstone, Joseph Harms, Anthony E. Mascia, Brian W Pogue, Roman Vasyltsiv, Zhiyan Xiao, Rongxiao Zhang, Yongbin Zhang

Affiliation: Cincinnati Children's Proton Therapy Center, University of Missouri, Dartmouth College, Thayer School of Engineering, Dartmouth College, Washington University in St. Louis, University of Wisconsin - Madison

Abstract Preview: Purpose: With developing FLASH trials requiring diligent delivery monitoring, current proton therapy in-vivo dosimetry (IVD) cannot provide comprehensive verification, including dose and dose-rate vol...

Determine Noise Weighting Factor in Photon-Counting CT Via Deep Learning for Personalized Noise Reduction

Authors: Xinhui Duan, Roderick W. McColl, Mi-Ae Park, Liqiang Ren, Gary Xu, Kuan Zhang, Yue Zhang

Affiliation: UT Southwestern Medical Center, Department of Radiology, UT Southwestern Medical Center, Imaging Services, UT Southwestern Medical Center

Abstract Preview: Purpose:
Image-based deep-learning noise-reduction techniques have been developed for photon-counting CT (PCCT) to improve image quality with reduced radiation dose. The denoising strength is typic...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity

Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...

Developing and Evaluating the First Pre-Treatment Physics Plan Checklist for Error Detection in Biology-Guided Radiotherapy (BgRT)

Authors: Michael Burke, David J. Carlson, Yiu-Hsin Chang, Huixiao Chen, Zhe (Jay) Chen, Emily A. Draeger, Dae Yup Han, Vanessa Hill, Ann-Teresa Jasman, John Kim, Svetlana Kuznetsova, MinYoung Lee, Daniel Longo, Henry S. Park, Adam Shulman, Lauren Tressel, Weili Zhong

Affiliation: Department of Therapeutic Radiology, Yale University School of Medicine

Abstract Preview: Purpose:
The complexity of biology-guided radiotherapy (BgRT), particularly with systems like RefleXion X1, necessitates robust pre-treatment quality assurance (QA) to ensure patient safety, treatm...

Development of a Deep Learning Model for Accurate Brain Dose Prediction in Multi-Target Stereotactic Radiosurgery Plan Evaluation

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Wenyin Shi, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Multi-target stereotactic radiosurgery (SRS) planning poses challenges due to complex geometries, small target volumes, and steep dose gradients. Achieving a balance between target coverage a...

Development of a Fast Quality Assurance Software Tool for Helical Online Adaptive Radiation Therapy

Authors: Guang-Pei Chen, Mi Huang, Haidy G. Nasief, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Recently, kV imaging has been integrated into the Accuray Radixact platform, facilitating online adaptive and scan-plan-treat workflows with helical delivery in the near future. In order to s...

Development of a Knowledge-Based Planning Model for Optimal Trade-Off Guidance in Locally Advanced Non-Small Cell Lung Cancer

Authors: Ming Chao, Hao Guo, Tenzin Kunkyab, Yang Lei, Tian Liu, Kenneth Rosenzweig, Robert Samstein, James Tam, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
The aim of the study is to develop a trade-off prediction model to efficiently guide the treatment planning process for patients with stage III non-small cell lung cancer (NSCLC).
Metho...

Direct-to-Unit Dose Calculations for Stereotactic Radiosurgery on a C-Arm Linac with Modern on-Board Imaging Solutions

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Haley K Perlow, Alex T. Price, Atefeh Rezaei, Prashant Vempati, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: The HyperSight imaging feature on C-arm linacs(HS-CBCT) offers increased CT number accuracy over conventional on-board imaging. The C-arm geometry allows for noncoplanar treatments common to ...

Dosimetric Comparison & Error Analysis of Aapm TG51 & WGTG51-e Protocol with Icru-90 Key-Data for High-Energy Clinical Electron Beam

Authors: Amar K. Basavatia, Sandeepan Ganguly, Lee C. Goddard, Wolfgang A. Tomé

Affiliation: Montefiore Medical Center

Abstract Preview: Purpose: To investigate the dosimetric impact of WGTG51-e Report 385, recently updated CoP for clinical electron beams. This study uses a chamber specific effective point of measurement (EPOM) shift t...

Dosimetric Impact of Target Coverage with Inter-Fraction Patient Yaw Setup Error in IMRT/VMAT Prostate Cancer Radiotherapy

Authors: Min Su

Affiliation: Mount Sinai School of Medicine

Abstract Preview: Purpose: To evaluate dosimetric impact of patient setup yaw error to target coverage for pelvis/prostate radiation external beam IMRT-VMAT treatment.
Methods: 9 Pelvis/prostate IMRT-VMAT treatment ...

Dosimetric Impact on Patient Roll/Yaw Change for Whole Breast 3D Radiotherapy

Authors: Min Su

Affiliation: Mount Sinai School of Medicine

Abstract Preview: Purpose: To evaluate dosimetric impact of target coverage and organ at risk (OARs) sparing for whole breast patient setup roll/yaw change in 3D-conformal radiotherapy.
Methods: 8 whole breast cases...

Dual-Domain Neural Network Cone-Beam CT Correction for Online Adaptive Proton Therapy

Authors: Daniel H. Bushe, Arthur Lalonde, Hoyeon Lee, Harald Paganetti, Brian Winey

Affiliation: Universite de Montreal, Massachusetts General Hospital, Massachusetts General Hospital and Harvard Medical School, University of Hong Kong

Abstract Preview: Purpose: Improving the precision and fidelity of daily volumetric imaging is essential for enabling adaptive proton therapy (APT). While cone-beam CT (CBCT) provides daily volumetric imaging, their ut...

EBT4 Film Dosimetry and the Significance of the Œ Fwhm Rule for Gamma Knife Output Factors

Authors: Jingying Lin, Stevan Pecic, Strahinja Stojadinovic

Affiliation: University of Belgrade, The University of Texas Southwestern Medical Center

Abstract Preview: Purpose: This study aims to determine the magnitude of polarization-induced dosimetric error for EBT4 films at different scanning orientations, and to provide guidance on selecting appropriate regions...

Enhance Four-Dimension Cone-Beam Computed Tomography (4D-CBCT) from Sparse Views Using a Novel Deep Learning Model

Authors: Lei Ren, Jie Zhang

Affiliation: University of Maryland School of Medicine

Abstract Preview: Purpose: 4D-CBCT is valuable for imaging anatomy affected by respiratory motions to guide radiotherapy delivery. However, 4D-CBCT often has undersampled projections acquired in each respiratory phase ...

Enhanced Prediction of Iroc Stereotactic Radiosurgery Phantom Audit Results with Treatment Parameters, Complexity Metrics, DVH, and Dosiomics Using Machine Learning

Authors: Lian Duan, Stephen F. Kry, Hunter S. Mehrens, Christine Peterson, Paige A. Taylor

Affiliation: The University of Texas MD Anderson Cancer Center, UT MD Anderson Cancer Center

Abstract Preview: Purpose: To develop predictive models for IROC SRS head phantom audits and to identify important factors influencing institutional performance.
Methods: The IROC SRS head phantom includes two TLDs ...

Enhancing Synthetic Pelvic CT Images from CBCT Using Vision Transformer with Adaptive Fourier Neural Operators

Authors: Rashmi Bhaskara, Oluwaseyi Oderinde

Affiliation: Purdue University

Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...

Evaluating Uncertainty Estimation Models for Clinical Integration of AI-Generated Radiotherapy Dose Distributions

Authors: Jacob S. Buatti, Kristen A. Duke, Malena Fassnacht, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia, Michelle de Oliveira

Affiliation: The University of Texas San Antonio, UT Southwestern Medical Center, UT Health San Antonio

Abstract Preview: Purpose:
Quantifying and visualizing uncertainty is critical for building clinical trust in AI-generated dose distributions. This study evaluates Monte Carlo Dropout (MCD), Snapshot Ensemble (SE), ...

Evaluation of MRI Distortion across a Multi-Site Health System and the Importance of MRI Distortion QA in Stereotactic Radiosurgery (SRS)

Authors: Emel Calugaru, Jenghwa Chang, Sean T Grace, Nicholas Harvey, Jessica Jung, Ching-Ling Teng

Affiliation: Northwell, Hofstra University, Hofstra University Medical Physics Program

Abstract Preview: Purpose: To evaluate the consistency of MRI distortion corrections across Northwell Health system and evaluate the necessity and importance of distortion QA for MRIs used for stereotactic radiosurgery...

FMEA for Direct to Unit Adaptive Radiotherapy

Authors: Haleem Azmy, Robbie Beckert, Farnoush Forghani, Dean Hobbis, Dan Hong, Hyun Kim, Eric Laugeman, Silpa Raju-Salicki, Domenic Sievert

Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine in St. Louis, Washington University School of Medicine, Wash U Medicine, Washington University in St. Louis

Abstract Preview: Purpose: A novel radiation therapy (RT) workflow has recently emerged with the advent of online adaptive RT systems, direct-to-unit (DTU). DTU utilizes online adaptive platforms (MR and CT based) to o...

Fast 3D Scintillation Dosimetry Using Single View Deep Learning Reconstruction

Authors: Louis Archambault, Nicolas Drouin, Alexis Horik, Simon Thibault

Affiliation: Département de Physique, de Génie Physique et D'optique, et Centre de Recherche sur le Cancer, Université Laval, Département de Physique, de Génie Physique et D'optique, et Centre d'optique, photonique et laser, Université Laval

Abstract Preview: Purpose: To develop a novel type of real-time 3D dosimeter for the quality assurance of linear accelerators used in external beam radiotherapy.
Methods: An experimental setup was constructed using ...

Feasibility of Using 68ga-PSMA for Biology-Guided Radiotherapy (BgRT) Treatment

Authors: Girish Bal, Thomas I. Banks, Bin Cai, Neil Desai, Aurelie Garant, Orhan Oz, Elizeva Phillips, Rameshwar Prasad, Chenyang Shen, Robert Timmerman

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, UT Southwestern Medical Center, RefleXion Medical

Abstract Preview: Purpose: This study reports findings from the first-in-human imaging-only trial evaluating the feasibility of using the novel PET tracer 68Ga-PSMA-11 (Illuccix) to guide external beam radiotherapy on ...

First in-Vivo Proton Radiography Experiments for an Image-Guided Small Animal Irradiation Platform with a TimePix3-Based Detector Setup

Authors: Niels Bassler, Jonathan Bortfeldt, Carlos Granja, Guyue Hu, Margarita Kozak, Julie Lascaud, Kirsten Lauber, Grigory Liubchenko, Jasper Nijkamp, Cristina Oancea, Prasannakumar Palaniappan, Katia Parodi, Marco Pinto, Per R. Poulsen, Marco Riboldi, Brita Singers SĂžrensen, Matthias WĂŒrl

Affiliation: Department of Nuclear Medicine, LMU University Hospital, LMU Munich, Department of Radiation Oncology, LMU University Hospital, LMU Munich, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t MĂŒnchen (LMU Munich), Danish Centre for Particle Therapy, Aarhus University Hospital, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen, Department of Experimental Clinical Oncology, Aarhus University, Department of Oncology, Aarhus University Hospital, Advacam

Abstract Preview: Purpose: To apply in-vivo proton radiography (pRad) to aid image registration and treatment plan refinement for a novel precision image-guided small animal proton irradiation platform.

Methods:...

Four-Dimensional Computed Tomography Based on 16cm-Long Detectors Vs 4cm-Long Detectors: Dose Validation

Authors: Qianyi Xu, Inhwan Yeo

Affiliation: INOVA Schar Cancer Institute, Thomas Jefferson University

Abstract Preview: Purpose:
Four-dimensional computed tomography(4DCT) is prone to a geometrical error when respiration changes upon patient shift. 4DCT with a longer-length detector(16cm), uninvolving the shift, has...

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...

Generating Synthetic Positron Emission Tomography from Computed Tomography Using Lightweight Diffusion Model for Head and Neck Cancer

Authors: Rashmi Bhaskara, Shravan Bhavsar, Ananth Grama, Oluwaseyi Oderinde, Shourya Verma

Affiliation: Purdue University

Abstract Preview: Generating Synthetic Positron Emission Tomography from Computed Tomography using Lightweight Diffusion Model for Head and Neck Cancer
Purpose: To generate synthetic PET tumor avidity segments direc...

HDR End-to-End Testing of Horizontal Leipzig Skin Applicators with Ir-192 Calibrated Oslds

Authors: ChangSeon Kim, Andrew Lukban, Mario Serrano-Sosa, Nadia M. Vassell

Affiliation: Mount Sinai Beth Israel

Abstract Preview: Purpose: Commissioning of Flexitron HDR horizontal Leipzig applicators typically includes indirect or direct output verification, using a well chamber specific Revised Correspondence Factor (CFrev) or...

High-Fidelity Synthetic CT Generation from CBCT for Dibh Breast Cancer Patients Using Shortest Path Regularization

Authors: Manju Liu, Weiwei Sang, Yanyan Shi, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lihua Zhang, Rihui Zhang

Affiliation: Jiahui International Hospital, Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aims to transform cone-beam computed tomography (CBCT) images acquired from deep inspiration breath-hold (DIBH) breast cancer patients into high-fidelity synthetic CT (sCT) images....

Iguard: A Fully Unsupervised Image-Guidance Anomaly Recognition and Detection Framework in CBCT-Guided Radiotherapy.

Authors: James M. Lamb, Dishane Chand Luximon, Jack Neylon, Rachel Petragallo, Moritz Ritter, Timothy Ritter

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, ETH Zurich, VCU Health System, Department of Radiation Oncology, University of Colorado

Abstract Preview: Purpose: Anomalies in cone beam computed tomography (CBCT) radiotherapy image guidance can signal treatment deviations. Repetitive review of setup image registrations by humans is inefficient, prone t...

Image Quality Enhancement for Transrectal Ultrasound Imaging of Prostate Brachytherapy Using Deep Learning: A Needle Eraser

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Serdar Charyyev, Xianjin Dai, PhD, Yu Gao, Thomas R. Niedermayr, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Real-time transrectal ultrasound imaging is the gold standard for needle placement and treatment planning of real-time based-ultrasound-based high dose-rate (HDR) prostate brachytherapy. Cumu...

Impact of Transfer Learning on Estimation of Intravoxel Incoherent Motion Parameters in the Liver

Authors: Marissa Brown, Geoffrey D. Clarke, Luke Norton

Affiliation: University of Texas Health Science Center at San Antonio

Abstract Preview: Purpose: To evaluate how different learning strategies affect convolutional neural network (CNN) estimates of the liver's intravoxel incoherent motion (IVIM) parameters.
Methods: A 3-stage U-Net wa...

Improving Adversarial Approaches to Synthetic CT Image Generation with Skin Surface Masks

Authors: Mahya Ahmadzadeh, Nagarajan Kandasamy, Keyur Shah, Gregory C. Sharp, Santhosh Vadivel, John MacLaren Walsh

Affiliation: Electrical and Computer Engineering Department, Massachusetts General Hospital, Emory University, Drexel University

Abstract Preview: Purpose: In image-guided radiotherapy (IGRT), cone beam CTs (CBCTs) suffer from distortions that degrade registration with planning CTs. While CycleGANs can generate synthetic CTs (sCTs) from CBCTs, e...

Initial Three-Year Machine Performance Assessment of a Superficial Radiation Therapy Unit

Authors: Vibha Chaswal, Stephen D. Davis, Alonso N. Gutierrez, Noah S. Kalman, Yongsook C. Lee, William Romaguera, Ranjini P. Tolakanahalli, D. Jay J. Wieczorek

Affiliation: Miami Cancer Institute, Baptist Health South Florida

Abstract Preview: Purpose: To report machine performance of our superficial radiation therapy unit (SRT-100 Vision, Sensus Healthcare, Boca Raton, FL) for the first three years after commissioning of the unit.
Metho...

Intelligent Black Box Recording for Radiation Therapy: Feasibility Study of Vision-Language Models for Treatment Monitoring.

Authors: Wookjin Choi, James M. Lamb, David Romanofski, David H. Thomas, Yevgeniy Vinogradskiy

Affiliation: Drexel, Department of Radiation Oncology, University of California, Los Angeles, Thomas Jefferson University

Abstract Preview: Purpose: To develop an intelligent Black Box Recorder for radiation therapy (RT) that monitors patient treatments using a vision language model.
Methods: The system captures synchronized screen rec...

Investigate Deep-Learned MRI Reconstruction with Data Consistency Mechanism and Task-Informed Loss

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

Affiliation: Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Ill-conditioned reconstruction problems in medical imaging, such as those arising from undersampled k-space data in MRI, can result in degraded image quality and clinical task-orientated perf...

Investigation into the Robustness of Spine Stereotactic Body Radiotherapy Plans to Patient Setup Errors

Authors: Yukio Fujita, Syoma Ide, Fumiki Ito, Kei Ito, Satoshi Kito, Keiko Murofushi, Yujiro Nakajima, Yuhi Suda, Kentaro Taguchi, Naoki Tohyama, Fumiya Tsurumaki, Riku Watanabe

Affiliation: Komazawa University Graduate School, Komazawa University, Tokyo Metropolitan Cancer and Infectious Diseases Center Komagome Hospital

Abstract Preview: Purpose: Spine stereotactic body radiotherapy (SBRT) demands high precision due to the target's proximity to the spinal cord and steep dose gradients, which complicate treatment planning. Consequently...

Is Simplicity Even Better: Deep Learning Algorithms for Breath Motion Phase Prediction in Motion Management

Authors: Amanda J. Deisher, Andrew YK Foong, Witold Matysiak, Jing Qian, Xueyan Tang, Erik J. Tryggestad, Mi Zhou

Affiliation: Mayo Clinic

Abstract Preview: Purpose: Phase gating is commonly employed to mitigate the impact of tumor motion in radiotherapy. Due to the machine-specific time delay between triggering and radiation delivery, the triggering sign...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...

Knowledge-Based Planning for Chest Wall with Lymph Nodes Irradiation VMAT

Authors: Nesrin Dogan, Panagiota Galanakou, Robert Kaderka

Affiliation: University of Miami, Sylvester Comprehensive Cancer Center, University of Miami Sylvester Comprehensive Cancer Center

Abstract Preview: Purpose:
To develop knowledge-based treatment planning (KBP) for volumetric modulated arc therapy (VMAT) in chest wall treatments with regional nodal involvement. Given the challenges posed due to ...

Lu-177 Recovery Coefficients Using Tc-99m Surrogate Method: Intra- & Inter-Scanner Comparison

Authors: Ben Piacitelli, Celeste Winters

Affiliation: OHSU, Department of Diagnostic Radiology, Oregon Health & Science University

Abstract Preview: Purpose: To compare recovery coefficients measured with Lu-177 and Tc-99m with the goal of assessing accuracy of the Tc-99m surrogate method and comparing RC reproducibility between scanners of the sa...

MC-Dolce: Monte Carlo-Based System for Dose and Linear Energy Transfer Calculations Engine for Carbon-Ion Radiotherapy

Authors: Min Cheol Han, Jin Sung Kim, Seok Ho Lee, Gahee Son, Yongdo Yun

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Hanyang University, Department of Integrative Medicine, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: This study aims to develop the MC-DOLCE, a Monte Carlo (MC)-based system capable of calculating physical and biological dose distributions, as well as linear energy transfer (LET) distributio...

Margins to Account for Cardiac and Respiratory Motion in Cardiac Radioablation

Authors: Alanah M. Bergman, Marc W Deyell, Tania Karan, Jakob Marshall, Justin Poon, Devin Schellenberg, Steven Thomas, Richard Thompson

Affiliation: University of British Columbia, University of Alberta, BC Cancer

Abstract Preview: Purpose: A conservative approach to account for random errors due to intra-fraction cardiac and respiratory motion during cardiac radioablation (CR) is to define a margin equal to the amplitude of car...

Mask-Less Adaptable Headrest for Head-and-Neck Radiotherapy

Authors: Alyssa Capizzi, John J Dombrowski, Nabil N. Khater

Affiliation: Saint Louis University

Abstract Preview: Purpose: To evaluate a mask-less adaptable headrest (MAHR) prototype for head-and-neck IMRT designed to reduce random and systematic shifts of patients’ setups. MAHR complements current image-guidance...

Minimizing Positioning Errors in Intracranial SRS: The Role of Verification Imaging after 6-Dof Corrections

Authors: Anthony J. Doemer, Yimei Huang, Benjamin Movsas, Ellen Park, Mira Shah, Salim Siddiqui, Karen C. Snyder, Kundan S Thind, Bo Zhao

Affiliation: Henry Ford Health

Abstract Preview: Purpose: The 6 degrees-of-freedom (6-DoF) robotic couch is considered essential for linac-based stereotactic radiosurgery (SRS), particularly for irregularly shaped targets adjacent to critical organs...

Multi-Center Diffusion-Weighted MRI Validation for 0.35T MR-Linac: A Repeatability and Reproducibility Study

Authors: Tess Armstrong, Nema Bassiri, Alonso N. Gutierrez, Michael Kasper, Natalia Lutsik, Eric Mellon, Kathryn E. Mittauer, Siamak P. Nejad-Davarani, Shyam Pokharel, Suresh Rana, Hui Wang, Joseph Weygand

Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Miami Cancer Institute, Baptist Health South Florida, ViewRay, Inc., Miami Cancer Institute, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida, Department of Radiation Oncology, University of Miami

Abstract Preview: Purpose: Radiation treatments on the MR-linac (MRL) enable daily acquisition of anatomical and physiological images for adaptive treatment planning. The apparent diffusion coefficient (ADC) estimated ...

Multi-Institutional Evaluation of Radiographic Automatic Exposure Control Performance Testing: Methodology, Outcomes, and Failure Rates

Authors: Caroline Cheney, Nicole M. Lafata, Zaiyang Long, Dustin W. Lynch, Erin B. Macdonald, Andy Madore, Douglas E. Pfeiffer, Colin Schaeffer, Alexander W. Scott

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, UVA Health, Duke University Health System, Mayo Clinic, Henry Ford Health, Boulder Community Health, Varian, Cedars-Sinai Medical Center

Abstract Preview: Purpose: This work evaluates the significance of performing established radiography automatic exposure control (AEC) tests by comparing testing methodology, outcomes, and failure rates across multiple...

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...

Nnae: Automating Anomaly Detection and Quality Assurance in Medical Image Segmentation

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, 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:
Deep learning-based automatic medical image segmentation is increasingly employed in clinical practice, significantly reducing manual workload. However, verifying segmentation results rema...

Novel AI-Powered Tool to Objectively Evaluate Brain Dose for Multi-Met Stereotactic Radiosurgery Optimization

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...

One Year Experience of Biology-Guided Radiotherapy (BgRT) on PET-Linac in an Academic Center

Authors: Shahed Badiyan, Girish Bal, Thomas I. Banks, Bin Cai, Tu Dan, Aurelie Garant, Andrew R. Godley, Steve Jiang, Orhan Oz, Arnold Pompos, Rameshwar Prasad, Chenyang Shen, David Sher, Robert Timmerman, Kenneth Westover

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, UT Southwestern Medical Center, RefleXion Medical

Abstract Preview: Purpose: Biology-guided radiotherapy (BgRT) is a novel FDA-cleared technology for treating lung and bone tumors based on 18F-FDG PET uptake. This study summarizes the first-year experience treating 29...

Optimization of the U-Net Model for the Radiation Dose Prediction in Lung Cancer RT Plans and Its Uncertainty Quantification

Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...

Optimizing Motion Management QA: Clinical Integration of Aapm TG-306 for the Radixact Synchrony System

Authors: Hulya Ozdemir Buss, Jeffrey Geiger, Kim Howard, Julius G. Ojwang, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: The Radixact Synchrony system integrates real-time motion tracking and compensates to improve treatment accuracy for moving targets. This study presents a streamlined and efficient quality as...

Patient-Specific Imaging Modality Agnostic Virtual Digital Twins Modeling Temporally Varying Digestive Motion

Authors: James M. Balter, Lando S. Bosma, Jorge Tapias Gomez, Nishant Nadkarni, Mert R Sanbuncu, William Paul Segars, Ergys D. Subashi, Neelam Tyagi, Harini Veeraraghavan

Affiliation: University of Michigan, The University of Texas MD Anderson Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Cornell University, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Develop patient-specific virtual digital twin (VDT) cohorts modeling physically realistic spatio-temporal gastrointestinal (GI) organs (stomach and duodenum) digestive motion.
Methods: Pat...

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...

Posterior-Mean Diffusion Model for Realistic PET Image Reconstruction

Authors: Osama R. Mawlawi, Yiran Sun

Affiliation: RICE University, UT MD Anderson Cancer Center

Abstract Preview: Purpose: Conventional PET reconstruction methods often produce noisy images with artifacts due to data/model mismatches and inconsistencies. Recently, deep learning-based conditional denoising diffusi...

Predicting Brain V60% in Linac-Based Single-Isocenter-Multiple-Targets (SIMT) Stereotactic Radiosurgery Using Machine Learning

Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...

Predicting CBCT-Based Adaptive Radiation Therapy Session Duration Using Machine Learning

Authors: Leslie Harrell, Sanjay Maraboyina, Romy Megahed, Maida Ranjbar, Xenia Ray, Pouya Sabouri

Affiliation: Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), University of California San Diego

Abstract Preview: Purpose: Real-time adaptive radiation therapy (ART) dynamically modifies patients’ treatment plan during delivery to account for anatomical and physiological variations. Addressing ART planning time v...

Predicting and Monitoring Response to Head and Neck Cancer Radiotherapy Using Multi-Modality Imaging and Radiobiological Digital Twin Simulations

Authors: Eric Aliotta, Michalis Aristophanous, Joseph O. Deasy, Bill Diplas, Milan Grkovski, James Han, Vaios Hatzoglou, Jeho Jeong, Nancy Y Lee, Ramesh Paudyal, Nadeem Riaz, Heiko Schoder, Amita Shukla-Dave

Affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: To forecast radiotherapy treatment response for head and neck cancer (HNC) using multimodality imaging and personalized radiobiological modeling.
Methods: Multi-modality imaging data from ...

Prior-Adapted Progressive Motion-Resolved CBCT Reconstruction Using a Dynamic Reconstruction and Motion Estimation Method

Authors: Hua-Chieh Shao, You Zhang, Ruizhi Zuo

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: Cone-beam CT (CBCT) provides on-board patient anatomy for image guidance and treatment adaptation in radiotherapy. However, to compensate for respiration-induced anatomical motion, motion-res...

Prospective Organ-Level Dose Estimation in CT Imaging Using Scout-Net: A Comparison with Established Methods

Authors: Maria Jose Medrano, Grant Stevens, Liyan Sun, Justin Ruey Tse, Adam S. Wang, Sen Wang

Affiliation: Department of Radiology, Stanford University, GE HealthCare, Stanford University

Abstract Preview: Purpose: Patient exposure to ionizing radiation is a major concern in CT imaging. Size-specific dose estimation methods can prospectively estimate organ-level radiation doses based on patient sizes an...

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...

Rapid 3D Prototyped Solid-Source Phantoms for Quality Assurance of Biology-Guided Radiotherapy (BgRT)

Authors: Jon Burns, Andrew Groll, Gopinath Kuduvalli, Thomas Laurence, Manoj Narayanan, Jeffrey Schmall, Sanchit Sharma

Affiliation: RefleXion Medical

Abstract Preview: Purpose: To simplify BgRT testing we have developed techniques that use 3D resin printed structures that can be filled with Ge-68 epoxy. This approach allows the development of highly complex, clinica...

Real-Time 3D Dose Verification for MR-Guided Online Adaptive Radiotherapy (ART) Via Geometry-Encoded Deep Learning Framework

Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, 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: Fast dose verification is essential for the safety and efficiency of MR-guided adaptive radiotherapy (ART) as patients anxiously waiting on the treatment couch. Conventional tools often requi...

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...

Robustness Enhancement for VMAT-TBI Planning and Treatment Delivery

Authors: Courtney R. Buckey, Quan Chen, Suzanne J. Chungbin, Edward L. Clouser, Yi Rong, Jun Tan, Jennifer Yan, Xiang Sheng Yan

Affiliation: Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Purpose:
To identify planning techniques that consistently result in robust VMAT-TBI plans that allow for larger patient setup errors.
Methods:
Conventional planning method often results in p...

Sensitivity of CT Ventilation Imaging to Image Acquisition and Reconstruction Parameters: A Phantom Study

Authors: Hilary Louisa Byrne, Paul J. Keall, John Kipritidis, Jeremy Lim

Affiliation: Northern Sydney Cancer Centre, University of Sydney, Image X Institute, Faculty of Medicine and Health, The University of Sydney

Abstract Preview: Purpose:
Non-contrast CT ventilation imaging (CTVI) has been developed as a cost-effective and accessible alternative to PET/SPECT V/Q imaging for visualizing lung function. However, the sensitivit...

Serial PET-CT Activity Concentration during Small Target Lung Tumor SBRT

Authors: Joseph Barbiere, Joseph Hanley, Brett Lewis, Jay Mistry, Alois M. Ndlovu, Roland Teboh

Affiliation: Hackensack University Medical Center, HUMC, Jersey Shore University Medical Center

Abstract Preview: Purpose:
Quantitative PET-CT can evaluate clinical response to radiotherapy. For tumors less than approximately 3cm partial volume effects due to the poor PET resolution makes accurate measurement ...

Structure-Based Diffusion Model for CT Synthesis from MR Images for Radiotherapy Treatment Planning

Authors: Samuel Kadoury, Redha Touati

Affiliation: Polytechnique Montréal

Abstract Preview: Purpose:
Generating synthetic CT images from MR acquisitions for radiotherapy planning allows to integrate soft tissue contrast alongside density information stemming from CT, thus improving tumor ...

Task-Specific Deep-Neural-Network Architecture Optimization for CBCT Scatter Correction

Authors: Hoyeon Lee

Affiliation: University of Hong Kong

Abstract Preview: Purpose: Deep-learning approaches are widely investigated for Cone-Beam CT (CBCT) scatter correction to improve the quality of the linear-accelerator mounted CBCT. This study aims to optimize the deep...

Teaching an Old Dog New Tricks: Unlocking Hidden Potential in Existing Frameworks for Versatile Radiotherapy Applications

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, 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:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...

Testing Experience in Dose Monitoring Solutions: Automation Aberrations in Automated Organ Dose Estimation

Authors: Lawrence T. Dauer, Yusuf Emre Erdi, Yiming Gao, Dustin W. Lynch, Usman Mahmood

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Radiation dose to patients in CT examinations (CTDIvol, DLP) is tracked in dose monitoring solutions. Some solutions push for automatically estimating patient organ doses based on exam images...

Testing the Performance of Rbe Models Using a Comprehensive Panel of Pancreatic Cancer Cell Lines

Authors: Joana Antunes, Scott James Bright, David B. Flint, Mojtaba Hoseini-Ghahfarokhi, Mandira Manandhar, Poliana Marinello, Gabriel O. Sawakuchi, Tingshi Su

Affiliation: MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, Laboratory of Instrumentation and Experimental Particle Physics; Faculty of Science of University of Lisbon, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, MD Anderson Cancer Center

Abstract Preview: Purpose: To study the accuracy of relative biological effectiveness (RBE) models to predict the RBE of a comprehensive panel of pancreatic cancer cell lines.

Methods: Clonogenic cell survival w...

The Development of a Novel Biomechanical Model for Accurate Contour Deformation during Online Adaptative Metastatic Bone Cancer Radiotherapy Planning.

Authors: Jeremy S. Bredfeldt, Benito De Celis Alonso, Braian Adair Maldonado Luna, Kevin M. Moerman, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, Kamal Singhrao

Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Harvard Medical School, Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Department of Mechanical Engineering, University of Galway, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla

Abstract Preview: Purpose: Online adaptive radiotherapy replanning for single-isocenter bone cancer metastasis treatment reduces on-table treatment time and patient discomfort compared to the multi-isocenter standard-o...

Towards Penile Small Vessel Imaging with Ferumoxytol-Enhanced MRI

Authors: Darren Fang, Amar Kishan, Justin McWilliams, Dan Ruan, Xiaodong Zhong

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of California, Los Angeles, Department of Radiological Sciences, University of California, Los Angeles

Abstract Preview: Purpose: Prostate radiotherapy can malform penile vasculature, contributing to erectile dysfunction and compromising quality of life. To detect, quantify, and preferably avoid such occurrences, this p...

Transformer-Based Proton Dose Prediction with and without Diffusion Process

Authors: Jing Qian, Brandon Reber, David M. Routman, Satomi Shiraishi

Affiliation: Mayo Clinic

Abstract Preview: Purpose: The dose distribution in proton radiotherapy (PRT) is characterized by sharp gradients, posing a challenge for machine learning-based dose prediction. While denoising with diffusion processes...

Two-Stage Clustering and Auto Machine Learning to Predict Chemoradiation Response in Tumor Subregions on FDG PET for La-NSCLC

Authors: Stephen R. Bowen, Shijun Chen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Qianqian Tong, Jiajie Wang, Shouyi Wang, Faisal Yaseen

Affiliation: The University of Texas at Austin, Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Tumor subregion clustering and prediction of region-specific response can augment assessments and adaptive treatment decisions. A modeling framework was constructed to predict chemoradiation ...

Ukan Architecture for Voxel-Level Dose Prediction in Radiotherapy

Authors: Lu Jiang, 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:
Conventional radiotherapy treatment planning is guided by a set of generic objectives that are unspecific to patient anatomy. Treatment planning thus heavily relies on the planner’s experi...

Ultra-Sparse-View Cone-Beam CT Reconstruction Based Strictly-Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy

Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang

Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University

Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...

Uncertainties on Synthetic-CT Generation from CBCT: Another Layer of Complexity in Abdominal Adaptive Radiotherapy

Authors: Laura I. Cervino, Wendy B. Harris, Paulo Quintero, Hao Zhang

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: To evaluate the impact of the prediction uncertainty from CBCT-based synthetic CT (sCT) generation in abdominal adaptive radiotherapy.

Methods: CT and CBCT images from 65 abdominal pat...

Universal MR-to-Synthetic CT: A Streamlined Framework for MR-Only Radiotherapy Planning

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, 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:
Converting MR images to synthetic CT (MR2sCT) is highly desirable as it streamlines the radiotherapy treatment planning workflow. This approach leverages the superior soft tissue visibilit...

Validation of Synthetic CT-Based Online Monitoring for Adaptive Proton Therapy

Authors: Ozgur Ates, Chin-Cheng Chen, Chia-Ho Hua, Matthew J. Krasin, Thomas E. Merchant

Affiliation: St. Jude Children's Research Hospital

Abstract Preview: Purpose: To validate the use of synthetic CTs generated from CBCT images for online monitoring, ensuring accurate and reliable daily plan quality assessments in adaptive proton therapy (APT).
Metho...

Virtual Monoenergetic Imaging for Radiotherapy: A Single CT Acquisition for Both Target Delineation and Dose Calculation

Authors: Harold Y Hu, Yanle Hu, Shuai Leng, Maryam Sadeghian, Joe Swicklik

Affiliation: Mayo Clinic Arizona, Basis Scottsdale, Mayo Clinic

Abstract Preview: Purpose: Radiotherapy CT simulation often requires two scans: a non-contrast scan for dose calculation and a contrast-enhanced scan for target delineation. Photon-counting-detector (PCD) CT allows the...

What Do We Do with Our Old Pinnacle Data?

Authors: Caiden Atienza, Daniel E. Hyer, Samuel D. Rusu, Blake R. Smith, Joel J. St-Aubin

Affiliation: Iowa Health Care, University of Iowa

Abstract Preview: Purpose: Pinnacle3 TPS (Philips Radiation Oncology Systems, Fitchburg, WI, USA) support is set to end by December 31, 2026. This work presents a validated method to archive Pinnacle data, which may be...

“See” through Surface: Transforming Surface Imaging into a Real-Time Three-Dimensional Imaging Solution for Intra-Treatment Image Guidance

Authors: Steve B. Jiang, Ruiqi Li, Hua-Chieh Shao, Kenneth Westover, You Zhang, Tingliang Zhuang

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

Abstract Preview: Purpose:
Respiratory motion is a long-standing challenge for lung SBRT, particularly for centrally-located lung tumors where increased toxicity demands more precise motion management during treatme...