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Results for "approach improve": 161 found

4D CBCT Reconstruction Using Denoising Diffusion Implicit Models

Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Bohong Huang, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Huiqiao Xie, Hao Zhang

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

Abstract Preview: Purpose: Four-dimensional cone-beam computed tomography (4D-CBCT) is critical in image-guided radiotherapy (IGRT) for visualizing tumor motion. However, sparse projection sampling often introduces sev...

A Clinically Aligned Embedding Model for Glioma Prognostication Via Radiology-Pathology Report Matching

Authors: Steve Braunstein, Yannet Interian, Hui Lin, Bo Liu, Janine Lupo, Olivier Morin, Benedict Neo

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Data Science, University of San Francisco, University of San Francisco

Abstract Preview: Purpose: Large Language Models (LLMs) demonstrate strong general text comprehension but remain limited in oncology due to insufficient contextual alignment. We pilot embedding alignment through radiol...

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 Five-Year Retrospective Analysis of Dose Reduction for the Top 10 Adult CT Protocols

Authors: Emi Ai Eastman, Christina Lee, Xinhua Li, Yifang (Jimmy) Zhou

Affiliation: Cedars-Sinai Medical Center

Abstract Preview: Purpose:
This study aimed to retrospectively evaluate dose reduction efforts in past five years using acquisition-level data and to compare the results with ACR achievable dose (AD) and dose refere...

A Framework for the Standardization of Radiomics Classes in the Presence of Blur and Noise

Authors: Huay Din, Grace Jianan Gang, Grace Hyun Kim, Michael F. McNitt-Gray, Joseph W. Stayman, Yijie Yuan

Affiliation: Johns Hopkins University, John Hopkins University, University of Pennsylvania, David Geffen School of Medicine at UCLA

Abstract Preview: Purpose:
Radiomics rely on quantitative features to discern underlying biological signatures. However, feature dependence on the imaging systems themselves hampers the creation of reproducible and ...

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 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 Hybrid Transformer-CNN for Tracking-Free 3D Ultrasound Volume Reconstruction from 2D Freehand Scans

Authors: Wenfeng He, Tian Liu, Pretesh Patel, Richard L.J. Qiu, Keyur Shah, Tonghe Wang, Xiaofeng Yang, Chulong Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Emory University, Medical Physics Graduate Program, Duke Kunshan University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study introduces a tracking-free approach to reconstruct 3D ultrasound (US) volumes from 2D freehand US scans. By eliminating the reliance on external tracking systems, this method aims ...

A Knowledge-Based Approach for High-Quality Accelerated Partial Breast Irradiation Using Stereotactic Body Radiotherapy

Authors: Drexell Hunter Boggs, Carlos E. Cardenas, Allison Dalton, John B Fiveash, Joel A. Pogue, Richard A. Popple, Farnaz Rahim Li

Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: External-beam Accelerated Partial Breast Irradiation (APBI) using stereotactic-body radiotherapy (SBRT) is increasingly adopted as an alternative to whole-breast radiation, offering targeted ...

A Method for Automatic Working Angle Prediction during Intracranial Aneurysms Embolization

Authors: Tina Ehtiati, Grace Jianan Gang, Limei Ma, Oleg Shekhtman, Visish M. Srinivasan

Affiliation: Siemens Medical Solutions USA, Inc., University of Pennsylvania

Abstract Preview: Purpose: Saccular aneurysms are the most common type of intracranial aneurysm and are typically treated by endovascular embolization. The procedure requires approximately orthogonal fluoroscopy images...

A New Approach for Teaching Mathematical and Computational Methods to Medical Physics Students

Authors: Jenghwa Chang, Marissa Joyce Vaccarelli

Affiliation: Northwell, Hofstra University Medical Physics Program

Abstract Preview: Purpose: AAPM Report 365 recommends medical physics graduate programs offer courses covering mathematical/statistical methods (section 3.1.7) as well as computational methods/medical informatics (sect...

A Novel Approach to Preclinical Intensity-Modulated Radiotherapy Using an Open-Source Ring-Based Compensator Device and Inverse Treatment Planning System

Authors: Benjamin R. Awad, Bulent Aydogan, Howard J Halpern, Erik Pearson, Gage H. Redler, Jordan M. Slagowski, Rajit Tummala, Autumn E. Walter-Denzin, Jimmy Zydlo

Affiliation: University of Wisconsin-Madison Department of Human Oncology, University of Oxford, The University of Chicago, Moffitt Cancer Center, California State University, Fresno, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Small animal models are crucial in cancer research to develop, validate, and translate basic scientific hypotheses into clinical advancements. This study aims to make small animal intensity-m...

A Novel Feature Selection Method for Survival Prediction of Head-and-Neck Following Radiation Therapy

Authors: Xiaoying Pan, X. Sharon Qi

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, School of Computer Science and technology,Xi'an University of Posts and Telecommunications

Abstract Preview: Purpose:
Survival prediction for cancer presents a substantial hurdle in personalized oncology, due to intricate, high-dimensional medical data. Our study introduces an innovative feature selection...

A Novel Method for Modeling the Rbe of Clinical Proton Beams

Authors: Anthony Hong Cheol Lim, Alexander R ODell, Alexander Stanforth, Chris C. Wang

Affiliation: Georgia Institute of Technology, Emory University

Abstract Preview: Purpose: The purpose of this work is to investigate the variation of proton RBE, with respect to depth, in the context of clinical SOBP. Employing a novel approach, this study conducts a Monte Carlo s...

A Novel Semi-Analytic Approach for Dose Calculation in Proton Minibeam Radiotherapy

Authors: Hao Gao, Wangyao Li, Yuting Lin, Chao Wang, Wei Wu

Affiliation: Institute of Modern Physics, Chinese Academy of Sciences, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Proton minibeam radiation therapy (pMBRT) delivers a unique peak-and-valley dose pattern using collimators with narrow slits, offering improved normal tissue sparing compared to conventional ...

A Practical Experimental Software Validation Method for Voxel-Based Personalised Dosimetry in Radiopharmaceutical Therapy

Authors: Thomas Gee, Sofia Michopoulou, Amit Nautiyal

Affiliation: University Hospital Southampton

Abstract Preview: Purpose: Dosimetry software that is accessible to departments offers new opportunities to improve patient-specific dosimetry. Prior to clinical decision-making, it is essential to validate dosimetry s...

A Real-Time Framework for Fiducial Tracking and Intrafraction Motion Assessment of Cyberknife in Stereotactic Body Radiation Therapy for Liver Cancer

Authors: Ruiyan Du, Mingzhu Li, Ying Li, Wei Liu, Shihuan Qin, Yiming Ren, Biao Tu, Hui Xu, Lian Zhang, Xiao Zhang, Zengren Zhao

Affiliation: Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Medical AI Lab, The First Hospital of Hebei Medical University, Hebei Provincial Engineering Research Center for AI-Based Cancer Treatment Decision-Making, The First Hospital of Hebei Medical University, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Mayo Clinic, Department of Oncology, The First Hospital of Hebei Medical University

Abstract Preview: Purpose: Fiducial tracking is widely used in CyberKnife to dynamically guide the gantry for moving target like liver cancer stereotactic body radiation therapy (SBRT). This study developed a robust fr...

A Robust Quantitative Metric for Optimal Beam Selection in Radiotherapy of the Peripheral Lung Lesions: A Crucial Step in Standardization of Lung SBRT

Authors: Leslie Bell, Kai Ding, Reza Farjam, Russell K Hales, Sarah Han-Oh, Hamed Hooshangnejad, Jina Lee, K. Ranh Voong

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University

Abstract Preview: Purpose: Optimal beam arrangement is crucial in automation and standardization of thorax radiotherapy where substantial tissue heterogeneity and several critical organs at risks (OARs) exist. Here, we...

A Self-Supervised Deep Learning Approach for Automatic Identification and Metal Artifact Reduction in Cone-Beam CT for Brachytherapy

Authors: Rani Anne', Wenchao Cao, Yingxuan Chen, Wookjin Choi, Firas Mourtada, Yevgeniy Vinogradskiy

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: In-room mobile cone-beam CT (CBCT) is emerging to enhance high-dose-rate (HDR) brachytherapy workflow using on-demand imaging. However, metal artifacts from X-ray markers inside gynecological...

A Vision-Language Deep Learning Model for Predicting Survival Outcomes in Glioblastoma Patients

Authors: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan

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

Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...

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-Assisted Cellular and Organoid Analysis for Lenalidomide-Based Radioimmunotherapy Against Glioblastoma

Authors: ISAAC Amoah, Jackie Austin, Charlotte Block, Kaylee Brilz, Dylan Bui, Andrew E. Ekpenyong, Jayce Hughes, Pralhad Itani, Natasha Ratnapradipa, Sara Strom, Jacob Woolf

Affiliation: Creighton University

Abstract Preview: Purpose:
Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults, with a median survival of approximately 15 months despite the current standard of care, which includes s...

AI-Driven Early Detection of Digital Radiography Performance Degradation: A Predictive Quality Control Approach

Authors: Giovanni Iacca, Gloria Miori, Laura Orsingher, Daniele Ravanelli, Annalisa Trianni

Affiliation: Department of Information Engineering and Computer Science, University of Trento, Medical Physics Department, S.Chiara Hospital, APSS

Abstract Preview: Purpose: This study aims to leverage artificial intelligence (AI) to predict and identify performance degradation in Digital Radiography (DR) systems, enabling proactive maintenance and minimizing cli...

AI-Driven Quality Assurance for Gamma Camera/SPECT Anomaly Detection Using Contrastive Learning

Authors: Shanli Ding, Osama R. Mawlawi, Tinsu Pan

Affiliation: UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Reliable detection of anomalies in Gamma Camera/SPECT flood images is vital for quality assurance (QA). Traditional methods relying on numerical thresholds and manual inspections often mis...

Accelerated Proton Density Imaging Via T2-Guided Cyclegan Super-Resolution without Paired Low-Resolution and High-Resolution Data

Authors: Yunxiang Li, Xinlong 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) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Acquiring high-resolution (HR) proton density (PD) images is time-consuming, while lower-resolution (LR) PD scans are faster but can lack sufficient details. We propose CycleHR, a T2-contrast...

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

Authors: Hongjing Sun, Timothy C. Zhu

Affiliation: University of Pennsylvania

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

Advancing Deep Segmentation Accuracy in CBCT for Radiotherapy Via Robust Scatter Mitigation: First Results from a Pilot Trial

Authors: Cem Altunbas, Farhang Bayat, Roy Bliley, Rupesh Dotel, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi

Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic, University of Colorado Anschutz Medical Campus

Abstract Preview: Purpose: Automatic segmentation of anatomical structures in CBCT images is key to enabling dose delivery monitoring and online plan modifications in radiotherapy. However, poor image quality can degra...

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...

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...

An Efficient, Low-Cost, and Accessible Film Dosimetry Scanning System

Authors: Parminder S. Basran, Wyatt Flanders, Skylar Sylvester

Affiliation: Cornell University

Abstract Preview: Purpose: To develop a reliable, efficient, and low-cost methodology for quantifying radiation doses using radiochromic film and a custom-built lightbox and to evaluate the system's performance compare...

An Energy Layer Optimization Approach for Spot Scanning Proton Arc Therapy

Authors: Wenhua Cao, Hadis Moazami Goudarzi, Madison Emily Grayson, Zongsheng Hu, Gino Lim, Steven Hsesheng Lin, Radhe Mohan

Affiliation: The University of Texas MD Anderson Cancer Center, Department of Industrial Engineering, University of Houston, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Proton Arc Therapy (PAT) offers significant potential in treating complex cancer cases by delivering a continuous radiation dose as the gantry rotates. This study aims to investigate the pote...

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

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

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

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

An Image Representation of Radiomics Data for Enhanced Deep Radiomics Analysis with Consideration of Feature Interactions

Authors: Xiaolong Fu, Runping Hou, Md Tauhidul Islam, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: To introduce a novel schematic image representation of radiomics data, called OmicsMap, for high-performance deep radiomics analysis. OmicsMap transforms tabular radiomics data into an image ...

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

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

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

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

An Integrated Robust Inverse Planning Based on AI-Built Dose Kernel Library for Preclinical Radio-Neuromodulation Using Focused Kv X-Rays

Authors: Wenbo Gu, Chenhui Qiu, Ke Sheng, Liyan Sun, Weiyuan Sun, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiology, Stanford University, University of Pennsylvania, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, Stanford University,

Abstract Preview: Purpose:
The small animal radio-neuromodulation platform developed in our previous work utilized focused kV x-ray beams rotating and translating in predefined trajectories to irradiate small, mm si...

Augmenting Histopathology Lymphocyte Detection with Gpt-4 in-Context Visual Reasoning

Authors: Kyle J. Lafata, Casey Y. Lee, Xiang Li, Megan K. Russ, Zion Sheng

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

Abstract Preview: Purpose:
Traditional deep learning-based cell segmentation models face limitations, such as the need for extensive training data and retraining when encountering new cell types or domains. This stu...

Auto-Segmentation Scripting to Generate Optimization Structures for Spine SBRT Planning

Authors: Jon Hansen

Affiliation: Washington University in St Louis

Abstract Preview: Purpose: Commercially available auto-segmentation software was utilized to generate institution-specific optimization structures for spine stereotactic body radiation therapy (SBRT). Implementation of...

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...

Automating Radiographic Sharp Score Prediction in Rheumatoid Arthritis Using Multistage Deep Learning Methods

Authors: Hajar Moradmand, Lei Ren

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

Abstract Preview: Purpose:
The Sharp-van der Heijde (SvH) score is essential for assessing joint damage in rheumatoid arthritis (RA) from radiographic images. However, manual scoring is time-intensive and prone to v...

BEST IN PHYSICS MULTI-DISCIPLINARY: Building a Cross-Modality Model to Integrate Bio-Clinical Features, Anatomical MRI, and White-Matter Pathlength Mapping for Personalized Glioblastoma RT Planning

Authors: Steve Braunstein, Angela Jakary, Hui Lin, Bo Liu, Janine Lupo, Tiffany Ngan, Ke Sheng, Nate Tran

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Radiology and Biomedical Imaging, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Current RT clinical target volumes (CTVs) for Glioblastoma (GBM) employ 2cm isotropic expansions of gross tumor volumes. However, studies showed patients still experience progression beyond t...

Backscattering of Compton Cameras: A Monte Carlo Simulation Approach

Authors: Jorge Naoki Dominguez Kondo, Qihui Lyu

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

Abstract Preview: Purpose:
Targeted alpha therapy (TAT) has emerged as a highly potent therapeutic method in oncology, but its development is limited by the lack of imaging methods to quantify its dosimetry. Convent...

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

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

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

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

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

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

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Biomechanically Informed Diagnostic-to-Synthetic CT Transformation for Expedited Radiation Therapy Planning

Authors: Liyuan Chen, Steve Jiang, Chenyang Shen

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center

Abstract Preview: Purpose: Delays in radiation therapy (RT) initiation caused by conventional CT simulation processes can hinder timely treatment delivery and patient outcomes. This study proposes a Virtual Treatment S...

Box-Prompt Zero-Shot Smart Segmentation in Radiation Oncology Using a SAM-Based Model: Smartsam

Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia

Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio

Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...

Characterizing and Modeling Higher-Order Motions of Collimator Subsystem on a 60RPM Gantry Linac for Improved Small Target Dosimetry

Authors: David J. Carlson, Yiu-Hsin Chang, Huixiao Chen, Zhe (Jay) Chen, Blake Gaderlund, Ray Yang

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

Abstract Preview: Purpose: To address the root cause of dosimetric discrepancy for small central targets (<2cm) especially sensitive to geometric alignment of beamlets, by modeling higher-order oscillations of the coll...

Cherenkov Image Denoising with Diffusion-Based Deep-Learning for High-Fidelity Video Display of EBRT

Authors: Petr Bruza, Jeremy Eric Hallett, Brian W Pogue, Yucheng Tang, Shiru Wang

Affiliation: NVIDIA Corp, Dartmouth College, Thayer School of Engineering, Dartmouth College, University of Wisconsin-Madison, University of Wisconsin - Madison

Abstract Preview: Purpose: Cherenkov imaging allows for real-time visualization of megavoltage X-ray or electron beam delivery during radiation therapy. By using a time-gated intensified CMOS camera synchronized with a...

Combining Patch-Based CNN Models with Hierarchical Shapley Explanations for Breast Cancer Diagnosis

Authors: Xuelian Chen, John Ginn, Zhuhong Li, Kaizhong Shi, Chunhao Wang, Jianliang Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao

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

Abstract Preview: Purpose: Developing deep learning-based models for accurate automated breast cancer diagnosis from mammography presents significant challenges due to the small size and subtle nature of breast lesions...

Commissioning of an AI-Assisted Tool for Enhancing Post-Radiosurgery Follow-up in Multiple Brain Metastases Patients

Authors: Rex Carden, Carlos E. Cardenas, Ho-hsin Rita Chang, John B Fiveash, Heinzman A. Katherine, Yogesh Kumar, Gaurav Nitin Rathi, Richard A. Popple, Kayla Lewis Steed

Affiliation: University of Alabama at Birmingham

Abstract Preview: Purpose: Brain metastases (BMs) often require multiple radiotherapy (RT) courses as new lesions appear. Comparing follow-up imaging with prior RT plans is time-intensive. We developed an AI tool that ...

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 Multispectral Singlet Oxygen Luminescent Dosimetry (MSOLD) and Singlet Oxygen Explicit Dosimetry (SOED) in BPD-Mediated PDT for Mice

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

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

Abstract Preview: Purpose:
Multispectral Singlet Oxygen Luminescent Dosimetry (MSOLD) has been developed as a real-time in vivo dosimetry technique for Photodynamic Therapy (PDT). This study investigates the feasibi...

Deep Autoencoder for Ring Artifact Denoising in Photon-Counting CT

Authors: Magdalena Bazalova-Carter, James Day, Xinchen Deng

Affiliation: University of Victoria

Abstract Preview: Purpose:
Ring artifacts in Photon-Counting Computed Tomography (PCCT) images can degrade image quality. this study aims to suppress ring artifacts with a novel autoencoder-based framework that leve...

Deep Learning-Based Plan Quality Prediction for Gamma Knife Radiosurgery of Brain Metastases

Authors: Chih-Wei Chang, Runyu Jiang, Mark Korpics, Yuan Shao, Aranee Sivananthan, Zhen Tian, Ralph Weichselbaum, Xiaofeng Yang, Aubrey Zhang, Xiaoman Zhang

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Department of Physics, University of Chicago, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, School of Public Health, University of Illinois Chicago

Abstract Preview: Purpose: Gamma Knife (GK) plan quality can vary significantly among planners, even for cases handled by the same planner. Although plan quality metrics such as coverage, selectivity, and gradient inde...

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

Authors: Hamdah Alanazi, Silvia Pella

Affiliation: FAU, Florida Atlantic University

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

Deep Learning–Based Dose Prediction for Automated Proton Radiation Therapy Planning of Breast Cancer

Authors: Ahssan Balawi, Peter Jermain, Timothy Kearney, Sonali Rudra, Michael H. Shang, Markus Wells, Mohammad Zarenia

Affiliation: Department of Radiation Medicine, MedStar Georgetown University Hospital

Abstract Preview: Purpose: To investigate the applicability and accuracy of a deep learning (DL) model in predicting radiation dose distribution for breast cancer patients treated with pencil-beam-scanning proton radio...

Development and Experimental Validation of an in-House Proton Treatment Planning System with Energy Layer Optimization

Authors: Hao Gao, Yuting Lin, Jufri Setianegara, Aoxiang Wang, Peng Xiao, Qingguo Xie, Yanan Zhu

Affiliation: Department of Biomedical Engineering, Huazhong University of Science and Technology, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Intensity-modulated proton therapy (IMPT) achieves uniform tumor dose distribution while sparing organs-at-risk (OAR) by optimizing spot weights across energy layers. Accelerating IMPT delive...

Development and Validation of Patient-Specific 3D-Printed Electron Applicators for Precision Radiotherapy

Authors: Md. Jobairul Islam

Affiliation: Department of Radiation Oncology, Labaid Cancer Hospital and Super Speciality Centre

Abstract Preview: Purpose: Electron radiotherapy is an effective treatment for superficial tumors but requires field-shaping devices like electron applicators, which are labor-intensive to produce. This study aimed to ...

Development of Preclinical Multiscale Dosimetry for Beta-Particle Emitting Radionuclide in Radiopharmaceutical Therapy

Authors: Adedamola Adeniyi, Bryan Bednarz, Malick Bio Idrissou, Reinier Hernandez, Ohyun Kwon, Brian W. Miller, Zachary S Morris, Maya Takashima, Jamey Weichert

Affiliation: Departments of Radiation Oncology and Medical Imaging, University of Arizona, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin–Madison, Department of Radiology, School of Medicine and Public Health, University of Wisconsin–Madison, Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin–Madison

Abstract Preview: Purpose: As radiopharmaceutical therapy (RPT) becomes more prevalent in clinical applications, understanding dose-response relationships in the tumor microenvironment (TME) and normal tissues is essen...

Dosimetric Analysis of Plans Using X-Ray and X-γ-Ray Combination Strategy for Advanced Cervical Cancer Patients with Pelvic Lymph Node Metastasis

Authors: Yi Li

Affiliation: Department of Radiation Oncology, the First Affiliated Hospital of Xi'an Jiaotong University

Abstract Preview: Purpose: Advances in radiotherapy technology are crucial for improving cervical cancer (CC) treatment. This study explores a novel X-ray and γ-ray dual-modality radiation (TaiChiB) system, comparing i...

Dosimetric Evaluation of Radiation Treatment Planning Algorithms in IMRT and VMAT Techniques: Analysis with Central and Peripheral Lung Tumors

Authors: Sumanta Manna, Atul Mishra, Surendra Prasad Mishra, Kailash Kumar Mittal, Anoop Kumar Srivastava, Neha Yadav

Affiliation: Department of Radiation Oncology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Department of radiation Oncology, Apollomedics Super Speciality Hospitals, Department of Radiation Oncology, Uttar Pradesh University of Medical Sciences, Department of Radiation Oncology, Kalyan Singh Super Specialty Cancer Institute

Abstract Preview: Purpose: This study aimed to assess the dosimetric performance of Volumetric Modulated Arc Therapy (VMAT), step-and-shoot Intensity-Modulated Radiation Therapy (ss-IMRT), and dynamic Intensity-Modulat...

Dosimetric Evaluation of the Aldo Function for Multiple Brain Metastases in Automated Stereotactic Radiosurgery Treatment Planning

Authors: Hsiao-Mei Fu, Shih-Ming Hsu, Chia-Ting Lee, Shih-Hua Liu, Tsung-Yu Yen

Affiliation: National Yang Ming Chiao Tung University, Mackay Memorial Hospital

Abstract Preview: Purpose: The Automatic Lower Dose Objective (ALDO) is a unique function designed to achieve 98% relative coverage across all targets in automated SRS treatment planning (HyperArc planning). This study...

Dosimetric Feasibility of Dominant Intraprostatic Lesion Dose Escalation in HDR Prostate Brachytherapy

Authors: Abby E. Besemer, Carolyn Eckrich, John M. Floberg, Michael J. Lawless, Jessica R. Miller, Joseph B. Schulz, Jordan M. Slagowski, Autumn E. Walter-Denzin

Affiliation: University of Wisconsin-Madison Department of Medical Physics, University of Wisconsin-Madison Department of Human Oncology, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Department of Radiation Oncology, Stanford University School of Medicine, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: The aim of this treatment planning study was to evaluate the feasibility of escalating dose with HDR prostate brachytherapy to imaging-identified intraprostatic macroscopic lesions while mode...

Dual Energy Cone Beam Computed Tomography for Artifact Reduction and Enhanced Image Quality Using Existing Hardware in Radiation Therapy

Authors: Michael J. Choi, Vindu Wathsala Kathriarachchi, Christopher L. Nelson, Andrew P. Soderstrom, Yawei Zhang

Affiliation: The University of Texas MD Anderson Cancer Center, MD Anderson, UF Health Proton Therapy Institute

Abstract Preview: Purpose: Cone Beam Computed Tomography (CBCT) is widely used in image-guided radiation therapy for patient positioning. While kV photons offer high image contrast, they are prone to artifacts caused b...

Dual-Domain Reconstruction Network for Nonstop Gated CBCT Imaging: Application in Respiratory Gating Ablative Radiotherapy for Pancreatic Cancer

Authors: Sean L. Berry, Weixing Cai, Laura I. Cervino, Yabo Fu, Daphna Gelblum, Wendy B. Harris, Xiuxiu He, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Boris Mueller, Huiqiao Xie, Mitchell Yu, Hao Zhang

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

Abstract Preview: Purpose: Gating ablative radiotherapy for pancreatic cancer accounts for tumor movement due to respiration and typically requires 5, 15, or 25 fractions. Pretreatment imaging verification is essential...

Efficient FAST-Forward Planning Strategy for X-Ray Based Online Adaptive Radiotherapy

Authors: Prasanna Alluri, Mona Arbab, Xingzhe Li, Chang-Shiun Lin, Mu-han Lin, David D.M. Parsons, Asal Rahimi, Justin D. Visak, Narine Wandrey

Affiliation: UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX

Abstract Preview: Purpose: Intelligence-Optimization-Engine (IOE) v1.0 relied heavily on planner expertise and patient-specific IMRT beam arrangements, requiring frequent revisions. While VMAT workflows offered potenti...

Efficient Robustness Optimization in Intensity Modulated Proton Therapy for Head and Neck Cancer Via Visual State Space Attention Generative Adversarial Networks (VSSA-GAN)

Authors: Nan Li, Yaoying Liu, Shouping Xu, Gaolong Zhang

Affiliation: Department of Radiation Oncology, School of Physics, Beihang University, School of physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose: In intensity-modulated proton therapy (IMPT) for head and neck cancer, CBCT registration ensures accurate setup, minimizing dose errors. Unlike IMRT, IMPT plans directly define tumor volumes ...

Enhanced Lung Function Assessment through Machine Learning Analysis of 4DCT Subregional Respiratory Dynamics

Authors: Jing Cai, Zhi Chen, Hong Ge, Yu-Hua Huang, Bing Li, Zihan Li, Ge Ren

Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital

Abstract Preview: Purpose: Algorithms based on subregional respiratory dynamics (SRD) capture spatiotemporal heterogeneity in the ventilation process, though rely on empirical modelings to map surrogate ventilation. Gi...

Enhanced Pelvic Organ Segmentation Using LLM-Driven Prompts for Prostate Cancer Low-Dose-Rate Brachytherapy

Authors: Yang Lei, Tian Liu, Ren-Dih Sheu, Meysam Tavakoli, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Emory University

Abstract Preview: Purpose:
The study aimed to improve target and organ at risk (OAR) segmentation in low-dose-rate brachytherapy (LDR-BT) for prostate cancer treatment, by integrating clinical guidelines into deep l...

Enhancing Adaptive Radiotherapy Segmentation with a 3D Unet Framework and Prior Fraction Information

Authors: Jennifer L. Dolan, Chengyin Li, Parag Parikh, Doris N. Rusu, Kundan S Thind

Affiliation: Henry Ford Health, Cedars-Sinai Medical Center

Abstract Preview: Purpose: The time and resource demands of online Adaptive Radiation Therapy (ART) can limit its widespread clinical adoption and potentially impact patient throughput. To address this, we developed a ...

Enhancing CNN-Based Brain Metastasis Detection in MRI By Integrating Locoregional 3D Deformation Technique

Authors: Minbin Chen, Ke Lu, Kaizhong Shi, Chunhao Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao

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

Abstract Preview: Purpose: MRI-based automatic detection of brain metastases is often challenged by the small size and subtle nature of metastases. This study aimed to develop a novel deep learning-based brain metastas...

Enhancing Lung SBRT Planning Efficiency: A Template-Based Approach Using Chest Wall Overlapping Cases

Authors: Felicia Chu, Qiongge Li, Jian Liu

Affiliation: Inova Hospital, Brown University Rhode Island Hospital, Hofstra University Medical Physics Program

Abstract Preview: Purpose:
This study aims to enhance the efficiency of stereotactic body radiation therapy (SBRT) planning for lung cancer by developing and evaluating optimization templates derived from historical...

Enhancing Proton Treatment and Mitigating Radiation-Induced Lung Injury Using a Novel Cycle Diffusion Approach for Lung Ventilation Estimation

Authors: Yang Lei, Haibo Lin, Tian Liu, Charles B. Simone, Shouyi Wei, Ajay Zheng

Affiliation: Icahn School of Medicine at Mount Sinai, New York Proton Center

Abstract Preview: Purpose: Radiation-induced lung injury (RILI), encompassing pneumonitis and fibrosis, represents a critical dose-limiting factor in lung cancer radiation therapy. Variability in treatment outcomes is ...

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 the Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncology

Authors: Meiyun Cao, Edward L. Clouser, Xiaoning Ding, Jason Michael Holmes, Shaw Hu, Linda L. Lam, Wendy S. Lindholm, Wei Liu, Samir H. Patel, Diego Santos Toesca, Jason Sharp, Sujay A. Vora, Peilong Wang

Affiliation: Department of Radiation Oncology, Mayo Clinic, Mayo Clinic Arizona, George Washington University

Abstract Preview: Purpose: In current clinical workflow of radiation oncology departments, therapists manually summarize CT simulation orders into summaries before the CT simulation for execution. This process signific...

Evaluation of Daily Respiratory Pattern from a Single Free-Breathing Cone Beam CT Scan

Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Xiuxiu He, Tianfang Li, Xiang Li, Hao Zhang

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

Abstract Preview: Purpose:
This work aims to develop an innovative technique to evaluate patients’ daily respiratory pattern using three-dimensional (3D) deformation vector fields (DVF) derived from a free-breathing...

Expanding the Reach: Integrating AI-Generated Auto Contours Via Ray Station’s Deep Learning Segmentation into Diverse Treatment Planning Systems

Authors: Raghavendra Raghavendra, Kanaparthy Raja Muralidhar, Venkataramanan Ramachandran, Srinivas Srinivas

Affiliation: Karkinos Healthcare

Abstract Preview: Purpose: This study explores the Integrating AI-Generated Auto Contours via Ray Station’s Deep Learning Segmentation into Diverse Treatment Planning Systems.
Methods: The research encompassed a gro...

Follow-the-Leader Framework for Adaptable Target Segmentation in Radiotherapy

Authors: Mingli Chen, Xuejun Gu, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: This study introduces a novel template-guided deep learning framework for primary gross tumor volume (GTVp) segmentation, addressing challenges posed by diverse tumor types and enabling a uni...

Foundation Model-Augmented Learning for Automatic Delineation in Precision Radiotherapy

Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...

Free-Breathing Spirometer-Gated Proton Pencil Beam Scanning Delivery Maintains Tumor Coverage with Improved Organ-at-Risk Sparing: A Motion Phantom Validation

Authors: Uriel Aura, Qing Chen, Arpit M. Chhabra, J Isabelle Choi, Chanda Guha, Meng Wei Ho, Sheng Huang, Minglei Kang, Stanislav Lazarev, Nancy Y Lee, Yang Lei, Haibo Lin, Hang Qi, Mahbubur Rahman, Charles B. Simone, Shouyi Wei, Irini Yacoub, Francis Yu, Anna Zhai, Ajay Zheng

Affiliation: DYN'R Medical System, New York Proton Center, Montefiore Medical Center and Albert Einstein College of Medicine, Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Tianjin Medical University Cancer Institute&Hospital, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Managing tumor motion during pencil beam scanning proton therapy remains challenging. This study investigated the feasibility and dosimetric benefits of Free-Breathing Respiratory-Gated Deliv...

From Concept to Clinic: A Phase-Based Approach for Implementing Auto-Segmentation in Radiation Therapy

Authors: Elizabeth L. Covington, Robert T. Dess, Charles S. Mayo, Michelle L. Mierzwa, Dan Polan, Jennifer Shah, Claire Zhang

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

Abstract Preview: Purpose: Auto-segmentation improves contour consistency and standardization in radiation therapy but may introduce variations from current practices, potentially impacting treatment outcomes and toxic...

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...

Functional Liver Image Guided Radiation Planning Using MRI with a Contrast Agent

Authors: Kenneth L. Homann, Natalie A Lockney, Hong Zhang

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

Abstract Preview: Purpose: The aim of this study is to develop a treatment planning methodology utilizing liver functional imaging via contrast-enhanced Magnetic Resonance Imaging (MRI) in patients undergoing stereotac...

Gene Interaction-Encoded Deep Learning Uncovers Microenvironment for Radiation-Induced Pulmonary Fibrosis

Authors: Md Tauhidul Islam, Junyan Liu, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Radiation-induced lung injury (RILI) is a common complication in patients receiving radiotherapy for lung cancer, with approximately 16%–28% developing pulmonary fibrosis. The exact mechanism...

Getting in Focus: Review of Current Focal Spot Size Testing Methods with Flat Panel Digital Radiography Detectors

Authors: Matthew R. Hoerner, Maryam Naseri, Mena Shenouda

Affiliation: Yale University School of Medicine, Yale University

Abstract Preview: Purpose:
Historically film has been the gold standard receptor for measurements of x-ray tube focal spot size. Flat Panel Digital Radiography Detectors (FPDRDs) have lower spatial resolution compar...

Graph-Based Feature Selection to Improve Stability and Reproducibility of CT-Based Radiomics in Head and Neck Squamous Cell Carcinoma: A Cross-Institutional Study

Authors: Daria Gaykalova, Ranee Mehra, Jason K Molitoris, Hajar Moradmand, Lei Ren, Amit Sawant, Phuoc Tran

Affiliation: University of Maryland School of Medicine, Maryland University Baltimore, University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Radiomics extracts quantitative imaging biomarkers from medical images. However, maintaining the reproducibility and stability of selected features across institutions and parameter settings ...

High Resolution Head Motion Correction Based on Pilot Tone Signals – a Calibration-Free Method

Authors: Cheng-Chieh Cheng, Jeffrey P Guenette, Yajun Li, Bruno Madore, Lei Qin

Affiliation: Brigham and Women's Hospital, National Sun Yat-sen University, Dana-Farber Cancer Institute

Abstract Preview: Purpose: Pilot tone (PT), a compact RF sensor, has been integrated into clinical practice for motion detection. Prior studies proposed mapping PT signals to head positions using a calibration step tha...

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....

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

Authors: Yu Gao, Lei Xing, Siqi Ye

Affiliation: Department of Radiation Oncology, Stanford University

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

Hypersight® Offline Adaptive Workflow

Authors: Doris Dimitriadis/Dimitriadou, Denisa R. Goia, M. Saiful Huq, Ronald John Lalonde, Noor Mail, Adam Olson, Tyler Wilhite

Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, UPMC

Abstract Preview: Purpose: The goal of the HyperSight® offline adaptive-workflow is to create a methodical approach to adaptive-radiotherapy (ART) that considers modifications in patient setup and anatomy. Through effi...

Image-Guided Adaptive Proton Therapy for Head and Neck Cancer Using a Novel Gantry-Less System

Authors: Philip Blumenfeld, Jon Feldman, Yair Hillman, Michael Marash, Aron Popovtzer, Alexander Pryanichnikov, Shimshon Winograd, Marc Wygoda, Vered Zivan

Affiliation: Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), P-Cure Ltd./Inc., Sharett Institute of Oncology, Hadassah Medical Center, Hebrew University of Jerusalem

Abstract Preview: Purpose:
Image-guided adaptive proton therapy (IGAPT) allows tailored dose adjustments to account for anatomical and physiological changes during treatment. Recent efforts have developed a cost-eff...

Impac of Respiratory Motion on Dosimetric and Biological Outcomes in Lung Cancer SIB-SBRT: A 4D Dose Calculation Approach

Authors: Xiangli Cui, Lingling Liu

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Hefei Cancer Hospital, Chinese Academy of Sciences

Abstract Preview: Purpose:
Respiratory motion introduces substantial dose uncertainties in lung cancer radiotherapy, particularly affecting dose distribution in Simultaneous Integrated Boost-Stereotactic Body Radiot...

Improved SNR and Estimation Accuracy for Deuterium-MRI Acquired with Chemical Shift Imaging at 7 Tesla

Authors: Muhammed AR Anjum, Andrew J. Fagan

Affiliation: Mayo Clinic

Abstract Preview: Purpose:
This study describes a novel post-processing method to boost image SNR for deuterium-MRI acquired using chemical shift imaging (CSI) at 7T. Deuterium MRI via exogenous administration of a ...

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...

Improving the Robustness of AI-Based Detection and Segmentation for Brain Metastasis By Optimizing Loss Function and Multi-Dataset Training

Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte

Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine

Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...

In-Silico Clinical Trials Enabled By Digital Twin Approach Can Accurately and Prospectively Predict Outcomes of Clinical Trials Combining Radiation and Systemic Therapy

Authors: Clemens Grassberger, David (Bo) McClatchy, Harald Paganetti

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Massachusetts General Hospital

Abstract Preview: Purpose: While randomized controlled trials (RCTs) are the gold standard for demonstrating efficacy, nearly 50% of late-stage clinical trials fail to meet their endpoint. Tools to study the design of ...

Incorporating Physicians’ Contouring Style into Auto-Segmentation of Clinical Target Volume for Post-Operative Prostate Cancer Radiotherapy Using a Language Encoder

Authors: Steve B. Jiang, Chien-Yi Liao, Dan Nguyen, Daniel Yang, Hengrui Zhao

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

Abstract Preview: Purpose:
Post-operative radiotherapy for prostate cancer requires precise contouring of the clinical target volume (CTV) to account for microscopic disease that is invisible in the image. However, ...

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 Radiomics and ADC Ratio for Multicenter Prostate Cancer Diagnosis: A Harmonized Machine Learning Approach

Authors: George Agrotis, Marios Myronakis, Dimitrios Samaras, Kyriaki Theodorou, Ioannis Tsougos, Vassilios Tzortzis, Maria Vakalopoulou, Alexandros Vamvakas, Aikaterini Vassiou, Marianna Vlychou

Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Radiology, University of Thessaly, Netherland Cancer Institute, Department of Urology, University of Thessaly, CentraleSupelec, University Paris-Saclay

Abstract Preview: Purpose: Prostate cancer (PCa) diagnosis remains challenging due to discrepancies in Gleason Scoring (GS) and risks of overdiagnosis and underdiagnosis. Multiparametric MRI (mpMRI), including Apparent...

Inter-Machine Harmonization in Echocardiographic Videos for Predicting Left Ventricular Ejection Fraction

Authors: Akihiro Haga, Ren Iwasaki, Kenya Kusunose, Makoto Miyake, Kenji Moriuchi, Yasuharu Takeda, Hidekazu Tanaka, Hirotsugu Yamada

Affiliation: Department of Cardiovascular Medicine, Nephrology, and Neurology Graduate School of Medicine, University of the Ryukyus, Graduate School of Biomedical Sciences, Tokushima University, Tokushima university, Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Department of Cardiology, Tenri Hospital, Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Division of Heart Failure, Department of Heart Failure and Transplant, National Cerebral and Cardiovascular Center

Abstract Preview: Purpose: Device dependency is a significant challenge in medical AI, potentially limiting generalization performance. This study aimed to develop a robust deep learning model for predicting left ventr...

Investigating Gammatile Migration: Implications for Dosimetry and Clinical Outcomes

Authors: Wesley A. Belcher, Robert A. Corns, Jae Won Jung, Matthew S Peach, Swarup Sharma

Affiliation: The University of North Carolina at Chapel Hill, East Carolina University Brody School of Medicine

Abstract Preview: Purpose: GammaTiles are a novel intracranial brachytherapy approach designed to directly deliver radiation therapy to residual or recurrent brain tumors following resection. Despite their promising th...

Investigating the Multimodal Fusion Techniques to Improve Prediction Accuracy of Biochemical Recurrence of Prostate Cancer

Authors: Clint Bahler, Ruchika Reddy Chimmula, Harrison Louis Love, Oluwaseyi Oderinde, Courtney Yong

Affiliation: Purdue University, Department of Urology, Indiana University School of Medicine, Advanced Molecular Imaging in Radiotherapy (AdMIRe) Research Laboratory, School of Health Sciences, Purdue University

Abstract Preview: Purpose: Prostate cancer (PCa) is a common malignancy in men, and predicting biochemical recurrence (BCR) is crucial for guiding treatment decisions. Integrating multimodal data, including clinical, i...

Joint Optimization of Patient-Specific Range Modulators and Beam Intensities for Conformal Flash Proton Therapy

Authors: Hao Gao, Jiayue Han, Wangyao Li, Yuting Lin, Jufri Setianegara, Aoxiang Wang, Yanan Zhu

Affiliation: Department of Biomedical Engineering, Huazhong University of Science and Technology, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Proton therapy leverages Bragg-peak-based dose delivery to achieve ultra-high-dose-rate FLASH with patient-specific range modulators (PSRM). Current proton FLASH (pFLASH) planning typically i...

Knowledge-Based Online Adaptive Proton Stereotactic Ablative Radiotherapy (SABR) for Localized Prostate Cancer Using Gaussian Process Regression

Authors: Hania A. Al-Hallaq, Duncan Henry Bohannon, Chih-Wei Chang, Anees H. Dhabaan, Vishal Dhere, H Scott McGinnis, Pretesh Patel, Sagar Patel, Keyur Shah, Xiaofeng Yang, Jun Zhou

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

Abstract Preview: Purpose: Two-fraction proton SABR is an attractive alternative to brachytherapy for localized prostate cancer. However, potential interfractional anatomical changes necessitate online adaptation, espe...

Knowledge-Informed Deep Learning for Accurate and Interpretable Extracapsular Extension Detection in Head and Neck Squamous Cell Carcinoma

Authors: William N. Duggar, Amirhossein Eskorouchi, Haifeng Wang

Affiliation: Mississippi State University, University of Mississippi Medical Center

Abstract Preview: Purpose:
Extracapsular extension (ECE) in lymph nodes represents a critical prognostic factor in head and neck squamous cell carcinoma (HNSCC), bearing important implications for staging, treatment...

Large Language Model Agents for Automated Radiotherapy Planning: A Knowledge-Enhanced Reinforcement Learning Approach

Authors: Hassan Bagher-Ebadian, Anthony J. Doemer, Ryan Hall, Joshua P. Kim, Bing Luo, Benjamin Movsas, Humza Nusrat, Kundan S Thind

Affiliation: Department of Physics, Toronto Metropolitan University, Henry Ford Health

Abstract Preview: Purpose: This study investigates the development and feasibility of local LLM-based agents to automate radiotherapy treatment planning, aiming to improve planning efficiency and consistency, while pre...

Liver Tumor Auto-Contouring Using Recurrent Neural Networks on MRI-Linac for Adaptive Radiation Therapy

Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao

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

Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...

Log File-Based Patient-Specific QA As a Viable Alternative to Measurement-Based QA in IMPT

Authors: Sina Mossahebi, Pouya Sabouri, Kayla Schneider, James W Snider

Affiliation: University of Maryland School of Medicine, Proton International, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiation Oncology, University of Arkansas for Medical Sciences

Abstract Preview: Purpose:
Conventional patient-specific QA (PSQA) for intensity-modulated proton therapy (IMPT) requires extensive measurements, straining resources in single-room proton centers. This study evaluat...

Mask-Based Synthetic Contrast-Enhanced CT Generation for Advancing Data Limited Segmentation on Cardiac Substructure

Authors: Jin Sung Kim, Chanwoong Lee, Young Hun Yoon

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

Abstract Preview: Purpose: Chest contrast-enhanced CT (CECT) serves as a valuable tool for cardiac imaging, but its lack of detailed anatomical visualization limits its utility in segmentation tasks. While CECT offers ...

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

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

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

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

Mesh-Based Multiregion Model of Adult Human Kidneys for Dosimetric Evaluation of Radiopharmaceutical Therapy

Authors: John P. Aris, Wesley E. Bolch, Chansoo Choi, Carlos G. Colon-Ortiz, Robert Joseph Dawson, Abdul-Vehab Dozic, Amy M. Geyer, Harald Paganetti, Shreya P. Pathak, Julia D. Withrow

Affiliation: St. Luke's Health System, Massachusetts General Hospital, University of Florida

Abstract Preview: Purpose: The goal of this study was to enhance the accuracy of renal dosimetry in radiopharmaceutical therapy (RPT) by developing a more detailed and precise kidney model. In RPT, accurate dose estima...

Mitigating Data-Driven Uncertainty in Machine Learning-Based Radiotherapy Outcome Prediction

Authors: Ali Ajdari, Alice Bondi, Thomas R. Bortfeld, Gregory Buti, Xinru Chen, Zhongxing Liao, Antony John Lomax, Ting Xu

Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Paul Scherrer Institut, ETH Zurich

Abstract Preview: Title: Addressing Imaging and Biomarker-driven Uncertainty in Machine Learning-based Radiotherapy Outcome Prediction
Alice Bondi, Gregory Buti, Antony Lomax, Thomas Bortfeld, Xinru Chen, Ting Xu, Z...

Multi-Criteria Optimization in Medical Physics Resource Allocation: Design of an Efficient and Equitable Scheduling System

Authors: Dalton Griner, Kathryn L. Kolsky, Joseph John Lucido, Andrew J. Veres

Affiliation: Mayo Clinic

Abstract Preview: Purpose: This project aimed to automate a complex and time-consuming employee scheduling process. By replacing the traditional manual method with a multi-criteria optimization-based system (MCO), the ...

Multi-Mechanism CNN and Long Short-Term Memory Fusion Model for Improved CT-Based Thyroid Cancer Diagnosis

Authors: Yunfei Dong, Dongyang Guo, Jiongli Pan, Tao Peng, Caiyin Tang, Zhenyu Yang, Fang-Fang Yin, Lei Zhang, Tianyi Zhang, Yaogong Zhang

Affiliation: Duke Kunshan University, Department of Radiology, Taizhou People’s Hospital Affiliated to Nanjing Medical University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aims to improve the accuracy of CT-based diagnosis of thyroid cancer by developing a hybrid model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...

Multi-Omics-Based Prognostic Prediction for Locally Advanced Hypopharyngeal Cancer Treated with Postoperative Chemoradiotherapy: A Dual-Center Study

Authors: Sixue Dong, Chaosu Hu, Weigang Hu, Xiaomin Ou, Jiazhou Wang, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aimed to predict the PFS of the patients who were diagnosed with hypopharyngeal cancer and received postoperative chemoradiotherapy by using multi-omics which integrating clinic...

Multi-Region Multiomic Features Improve Random Forest Toxicity Modeling of Radiation Pneumonitis

Authors: Laurence Edward Court, Alexandra Olivia Leone, Zhongxing Liao, Saurabh Shashikumar Nair, Joshua S. Niedzielski, Ramon Maurilio Salazar, Ting Xu

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

Abstract Preview: Purpose: Radiation Pneumonitis (RP) predictive models often rely on clinical and DVH parameters, but multiomic features from CT imaging and 3D dose distributions from various regions could provide add...

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...

Multimodal Attention Fusion Model Leveraging Structured and Unstructured EHR Data for Hospital Readmission Prediction in Head and Neck Cancer

Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas

Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco

Abstract Preview: Purpose: Hospital readmission prediction models often rely on structured Electronic Health Record (EHR) data, overlooking critical insights from unstructured clinical notes. This study presents a mult...

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

Authors: Peng Dong, Lei Xing

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

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

Novel Approach to Improve Treatment Planning Process for Mixed Fractionation Schemes on ZAP-X

Authors: Michael Evan Chaga, Timothy Chen, Darra M. Conti, Shabbar Danish, Jing Feng, Wenzheng Feng, Joseph Hanley, Tingyu Wang

Affiliation: Hackensack Meridian Health, Jersey Shore University Medical Center

Abstract Preview: Purpose: Using mixed fractionation schemes is a common technique in treating CNS lesions. This article describes an innovative plan-and-split approach for more efficient planning on the ZAP-X and thus...

Oncoflat: Automated 3D-to-2D Bolus Unfolding Tool for Radiation Therapy

Authors: Jeonghoon Park, Amritha Praveen, Siddhant Sen, James J. Sohn, Ethan D. Stolen

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, The University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago, Department of Psychology, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Accurate fabrication of custom boluses is essential in radiation therapy to enhance dose delivery to superficial tumors, especially in anatomically complex regions. This study introduces a no...

Optimized Dosimetric Planning for Trigeminal Neuralgia Using Cyberknife S7 Precision TPS with Volo Optimizer

Authors: Amy Fitzpatrick, Kim Howard, Julius G. Ojwang, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: This study evaluates the dosimetric advantages and workflow improvements of the CyberKnife S7 Precision Treatment Planning System (TPS) with the VOLO optimizer for stereotactic radiosurgery (...

Optimizing Design to Enhance the Energy Separation in a Kv Dual-Layer Imager (DLI)

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: Multi-layer flat-panel imagers can improve for clinical image-guided radiotherapy applications, including the enhanced visualization of soft tissue and a reduction in image artifacts. Each im...

Optimizing Dosimetry in Rpt Clinics: Tackling Initial Hurdles and Ensuring Image Accuracy.

Authors: Siju C. George, Alonso N. Gutierrez, Vivek Mishra, Ranjini P. Tolakanahalli

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

Abstract Preview: Purpose: This presentation focuses on optimizing dosimetry in RPT clinics by tackling initial setup challenges and ensuring the accuracy of SPECT/CT imaging for dosimetry. It will address the qualific...

Optimizing Low-Dose Imaging Parameters for Dual-Energy Cone-Beam Computed Tomography in Image-Guided Radiation Therapy

Authors: Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Luke Layman, Jason Patrick Luce, Ha Nguyen, John C. Roeske

Affiliation: Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago

Abstract Preview: Purpose:
This study aims to optimize virtual monoenergetic (VM) images obtained from dual-energy (DE) cone-beam computer tomography (CBCT) protocols for Image-Guided Radiation Therapy (IGRT). The o...

Optimizing Prostate Cancer Radiotherapy: Comprehensive Analysis of Automated Planning with Neural Network-Based Dose Prediction

Authors: Seungtaek Choi, Laurence Edward Court, Eun Young Han, Yusung Kim, Hunter S. Mehrens, Tucker J. Netherton, Shiqin Su

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

Abstract Preview: Purpose: Automated treatment planning is gaining traction for its enhanced consistency and efficiency. A key challenge, however, lies in the inability of neural network dose predictions directly trans...

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...

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

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

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

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

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

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

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

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

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...

Preliminary Clinical Experience with MRI-Guided Online Adaptive Radiotherapy for Esophageal Cancer Patients

Authors: Ali Hosni, Oleksii Semeniuk, Andrea Shessel, Teo Stanescu

Affiliation: Princess Margaret Hospital, Princess Margaret Cancer Centre, Brown University Health

Abstract Preview: Purpose: To report on early clinical experience with a two-phase radiotherapy approach for esophageal cancer patients, utilizing CBCT-based conventional C-arm linear accelerator radiotherapy and MR-gu...

Prior-Model-Free Dynamic CBCT Reconstruction Via Combined Optical Surface and X-Ray Imaging

Authors: Hua-Chieh Shao, Guoping Xu, You Zhang, Tingliang Zhuang

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:
Advancements in onboard X-ray hardware allow high-quality CBCT imaging with a short scan time (~6s for Varian HyperSight), enabling CBCT-based dose calculation and treatment planning. Howe...

Prostate Brachytherapy Training – a Virtual Approach

Authors: Fahad Alam, Douglas A Hoover, Raffi Karshafian, Andrew Loblaw, Lucas Mendez, Lucas Mendez, Gerard Morton, Humza Nusrat, Moti R. Paudel, Mackenzie Smith, Amandeep Tagger, Anton Varlukhin

Affiliation: Odette Cancer Center, Sunnybrook Health Sciences Center, Department of Anesthesiology, Temerty Medicine, University of Toronto, Department of Physics, Toronto Metropolitan University, Department of Radiation Oncology, Temerty Medicine, University of Toronto, Department of Radiation Oncology, London Health Sciences Centre

Abstract Preview: Purpose: Prostate brachytherapy utilization has declined, due in part to limitations seen with in-person training including time and space constraints in the operating room. Virtual reality addresses ...

Proton Pencil Beam Scanning Ultra-High Dose Rate 3D Lattice Radiotherapy: A Proof-of-Concept Flash Sfrt Study

Authors: Richard Bakst, Arpit M. Chhabra, J Isabelle Choi, Chanda Guha, Minglei Kang, Nancy Y Lee, Haibo Lin, Hang Qi, Charles B. Simone, Pingfang Tsai, Milo Vermeulen, Shouyi Wei, Xiaodong Wu, Lee Xu, Irini Yacoub, Xingyi Zhao, Ajay Zheng

Affiliation: University of Miami, Peking University, New York Proton Center, Montefiore Medical Center and Albert Einstein College of Medicine, icahn school of medicine at mount sinai, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose:
Three-dimensional lattice radiation therapy (3D-LRT) effectively achieves local tumor control with limited morbidity. Pencil beam scanning (PBS) proton therapy provides precise dose confor...

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

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

Affiliation: Duke University Medical Center

Abstract Preview: Purpose: Gradient-based optimization is the standard approach for IMRT fluence map optimization (FMO). Recently, a machine learning (ML)-assisted framework using a one-layer neural network was propose...

Quantification of Iodine and Calcium Materials through HU Spectral Curve Analysis in Dual-Energy CT for Radiotherapy Planning

Authors: Sean L. Berry, Weixing Cai, Laura I. Cervino, Maria F. Chan, Yabo Fu, Puneeth Iyengar, Hsiang-Chi Kuo, Nancy Lee, Tianfang Li, Xiang Li, Jean M. Moran

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

Abstract Preview: Purpose: Iodine maps derived from Dual-Energy CT (DECT) provide critical biological information for radiotherapy treatment planning, but clinical iodine maps often mistakenly include bones due to insu...

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...

Reasoning-Driven Prompts Improve EHR-Based Outcome Prediction and Clinical Interpretability in Large Language Models

Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas

Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco, University of San Francisco

Abstract Preview: Purpose: As Large Language Models (LLMs) continue to evolve, their ability to analyze Electronic Health Record (EHR) notes for clinical decision support expands. Chain of Thought (COT) reasoning, an e...

Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

Authors: Yizheng Chen, Md Tauhidul Islam, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
Biomedical image segmentation (BIS) is a cornerstone of medical physics, enabling accurate delineation of anatomical structures and abnormalities, which is critical for diagnosis, treatmen...

Refining the in-House Modified COMS Eye Plaque Workflow

Authors: Vishruta A. Dumane, Andrew Lukban, Kiran Pant, Charlotte Elizabeth Read, Ren-Dih Sheu, Nadia M. Vassell

Affiliation: Icahn School of Medicine at Mount Sinai, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology

Abstract Preview: Purpose: This work introduces a refined in-house modified COMS eye plaque management system to streamline processes, reduce redundancies, and enhance usability.
Methods: A web-based application wit...

Research on Multi-Organ Segmentation Based on Cross-Domain Transfer Learning

Authors: Jiali Gong, Yi Guo, Chi Han, Wanli Huo, Hongdong Liu, Zhao Peng, Yaping Qi, Zhaojuan Zhang

Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, Department of Oncology, Xiangya Hospital, Central South University, 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, Division of lonizing Radiation Metrology, National Institute of Metrology, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University

Abstract Preview: Purpose: To address overfitting from limited training data in multi-organ segmentation, an efficient transfer learning framework is proposed. It reduces reliance on training samples, enabling a single...

Routine Quality Monitoring in Abdominal CT Using Global Noise Reference Levels in a 4-Parameter Protocol Summary Plot

Authors: Joke Binst, Hilde TC Bosmans, Niki Fitousi, Bram Miseur, Dimitar Petrov, Kwinten Torfs, Janne Vignero

Affiliation: Qaelum NV, Department of radiology, UZLeuven, Department of imaging and pathology, KULeuven

Abstract Preview: Purpose: Routine quality monitoring in CT abdomen is crucial for ensuring optimal image quality and patient safety, but the simultaneous evaluation of all aspects of importance is challenging. The pur...

SRS Treatment Planning for Brain Metastases on Varian Truebeam and Elekta Gamma Knife Icon

Authors: Carl D. Elliston, Lawrence Koutcher, Michael J. Price, Adam C. Riegel, Michael B Sisti, Tony J.C. Wang, Andy (Yuanguang) Xu

Affiliation: Columbia University Irving Medical Center

Abstract Preview: Purpose: An inverse treatment planning software was recently introduced to Gamma Knife radiosurgery. The purpose of this study is to compare the plan quality of the Gamma Knife ”Lightning” with that o...

Safety of Off-Axis Treatment for Selection of Optimal Beam Angles in SBRT of the Posteriorly Located Lung Lesions

Authors: Reza Farjam, Russell K Hales, Todd R. McNutt, Mohammad Rezaee, Ehsan Tajikmansoury, K. Ranh Voong

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University

Abstract Preview: Purpose: Optimal beam angles and off-axis isocenter selection are important to achieve high quality plan and collision-free delivery in stereotactic body radiotherapy (SBRT) of the posteriorly located...

Scissor-Beam Based Carbon Ion Minibeam Treatment Planning Method

Authors: Hao Gao, Qiang Li, Yuting Lin, Wei Wang, Wei Wu, Weijie Zhang

Affiliation: Institute of Modern Physics, Chinese Academy of Sciences, China, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Carbon minibeam radiation therapy (cMBRT) offers high peak-to-valley dose ratio (PVDR) and relative biological effectiveness. A key challenge is balancing uniform target coverage with PVDR pr...

Scoring Functions for Reinforcement Learning in Accelerated Partial Breast Irradiation Treatment Planning

Authors: Rafe A. McBeth, Kuancheng Wang, Ledi Wang

Affiliation: Department of Radiation Oncology, University of Pennsylvania, Georgia Institute of Technology, University of Pennsylvania

Abstract Preview: Purpose:
The integration of AI in clinical workflows presents unprecedented opportunities to enhance treatment quality in radiation oncology, yet it also demands innovative approaches to address th...

Simulation Design of a Dedicated Head Coil for Enhanced EPT Imaging to Map the Electrical Properties of Tumor Tissues

Authors: Jingyao Chen, Yingli Yang, Jie Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Ruijin Hospital, Shanghai United imaging Healthcare Advanced Technology Research Institute

Abstract Preview: Purpose: Magnetic Resonance Electrical Properties Tomography (MR EPT) is a method to spatially mapping the conductivity and permittivity based on small B1 field changes after the imaged object was int...

Spatially Informed Auto-Segmentation of Cardiac Nodes for Radiotherapy Treatment Planning

Authors: Ming Dong, Carri K. Glide-Hurst, Joshua Pan, Nicholas R. Summerfield

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Radiation dose to the cardiac nodes is more strongly associated with conduction disorders and arrythmias than whole heart (WH) metrics. However, node segmentation is challenging due to comple...

Streamlining Quad-Shot Radiotherapy: Automated Workflow Enables Same-Day Treatment for Palliative Lung Cancer

Authors: Laura I. Cervino, Sharif Elguindi, Yu-Chi Hu, Licheng Kuo, Xiaoning Liu, Jennifer Ma, Pengpeng Zhang

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

Abstract Preview: Purpose:
Quad-shot radiotherapy (QSRT) is an emerging paradigm in palliative cancer treatment. This study aimed to streamline the QSRT workflow using automation to improve efficiency while maintain...

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...

The Effect of 2D Antiscatter Grid-Based CBCT on Tissue Visualization in the Prostate Region: An Observer Study on Tissue Delineation Accuracy

Authors: Cem Altunbas, Adam Avant, Farhang Bayat, Roy Bliley, Ian Boor, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi

Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic

Abstract Preview: Purpose: Improved soft tissue visualization plays an important role in target localization and treatment plan adaptation in CBCT-guided radiotherapy. In this work, a novel CBCT approach, 2D antiscatte...

The GYN Webapp: A Centralized Tool for Enhancing HDR Brachytherapy Treatment Quality and Clinical Outcomes

Authors: Kevin Albuquerque, Ti Bai, Yesenia Gonzalez, Brian A. Hrycushko, Zohaib Iqbal, Paul M. Medin, Shanshan Tang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Cervical cancer remains one of the most common and significant gynecological (GYN) malignancies globally, often presenting at advanced stages where radiation therapy and high-dose-rate (HDR) ...

Unsupervised Task-Specific Histology Image Stain Standardization and Crypt Detection for Evaluating Normal Tissue Flash Irradiation Response

Authors: Muhammad Ramish Ashraf, Kerriann Casey, Suparna Dutt, Jie Fu, Edward Elliot Graves, Xuejun Gu, Hao Jiang, Brianna Caroline Lau, Billy W Loo, Weiguo Lu, Rakesh Manjappa, Stavros Melemenidis, Erinn Bruno Rankin, Lawrie Skinner, Luis Armando Soto, Murat Surucu, Vignesh Viswanathan, Zi Yang, Amy Shu-Jung Yu

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, 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, Department of Comparative Medicine, Stanford University School of Medicine, Department of Radiation Oncology, Stanford University Cancer Center

Abstract Preview: Purpose: The intestine is a classical preclinical model for studying radiation injury, and histological quantification of intestinal crypts is a key assay for assessing this response. However, substan...

Using Single-Energy Bragg Peak (SEBP) Flash Combined with Intensity-Modulated Proton Therapy (IMPT) for Flash Treatment in a Clinical Synchrotron-Based Proton System

Authors: Chingyun Cheng, Ben Durkee, Carri K. Glide-Hurst, Minglei Kang, Haibo Lin, Bhudatt R. Paliwal, Charles B. Simone, Zhizhen Wei, Tengda Zhang, Xingyi Zhao

Affiliation: University of Wisconsin, Department of Mechanical Engineering, University of Wisconsin-Madison, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, New York Proton Center, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Transmission Beam (TB), Single-Energy Bragg Peak (SEBP), and Single-Energy Spread-Out Bragg Peak (SESOBP) are primary proton conformal FLASH techniques. However, each comes with significant l...

Utilization of Log File Analysis to Determine Deliverability of VMAT Plans As a Function of Plan Complexity

Authors: Jameson T. Baker, Sean T Grace, Cindy Pham, Michael A. Trager

Affiliation: Northwell

Abstract Preview: Purpose:
In VMAT planning, increasing complexity in MLC motion and modulation may improve dose distributions and OAR sparing while maintaining PTV coverage. However, increasing complexity can creat...

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...

Validation of a Pharmacokinetic Model for Dosimetry in Nuclear Medicine

Authors: Farhad Jafari, Brandon Hai Nguyen

Affiliation: Department of Radiation Oncology, University of Minnesota Medical School, Department of Radiology, University of Minnesota

Abstract Preview: Purpose: To validate a bottom-up approach to dosimetry in nuclear medicine.

Methods: A pharmacokinetic model is developed to represent the flow of activity between different compartments of the...

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...

Voxel-Based Radiobiological Modelling for Evaluating Radiotherapy Treatment Plans in Relation to Radiation-Induced Acute Mucosal Toxicity (including oral and pharyngeal mucositis): A Single-Institutional Study Focused on Head-and-Neck Carcinoma.

Authors: Rama Bhawani, Mary Joan, Ajay Katake, Munish Kumar, Chhape Ram, Megha Sharma, Balbir Singh, Vikram Singh

Affiliation: SLBSGMC & HOSPITAL, MOHANDAI OSWAL HOSPITAL, WOCKHARDT HOSPITAL, Christian Medical College and Hospital,, AMERICAN ONCOLOGY INSTITUTE

Abstract Preview: Purpose: This study aims to evaluate the utility of voxel-based radiobiological modelling in assessing IMRT radiotherapy treatment plans concerning radiation-induced acute mucosal toxicity, specifical...

Weak-to-Strong Generalization for Interpretable Deep Learning-Based Histological Image Classification Guided By Hand-Crafted Features

Authors: Mark Anastasio, Zong Fan, Hua Li, Changjie Lu, Lulu Sun, Xiaowei Wang, Zhimin Wang, Michael Wu

Affiliation: University of Illinois at Urbana-Champaign, University of Illinois at Chicago, Washington University School of Medicine, University of Illinois Urbana-Champaign, Washington University in St. Louis, University Laboratory High School

Abstract Preview: Purpose: Histological whole slide images (WSIs) are vital in clinical diagnosis. Although deep learning (DL) methods have achieved great success in this task, they often lack interpretability. Traditi...