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Results for "automated mri": 37 found

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 No-Reference Medical Image Quality Assessment Method Based on Automated Distortion Recognition Technology: Application to Preprocessing in MRI-Guided Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Yuan Tang, Zilin Wang, Guohua Wu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
To develop a novel no-reference image quality assessment (NRIQA) method for evaluating the effectiveness of image preprocessing in MRI-guided radiotherapy (MRIgRT), thereby enhancing clini...

A Semi-Automated Landmark Identification Framework for Liver MR-CT Image Pairs: Towards a Multi-Modality DIR Benchmark Dataset

Authors: Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...

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

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

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

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

An Advanced Automated Pipeline for Brain Tumor Segmentation on MRI Images in Gamma Knife Radiotherapy

Authors: Zachery Colbert, Matthew Foote, Michael Huo, Mark Pinkham, Prabhakar Ramachandran, Mihir Shanker

Affiliation: Radiation Oncology, Princess Alexandra Hospital, Ipswich Road, Princess Alexandra Hospital

Abstract Preview: Purpose: The study aimed to develop and implement deep learning-based autosegmentation models for the autosegmentation of four key tumor types: brain metastasis, pituitary adenoma, vestibular schwanno...

An Automated System for MRI Coil Performance Evaluation

Authors: Michael Cuddy, Samuel J. Fahrenholtz, Khushnood Hamdani, Saman Jirjes, Robert G. Paden, Jeremiah W. Sanders, William F. Sensakovic, Wolfgang Stefan, Jeffrey Xiao, Yuxiang Zhou

Affiliation: Mayo, Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Title: An automated system for MRI coil performance evaluation

Purpose: To develop an automated quality control (QC) system for MRI coils to assess element-level signal-to-noise ratio (SNR), ar...

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...

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...

Auto-Contouring of OAR Enhances Patient Safety and Workflow in Gamma Knife Stereotactic Radiosurgery

Authors: Sven Ferguson, S. Murty Goddu, Ana Heermann, Taeho Kim, Nels C. Knutson, Hugh HC Lee, Shanti Marasini, Timothy Mitchell, Seungjong Oh, Kevin Renick

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

Abstract Preview: Purpose: In the Gamma Knife stereotactic radiosurgery (GK-SRS), the delineation of organs-at-risks (OARs) was not fully automated. Due to the cumbersome nature of manual OAR contouring, dose evaluatio...

Automated Framework for Predicting Tumour Growth in Vestibular Schwannomas Using Contrast-Enhanced T1-Weighted MRI

Authors: Mehdi Amini, Minerva Becker, Simina Chiriac, Alexandre Cusin, Dimitrios Daskalou, Ghasem Hajianfar, Sophie Neveu, Marcella Pucci, Yazdan Salimi, Pascal Senn, Habib Zaidi

Affiliation: Geneva University Hospital, Division of Radiology, Diagnostic Department, Geneva University Hospitals, Service of Otorhinolaryngology-Head and Neck Surgery, Department of Clinical Neurosciences, Geneva University Hospitals

Abstract Preview: Purpose: Personalized prediction of vestibular schwannoma (VS) tumour growth is crucial for guiding patient management decisions toward observation versus intervention. This study proposes an automate...

Automated MR Segmentation for Online Adaptive MR-Linac Therapy Using an in-House Model

Authors: David L. Barbee, David Byun, Matt Long, Jose R. Teruel Antolin, Michael J Zelefsky

Affiliation: NYU Langone Health

Abstract Preview: Purpose:
Online adaptive MR-Linac therapy requires contour adaptation, often adding 20 minutes to treatment time and reducing machine throughput. This study introduces a fully automated MR contour ...

Automated Multimodal Image Registration for Prostate Bed Radiation Treatment

Authors: Quan Chen, Xue Feng, Chunhui Han, Gaofeng Huang, Trevor Ketcherside, Yi Lao, Yun Rose Li, An Liu, Bo Liu, Kun Qing, William T. Watkins

Affiliation: Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, City of Hope National Medical Center, Mayo Clinic Arizona, Carina Medical LLC

Abstract Preview: Purpose: New treatment platforms such as Ethos (Varian Medical Systems) allow the introduction of multi-modal imaging into adaptive radiotherapy workflow to facilitate an up-to-date view of patientsโ€™ ...

Automated Plan Optimization Using an Adaptive Objective Function Template in Prostate Cancer

Authors: Michael Joseph Dance, Shiva K. Das, John Dooley, David V. Fried, Spencer Lynch, Michael Repka, Shivani Sud, Neil Ari Wijetunga

Affiliation: University of North Carolina

Abstract Preview: Purpose: The growing complexity of radiation therapy treatment planning presents challenges in maintaining efficient clinical workflows while ensuring plan quality. This study evaluates the use of an ...

Automated Treatment Planning for Linac-Based Stereotactic Radiosurgery of Intraocular Malignancies Via Hyperarc Knowledge-Based Planning

Authors: Chase Cochran, Shane McCarthy, Damodar Pokhrel, William St Clair

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

Abstract Preview: Purpose: Manually generating intraocular stereotactic radiosurgery (SRS) plans involves significant challenges, including lengthy planning times and inter-planner variability. Knowledge-based SRS plan...

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...

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

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

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

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

Can AI Agent be a Good Judge for Online Adaptive Radiotherapy Plan Evaluation?

Authors: Steve B. Jiang, Mu-Han Lin, Dan Nguyen, Beiqian Qi, Daniel Yang, Ying Zhang

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:
Online adaptive radiotherapy (oART) is a resource-intensive workflow requiring significant time and effort required from clinicians, particularly for the online evaluation of plan quality....

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 ...

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...

Deep Learning-Based Categorization of Brain Tumours Using Brain MRI : Advancing Precision Medicine in Neuroimaging

Authors: William F.B Igoniye, Belema Manuel, Christopher F. Njeh, O Ray-offor

Affiliation: Indiana University School of Medicine, Department of Radiation Oncology, Department of Radiology, University of Port Harcourt Teaching Hospital

Abstract Preview: Purpose: The accurate and efficient categorization of brain tumors is essential for effective treatment planning and improved patient outcomes. Current MRI-based diagnostic methods are time-intensive ...

Determine Noise Weighting Factor in Photon-Counting CT Via Deep Learning for Personalized Noise Reduction

Authors: Xinhui Duan, Roderick W. McColl, Mi-Ae Park, Liqiang Ren, Gary Xu, Kuan Zhang, Yue Zhang

Affiliation: UT Southwestern Medical Center, Department of Radiology, UT Southwestern Medical Center, Imaging Services, UT Southwestern Medical Center

Abstract Preview: Purpose:
Image-based deep-learning noise-reduction techniques have been developed for photon-counting CT (PCCT) to improve image quality with reduced radiation dose. The denoising strength is typic...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity

Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...

Development and Clinical Validation of Hyperarc Stereotactic Radiosurgery Method for Intraocular Tumors

Authors: Chase Cochran, Damodar Pokhrel, William St Clair

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

Abstract Preview: Purpose: Currently, intraocular disease is primarily treated via COMS-plaques brachytherapy. Various stereotactic approaches via photons/proton beam have also been implemented (CyberKnife/GammaKnife/p...

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...

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 ...

Dose Dependent White Matter Injuries Quantified By Axial and Radial Diffusivity of Diffusion Tensor Imaging Significantly Correlate with Radiation-Induced Neurocognitive Decline in Diffuse Glioma Patients Underwent Chemoradiation Therapy

Authors: Robert Fucetola, Jiayi Huang, Zhihua Liu, Chongliang Luo, Tong Zhu

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

Abstract Preview: Purpose:
This prospective observational study investigates radiation-induced white matter (WM) injuries using longitudinal diffusion tensor imaging (DTI) in patients with diffuse glioma following r...

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

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

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

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

Evaluating Dose Variability in Bladder Contouring for MR-Guided Prostate Cancer Radiotherapy

Authors: Emily Helen Hayes, Chihray Liu

Affiliation: University of Florida

Abstract Preview: Purpose: To evaluate dosimetric discrepancies in bladder dose calculations among rigid, deformed, and manual contouring methods in prostate cancer patients and assess dose variations resulting from bl...

Evaluating the Radiological Safety of 64Cu-Macrin in PET/MRI Studies through Radiopharmaceutical Dosimetry

Authors: Alejandro Bertolet, Mislav Bobiฤ‡, Carlos Huesa-Berral, Aileen O'Shea, Ralph Weissleder

Affiliation: Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital and Harvard Medical School

Abstract Preview: Purpose: To develop a pipeline for estimating the absorbed dose to various organs from positron emission tomography (PET) combined with magnetic resonance imaging (MRI). We use this pipeline to evalua...

Evaluating the Role of Gradient Magnitude in Entorhinal Cortex for Dementia Diagnosis Using T1 MR Images

Authors: Yongha Gi, Jinju Heo, Jinyoung Hong, Yunhui Jo, Yousun KO, HyeongJin Lim, Sang Yoon PARK, Myonggeun Yoon

Affiliation: Korea University, Institute of Global Health Technology (IGHT), Korea University, Republic of Korea

Abstract Preview: Purpose: To evaluate the effectiveness of the gradient magnitude (GM) feature of the entorhinal cortex, observed in T1 MR images, in dementia classification.
Methods: A total of 1,422 ADNI T1 MR da...

Exploring the Compatibility of VMAT and Respiratory Beam Gating on MR-Linac: A Proof-of-Concept Study

Authors: Caiden Atienza, Pim T. S. Borman, Martin F. Fast, Daniel E. Hyer, Bas W. Raaymakers, Jeffrey E. Snyder, Prescilla Uijtewaal, Peter Woodhead

Affiliation: Department of Radiotherapy, University Medical Center Utrecht, Yale New Haven Health, University of Iowa

Abstract Preview: Purpose:
On conventional C-arm linacs, VMAT is the preferred delivery modality due to its superior efficiency and highly conformal dose distributions. MR-linacs offer superior soft-tissue imaging t...

Fully Automated Zero-Shot Organ Segmentation in Male Pelvic MR Images for MR-Guided Radiation Therapy

Authors: Jihun Kim, Jin Sung Kim, Jun Won Kim, Yong Tae Kim, Chanwoong Lee, Jihyn Pyo, Young Hun Yoon

Affiliation: 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

Abstract Preview: Purpose: Although segmentation foundation models have recently demonstrated promising zero-shot performance on natural images, its clinical application to magnetic resonance (MR) images still requires...

Novel Automatic Detection of Surface Brachytherapy Applicators and Catheters on Vibe MR Images

Authors: Ivan M. Buzurovic, Evangelia Kaza

Affiliation: Department of Radiation Oncology, Dana-Farber/Brigham and Womenโ€™s Cancer Center, Harvard Medical School, Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology

Abstract Preview: Purpose: Recent advances allow for depiction of surface brachytherapy flap applicators using MRI, with empty catheters detected by signal intensity reduction. As manual catheter detection is subjectiv...

Patient-Specific Imaging Modality Agnostic Virtual Digital Twins Modeling Temporally Varying Digestive Motion

Authors: James M. Balter, Lando S. Bosma, Jorge Tapias Gomez, Nishant Nadkarni, Mert R Sanbuncu, William Paul Segars, Ergys D. Subashi, Neelam Tyagi, Harini Veeraraghavan

Affiliation: University of Michigan, The University of Texas MD Anderson Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Cornell University, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Develop patient-specific virtual digital twin (VDT) cohorts modeling physically realistic spatio-temporal gastrointestinal (GI) organs (stomach and duodenum) digestive motion.
Methods: Pat...

Prompt Preset for Imaging Physics Education and Board Style Question Generation: Development and Validation

Authors: Rose Al Helo, Shengwen Deng, Sven L. Gallo, David W. Jordan

Affiliation: Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center, University Hospitals Cleveland Medical Center, Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center; School of Medicine, Case Western Reserve University; Department of Radiology, Louis Stokes Cleveland VA Medical Center

Abstract Preview: Purpose: From an educator perspective, preparing test questions for trainees is time-consuming and requires a lot of quality verification steps (review of stems, distractors, referencing) that can pot...

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...

Treatment Plan Evaluation of the Patient-Tailored Architect Applicator for Cervical Cancer Brachytherapy

Authors: Jenny Dankelman, Ben J. M. Heijmen, Inger-Karine K. Kolkman-Deurloo, Remi A. Nout, Linda Rossi, Robin Straathof, Linda Wauben, Henrike Westerveld, Nick J. van De Berg, Sharline M. van Vliet - Perez

Affiliation: Department of BioMechanical Engineering, Delft University of Technology, Department of Gynecological Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam

Abstract Preview: Purpose:
To quantify the dosimetric advantages of the 3D-printed patient-tailored ARCHITECT applicator with optimized needle channel configurations compared to clinically used intracavitary/interst...