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Results for "two stage": 75 found

A Conditional Point Cloud Diffusion Model for Deformable Liver Motion Tracking Via a Single Arbitrarily-Angled X-Ray Projection (PCD-Liver)

Authors: Yunxiang Li, Hua-Chieh Shao, Chenyang Shen, Jing Wang, 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: Accurate liver deformable motion tracking is essential in image-guided radiotherapy to enable precise tumor targeting during treatment. We developed a conditional point cloud diffusion model ...

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 Dosimeter Independent Method for Measuring Dose from Contrast Enhanced Mammography Exposure.

Authors: Mitya M. Barreto, Nichole A. Harris

Affiliation: Department of Radiology, University Hospitals Cleveland Medical Center

Abstract Preview: Purpose: To evaluate dosimeter dependence of measured AGD, and to develop a dosimeter independent method for evaluating the AGD, for CEDM exposures.
Methods: Three solid-state dosimeters (Raysafe-X...

A Foundational Model for Medical Imaging Modality Translation in Head and Neck Radiotherapy

Authors: Jie Deng, Yunxiang Li, Xiao Liang, Weiguo Lu, Jiacheng Xie, 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, University of Texas 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: Recently, foundational models trained on large datasets have shown remarkable performance across various tasks. Developing a foundational model for medical image modality translation in head-...

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 Population-Based and Patient-Specific Framework for 2D–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. 2D–3D deformable registration addresses this problem by estimating LA-CBCTs from defor...

A Hybrid Radiomics-Integrated Machine Learning Framework for Early Identification of Potential Radiation Pneumonitis in Lung Cancer Patients

Authors: Christos Ilioudis, Marios Myronakis, Sotirios Raptis, Kyriaki Theodorou

Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Information and Electronic Engineering, International Hellenic University (IHU)

Abstract Preview: Purpose: This study presents a radiomics-driven, machine learning framework developed to predict the possibility of Radiation Pneumonitis (RP), as a side effect of radiation therapy in lung cancer pat...

A Method to Reduce Workload in Adaptive Radiotherapy

Authors: Ramesh Boggula, Lincoln Houghton

Affiliation: Karmanos Cancer Institute, Wayne State University

Abstract Preview: Purpose: To evaluate an approach that selectively applies adaptive re-planning only when needed to reduce clinical workload while maintaining treatment quality. Daily adaptive radiotherapy (ART) has t...

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 Window-Level Based Approach for Generating Missing Tissue in CT Scans Using a Transformer-Gan Model

Authors: Mojtaba Behzadipour, Siyong Kim, Mitchell Polizzi, Richard R. Wargo, Lulin Yuan

Affiliation: VCU Health - Department of Radiology, Virginia Commonwealth University

Abstract Preview: Purpose:
The purpose of this study is to develop a method for generating missing tissue in CT scans of patients with large body sizes, where the field of view (FOV) of the scanner fails to capture ...

AI-Based SBRT Dose Prediction Directly from Diagnostic PET/CT: Applications for Multi-Disciplinary Lung Cancer Care

Authors: Pradeep Bhetwal, Wookjin Choi, Adam Dicker, Rupesh Ghimire, Yingcui Jia, Lauren Nkwonta, Yevgeniy Vinogradskiy, Wentao Wang, Maria Werner-Wasik

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Multi-disciplinary clinics are becoming standard of care for patients with lung cancer treated with SBRT. To improve clinical decision support in a multi-disciplinary clinic, it would be bene...

Advancing Biodosimetry with AI: Detecting Dicentric Chromosomes Using Convolutional Neural Networks

Authors: Adayabalam Balajee, Elijah Berberette, Maria Escalona, Dray Gentry, Chester R. Ramsey, Terri Ryan

Affiliation: ORAU, Thompson Proton Center, University of Tennessee

Abstract Preview: Purpose:
Dicentric chromosomes, characterized by two centromeres on a single chromosome, are key biomarkers in biological dosimetry for quantifying ionizing radiation exposure. However, manual dete...

Advancing Post-Radiotherapy Toxicity Extraction: A Novel Privacy-Preserving, Parameter-Efficient Language Model Fine-Tuning

Authors: Hassan Bagher-Ebadian, Indrin J. Chetty, Mohamed Elshaikh, Ahmed I Ghanem, Mohammad M. Ghassemi, Reza Khanmohammadi, Benjamin Movsas, Shayan Siddiqui, Kundan S Thind, Jawad Turfa

Affiliation: Michigan State University, Department of Radiation Oncology,Cedars-Sinai Medical Center, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health

Abstract Preview: Purpose: Extracting late radiotherapy-induced toxicities from free-text notes using natural language processing is complicated by negative symptom identification, computational demands, and data priva...

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 Automated Solution to Staged Treatments for Arteriovenous Malformations in Gammaknife

Authors: Strahinja Stojadinovic, Robert Timmerman, Yulong Yan

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

Abstract Preview: Purpose: Radiosurgery for large (>10cc) arteriovenous malformations (AVMs) poses significant challenges due to increased risks of complications and lower obliteration rates. To mitigate toxicity, larg...

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...

Assessing Mlc Errors and Their Dosimetric Impact Delivered on Elekta Linear Accelerator from Two TPS Systems

Authors: Richard Lesieur, Olivia Magneson, David E. Solis, Sotirios Stathakis

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: This study evaluates the deliverability and precision of multileaf collimator (MLC) positioning in treatment plans generated by two different Treatment Planning Systems (TPS), Monaco and Pinn...

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 Full-Body Tumor Segmentation from PET/CT Images

Authors: Austin Castelo, Xinru Chen, Caroline Chung, Laurence Edward Court, Jaganathan A Parameshwaran, Zhan Xu, Jinzhong Yang, Yao Zhao

Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
To develop a deep learning-based segmentation model to automatically delineate tumors from full-body PET/CT images.
Methods:
PET/CT image pairs of 91 patients were collected for this...

Automatic Breast VMAT Planning Using Script and Rapidplan on Eclipse

Authors: Maria Jose Almada, Bruno Forti, Patricia Murina, Carlos Daniel Venencia

Affiliation: Instituto Zunino - Fundacion Marie Curie, Dra.

Abstract Preview: Purpose: The use of VMAT for the breast requires duplication of the patient's CT, several planning structures, and patient-specific dose-volume constraints depending on the patient's anatomy, fraction...

BEST IN PHYSICS IMAGING: Cross-Contrast Diffusion: A Synergistic Approach for Simultaneous Multi-Contrast MRI Super-Resolution

Authors: Yifei Hao, Wenxuan Li, Xiang Li, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Yaogong Zhang

Affiliation: Duke University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Diffusion-based deep-learning frameworks have been recently used in MRI resolution enhancement, or super-resolution. Multi-contrast MRI share common anatomical structures while holding comple...

Binary Classification of Lymphedema in 3DCRT Patients Using Machine Learning on 3D Dose Distribution Data

Authors: Jee Suk Chang, Hojin Kim, Jin Sung Kim, Jaehyun Seok

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

Abstract Preview: Purpose: This study aims to leverage 3D dose distribution data to develop a machine learning model capable of accurately predicting lymphedema occurrence in patients undergoing 3D conformal radiation ...

Biologically Guided Deep Learning for MRI-Based Brain Metastasis Outcome Prediction after Stereotactic Radiosurgery

Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University

Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...

Breathing New Life into Pulmonary Imaging: Development and Clinical Validation of an X-Ray Interferometry System

Authors: Rachael Blair, Les Butler, Lillian Dickson, Kyungmin Ham, Charles Hartman, Kenneth (Kip) Matthews, Corinne Vanya

Affiliation: Louisiana State University, University of Minnesota, Refined Imaging LLC, Center for Advanced Microstructures and Devices

Abstract Preview: Purpose:
To develop and evaluate an x-ray interferometry system (XIS) for low-dose, high-sensitivity diagnostic imaging of lung diseases such as chronic obstructive pulmonary disease (COPD), asthma...

Clinical I-131 Dosimetry: Audit, Review, and Evaluation

Authors: Colin Adam Doyle, Celeste Winters

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

Abstract Preview: Purpose: To audit our radioactive iodine (I-131) dosimetry protocol, review dosimetry methods used at other facilities, investigate the clinical impact of I-131 dosimetry at our facility, and test the...

Clinically Ready Simulation Package for Monitoring Gamma Hotspot Emission, and Detection in Patient Anatomy

Authors: Ananta Raj Chalise, Matthias K Gobbert, Zhuoran Jiang, Sina Mossahebi, Stephen W. Peterson, Jerimy C. Polf, Lei Ren, Ehsan Shakeri, Vijay Raj Sharma, Jie Zhang

Affiliation: University of Maryland School of Medicine, University of Maryland Baltimore County, University of Maryland, Baltimore County, Stanford University, University of Maryland, School of Medine, Department of Physics, University of Cape Town, M3D, Inc

Abstract Preview: Purpose: Prompt gamma (PG) imaging is a promising modality for proton dose verification. Currently, there is a lack of effective tool to investigate the PG emission during proton therapy and optimize ...

Comparison of Respiratory Motion between 4D-MR and 4D-CT in Compression Belt Patients

Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis, Hamlet Spears

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: This study evaluates the range of motion of abdominal organs using 4D stack-of-stars magnetic resonance (MR) imaging and 4D computed tomography (CT), the current clinical standard. Accurate o...

Comprehensive Evaluation of Federated Learning Strategies for Head and Neck Tumor Segmentation on PET/CT Images

Authors: Jingyun Chen, Yading Yuan

Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology

Abstract Preview: Purpose: To evaluate centralized and decentralized strategies for federated head and neck tumor segmentation on PET/CT.
Methods: We utilized training data from the HEad and neCK TumOR segmentation ...

Demystifying Magnetic Resonance Imaging: Targeted Educational Initiatives for Medical Physicists in TĂŒrkiye and Preclinical Medical Students in the United States

Authors: Samuel A. Einstein, Jesutofunmi Fajemisin, Evren O. Göksel, Görkem O. GĂŒngör, Marthony Robins, Travis C. Salzillo, Charles R. Thomas, Turgay Toksay, Joseph Weygand, Yue Yan

Affiliation: Acibadem MAA University, Department of Radiation Oncology and Applied Science, Dartmouth Health, Dartmouth College, Moffitt Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Penn State College of Medicine, Bursa Ali Osman Sönmez Oncology Hospital

Abstract Preview: Purpose: Magnetic resonance imaging (MRI) is an indispensable clinical tool, offering unparalleled soft tissue contrast critical for diagnosing and managing a wide range of conditions. However, its co...

Development and Validation of Novel Two-Stage Vascular Segmentation Model for Interventional Angiography

Authors: Abid Khan, Chad Klochko, Michael J Kovalchick, Hyeok Jun Lee, Hani Nasr, Krishnan Shyamkumar, Kundan S Thind

Affiliation: Henry Ford Radiology, Wayne State University, Henry Ford Health, HFHS

Abstract Preview: Purpose: Automated vascular segmentation in interventional angiography is challenged by contrast kinetics, vessel variations, and 2D projections, limiting the effectiveness of single-model approaches....

Development of a Brain-like Digital Reference Object of Resting-State Functional MRI

Authors: Henry Szu-Meng Chen, Mu-Lan Jen, Vinodh A. Kumar, Ho-Ling Anthony Liu, Jian Ming Teo

Affiliation: School of Medicine, University of Colorado Denver, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Resting-state (rs-) fMRI detects functional networks by measuring synchronization of low-frequency oscillations in blood-oxygenation-level-dependent (BOLD) signals between brain regions. Stan...

Development of an MRI Guided Precision Small Animal Radiotherapy System

Authors: Yaowen Cao, Yunwen Huang, Yidong Yang, Xiaogang Yuan, Ning Zhao, Cheng Zheng

Affiliation: Department of Life Sciences and Medicine, 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: MRI has better soft tissue contrast than cone beam CT which is commonly used in image guided radiotherapy. This study aims to develop a low-field MRI system for precision small animal radiati...

Direct in-Vivo Real-Time Singlet Oxygen Detection in Photofrin-Mediated Photodynamic Therapy (PDT) Using Multispectral Singlet Oxygen Dosimetry (MSOLD)

Authors: Theresa Busch, Robert H Hadfield, Madelyn Johnson, Baozhu Lu, Hongjing Sun, Brian C. Wilson, Weibing Yang, Timothy C. Zhu

Affiliation: University of Glasgow, University of Toronto, University of Pennsylvania

Abstract Preview: Purpose: Direct detection of singlet-state oxygen (ÂčO₂) is crucial for advancing type II photodynamic therapy (PDT), but its short lifetime makes in vivo measurement highly challenging. Although Photo...

Discriminative Uncertainty Learning for Cancer Classification

Authors: Wei Wei, Yading Yuan

Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology

Abstract Preview: Purpose: To investigate an uncertainty modeling method to improve the performance of cancer classification with the ability to produce uncertainty score.
Methods: Deep learning has achieved state-o...

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...

Establishing Radiotherapy in Malawi through an International Medical Physics Collaboration

Authors: Ruth Afanador, Daniela Branco, John M Bryant, John Campbell, Clement Chaphuka, Samuel A. Einstein, David B. Flint, Jeffrey R. Kemp, Mussa Kumwembe, Daniel J Mollura, Joseph Weygand

Affiliation: RAD-AID International, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Applied Science, Dartmouth Health, UNC Health, Malawi National Cancer Center, Kamuzu Central Hospital, Penn State College of Medicine, Sutter Health, New York University, University of California San Diego / California Protons, Department of Radiation Oncology, Moffitt Cancer Center

Abstract Preview: Purpose: Malawi, a landlocked country in southeastern Africa with a population of over 20 million, ranks among the world’s least-developed nations and has the fourth-lowest gross domestic product per ...

Evaluating the Performance and Limitations of an Automated Treatment Planning Tool for Intact Breast Radiotherapy across Diverse Patient Populations

Authors: Shatha Al Afifi, Hana Baroudi, Leonard Che Fru, Laurence Edward Court, Suzanne B. Evans, Kent A. Gifford, Adam D. Melancon, Melissa P. Mitchell, Issa Mohamad, Patricia Murina, Manickam Muruganandham, Tucker J. Netherton, Callistus M. Nguyen, Joshua S. Niedzielski, Deborah L. Schofield, Simona Shaitelman, Willie Shaw, Sanjay S. Shete, Adam Shulman, Brendon Smith, Sheeba Thengumpallil, Carlos Daniel Venencia, Conny Vrieling

Affiliation: University of Cape Town, MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, University of the Free State, UT MD Anderson Cancer Center, King Hussein Cancer Center, Instituto Zunino - Fundacion Marie Curie, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Dra., Hirslanden Clinique des Grangettes, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Therapeutic Radiology, Yale University School of Medicine, Yale University, The University of Texas, MD Anderson, Houston TX

Abstract Preview: Purpose:
Automated contouring and planning tools are usually trained on single-institution datasets, seldom tested across diverse patient populations. This introduces a risk of population bias, res...

Evaluation of a Commercially Available Solution for Dose Verification Using Daily AI Generated Pseudo-CT from CBCT.

Authors: Chloe DiTusa, Panayiotis Mavroidis, Christopher W. Schneider, Sotirios Stathakis

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center, University of North Carolina

Abstract Preview: Purpose: To evaluate and compare dose calculation differences between Monaco and AdaptBox by TheraPanacea on AI-generated pseudo-CTs (pCTs) from a CBCT.

Methods: Dose calculations in water phan...

Exploring NSCLC Microenvironments: Multi-Score Survival Models Integrationg Radiomics-Based Regional Imaging Features and Genomics

Authors: Nobuki Imano, Daisuke Kawahara, Misato Kishi, Yuji Murakami

Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University

Abstract Preview: Purpose: This study aims to develop a comprehensive Multi-score by integrating Radiomics-score (Rad-score), Gene-score derived from gene expression levels, and tumor environment Rad-score (TE-Rad-scor...

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...

First in-Vivo Application of a Novel Precision Small Animal Irradiation Platform with Proton IMPT Delivery and Advanced on-Board Image-Guidance

Authors: Niels Bassler, Jonathan Bortfeldt, Davide Boscaini, Francesco Evangelista, Guyue Hu, Ze Huang, Margarita Kozak, Julie Lascaud, Giulio Lovatti, Eero Lönnqvist, Jasper Nijkamp, Munetaka Nitta, Prasannakumar Palaniappan, Katia Parodi, Marco Pinto, Per R. Poulsen, Marco Riboldi, Babak Sharifi, Brita Singers SÞrensen, Peter Thirolf

Affiliation: Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t MĂŒnchen (LMU Munich), Ludwig-Maximilians UniversitĂ€t, 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

Abstract Preview: Purpose: To perform the first in vivo application of a novel small animal radiation research platform combining on-board image-guidance with multi-field intensity modulated spot scanning delivery [1] ...

Foresight Planning: Radiotherapy Plan Optimization Via Self-Supervised Model Predictive Control

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

Affiliation: Duke University Medical Center

Abstract Preview: Purpose:
Treatment planning for intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) relies on inverse planning, an iterative and non-intuitive process of adjust...

Fully Automatic Pipelines for Anatomical ROI Detection and Exposure Index Calculation in X-Ray Imaging : Foundation Model-Based Frameworks for Dose Standardization

Authors: Yoonha Eo

Affiliation: Yonsei University

Abstract Preview: Purpose: To develop a fully automatic and unsupervised algorithm for estimating the Exposure Index (EI) of various Regions of Interest in X-ray imaging using advanced foundation models. Traditional EI...

Improving 4D-MRI Parameters for Abdominal Tumor Motion Management: A Phantom Study

Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: For soft-tissue abdominal tumors, a 4D-MR may provide improved tumor tracking over the clinical standard 4D-CT. This project aims to optimize a clinically available 4D-MR pulse sequence to ac...

Innovative Deep Learning Network for Overall Survival Prediction for NSCLC: Outperforming Pre-Trained Models VGG16 and ResNet50

Authors: Ryan Alden, Tithi Biswas, Kaushik Halder, Felix Maria-Joseph, Michael Mix, Rihan Podder, Tarun Kanti Podder

Affiliation: SUNY Upstate Medical University, IIT-Roorkee, University of Florida

Abstract Preview: Purpose: Early-stage NSCLC patients undergoing SBRT often die due to intercurrent illnesses. However, prediction of overall survival (OS) remains crucial due to the risk of disease recurrence. This st...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

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

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

Integrating Multiple Modalities with Pretrained Swin Foundation Model for Head and Neck Tumor Segmentation

Authors: Jue Jiang, Aneesh Rangnekar, Shiqin Tan, Harini Veeraraghavan

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Weill Cornell Graduate School of Medical Sciences

Abstract Preview: Purpose: Clinicians often use information from FDG-PET and CT to interpret and delineate gross tumor (GTVp) and nodal (GTVn) volumes for radiotherapy planning in head and neck (HN) cancer patients. He...

Inter-Patient Registration Methods for Voxel-Based Analysis in Lung Cancer

Authors: Chloe Min Seo Choi, Joseph O. Deasy, Jue Jiang, Sudharsan Madhavan, Nikhil Mankuzhy, Nishant Nadkarni, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu

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

Abstract Preview: Purpose: Voxel-based analysis (VBA) requires accurate topology-preserving inter-patient deformable image registration (DIR). This study assessed whether guiding a DIR method with geometric priors of t...

Key Tumor Volume Zones for Advancing the Radiomics-Based Distant Recurrence Prediction

Authors: Ryan Alden, Tithi Biswas, Kaushik Halder, Felix Maria-Joseph, Michael Mix, Rihan Podder, Tarun Kanti Podder

Affiliation: SUNY Upstate Medical University, IIT-Roorkee, University of Florida

Abstract Preview: Purpose: Radiomics feature-based model for predicting distant recurrence can potentially provide critical insight for clinical decision-making and assistance in treatment strategies. This study focuse...

Neural Implicit K-Space for Accelerated Patient-Specific Non-Cartesian MRI Reconstruction

Authors: Daniel O Connor, Mary Feng, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger, Jess E. Scholey, Ke Sheng, DI Xu, Wensha Yang, Yang Yang

Affiliation: UCSF, University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, University of San Francisco, Department of Radiology, University of California, San Francisco, University of California San Francisco, Siemens Medical Solutions USA Inc.

Abstract Preview: Purpose: The scanning time for a fully sampled MRI is lengthy. Compressed sensing (CS) has been developed to minimize image artifacts in accelerated scans, but the required iterative reconstruction is...

Neutron Dose Measurements with Multiple Dosimetry Techniques for Fetal Dose Estimation

Authors: Ahmet S. Ayan, Estelle Batin, Austin M. Faught, Peter E. Klages, Eunsin Lee, Collin Nappi, Mina Okello, Meghana Ramani, Zachary X. Richards, Parisa Sadeghi

Affiliation: Department of Radiation Oncology, The Ohio State University Wexner Medical Center, The Ohio State University Wexner Medical Center, Ohio State University, The Ohio State University

Abstract Preview: Purpose: Neutron doses are not modelled in proton treatment planning systems, so measurements were taken with two independent dosimeter types to quantify representative neutron fetal doses in pencil b...

Optimizing Timing of Physics Consults for Proton Prostate Therapy: Improving Patient Experience and Operational Efficiency

Authors: Charles D. Bloch, Stephen R. Bowen, Bing-Hao Chiang, Alex Egan, Eric C. Ford, Sharareh Koufigar, Dominic A. Maes, Juergen Meyer, Sharon Pai, Frank Rafie, Rajesh Regmi, Jatinder Saini, George A. Sandison, Marco Schwarz, Bishwambhar Sengupta, Tony P. Wong

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

Abstract Preview: Purpose: This study aimed to optimize the strategy and timing of physics consults for proton prostate patients to improve the patient experience and resource utilization in our radiation oncology depa...

Optimizing Vessel Wall Visualization Using a Novel Black-Blood CT Technique on Craniocervical CT Angiography

Authors: Xiaohu Li, Jianjun Shen, Guozhi Zhang, Sihua Zhong, Jingjie Zhou

Affiliation: United Imaging Healthcare

Abstract Preview: Purpose:
Visualization of carotid artery vessel wall on computed tomography angiography (CTA) imaging is challenging. This study aims to develop a novel post-processing technique, black-blood compu...

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...

Photon-Proton Treatment Compatible Couch Tops Render Modality-Dependent Support Structure Models

Authors: Estelle Batin, Michael A. Carlson, Nilendu Gupta, Zachary X. Richards, Diana Shvydka

Affiliation: Department of Radiation Oncology, The Ohio State University Wexner Medical Center

Abstract Preview: Purpose: With an increase in world-wide proton treatment availability, patients sometimes are transferred between proton and photon modalities. Among the main reasons for modality shifts are proton be...

Physics and Geometry Input-Based Neural Network Dose Engine

Authors: Ricardo Garcia Santiago, Narges Miri, Daryl P. Nazareth, Ankit Pant, Mukund Seshadri

Affiliation: Roswell Park Comprehensive Cancer Center

Abstract Preview: Purpose: To develop a transformer-based deep learning network framework for predicting VMAT dose distributions. This can provide fast and efficient calculations with accuracies potentially comparable ...

Predicting Pathological Complete Response to Neoadjuvant Chemotherapy for Breast Cancer at Early Time Points Using a Two-Stage Dual-Task Deep Learning Strategy

Authors: Bowen Jing, Jing Wang

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

Abstract Preview: Purpose: Medical images acquired at multiple time points during neoadjuvant chemotherapy allow physicians to assess patients’ responses and personalize treatment plans accordingly. Studies from the I-...

Radiochemical Monte Carlo Model to Investigate the Oxygen Impacts on Radical Yields Under Proton Flash Irradiation

Authors: Yao Hao, Yuting Peng, Francisco Javier Reynoso, Tianyu Zhao, Xiandong Zhao

Affiliation: Varian, University of South Florida, Washington University School of Medicine, Washington University School of Medicine, Department of Radiation Oncology

Abstract Preview: Purpose: Ultra-high dose-rate (FLASH) dose rate (> 40 Gy/s) may result in a radio-protective effect in healthy tissue compared with conventional dose rate (CDR). This effect has been observed in vivo ...

Raman Spectroscopy Identifies Biomolecular Differences between Caucasian and African American Prostate Cancer Patients

Authors: Nrusingh C. Biswal, Manas R. Gartia, Maria Iftesum, Sanjit K. Roy, Gyana Ranjan Sahoo, Elnaz Sheikh, Hem D. Shukla, Madhur Srivastava

Affiliation: Department of Chemistry and Chemical Biology, Cornell University, Department of Radiation Oncology, University of Maryland School of Medicine, Department of Mechanical and Industrial Engineering, Louisiana State University

Abstract Preview: Purpose: Prostate cancer incidence and mortality levels in African-American men are the highest among all ethnic groups. This points to the role of biological factors in driving disparate outcomes. He...

Refresher Training - a Method to Ensure Radioactive Material Program Compliance

Authors: Robert A. Rodgers

Affiliation: Vanderbilt University School of Medicine

Abstract Preview: Purpose: Preparing for radioactive material (RAM) program audits or inspections can be stressful. A five-step method to ensure program compliance is described. This method is adaptable to implementing...

Region-Specific Structure-Function Coupling Alterations in Parkinson’s Disease: Insights from Multi-Modal MRI

Authors: Yifei Hao, Ting Huang, Wenxuan Li, Xiang Li, Manju Liu, Rong Liu, Tao Peng, Yulu Wu, Fang-Fang Yin, Lei Zhang, Yaogong Zhang, Jiangtao Zhu

Affiliation: Duke University, Department of Radiology, The Second Affiliated Hospital of Soochow University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study investigates the alterations in structure-function coupling (SC-FC) networks in Parkinson’s disease (PD) patients, focusing on region-specific disruptions and compensatory mechanis...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu

Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...

Spatial Resolution Degradation in Weekly Computed Tomography Quality Control and Implications for X-Ray Tube Replacement

Authors: Hadley Anna DeBrosse, Kevin J. Little

Affiliation: The Ohio State University

Abstract Preview: Purpose: This work examines the consistency and pattern of spatial resolution degradation in weekly quality control (QC) testing prior to CT tube failure and replacement and investigates potential cor...

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...

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 ...

Supercomputing-Enabled CT Virtual Imaging Trials: A Population-Scale Pilot Study

Authors: Ehsan Abadi, Zakaria Aboulbanine, Nicholas D Felice, David Fenwick, Anuj J. Kapadia, Cindy Marie McCabe, Jayasai Ram Rajagopal, Ehsan Samei

Affiliation: Duke University, Oak Ridge National Laboratory, Center for Virtual Imaging Trials, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose:
Virtual imaging trials (VITs) offer a computational alternative to clinical imaging trials leveraging virtual patients, scanners, and interpreters to assess imaging questions. To provide m...

The Impact of Implant Position and Different Radiotherapy Techniques on Dosimetry in Post-Mastectomy Breast Reconstruction for Breast Cancer

Authors: Xiu tong Lin

Affiliation: Department of Radiation physics and technology, Shandong Second Provincial General Hospital

Abstract Preview: Purpose: To compare the dosimetric differences between the photon and proton plans and between the different target according to the placement of the implants for patients undergoing radiotherapy afte...

Topas-Nbio – Status and Outlook after a Decade of Developments

Authors: Alejandro Bertolet, Jorge Naoki Dominguez Kondo, Bruce A. Faddegon, Kathryn D Held, Nicolas Henthorn, Jay LaVerne, Thongchai Masilela, Stephen J. McMahon, Isaac Meyer, Victor V. Onecha, Harald Paganetti, Jose A. Ramos-Mendez, Jan PO Schuemann, Wook-Geun Shin, Michael Taylor, John Warmenhoven

Affiliation: Massachusetts General Hospital, Queen's University Belfast, Massachusetts General Hospital and Harvard Medical School, University of California San Francisco, University of Manchester, Notre Dame University

Abstract Preview: Purpose: TOPAS-nBio brings a cutting-edge Monte Carlo (MC) simulation framework to the research community to test hypotheses of radiation effects at the nanometer/cell scale. Here, we present the deve...

Two Years in - Lessons Learned from Managing a Global Medical Physics Webinar Series

Authors: Ghada Aldosary, Abdullah A. Alshreef, Amineh Khatib Hamad, Eenas A. Omari

Affiliation: Loma Linda University Medical Center, Jerusalem, KASCH- Ministry of National Guard Health Affairs, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose:
Webinars are an effective tool for disseminating knowledge and expertise to a global audience. A medical physics webinar series was established in 2022 to provide accessible continued educ...

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 ...

Uncertainty-Guided Cross-Domain Adaptation for Unsupervised Medical Image Segmentation

Authors: Yunxiang Li, Weiguo Lu, 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:
Curating high-quality, labeled data for medical image segmentation can be challenging and costly, considering the existence of various image domains with differing modalities/protocols. Cr...

Use of Radiopaque Rectal Spacer for IGRT – a Preliminary Analysis of Alignment Accuracy and Interobserver Variability

Authors: Joseph A. Miccio, Nicholas J. Potter, Zain Siddiqui

Affiliation: Penn State Health Milton S. Hershey Medical Center

Abstract Preview: Purpose: Fiducial markers are the gold standard for prostate alignment during CT-based image-guided radiotherapy (IGRT). Radiopaque hydrogel rectal spacers reduce rectal toxicity by displacing the rec...

Utilizing Large Language Models for Efficient and Accurate Clinical Data Enrichment

Authors: Ara Alexandrian, Jessica Ashford, Jean-Guy Belliveau, Allison Dalton, Nathan Dobranski, Krystal M. Kirby, Garrett M. Pitcher, David E. Solis, Hamlet Spears, Angela M. Stam, Sotirios Stathakis, Jason Stevens, Rodney J. Sullivan, Sean Xavier Sullivan, Natalie N. Viscariello

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center, The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: To improve retrospective risk analysis in radiation oncology by leveraging Large Language Models (LLMs) to extract richly annotated data from unstructured clinical incident reports.
Method...

VMAT Machine Parameter Optimization Using Policy Gradient Reinforcement Learning

Authors: Avinash Mudireddy, Nathan Shaffer, Joel J. St-Aubin

Affiliation: University of Iowa

Abstract Preview: Purpose: This work demonstrates preliminary results in training a reinforcement learning (RL) network to perform VMAT machine parameter optimization.
Methods: We implemented a policy gradient RL al...

Variations in Automatic Dose Response Curves across Fluoroscope Types and Manufacturers for Abdominal Imaging

Authors: Hadley Anna DeBrosse, Edward J. Stafford, Kevin A. Wunderle

Affiliation: Ohio State University, The Ohio State University

Abstract Preview: Purpose: To investigate automatic dose response curves from fluoroscopes across multiple manufacturers for an abdominal imaging protocol.
Methods: ADRC response for multiple fluoroscopes were evalu...