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Results for "structure errors": 39 found

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

Authors: Rex A. Cardan, Richard A. Popple

Affiliation: University of Alabama at Birmingham

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

A Dual Energy CT-Guided Intelligent Radiation Therapy Platform

Authors: Jiayi Chen, Manju Liu, Ning Wen, Haoran Zhang, Yibin Zhang

Affiliation: Department of Radiation Oncology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines...

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

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

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

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

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

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

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

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

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

Authors: Weigang Hu

Affiliation: Fudan University Shanghai Cancer Center

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

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

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

Affiliation: Johns Hopkins University, University of Florida

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

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

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

Affiliation: University of Michigan

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

An Agglomerative Clustering-Based Program for Optimizing Multiple-Target SRS Treatment Planning

Authors: Josephine Chen, CheukKai Becket Hui, Yildirim D. Mutaf

Affiliation: Kaiser Permanente

Abstract Preview: Purpose:
To demonstrate the effectiveness of a target clustering program in generating cluster configurations and isocenter placements for multiple brain lesions in SRS treatment planning, with the...

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

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

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

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

Automatic Contour Quality Assurance Using Deep-Learning Based Contours

Authors: Laurence Edward Court, Raphael Douglas, David Fuentes, Anuja Jhingran, Barbara Marquez, Raymond Mumme, Christine Peterson, Julianne M. Pollard-Larkin, Surendra Prajapati, Dong Joo Rhee, Thomas J. Whitaker

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

Abstract Preview: Purpose: Safe deployment of auto-contouring models requires the inclusion of automated quality assurance (QA). One approach is to use an independent auto-contouring model and compare the contours geom...

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

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

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

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

BEST IN PHYSICS MULTI-DISCIPLINARY: Foundation Model-Empowered Unsupervised 3D Deformable Medical Image Registration

Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang

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

Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...

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

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

Affiliation: Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center

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

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

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

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

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

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

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

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

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

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 ...

Development and Validation of a Scalable Radiomics Pipeline for Lung Cancer Research Using Clinical and Public Datasets

Authors: Pradeep Bhetwal, Yingxuan Chen, Wookjin Choi, Michael Dichmann, Adam Dicker, Rupesh Ghimire, Yevgeniy Vinogradskiy, Maria Werner-Wasik

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Radiomics has emerged as a powerful tool in medical research. However, the lack of standardized and reproducible pipelines limits its clinical adoption. This study developed a robust and scal...

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

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

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

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

Development of a Quantitative Surface Mapping Analysis Framework Involving a Robust Mask Removal Algorithm for Improved Objective Patient Setup Assessment in Head and Neck Intensity Modulated Proton Therapy

Authors: Grant Evans, Maxwell Arthur Kassel, Charles Shang, Michael H. Shang, Stephen Shang, Timothy R Williams

Affiliation: South Florida Proton Therapy Institute, SFPRF, Department of Radiation Medicine, MedStar Georgetown University Hospital

Abstract Preview: Purpose:
Daily image guidance for head and neck intensity-modulated proton therapy (IMPT) presents significant challenges due to large target volumes and anatomical changes. Geometric deviations al...

Geant4-DNA Simulation of Human Breast Cancer Cells Line MCF7 Irradiation with 213bi As Targeted Radionuclides

Authors: Hamid Abdollahi Nasehabad, Mehrangiz Amiri, Mohammad Reza Deevband, Faraz Kalantari, Milad Peer-Firozjaei, Ali Shabestani Monfared, Ehsan Tajikmansoury

Affiliation: Biomedical Engineering and Medical Physics Department, School of Medicine, Shahid Beheshti University of Medical Sciences, Department of Radiology, University of British Columbia, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiobiology and Medical Physics, Babol University of Medical Sciences, 1. Department of Radiobiology and Medical Physics, Babol University of Medical Sciences, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine

Abstract Preview: Purpose:
Targeted radionuclide therapy (TRNT) with 213Bi- labeled radiopharmaceuticals is a promising approach in targeted alpha and beta therapy for cancer. This study aims to assess double-strand...

Improving Head and Neck Radiotherapy Accuracy through Real-Time Volumetric Imaging Using a Kalman Filter Approach

Authors: Youssef Ben Bouchta, Chen Cheng, Owen Thomas Dillon, Mark Gardner, Paul J. Keall, Purnima Sundaresan

Affiliation: Radiation Oncology Network, Western Sydney Local Health District, Image X Institute, Faculty of Medicine and Health, The University of Sydney

Abstract Preview: Purpose: There are three clinical motivations for real time IGRT in head and neck cancer radiation therapy: (1)50% of patients experience anxiety from the patient mask (2)patient motion still occurs d...

Latent Diffusion Model-Driven Semi-Supervised Semantic Segmentation of Cell Nuclei

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

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

Abstract Preview: Purpose: Automated semantic segmentation of cell nuclei in microscopic images is vital for disease diagnosis and tissue microenvironment analysis. However, obtaining large annotated datasets for train...

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

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

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

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

Mask Guided Diffusion Model for Metal Artifacts Reduction

Authors: Shusen Jing, Qihui Lyu, Dan Ruan, Ke Sheng, Qifan Xu

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

Abstract Preview: Purpose: Metallic implants can significantly distort sinograms, leading to severe artifacts in computed tomography (CT) reconstructions. Reconstructing CT images containing metal is fundamentally an i...

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

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

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

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

Personalized Organ Dose Estimation Using Monte Carlo Simulations, Auto-Segmentation, and Anatomical Extension from Clinical CT Scans

Authors: Belen Juste, Choonsik Lee, Matthew Mille, Rafael Miró, Sergio Morato Rafet, Agustin Santos, Gumersindo Verdú

Affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Universitat Politècnica de València, Servicio de Radiofísica y Protección Radiológica, Consorcio Hospitalario Provincial de Castellón, National Cancer Institute

Abstract Preview: Purpose: To evaluate the differences in CT scan radiation dose estimation between personalized dose reconstruction, based on real patient CT images, and generalized phantom-based dose calculations.

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

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

Affiliation: RefleXion Medical

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

Real-Time 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...

Remote Evaluation of Flash Beamlines for Electron, Proton, and MV Photons

Authors: Alexander Baikalov, Luke Connell, Nolan M. Esplen, Michele M. Kim, Stephen F. Kry, Emil Schueler, Hayden Scott, Ryan Sun, Paige A. Taylor, Uwe Titt

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

Abstract Preview: Purpose: to develop an affordable, portable device for accurately measuring FLASH dose rates from protons, electrons, and photons. 4 detectors were utilized to measure the temporal structure of proton...

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

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

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

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

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

Authors: Samuel Kadoury, Redha Touati

Affiliation: Polytechnique Montréal

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

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

Authors: Hoyeon Lee

Affiliation: University of Hong Kong

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

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

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang

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

Abstract Preview: Purpose:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...

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

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

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

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

Ukan Architecture for Voxel-Level Dose Prediction in Radiotherapy

Authors: Lu Jiang, Ke Sheng

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

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

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

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

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

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

Using Multiple Sequences MRI for Synthesizing CT Based on a Deep Learning Approach

Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, 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, School of Physics, Beihang University, Beijing, 102206, Peopleʼs Republic of China

Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...

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...

What Do We Do with Our Old Pinnacle Data?

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

Affiliation: Iowa Health Care, University of Iowa

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