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Results for "specific adaptive": 44 found

4D CBCT Dynamic Images Recovery Using a 4D Neural Network

Authors: Ziheng Deng, Yao Hao, Runping Hou, Deshan Yang, Jun Zhao, Yufu Zhou

Affiliation: Department of Radiation Oncology, Duke University, School of Biomedical Engineering, Shanghai Jiao Tong University, Washington University School of Medicine, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: 4D CBCT has been developed to provide dynamic images for image-guided radiation therapy. However, as projection data are sorted into sparse and clustered phase-specific bins, 4D CBCT images a...

A Deep Learning Approach to the Prediction of Gamma Passing Rates in VMAT Radiotherapy Plans for Adaptive Treatment.

Authors: Jenghwa Chang, Kuan Huang, Lyu Huang, Jason Lima, Jian Liu, Farzin Motamedi

Affiliation: Northwell, Department of Computer Science and Technology, Kean University, Physics and Astronomy, Hofstra University, Hofstra University Medical Physics Program

Abstract Preview: Title: A Deep Learning Approach to the Prediction of Gamma Passing Rates in VMAT Radiotherapy Plans for Adaptive Treatment.
Purpose: This study aims to develop a deep learning algorithm to predict ...

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

Authors: Suman Gautam, Tianjun Ma, William Song

Affiliation: Virginia Commonwealth University

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

A Dynamic Reconstruction and Motion Estimation Framework for Cardiorespiratory Motion-Resolved Real-Time Volumetric MR Imaging (DREME-MR)

Authors: Jie Deng, 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: Based on a 3D pre-treatment MRI scan, we developed DREME-MR to jointly reconstruct the reference patient anatomy and a data-driven, patient-specific cardiorespiratory motion model. Via a moti...

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

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

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

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

An Adaptive Radiotherapy Strategy Study Based on Segmented Synthesis and Deformational Registration

Authors: Jie Hu, Zhengdong Jiang, Nan Li, Tie Lv, Yuqing Xia, Shouping Xu, Gaolong Zhang, Wei Zhao, Changyou Zhong

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Radiotherapy Department of Meizhou People’s Hospital (Huangtang Hospital), UT Health San Antonio, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology

Abstract Preview: Purpose: Patients usually undergo cone-beam computed tomography (CBCT) scans which are used for patient set-up before radiotherapy. However, the low image quality of CBCT hinders its use in adaptive r...

An Automated Notification System for Identifying Patients Eligible for Biology-Guided Radiotherapy

Authors: Shahed Badiyan, Bin Cai, Tu Dan, Michael Dohopolski, Steve B. Jiang, Deepkumar Mistry, Arnold Pompos, Robert Timmerman, Jing Wang

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, University of Texas Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Biology-guided radiotherapy (BGRT) offers significant potential for personalized and adaptive cancer treatment, with clinically available systems such as SCINTIX from Reflexion now being intr...

Assessment of Automated Planning Templates for Genitourinary and Gastrointestinal Disease Sites for Online MR-Guided Adaptive Radiotherapy

Authors: Shahed Badiyan, Tsuicheng D. Chiu, Viktor M. Iakovenko, Steve Jiang, Christopher Kabat, Mu-Han Lin, Roberto Pellegrini, Arnold Pompos, Edoardo Salmeri, David Sher, Sruthi Sivabhaskar, Justin D. Visak

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, Global Clinical Science, Elekta AB, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Adaptive treatment planning requires robust strategies to enable streamlined on-couch processes, creating a significant barrier for planners transitioning from conventional to adaptive planni...

Automatic Specific Absorption Rate (SAR) Prediction for Hyperthermia Treatment Planning (HTP) Using Deep Learning Method

Authors: Yankun Lang, Lei Ren, Dario B. Rodrigues

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

Abstract Preview: Purpose:
HTP of microwave (MW) phased-array systems determine MW antenna settings to maximize energy absorption (SAR in W/kg) in tumor. Conventional HTP algorithms calculate SAR based on electromag...

BEST IN PHYSICS MULTI-DISCIPLINARY: Quantitative MRI Oximetry: Combining EPR and OE-MRI for Volumetric Mapping of Hypoxia in Tumors

Authors: Victor B. Kassey, Maciej M. Kmiec, Periannan Kuppusamy, Sergey V. Petryakov, Conner Ubert

Affiliation: Dartmouth College

Abstract Preview: Purpose: Tumor hypoxia—a state of reduced oxygen supply—is well known to affect treatment response, particularly in radiotherapy and chemotherapy. Oxygen-enhanced magnetic resonance imaging (OE-MRI) u...

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

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

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

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

Characterizing the Stability of Upright CT for Proton Therapy

Authors: Brian Burger, Carri K. Glide-Hurst, John W. Hayes, Carson Hoffman, Minglei Kang, Jessica R. Miller, Jordan M. Slagowski, Yuhao Yan

Affiliation: Department of Human Oncology, University of Wisconsin-Madison, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Leo Cancer Care

Abstract Preview: Purpose: The combination of upright CT and patient positioner for particle therapy present tremendous potential for high precision IGRT and online adaptive radiation therapy (ART), where reliable CT p...

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

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

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

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

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

Authors: Derek Tang, Susu Yan

Affiliation: Massachusetts General Hospital

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

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 Aided Oropharyngeal Cancer Autoplanning

Authors: Mark Bowers, Gabriel Carrizo, Jimmy Caudell, Vladimir Feygelman, Kevin Greco, Christian Hahn, Jihye Koo, Kujtim Latifi, Fredrik Lofman, Jacopo Parvizi, Muqeem Qayyum, Caleb Sawyer

Affiliation: RaySearch Laboratories, Moffitt Cancer Center

Abstract Preview: Purpose: Head and neck (H&N) radiotherapy planning is complex, with multiple competing objectives. We endeavored to improve efficiency of planning by developing a deep learning (DL) model trained to p...

Detector Physics-Incorporated Diffusion Denoising Models for Digital Breast Tomosynthesis with Dual-Layer Flat Panel Detectors

Authors: Alexander Bookbinder, Matthew Tivnan, Xiangyi Wu, Wei Zhao

Affiliation: Stony Brook Medicine, Massachusetts General Hospital

Abstract Preview: Purpose: To investigate and benchmark a system-adaptive diffusion-based digital breast tomosynthesis (DBT) denoising model for a direct-indirect dual-layer flat panel detector (DI-DLFPD) with a k-edge...

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...

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...

Evaluating Necessity of Patient-Specific Deep Learning-Based Auto-Segmentation for Improved Adaptation for Abdominal Tumors

Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: In an effort to improve contouring accuracy for abdominal MR guided online adaptive radiotherapy (MRgOART), patient-specific deep learning-based auto-segmentation (PS-DLAS) has been proposed....

Evaluation of Fast Monte Carlo Secondary Dose Calculation for Intensity Modulated Proton Therapy in Heterogeneous Materials

Authors: Ergun E. Ahunbay, Abdul Kareem Parchur, Eric S. Paulson, Ilaria Rinaldi, Angelo Schiavi, Li Zhao

Affiliation: Sapienza University of Rome, Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Secondary dose calculations (SDC) facilitate patient-specific quality assurance for online adaptive intensity-modulated proton therapy (IMPT). However, there is currently a lack of commercial...

Evaluation of an Adaptive Denoising Diffusion Probabilistic Model (DDPM) for Fast MRI in Radiotherapy Planning of Pediatric Brain Tumors

Authors: Chia-Ho Hua, Jirapat Likitlersuang, Jinsoo Uh

Affiliation: St. Jude Children's Research Hospital

Abstract Preview: Purpose: AI-based fast MRI, which reconstructs images from undersampled k-space data, has not yet been tailored for RT planning. This study aims to evaluate the fast MRI performance of our recently pr...

Frequent MR Imaging of Fibrosis during Radiation Therapy: Implications for Adaptive RT in Gynecologic Cancer

Authors: Himanshu Bhat, Bruce Lewis Daniel, Junghoon Lee, Michael B. Roumeliotis, Ehud J. Schmidt, Ravi Seethamraju, Khadija Sheikh, Pan Su, Akila N. Viswanathan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Siemens Medical Solutions USA Inc., Stanford Medical School, Department of Cardiology, Johns Hopkins University

Abstract Preview: Purpose: To perform frequent MRI during EBRT and brachytherapy (BT) to evaluate RT-induced fibrosis and remnant tumor changes, identified using ultrashort echo-time (UTE) and multiparametric (mpMRI), ...

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...

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...

Implementation of a Virtual Quality Assurance System Using Raystation for Online MR-Linac Adaptive Radiotherapy

Authors: Min-Sig Hwang, Danny K. Lee, Daniel C. Pavord, Kyung Lim Yun

Affiliation: Allegheny Health Network

Abstract Preview: Purpose: Ensuring the quality of treatment plans through patient-specific pre-treatment quality assurance (QA) is essential. However, the use of physical phantom-based QA devices is not feasible for o...

Improving Segmentation Precision in Prostate Cancer Adaptive Radiotherapy with the Intentional Deep Overfit Learning (IDOL) Approach

Authors: Seungryong Cho, Donghyeok Choi, Joonil Hwang, Byung-Hee Kang, Jin Sung Kim, Eungman Lee, Younghee Park

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

Abstract Preview: Purpose: Radiation therapy (RT) is critical for cancer treatment, but changes in tumor size and shape during therapy challenge precise dose delivery. Adaptive radiation therapy (ART) addresses these v...

Initial Phantom Studies Towards Implementation of Sequential Dual Energy CBCT on an Adaptive Radiotherapy Linac Platform

Authors: James M. Balter, Alexander Moncion, Ikechi S Ozoemelam

Affiliation: University of Michigan

Abstract Preview: Purpose: Sequential dual-energy cone beam computed tomography (DE-CBCT) integrated with an online adaptive platform could potentially improve soft tissue visualization for more accurate anatomical del...

Investigation of Metallic Artefact Reduction Capabilities of Hypersight Enabled Platforms

Authors: Harald Keller, Iymad Mansour, Jeff D. Winter

Affiliation: Princess Margaret Cancer Centre

Abstract Preview: Purpose: The growing number of adaptive therapy applications is motivating image segmentation and direct dose calculation on CBCT. The purpose of this investigation is to evaluate the recently release...

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...

Modulation of the Tumor Microenvironment By Radiation Therapy to Enhance Immune Activity in Glioblastoma

Authors: MacKenzie Rachelle Coon, Justin Geise, Judith Noemi Rivera, Matthew L. Scarpelli, Jessica Leigh Veenstra, Chandler Zaugg

Affiliation: Purdue University, Indiana University

Abstract Preview: Purpose: Glioblastoma (GBM) is among the most aggressive and treatment-resistant cancers due to its immunosuppressive tumor microenvironment. Immunotherapy holds promise for GBM treatment, but its eff...

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...

Optimizing Quality Assurance CT Frequency and Setup Uncertainty in Brain Proton Therapy Patients for Reduced Normal Tissue Dose

Authors: Rachel B. Ger, Heng Li, Anh Tran

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

Abstract Preview: Purpose: Proton therapy patients undergo quality assurance CT scans (QACTs) during treatment to verify dosimetric accuracy and utilize robustness scenarios for setup and range uncertainties. For intra...

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...

Proactive Quality Assurance for Adaptive Radiotherapy: Real-Time Mlc Verification with Myqa SRS

Authors: James L. Giltz, Michael J. Merrick

Affiliation: Alyzen Medical Physics, University of Kentucky

Abstract Preview: Purpose: To evaluate the capability of MyQA SRS in performing high-resolution machine QA to verify multileaf collimator (MLC) behavior and integrity for adaptive radiotherapy (ART). This study demonst...

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

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

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

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

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...

Tailor-TS System: Tailored Tumor Segmentation System with Facility-Specific Semi-Supervised Learning

Authors: Gong Vincent Hao, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami, Ikuno Nishibuchi, Peiying Colleen Ruan, Daguang Xu, Dong Yang

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

Abstract Preview: Purpose:
Accurate tumor segmentation in head and neck cancer is critical for effective treatment planning, but variability in practices across medical facilities poses challenges for standardizatio...

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

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

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

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

Universal Anatomical Mapping and Patient-Specific Prior Implicit Neural Representation for MRI Super-Resolution

Authors: Jie Deng, Yunxiang Li, 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: Magnetic Resonance Imaging (MRI) has exceptional soft tissue contrast and an essential role in radiotherapy. The introduction of clinical MR-LINACs has enabled adaptive radiotherapy (ART) usi...

Validating a Pre-Existing CT HU-to-Mass Density Curve for Direct Dose Calculation on High Quality Cbcts

Authors: Casey E. Bojechko, Tricia Chinnery, Grace Gwe-Ya Kim, Xenia Ray

Affiliation: University of California San Diego

Abstract Preview: Purpose: To evaluate the use of a calibration curve generated from the CT simulator for direct dose calculation on cone beam computed tomography (CBCT) images taken with the on-board imaging system. T...

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

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

Affiliation: St. Jude Children's Research Hospital

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