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Results for "oar metrics": 135 found

A Causal Machine Learning Analysis of Dosimetric and Clinical Predictors of Osteoradionecrosis in Head and Neck Cancer Radiotherapy

Authors: Jingyuan Chen, Sheng Li, Tianming Liu, Wei Liu, Zhengliang Liu, Zhong Liu, Daniel Ma, Samir H. Patel, Guangya Wang, Yunze Yang

Affiliation: University of Miami, Mayo Clinic, School of Data Science, University of Virginia, School of Computing, University of Georgia, Department of Radiation Oncology, Mayo Clinic, Institute of Western China Economic Research, Southwestern University of Finance and Economics

Abstract Preview: Purpose:
Traditional patient outcome analyses relied heavily on conventional statistical models that primarily elucidate correlation rather than causal relationships. In this study, we aim to ident...

A Comparison of Non-Adaptive Versus Online Adaptive Radiotherapy for Prostate Cancer Using FLOW-RT-- Fast, AI-Driven but Learning-Enabled, Online Adaptive Workflow for Radiotherapy

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Beatriz Guevara, Lauren E Henke, Angela Jia, Rojano Kashani, Kyle O'Carroll, Alex T. Price, Adithya Reddy, Atefeh Rezaei, Daniel E Spratt, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: To evaluate the effect of unedited AI-generated contours used for online adaptive radiotherapy (FLOW-ART) on the plan quality of prostate treatments as compared to non-adaptive (non-ART) proc...

A Customizable Phantom Insert Design for Testing Deformable Image Registration with Simulated Respiratory Motion

Authors: Mubasheer Chombakkadath, Tara E. Tyson, Iris Z. Wang

Affiliation: Roswell Park Comprehensive Cancer Center, University at Buffalo (SUNY)

Abstract Preview: Purpose: Deformable image registration (DIR) is critical in adaptive radiation therapy (ART). Existing DIR phantoms either simulate tumor shape or volume changes but lack comprehensive motion simulati...

A Dosimetric Investigation into the Potential of Aperture-Based Techniques to Improve the Clinical Outcomes of Single-Energy Proton Bragg Peak Flash Therapy for Ocular Cancers

Authors: Arpit M. Chhabra, J Isabelle Choi, Minglei Kang, Haibo Lin, Hang Qi, Charles B. Simone, Shouyi Wei, Irini Yacoub, Francis Yu, Xingyi Zhao, Ajay Zheng

Affiliation: New York Proton Center, 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:
Pencil beam scanning (PBS) proton therapy effectively treats ocular cancer by minimizing exit doses to normal tissues. However, challenges remain in sparing nearby organs-at-risk(OARs). Ul...

A Dosimetric Study of Misconnection to Unloaded Needles in Interstitial HDR Brachytherapy

Authors: Shifeng Chen, Mariana Guerrero, Brian A. Hrycushko, Kai Huang, Kai Jiang, Narottam Lamichhane, Paul M. Medin, Elizabeth Nichols

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland Medical Center

Abstract Preview: Purpose: Unloaded needle catheters, if not handled properly, pose a risk for channel misconnection in interstitial high dose rate (iHDR) brachytherapy. This study aims to investigate the dosimetric im...

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 Automated Selection of Dose-Volume Objectives to Improve Radiation-Induced Immune Suppression (RIIS)-Related Overall Survival (OS) Following Chemo-Radiotherapy

Authors: Gabriel Lucas Andrade de Sousa, Einsley-Marie Janowski, Cam Nguyen, Krishni Wijesooriya

Affiliation: Department of Radiation Oncology, University of Virginia, Department of Physics, University of Virginia

Abstract Preview: Purpose: Optimizing radiation therapy (RT) to spare the immune system may improve Overall Survival (OS) in cancer patients. This study develops a computational algorithm to identify optimal dose-volum...

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 Forward Planning with the Venezia HDR Applicator

Authors: Timothy J Allen, David A. Sterling

Affiliation: University of Minnesota Physicians, Department of Radiation Oncology, University of Minnesota, Minneapolis

Abstract Preview: Purpose: Treatment planning for the Venezia HDR brachytherapy applicator is often performed using inverse planning tools such as IPSA or HIPO. However, there are planners who are either unfamiliar wit...

A New Voxel-Based Similarity Approach for Assessing Contour Similarity and Clinical Dosimetric Effect

Authors: Shari Damast, Svetlana Kuznetsova, Christopher J. Tien

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

Abstract Preview: Purpose: Current contour similarity evaluation approaches (Dice Similarity Coefficient, Mean Distance to Agreement) are limited to geometric agreement without assessment of ultimate dosimetric impact....

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 Metric for Predicting Heart Dose Assessment in Left-Sided Breast Cancer Radiotherapy

Authors: Yufeng Cao, Arun Gopal, Kai Huang, Kai Wang

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

Abstract Preview: Purpose: The treatment of left-sided breast tumors poses significant concerns regarding the risk of radiation-induced damage to nearby organs, particularly the heart. In clinical practice, breath-hold...

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

Authors: Chuan He, Anh H. Le, Iris Z. Wang

Affiliation: Roswell Park Comprehensive Cancer Center, Cedars-Sinai

Abstract Preview: Purpose: To develop a non-measured and DVH-based (NMDB) IMRT QA framework integrating machine learning (ML) to classify lung SBRT VMAT plans prone to delivery errors
Methods: 560 Eclipse AcurosXB l...

A Novel Optimization Algorithm That Improves DVH Based Planning for Direction Modulated Brachytherapy Tandem Applicator.

Authors: Christopher L. Deufel, Suman Gautam, William Y. Song

Affiliation: Virginia Commonwealth University, Mayo Clinic

Abstract Preview: Purpose: Direction modulated brachytherapy creates anisotropic dose distribution from an isotropic source. This study aims to develop a truncated conditional value at risk optimization algorithm for D...

A Quantitative Analysis of Hypersight CBCT Image Quality Using a Phantom-Based Approach Under Different Scatter Conditions

Authors: Denisa R. Goia, M. Saiful Huq, Ronald John Lalonde, Fang Li, Noor Mail, Joseph Shields, Christopher Tyerech

Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Department of Radiation Oncology, University of Pennsylvania, UPMC

Abstract Preview: Purpose: HyperSight is a new platform for image-guided radiation therapy, offering advanced reconstruction algorithms, a large field-of-view, and rapid acquisition times. To validate the performance o...

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

Authors: Weigang Hu

Affiliation: Fudan University Shanghai Cancer Center

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

Advancing Cardiac Sparing with Upright Patient Geometry and Deep Learning

Authors: Shae Gans, Carri K. Glide-Hurst, Mark Pankuch, Chase Ruff, Niek Schreuder, Nicholas R. Summerfield, Yuhao Yan

Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Northwestern Medicine Proton Center, Northwestern Medicine Chicago Proton Center, Leo Cancer Care

Abstract Preview: Purpose: Novel upright patient positioners coupled with diagnostic-quality vertical CT at treatment isocenter introduce a significant opportunity for improved image-guided particle therapy. Treating p...

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

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

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

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

An Automated Solution to Staged Treatments for Arteriovenous Malformations in Gammaknife

Authors: Strahinja Stojadinovic, Robert Timmerman, Yulong Yan

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

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

An Automated Tool for the Categorization of a Clinical Database By Anatomic Region for Big Data Applications

Authors: Yasin Abdulkadir, Justin Hink, James M. Lamb, Jack Neylon

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

Abstract Preview: Purpose: Curation remains a significant barrier to the use of ‘big data’ radiotherapy planning databases of 100,000 patients or more. Anatomic site of treatment is an important stratification for almo...

An Efficient Deep Learning Model with Multi-Scale Integration for Automated Pancreas Segmentation on MR Images

Authors: Jingyun Chen, Yading Yuan

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

Abstract Preview: Purpose: To develop and evaluate the Scale-attention network (SANet) for automated pancreas segmentation on MR images.
Methods: To develop SANet, we extended the classic U-Net design with a dynamic...

An Evaluation of an SRS Quality Assurance System for Complex Patient Plans.

Authors: John Bennet, Indrin J. Chetty, Tai H. Dou

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

Abstract Preview: Purpose:
To investigate the effect of complexity of stereotactic radiosurgery (SRS) volumetric modulated arc therapy plans on gamma pass rates (GPR) using a novel high-resolution ion chamber array ...

An Optimal-Mass-Transport-Based Mathematical Model Applied to Brain DCE-MRI to Differentiate Brain Metastases Recurrence from Radiation Necrosis

Authors: Aditya P. Apte, Xinan Chen, Joseph O. Deasy, Ramesh Paudyal, Kyung Peck, Amita Shukla-Dave, Nathaniel Swinburne, Robert J. Young

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

Abstract Preview: Purpose: We apply our novel formulation of unbalanced-regularized-optimal-mass-transport (urOMT) theory to brain DCE-MRI data to quantify and visualize the behaviors of fluid flows in post-treatment f...

Artificial Intelligence (AI)-Driven Automatic Contour Quality Assurance (QA) with Uncertainty Quantification

Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, Ying Zhang, You Zhang

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

Abstract Preview: Purpose: Accurate delineation of treatment targets and organs-at-risk is crucial for radiotherapy. Despite significant progress in artificial intelligence (AI)-based automatic segmentation tools, effi...

Asymmetrical High Performance Brain Dedicated PET System: Design Optimization and Performance Evaluation

Authors: Yuemeng Feng, Hamid Sabet

Affiliation: Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: We propose a novel brain-dedicated PET system comprising elliptical cylinder with a neck cut-out, supplemented by front and back panels to improve sensitivity and line-of-response sampling. T...

Automated Treatment Planning for Stereotactic Recurrent Head and Neck Cancers Using Knowledge-Based Planning, Multicriteria Optimization, and Dosimetric Scorecards

Authors: Shane McCarthy, Damodar Pokhrel, William St. Clair, Eddy S Yang

Affiliation: University of Kentucky, Department of Radiation Medicine

Abstract Preview: Purpose: Demonstration of automated stereotactic treatment planning for recurrent head and neck (RHN) cancers using knowledge-based planning, multicriteria optimization (MCO), and dosimetric scorecard...

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...

Bridging the Gap of Radiotherapy Planning Quality between a High-Income Countrie to a Middle-Income Country By the Dosimetric Validation of a KBP Model Vs Junior, Senior Dosimetrists and MCO Planning

Authors: Eduardo Florian, Hiram Gay, Geoffrey D. Hugo, Otto Hurtarte, Milton Ixquiac, Erick Orlando Montenegro, Franky Eduardo Reyes, Francisco Javier Reynoso, Edgar Aparicio Ruiz, Baozhou Sun, Jacaranda Van Rheenen, Kevin Vega, Angel Velarde, Vicky de Falla

Affiliation: WashU Medicine, Liga Nacional Contra el Cancer, Liga Nacional Contra el Cancer/INCAN, Liga Nacional Contra el Cancer / INCAN, Liga Nacional Contra el Cancer and Universidad de San Carlos de Guatemala, Washington Univ. in St. Louis, Liga Nacional Contra el Cáncer / INCAN, Washington University in St. Louis, Varian, Baylor College of Medicine

Abstract Preview: Purpose:
IMRT has become the standard of care in high-income countries (HICs) due to reduced toxicity and improved treatment outcomes.
The purpose of this work is validating the KBP model shared...

Case-By-Case Analysis of Proton Spot Spacing and Dosimetric Variability in Proton Arc Lung Cancer Planning

Authors: Nebi Demez, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Umesh Rana, Nishan Shrestha, Somol Sunny

Affiliation: Florida Atlantic University, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: DynamicARC is an advanced proton therapy technique that leverages pencil beam scanning to deliver dose to the patient while the gantry rotates around the patient. This study investigates the ...

Characterization of HCC Tumor Response in 90Y-Radioembolization Clinical Trial RAPY90D Using Prospective Voxel Dosimetry

Authors: E Courtney Henry, Srinivas Cheenu Kappadath, Armeen Mahvash

Affiliation: UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Characterization of hepatocellular carcinoma (HCC) tumor responses for single-arm single-center prospective 90Y-radioembolization clinical trial (n=40) that used patient-specific voxel-dos...

Commission and Clinical Implementation of the 1st Step-and-Shoot Proton Arc Therapy for Head and Neck Cancer Patient Treatment

Authors: Xiaoda Cong, Rohan Deraniyagala, Xuanfeng Ding, Xiaoqiang Li, Jian Liang, Peilin Liu, Craig Stevens, Xiangkun Xu, Weili Zheng

Affiliation: Corewell Health William Beaumont University Hospital, Corewellhealth William Beaumont University Hospital, William Beaumont University Hospital, Corewellhealth William Beaumont Hospital, Department of Radiation Oncology, Corewell Health William Beaumont University Hospital

Abstract Preview: Purpose:
Commission a step-and-shoot arc therapy(SPArc-step&shoot) for treating head-neck cancer patients as a desired interim milestone toward full dynamic treatment.
Methods:
An in-house de...

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 ...

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

Authors: Jingyun Chen, Yading Yuan

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

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

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

Authors: Hao Peng, Yajun Yu

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

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

Contrast-Free Full Intracranial Vessel Geometry Estimation from MRI with Metric Learning-Based Inference

Authors: Zhaoyang Fan, Eric Nguyen, Dan Ruan, Jiayu Xiao

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

Abstract Preview: Purpose: MR vessel wall imaging (VWI) has been shown to be effective for evaluating intracranial atherosclerosis disease. However, VWI typically also requires an MR angiography (MRA) in the same imagi...

Contrastive Learning and Hybrid CNN-Transformer Model for Unpaired MR Image Synthesis in Acute Cerebral Infarction

Authors: Kota Hirose, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami

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

Abstract Preview: Purpose: Synthesizing medical images can address the lack of or unscanned medical images, reducing scanner time and costs. However, paired image scarcity remains a challenge for image synthesis. We pr...

Could Synthetic CTs Simulating Patient Anatomical Changes Help Improve the Robustness of Head-and-Neck Proton Plans?

Authors: Nrusingh C. Biswal, Matthew J Ferris, Michael J. MacFarlane, Jason K Molitoris, Byong Yong Yi, Mark J. Zakhary

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

Abstract Preview: Purpose: Proton head-and-neck treatment plans often struggle to maintain plan quality over the course of treatment due to tumor response, weight-loss, and setup variability. Plan robustness to these c...

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

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

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

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

Decision Support for Adaptive Vs Non-Adaptive SBRT for Left-Sided Adrenal Tumors

Authors: Robbie Beckert, Austen N. Curcuru, Farnoush Forghani, Yi Huang, Geoffrey D. Hugo, Hyun Kim, Eric Laugeman, Luke Christian Marut, Thomas R. Mazur, Allen Mo, Emily Sigmund

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

Abstract Preview: Purpose: Adaptive SBRT is resource intensive, requiring additional personnel for online planning, and should be reserved for cases where it is most beneficial. The purpose of this research is to creat...

Deep Learning-Based Auto Segmentation of Oars in Head and Neck Radiation Therapy

Authors: Laila A Gharzai, Bharat B Mittal, Poonam Yadav

Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern University Feinberg School of Medicine

Abstract Preview: Purpose: Multiple studies have shown the increasing role of deep learning in segmenting regions of interest. This work presents the feasibility of auto-segmenting the critical structures for head and ...

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

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

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

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

Deep Learning-Based 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 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 Validation of a Deep Learning-Based Auto-Segmentation Module for Vestibular Schwannoma

Authors: John Byun, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Xianghua Ye, Kangning Zhang

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

Abstract Preview: Purpose: Accurate and automated delineation of vestibular schwannoma (VS) volume is crucial for disease management, as both treatment approaches (stereotactic radiosurgery and invasive surgery) and mo...

Development of a Knowledge-Based Planning Model for Intensity Modulated Proton Therapy in Breast Cancer Treatment

Authors: Parker Anderson, Elizabeth L. Bossart, Jonathan Cyriac, Nesrin Dogan, Robert Kaderka, Yihang Xu

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

Abstract Preview: Purpose:
Knowledge-based planning (KBP) can enhance the treatment planning process in cancer radiotherapy (RT). By training a KBP model with high-quality treatment plans developed by experts, dose-...

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

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

Affiliation: Icahn School of Medicine at Mount Sinai

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

Development of a Template-Based Planning Workflow for Offline Adaptive Head and Neck Cancer Using Ethos 2.0

Authors: Kaelyn Becker, Xenia Ray

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

Abstract Preview: Purpose: Ethos 2.0 with HyperSight (Varian Medical Systems) imaging enables nearly fully automated offline adaptive radiotherapy including automated deformation of targets and recalculation on the Hou...

Direct Dose Verification in Liver SBRT Utilizing an Accumulative Daily CBCT Algorithm

Authors: Michael Buckstein, Yang Lei, Tian Liu, Charlotte Elizabeth Read, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose: Inter-fraction anatomic variations in liver SBRT can cause significant discrepancies between planned and delivered doses. We developed a CBCT-based accumulative algorithm to directly compare ...

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

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

Affiliation: University Hospitals Seidman Cancer Center

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

Discriminative Uncertainty Learning for Cancer Classification

Authors: Wei Wei, Yading Yuan

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

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

Dosimetric 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 Effect of Patient Positioning Errors in Dual-Isocenter VMAT for Bilateral Breast Cancer Treatment: A Quantitative Assessment

Authors: Awens Alphonse, Nebi Demez, Noufal Manthala Padannayil, Haley Park, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Nishan Shrestha, Somol Sunny

Affiliation: Florida Atlantic University, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: This study evaluates the dosimetric effects of patient positioning errors, including setup inaccuracies and yaw deviations, on dual-isocenter volumetric modulated arc therapy (VMAT) plans for...

Dosimetric Impact of Adaptive Radiotherapy with Ethos for Prostate Cancer: Localized Analysis of Bladder and Rectum across Planned, Non-Adaptive Accumulated, and Adapted Treatments

Authors: Huisi Ai, Scott Glaser, Yi Lao, Percy Lee, Sara N. Lim, An Liu, Bo Liu, Borna Maraghechi, Kun Qing, Chengyu Shi, William T. Watkins, Terence Williams, Qiuyun Xu, Jiahua Zhu

Affiliation: WashU Medicine, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, City of Hope Orange County, Department of Radiation Oncology, City of Hope National Medical Center, Department of Radiation Oncology, City of Hope Orange County, Department of Radiation Oncology, City of Hope Medical Center

Abstract Preview: Purpose: To employ a novel surface dose mapping approach for localized assessment of the dosimetric impact of Ethos adaptive radiotherapy (ART) for prostate cancer (PC).
Methods: This study include...

Dosimetry Impact of Overlapping Reconstruction of CT Simulation in Stereotactic Radiosurgery Planning

Authors: Matthew Stephen Andriotty, Chi Ma, Xiao Wang, Keying (Karen) Xu, Suhong Yu, Ning J. Yue, Yin Zhang

Affiliation: Brigham and Women's Hospital, Rutgers Cancer Institute of New Jersey

Abstract Preview: Purpose: To evaluate the effects of overlapping CT reconstruction on dosimetry calculation for LINAC-based SRS patients simulated on CT simulators from three different vendors.
Methods: CT simulati...

Early Evaluation Study for Stereotactic Adaptive Radiotherapy for Pancreatic Cancer with Ethos 2.0 System

Authors: Kenneth W. Gregg, Beatriz Guevara, Lauren E Henke, Rojano Kashani, Kyle O'Carroll, Gisele Castro Pereira, Christian Erik Petersen, Alex T. Price, Meiying Xing, Reine abou Zeidane

Affiliation: university hospital, University Hospitals Seidman Cancer Center

Abstract Preview: Purpose:
Experimental data have shown the inconsistent monitor unit and target coverage in Ethos 1.1. This can lead to inaccurate dose delivery, compromising patient safety and treatment outcomes. ...

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 Robustness in Proton Therapy through Online Adaptive Workflow: An in-Silico Study

Authors: Robbie Beckert, Weiren Liu, Thomas R. Mazur, Allen Mo, Stephanie Perkins, Hailei Zhang, Tianyu Zhao

Affiliation: Washington University in St. Louis School of Medicine, University of South Florida, WashU Medicine

Abstract Preview: Purpose: Online adaptation may mitigate uncertainties in proton therapy arising from interfractional anatomical changes. While robust optimization accounts for setup and range uncertainties during pla...

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 ...

Equivalent Uniform Dose and Duodenal Toxicity Correlation in Pancreatic Cancer Irradiation

Authors: Samira Dabaghmanesh, Beth A. Erickson, William Hall, Jason Hirshberg, An Tai

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Treatment plan evaluation for minimizing duodenal toxicity often involves multiple dose-volume constraints that vary based on fractionation. The Equivalent Uniform Dose (EUD) has emerged as a...

Evaluating Deep Learning Models for Accurate Segmentation of GTV and Oars in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer

Authors: Christopher G. Ainsley, Pradeep Bhetwal, Yingxuan Chen, Wookjin Choi, Vimal K. Desai, Karen E. Mooney, Adam Mueller, Hamidreza Nourzadeh, Yevgeniy Vinogradskiy, Maria Werner-Wasik

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: MR-guided adaptive radiotherapy (MRgART) has demonstrated improved outcomes for patients with pancreatic cancer. However, the time-consuming re-segmentation of targets and organs-at-risk (OAR...

Evaluating Supervised Learning Models for Binary Classification of Radiomic Data in Predicting Head and Neck Cancer Treatment Outcomes

Authors: Theodore Higgins Arsenault, Kyle O'Carroll, Christian Erik Petersen, Alex T. Price, Meiying Xing

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: To assess the performance of various supervised learning models’ ability to predict binary classification of radiomic data for head and neck (H&N) cancer treatment outcomes.
Methods: Using...

Evaluating the Impact of Reconstruction Algorithm on Wide-Angle Digital Breast Tomosynthesis System Optimization for Microcalcification Detection

Authors: Xiaoyu Duan, Xinyu Hu, Runqiu Li, Xiang Li

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

Abstract Preview: Purpose:
Accurate detection of small-sized microcalcifications (μCalcs) (< 500 µm) is critical for early breast cancer diagnosis, requiring optimal imaging systems and reconstruction algorithms. Ho...

Evaluating the Impact of Spot Spacing on Dosimetric Outcomes in Dynamic Arc Proton Therapy for Prostate SBRT

Authors: Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Umesh Rana, Hina Saeed, Nishan Shrestha, Somol Sunny

Affiliation: Florida Atlantic University, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: DynamicARC is a novel pencil beam scanning (PBS) proton therapy technique with the potential to provide more conformal dose distributions and reduce treatment time. This study investigates th...

Evaluation of Concomitant Imaging Dose in 4D-CBCT Guided Thoracic Radiotherapy

Authors: Yuchao Hu, Yajun Jia, Zhangmin Li, Yong Sang, Jianan Wu, Man Zhao

Affiliation: Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, Guangzhou Concord Cancer Hospital, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose: To evaluate the imaging dose of 4D-CBCT in patients treated with thoracic radiotherapy.
Methods: A model of the Elekta XVI imaging system was created in TOPAS software. Percentage depth do...

Evaluation of Dose-Rate Metrics in Intensity Modulated Proton Therapy for Prostate Cancer Treatments

Authors: Stella Flampouri, Edgar Gelover, William Andrew LePain, Roelf L. Slopsema, Alexander Stanforth, Mingyao Zhu

Affiliation: Emory Healthcare, Emory University

Abstract Preview: Purpose: Little consideration was given to the change in dose rate (DR) observed when moving to pencil beam scanning (PBS). This study reports on DR in clinical prostate PBS plans. While dose distribu...

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

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

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

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

Evaluation of Thoracic Direct Dose Calculation Using Truebeam Linac with Hypersight Imaging CBCT Solution

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Alex T. Price, Sagar Regmi, Atefeh Rezaei, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: To investigate the feasibility and accuracy of using a Hounsfield Unit(HU) calibrated cone-beam computed tomography(CBCT) for direct dose calculation in thoracic treatment settings. In combin...

Evaluation of Treatment Delivery Efficiency and Workflow Optimization in Prostate Stereotactic Body Radiation Therapy: A Comparative Study of C-Arm and O-Ring Linear Accelerators

Authors: Yijian Cao, Jenghwa Chang, Lyu Huang

Affiliation: Northwell, Hofstra University Medical Physics Program

Abstract Preview: Purpose: This study evaluates the treatment delivery efficiency and workflow of two advanced linear accelerator systems—Varian’s TrueBeam (C-arm) and Halcyon (O-ring)—for prostate Stereotactic Body Ra...

Evaluation of Treatment Planning Feasibility and Dosimetric Quality of the Reflexion™ X1 System for Complex Spinal Targets

Authors: Thomas I. Banks, Bin Cai, Andrew R. Godley, Yang Kyun Park, Hao Peng, Rameshwar Prasad, Chenyang Shen, Shunyu Yan, Haozhao Zhang

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

Abstract Preview: Purpose:
The RefleXion® X1 (RefleXion Medical, Inc., Hayward, CA) uniquely integrates KVCT and PET as on-board image guidance for radiotherapy. It has been installed and commissioned for clinical u...

Explainable Hybrid CNN-LLM Model to Guide Treatment Planning of Cervical Cancer High Dose Rate Brachytherapy

Authors: Adnan Jafar, Xun Jia, Michael B. Roumeliotis

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

Abstract Preview: Purpose: HDR brachytherapy (HDRBT) treatment planning is challenging due to the need for high-quality plans under time pressure, considering anatomy and applicator geometry. This study proposes an exp...

Feasibility Study of Ethos Artificial-Intelligence Online Adaptive Prostate SBRT

Authors: Miguel Albaladejo, Ana Corbalan, Aitor Ortega, Vicente Puchades, David Ramos, Alfredo Serna-Berna, Jonattan Suarez

Affiliation: Hospital General Universitario Santa Lucia

Abstract Preview: Purpose:
Prostate SBRT treatments are frequently delivered using standard VMAT IGRT technique. The aim of this study is to test the feasibility of Ethos Artificial Intelligence (AI) prostate SBRT b...

Finding the Best Match of 4D-CT Phases to Delineate Volumes for Bgrt

Authors: Resat Aydin, Joseph Barbiere, Brett Lewis, Roland Teboh

Affiliation: HUMC, Hackensack University Medical Center

Abstract Preview: Purpose:
Accurately compensating for respiratory-induced tumor motion is critical in BgRT, where precise delineation of volumes ensures effective dose delivery. We propose an integrated approach th...

Fine-Tuning AI-Based Generative Models for Small-Sample Glioma MRI Generation.

Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...

Foundation Models with Balanced Data Sampling Enhance Auto-Segmentation for Cardiac Substructures

Authors: Chloe Min Seo Choi, Nikhil Mankuzhy, Aneesh Rangnekar, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu

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

Abstract Preview: Purpose: Cardiac substructure irradiation predisposes patients for poor outcomes in thoracic radiation therapy. A deep learning model was developed to segment the cardiac substructures invariant to co...

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...

Generating Brain Pseudo-CT from PET-Only Images Using Deep Learning Method

Authors: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences, Tehran University of Medical Science

Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...

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

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

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

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

Geometrically Derived Density Compensation Function for 3D Non-Cartesian MRI Reconstruction

Authors: Oluyemi Bright Aboyewa, KyungPyo Hong, Daniel Kim

Affiliation: Department of Radiology, Northwestern University

Abstract Preview: Purpose: While non-Cartesian MRI is desirable for fast imaging with high spatial resolution and robustness to motion, it requires long post-processing times. Preconditioning with an adequate density c...

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-Fidelity Treatment Optimization for Online Adaptive Stereotactic Partial Breast Irradiation: Integrating Dose and Treatment Time Considerations

Authors: Drexell Hunter Boggs, Carlos E. Cardenas, Jingwei Duan, Joseph Harms, Joel A. Pogue, Richard A. Popple, Courtney Bosse Stanley, Dennis N. Stanley, Sean Xavier Sullivan, Natalie N. Viscariello

Affiliation: Washington University in St. Louis, The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: CBCT-guided online adaptive radiation therapy (OART) with Ethos for stereotactic accelerated partial breast irradiation (APBI) can mitigate inter-fraction variation, leading to dosimetric adv...

Human-like Deep Learning-Based Whole-Brain Radiotherapy Treatment Planning

Authors: Adnan Jafar, Xun Jia, An Qin

Affiliation: Johns Hopkins University

Abstract Preview: Purpose: 3D whole-brain radiotherapy (WBRT) is widely used due to its simplicity and effectiveness. While modern treatment planning systems, like RayStation, offer automated Field-in-Field planning, p...

Impact of Arc Number Variation on VMAT Lattice Radiotherapy Plans

Authors: Minbin Chen, Gang Liu, Manju Liu, Weiwei Sang, Pulin Sun, Mingyuan Ye, Fang-Fang Yin, Lihua Zhang, Haiming Zhu

Affiliation: Jiahui International Hospital, Radiation Oncology, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: This study aims to evaluate the effects of varying the number of arcs on treatment plans created using Volumetric Modulated Arc Therapy (VMAT) for Lattice radiotherapy (LRT).
Methods: Thre...

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-Vivo Image Quality of Head/Neck and CNS with an Advanced C-Arm Linac CBCT Solution

Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Christian Erik Petersen, Alex T. Price, Atefeh Rezaei, Runyon C. Woods

Affiliation: University Hospitals Seidman Cancer Center

Abstract Preview: Purpose: CBCT is subject to more artifacts due to increased photon scatter, especially in areas of increased tissue heterogeneities compared to fan-beam CTs (FBCTs). Improved imaging panels combined w...

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

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

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

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

Integrated Catheter Position and Dwell Time Optimization for Focal Dose Escalation in Prostate HDR Brachytherapy

Authors: Bryan Bednarz, John M. Floberg, Joseph B. Schulz, Jordan M. Slagowski

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

Abstract Preview: Purpose: Catheter placement for high-dose-rate brachytherapy (HDR BT) is clinician dependent and potentially suboptimal for delivering simultaneous integrated boosts to intraprostatic gross tumor volu...

Integrating Clinical Knowledge Via Llms for Precise Organ-at-Risk Segmentation in Pancreatic Cancer SBRT

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...

Integrating Knowledge-Based Planning with Ethos 2.0 for High-Quality Online Adaptive Lung SABR

Authors: Shahed Badiyan, Chien-Yi Liao, Mu-Han Lin, Dan Nguyen, Justin D. Visak, Hui Ju Wang, Brien Timothy Washington, Kenneth Westover, Yuanyuan Zhang

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

Abstract Preview: Purpose: Knowledge-based planning (KBP) plays a crucial role in improving treatment plans by leveraging previous clinical data to guide new cases. KBP is applied to the Ethos 2.0 Intelligent Optimizat...

Integrating Large Kernel Attention Mechanism into Deep Learning Model for Automatic and Auccrate Segmentation of Gross Tumor Volume in Lung Cancer Patients

Authors: Xuezhen Feng, Li-Sheng Geng, Haoze Li, Xi Liu, Tianyu Xiong, Ruijie Yang

Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, School of Physics, Beihang University, School of Nuclear Science and Technology, University of South China, Department of Radiation Oncology, Peking University Third Hospital

Abstract Preview: Purpose: This study aimed to develop a deep learning-based algorithm for automatically delineate gross tumor volume (GTV) for lung cancer patients, alleviating the workload of radiologists and improvi...

Introduce a Novel Spot-Scanning Proton Arc(SPArc) Optimization Algorithm for Single Energy Extraction(SEE) Synchrotron-Accelerator-Based Proton Therapy System (PTS)

Authors: Xiaoda Cong, Xuanfeng Ding, Gang Liu, Peilin Liu, Jiajian Shen

Affiliation: Department of Radiation Oncology, Mayo Clinic, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Corewellhealth William Beaumont University Hospital

Abstract Preview: Purpose: This study aims to develop the first SPArc optimization algorithm based on the Dynamic Programming (SPArc-DP), to improve the treatment delivery efficiency for synchrotron-accelerator-based P...

Introducing an Equieffective 3D Dose Visualization Tool for Reirradiation Special Medical Physics Consults

Authors: James Irrer, Charles K. Matrosic, Martha M. Matuszak, Charles S. Mayo, Kelly C. Paradis, Joann I. Prisciandaro, Benjamin S. Rosen, John Yao, Claire Zhang

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

Abstract Preview: Purpose: To introduce an in-house developed tool, BioDoseUI, designed to calculate and visualize 3D equieffective dose (EQD2Gy) for treatment planning systems (TPS) without such capabilities, to facil...

Investigating Pitch Factor on Plan Quality in Patients Treated with Hippocampal Avoidance Whole Brain Radiotherapy Using Volo Ultra-Optimized Helical Tomotherapy Plans

Authors: Awens Alphonse, Nebi Demez, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Gagandeep Saini, Nishan Shrestha, Somol Sunny

Affiliation: Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: This study examined the impact of varying the pitch factor in hippocampal-avoidance whole-brain (HP-WB) radiotherapy treatments, utilizing the newly introduced VOLO Ultra optimization for Hel...

Investigating the Use of a DWI Phantom for Routine QA of an MR-Linac at Room Temperature

Authors: Nicholas Carlson, Joel J. St-Aubin

Affiliation: University of Iowa Hospitals and Clinics, University of Iowa

Abstract Preview: Purpose: To establish baselines metrics and determine longitudinal accuracy and reproducibility of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) values for a 1.5T Elekta Un...

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-Based Three-Dimensional Dose Prediction for High Dose Rate Prostate Brachytherapy

Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi

Affiliation: UC San Diego, Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...

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...

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 ...

Maximizing Integrated Treatment Planning Tools to Increase Automation for X-Ray-Based Adaptive Lung Sabr

Authors: Shahed Badiyan, Chien-Yi Liao, Mu-Han Lin, David D.M. Parsons, Justin D. Visak, Brien Timothy Washington, Kenneth Westover, Yuanyuan Zhang

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

Abstract Preview: Purpose: Adaptive radiotherapy (ART) programs are resource-intensive due to their technical complexities, requiring highly skilled planners. Leveraging integrated automated treatment planning system (...

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

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

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

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

Multi-Institutional Analysis of CT Dose Index Variability and Radiomics Features

Authors: Caroline Chung, Michael Knopp, Stephen F. Kry, Hunter S. Mehrens, John Rong

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

Abstract Preview: Purpose: To evaluate the variability of CT dose index (CTDIvol) and radiomics features across a large cohort of radiotherapy simulation CT scans from multiple institutions.
Methods: Three IROC phan...

Multi-Organ Segmentation of Pelvic Cone-Beam Computed Tomography (CBCT) with Transformer Models to Enhance Adaptive Radiotherapy for Prostate Cancer

Authors: Ming Chao, Thomas Chum, Tenzin Kunkyab, Yang Lei, Tian Liu, Richard G Stock, Hasan Wazir, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
This study aims to develop effective strategies for multi-organ segmentation of pelvic cone-beam computed tomography (CBCT) images based on transformer models to facilitate adaptive radiat...

Multi-Vendor Validation of a Deep Learning-Based Synthetic CT Generation Model for MR-Only Radiotherapy Planning in the Pelvis

Authors: Gregory Bolard, Rabten Datsang, Sarah Ghandour, Timo Kiljunen, Pauliina Paavilainen, Sami Suilamo, Katlin Tiigi

Affiliation: Turku University Hospital, Virginia Commonwealth University, MVision AI, North Estonia Medical Centre, Docrates Cancer Center, Hopital Riviera-Chablais

Abstract Preview: Purpose: To verify the performance of a vendor-neutral deep learning model for synthetic CT generation from T2-weighted and balanced steady-state MR sequences to support both MR-only simulation and MR...

Multimodal Framework for Predicting Radiation-Induced Severe Acute Esophagitis in Esophageal Cancer

Authors: Yeona Cho, Chloe Min Seo Choi, Joseph O. Deasy, Jue Jiang, Jihun Kim, Jin Sung Kim, Nikhil Mankuzhy, Aneesh Rangnekar, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu

Affiliation: University of Freibrug, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Gangnam Severance Hospital, Yonsei University College of Medicine, Memorial Sloan Kettering Cancer Center, Yonsei University

Abstract Preview: Purpose: We hypothesized that combining clinical, imaging, and radiotherapy dose-distribution features could increase predictive model accuracy in radiation-induced severe acute esophagitis (SAE) in e...

Novel Methods to Select Patients for Functional Avoidance Radiotherapy

Authors: Vikas Aragam, Edward Castillo, Richard Castillo, Yingxuan Chen, Yevgeniy Vinogradskiy, Lydia J. Wilson

Affiliation: Thomas Jefferson University, Emory University, University of Texas at Austin

Abstract Preview: Purpose: 4DCT-based ventilation imaging (4DCT-ventilation) has been innovatively applied in radiotherapy treatment planning to minimize doses to functional portions of the lung, known as functional av...

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

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

Affiliation: Virginia Commonwealth University

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

Optimizing 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...

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...

Population Level Robustness Evaluation for Establishment of Benchmarks for Optimized Plans for Prostate Proton Therapy

Authors: Laura Buchanan, Samantha G. Hedrick, Stephen L. Mahan, Isabella Pfeiffer, Chester R. Ramsey, Taylor Ransom

Affiliation: Thompson Proton Center, University of Tennessee

Abstract Preview: Purpose: Proton pencil beam scanning can reduce normal tissue dose but is highly sensitive to setup, anatomical changes, and range variations. These uncertainties may compromise target coverage and or...

Predicting Proton Therapy Dose Delivery Accuracy: A Machine Learning Approach Using Iroc’s Proton Phantom Data

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

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

Abstract Preview: Purpose: To develop a machine learning model for predicting dose delivery accuracy and identifying its key factors in IROC’s proton phantom program.
Methods: IROC’s proton QA program has six proton...

Prediction of Head and Neck Cancer Using Artificial Neural Network through Basic Health Data

Authors: Abdullah Hidayat, Wazir Muhammad

Affiliation: Florida Atlantic University

Abstract Preview: Purpose: This study aims to predict Head and Neck cancer using an artificial neural network (ANN) through readily available basic health data. The goal is to uncover hidden patterns and predictors in ...

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...

Prostate Dosimetric Comparison between Cyberknife and Radixact Modalities Using Precision and Raystation Planning Systems

Authors: Mireille Conrad, Cédric De Marco, Marie Fargier-Voiron, Maud Jaccard, Oscar Matzinger, Nicolas Joel Lionel Perichon

Affiliation: Clinique De Genolier

Abstract Preview: Purpose: The Accuray Synchrony real-time motion fiducial tracking solution allows for prostate stereotactic treatment on both Cyberknife and Radixact machines. In our radiotherapy department, two solu...

Proton Vs Photon Therapy for Stereotactic Arrhythmia Radioablation of Ventricular Tachycardia

Authors: Chih-Wei Chang, Kristin A Higgins, Xiaojun Jiang, Pretesh Patel, Justin R. Roper, Keyur Shah, Sibo Tian, Zhen Tian, Yinan Wang, Xiaofeng Yang, Jun Zhou

Affiliation: Department of Radiation Oncology, City of Hope Cancer Center Atlanta, Emory University, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Ventricular tachycardia (VT) is a life-threatening arrhythmia commonly treated with catheter ablation; however, some cases remain refractory to conventional treatment. Stereotactic arrhythmia...

Quantitative 3D Surface Mapping of Cherenkov Images for Real-Time Beam Deviation Detection in Radiotherapy

Authors: Petr Bruza, Alexander Geiersbach, David J. Gladstone

Affiliation: Thayer School of Engineering, Dartmouth College

Abstract Preview: Purpose: Cherenkov images are two-dimensional projections of the surface light emissions, and lack spatial information about the radiotherapy beam delivery. We implement the first fusion of Cherenkov ...

Radiobiological Calculations of Daily Doses Using Pseudo CT (pCT)

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

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

Abstract Preview: Purpose:
To calculate radiobiological metrics of daily dose delivered for head and neck (HN) patients using the daily cone beam CT (CBCT) to generate a pseudo CT (pCT). Moreover, this work compares...

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

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

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

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

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

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

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

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

Reducing Distal-Edge Toxicity in Breast Proton Therapy Via LETd and Track-End Optimization

Authors: Matthew Case, Richard Castillo, Sunil Dutta, Edgar Gelover, Katja M. Langen, Alexander Stanforth, Mingyao Zhu

Affiliation: Emory University

Abstract Preview: Purpose: To evaluate the application of LETd and track-end (TE) objective functions during the optimization of breast proton therapy plans to decrease the risk of lung toxicity and rib fractures.
M...

Retrospective Study Using Avi Planner for Head and Neck Cancer Cases: Our Experience at Nsia-Luth Cancer Center, South - West Nigeria

Authors: Adebayo Abe, Samuel Olaolu Adeneye, Eben Aje, Bidemi I. Akinlade, Inioluwa Damilola Ariyo, Lilian Ekpo, Muhammad Habeebu, Adedayo O. Joseph, Charles S. Mayo, Noah Ndianaobong, Ikechi S Ozoemelam, Margaret Dideolu Taiwo, Godwin Uwagba

Affiliation: University of Michigan, University of Ibadan, University of Lagos, Missouri University of Science and Technology, NSIA-LUTH Cancer Center, University of Lagos, NSIA-LUTH Cancer Centre, NSIA-LUTH Cancer Center

Abstract Preview: Purpose:
Head and neck cancers (HNC) present significant challenges in radiotherapy due to complex anatomy and the proximity to critical organs at risk (OARs). These challenges are compounded in na...

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...

Significantly Limiting Posterior Gantry Angles in Prostate VMAT Optimization: A Dosimetric Assessment of Plan Quality

Authors: Yijian Cao, Sean T Grace, Marissa Joyce Vaccarelli

Affiliation: Northwell

Abstract Preview: Purpose:
This study investigates the dosimetric efficacy of significantly limiting gantry angles in prostate radiation therapy to as a promising strategy to maintain plan quality while enhancing ma...

Simulating Realistic Digital Phantoms for Virtual Clinical Trials in Radiology and Radiation Oncology Using a Deep-Learning Based Conditional Denoising Diffusion Probabilistic Model (c-DDPM)

Authors: Matthew Brown, Yushi Chang, Jinhyuk Choi, William Silva Mendes, Lei Ren, Aman Sangal, William Paul Segars, Phuoc Tran, Hualiang Zhong

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Digital phantoms like XCAT are essential for imaging and treatment optimization in radiology and radiation oncology. However, the lack of realistic textures (HU distribution) in XCAT limits i...

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

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

Affiliation: Mercy Hospital Springfield

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

Stereotactic Body Radiosurgery for Refractory Ventricular Tachycardia: Presenting Efficient Clinic Workflow, Dosimetric Analysis and Patients Reported Clinical Results

Authors: Karam Ayoub, Aaron B Hesselson, Ronald C McGarry, Joshua Misa, Damodar Pokhrel

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Department of Cardiology

Abstract Preview: Purpose: Noninvasive stereotactic body radiosurgery (SBRS) is emerging treatment option for advanced heart failure patients with refractory-ventricular tachycardia (rVT) who experienced recurrent impl...

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

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

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

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

Text-Conditioned Latent Diffusion Model for Synthesis of Contrast-Enhanced CT from Non-Contrast CT

Authors: Yizheng Chen, Michael Gensheimer, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Automatically translating non-contrast to contrast-enhanced computed tomography (CT) images is critical for improving clinical workflow, reducing heathcare cost, minimizing radiation exposure...

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) ...

The Impact of Intempo Imaging on Cyberknife Prostate Plans

Authors: Lei Fu, Eric Gressen, Yingcui Jia, Shari Rudoler, Yevgeniy Vinogradskiy, Qianyi Xu

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: InTempo imaging in the Accuray CyberKnife System improves the ability to track/correct target motion during treatment. However, no studies have provided information on the impact of InTempo I...

To Establish Local Diagnostic Reference Levels (DRLs) for Head and Neck Computed Tomography (CT) Exams in Abuja, Nigeria, and to Investigate the Performance of Brain Metastasis (BM) and Brain Lesion (BL) Segmentation Techniques Using U-Net Models.

Authors: Nuraddeen Nasiru Garba, Kalpana M Kanal, Abdullahi Mohammed, Rabiu Nasiru, Muhammad SHAFIU Shehu, Daniel Vergara, Joseph Everett Wishart

Affiliation: AHMADU BELLO UNIVERSITY, ZARIA, University of Washington

Abstract Preview: Purpose: To establish local Diagnostic Reference Levels (DRLs) for head and neck computed tomography (CT) exams in Abuja, Nigeria, and to investigate the performance of brain metastasis (BM) and brain...

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...

When Protons Are Unavailable: Study of High Quality Knowledge-Based Planning Models for the Treatment of Unilateral Head and Neck Patients

Authors: Kenny Guida, Daniel Johnson, Wesley Tucker

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

Abstract Preview: Purpose: Intensity modulated proton therapy (IMPT) has emerged as a standard of care for unilateral head and neck (HN) cancers due to superior OAR sparing. With the increase of proton centers national...

Whole Heart Sparing Ethos Adaptive Radiotherapy for Lung Cancer

Authors: Ibrahim Aref, David Bergman, Justine M. Cunningham, Payton Dolan, Aharon Feldman, Yimei Huang, Joshua P. Kim, Brett M. Miller, Emily Moats, Benjamin Movsas, Kundan S Thind

Affiliation: Henry Ford Health

Abstract Preview: Purpose: Cardiac radiation dose is directly associated with adverse cardiac events which are predictive of mortality in lung cancer patients. In fractionated lung radiotherapy, studies have shown a hi...