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Results for "liver mri": 36 found

12 Year Clinical Experience with Low-Tesla MRI for Tumor Progression

Authors: Soon N. Huh, Perry B. Johnson, Jiyeon Park, Ryan Stevens

Affiliation: University of Florida Health Proton Therapy Institute, UF Health Proton Therapy Institute, UFHPTI

Abstract Preview: Purpose:
Low-Tesla MRI (0.23T Panorama MR Scanner, Philips) has been used for tumor progression during proton therapy treatments, and for initial contouring in addition to diagnostic MRI. The pulse...

4D Monte Carlo Dose Evaluation for Mobile Targets in a Magnetic Field

Authors: Odunola Grace Babawale, B. Gino Fallone, Alireza Gazor, Andrei D. Ghila, Patricia A. K. Oliver, Michael W. Reynolds, Keith D. Wachowicz, Tania Rosalia Wood, Shima Y. Tari, Eugene Yip, Jihyun Yun

Affiliation: Nova Scotia Health, Dept. of Medical Physics and Dalhousie University, Dept. of Physics and Atmospheric Science, Dept. of Radiation Oncology, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com, Department of Medical Physics, Arthur J. E. Child Comprehensive Cancer Centre, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Department of Medical Physics, BC Cancer, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute

Abstract Preview: Purpose: To evaluate the dose to a moving target and its surroundings in a magnetic field using 4D-Monte-Carlo (MC) simulation.
Methods: The study utilizes a previously validated MC model of our li...

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 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 SAM-Guided and Match-Based Semi-Supervised Segmentation Framework for Medical Imaging

Authors: Weiguo Lu, Jax Luo, Xiaoxue Qian, Hua-Chieh Shao, Guoping Xu, 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, Harvard Medical School

Abstract Preview: Purpose:
Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. This study leverages th...

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...

Addressing Missing MRI Sequences: A DL-Based Region-Focused Multi-Sequence Framework for Synthetic Image Generation

Authors: Amir Abdollahi, Oliver Jรคkel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome

Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH

Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...

An Efficient Workflow for X-Ray Imaging-Based IGRT/ART

Authors: Lili Chen, Ahmed A. Eldib, Chang Ming Charlie Ma

Affiliation: Fox Chase Cancer Center

Abstract Preview: Purpose: Specialized adaptive radiotherapy (ART) systems have been developed and clinically implemented, which are either cost-ineffective such as MR-linacs or inflexible in workflow such as the Ethos...

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...

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...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

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

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

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

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...

Comparitive Case Analysis of Maa Mapping and Angiographic Iodinated Contrast for Y-90 SIRT Treatment Planning

Authors: Shengwen Deng, Sven L. Gallo, Robert S. Jones, David W. Jordan, Arashdeep Kaur, Aishwarya M. Kulkarni, Quibai Li, William R.M. Pedersen

Affiliation: Department of Radiology, University Hospitals Cleveland Medical Center; School of Medicine, Case Western Reserve University, Department of Radiology, Radiation Safety, 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:
Y-90 (Yttrium) SIRT radioembolization takes advantage of delivering localized radiation to the liver. Pre-treatment dosimetry is highly dependent on accurate MAA mapping, which may have an...

Decoupling Cardiorespiratory Motion of Cardiac Substructures Via 5D-MRI for Radiotherapy

Authors: Carri K. Glide-Hurst, Thomas M Grist, Kevin M. Johnson, Prashant Nagpal, Tarun Naren, Chase Ruff, Oliver Wieben, Jiwei Zhao

Affiliation: Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Department of Radiology, University of Wisconsin-Madison, Department of Medical Physics, University of Wisconsin-Madison, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison

Abstract Preview: Purpose: Cardiotoxicity is a devastating side effect for thoracic radiotherapy (RT). Currently, standard RT imaging is insufficient to decouple cardiorespiratory motion, limiting substructure-specific...

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 Evaluation of Fat Fraction Reference Materials for Magnetic Resonance Imaging

Authors: Hyo-Min Cho, Cheolpyo Hong, Changwoo Lee, Sunyoung Lee

Affiliation: Daegu Catholic University, Korea Research Institute of Standards and Science (KRISS), Korea Research Institute of Standards and Science

Abstract Preview: Purpose: With the increasing prevalence of metabolic syndrome, the importance of diagnosing obesity and fatty liver diseases has grown significantly. As a result, there is a rising demand for non-inva...

Development and Validation of an MR-Compatible Anthropomorphic Motion Phantom for Liver Motion Assessment and MR-Linac Gating System Optimization

Authors: Tsuicheng D. Chiu, Weiguo Lu, Aaron Thomlinson, You 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, University of Texas Southwestern Medical Center

Abstract Preview: Purpose: To develop and validate an MR-compatible anthropomorphic motion phantom to assess liver motion, real-time dosimetry, and gating system performance under controlled and reproducible respirator...

Evaluate a Deep-Learning Auto-Segmentation Software for Liver SIRT

Authors: Wookjin Choi, Jun Li

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Resin Yttrium-90 (Y-90) selective internal radiation therapy (SIRT) is a radioembolization procedure which uses Y-90 microspheres to treat metastatic liver cancer. In the procedure, liver vol...

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 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....

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...

Evaluation of AI-Generated Synthetic 4DCT from 3DCT for Radiotherapy Planning

Authors: Shinichiro Mori, Isabella Pfeiffer, Chester R. Ramsey, Alexander Usynin

Affiliation: Thompson Proton Center, National Institutes for Quantum Science and Technology, Thompson Cancer Survival Center

Abstract Preview: Purpose: Four-dimensional CT imaging (4DCT) has become a standard tool for managing respiratory motion in radiation therapy. However, many treatment delivery systems and most diagnostic CT scanners la...

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

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

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

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

High-Fidelity Monte-Carlo Model Development and Validation of a 0.5T Bi-Planar Linac-MR Using Topas: Multileaf Collimator Modeling, Positioning, and Dose Verification in Slab Phantoms

Authors: B. Gino Fallone, Alireza Gazor, Andrei D. Ghila, Gawon Han, Patricia A. K. Oliver, Michael W. Reynolds, Keith D. Wachowicz, Tania Rosalia Wood, Shima Y. Tari, Eugene Yip

Affiliation: Medical Physics Division, Department of Oncology, University of Alberta, Nova Scotia Health, Dept. of Medical Physics and Dalhousie University, Dept. of Physics and Atmospheric Science, Dept. of Radiation Oncology, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com, Department of Medical Physics, Arthur J. E. Child Comprehensive Cancer Centre, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Department of Medical Physics, BC Cancer, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute

Abstract Preview: Purpose: To develop and validate a high-fidelity Monte-Carlo (MC) model of a 0.5T bi-planar Linac-MR in TOPAS, focusing on accurate Multileaf Collimator (MLC) modelling and positioning for open apertu...

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...

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...

MR-Based Functional Liver Imaging and Dosimetry to Predict Albi Change Post-SBRT

Authors: Madhava Aryal, James M. Balter, Yue Cao, Daniel T Chang, Kyle Cuneo, Joseph R. Evans, Theodore Lawrence, John Rice, Randall K. Ten Haken, Lise Wei

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

Abstract Preview: Purpose: This study aims to identify predictors of global liver function change measured by albumin-bilirubin (ALBI) score following stereotactic body radiation therapy (SBRT) in hepatocellular carcin...

Neural Implicit K-Space for Accelerated Patient-Specific Non-Cartesian MRI Reconstruction

Authors: Daniel O Connor, Mary Feng, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger, Jess E. Scholey, Ke Sheng, DI Xu, Wensha Yang, Yang Yang

Affiliation: UCSF, University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, University of San Francisco, Department of Radiology, University of California, San Francisco, University of California San Francisco, Siemens Medical Solutions USA Inc.

Abstract Preview: Purpose: The scanning time for a fully sampled MRI is lengthy. Compressed sensing (CS) has been developed to minimize image artifacts in accelerated scans, but the required iterative reconstruction is...

Optimal Choice of Companion Radiotracer for TAT 225Ac-Mti-201.

Authors: Vinay K Banka, Mikalai Budzevich, William R. Gibbons, Mark L. McLaughlin, Jacob Moriarty, Eduardo G. Moros, David L. Morse, Christopher J. Tichacek, Thad J. Wadas

Affiliation: Modulation Therapeutics Inc, Moffitt Cancer Center, University of Iowa

Abstract Preview: Purpose: A targeted alpha therapy drug, 225Ac-MTI-201, has been developed targeting the Melanocortin 1 Receptor for metastatic uveal melanoma and is currently in FIH clinical trials. Since alpha emiss...

PCA-Based Future Frame Prediction for Real-Time MRI-Guided Radiotherapy

Authors: B. Gino Fallone, Gawon Han, Keith D. Wachowicz, Mark G. Wright, Eugene Yip, Jihyun Yun

Affiliation: Medical Physics Division, Department of Oncology, University of Alberta, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com

Abstract Preview: Purpose: MRI-radiotherapy hybrid systems can guide the therapeutic beam, dynamically adjusting to a moving tumor in real-time. However, there is a time delay from imaging and beam control, requiring p...

Performance Comparison of Artificial Intelligence-Based Auto-Segmentation Software on Pediatric CT Image Datasets for the Creation of Patient Specific Computational Phantoms

Authors: Wesley E. Bolch, Emily L. Marshall, Dhanashree Rajderkar, Wyatt Smither

Affiliation: University of Florida

Abstract Preview: Purpose: To determine the accuracy of TotalSegmentator, an AI-based automatic segmentation toolkit, on pediatric CT scans as the original software was trained on adult image datasets with a mean patie...

Preliminary Evaluation of Ultrasound-Derived Fat Fraction Reliability in a Pediatric Cohort

Authors: Lizbeth Ayala-Dominguez, Aaron L Carrel, Diego Hernando, Gabrielle L Hoffmann, Amber Possell, Ivan M. Rosado-Mendez, Jiayi Tang, Andrew Wentland

Affiliation: Department of Pediatrics, University of Wisconsin-Madison, Department of Radiology, University of Wisconsin-Madison, Department of Medical Physics, University of Wisconsin-Madison, Departments of Medical Physics and Radiology, University of Wisconsin-Madison

Abstract Preview: Purpose: Metabolic dysfunction-associated steatotic liver disease (MAFLD) is the leading cause of chronic liver disease in children. While biopsy remains the diagnostic standard, non-invasive imaging ...

Radiation Sub-Segmentectomy in 90y Radioembolization: Post-Therapy Dosimetry, Treatment Response, and Pathological Necrosis

Authors: Guilherme Rosa Ferreira, Dan Giardina, John Karageorgiou, Chris Malone, Allan Thomas

Affiliation: Washington University School of Medicine, Mallinckrodt Institute of Radiology, Washington University School of Medicine

Abstract Preview: Purpose: Radiation segmentectomy has become a primary strategy in 90Y radioembolization, with localized treated volumes that can include up to two liver segments. The goal is complete pathological nec...

Rapid Reconstruction of Extremely Accelerated Liver 4D MRI Via Chained Iterative Refinement

Authors: Mary Feng, Yi Lao, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger

Affiliation: University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, City of Hope National Medical Center, University of California San Francisco, Siemens Medical Solutions USA Inc.

Abstract Preview: Purpose: 4D MRI with high spatiotemporal resolution is vital to characterize the tumor/tumor motion for liver radiotherapy. However, high-quality 4D MRI requires an impractically long scanning time fo...

The Role of 3D Vane MRI in Accurate Phase Matching with 4D-CT for Motion Representation in Liver Cancer Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Junchao Li, Fei Liu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Tongji Medical College, Huazhong University of Science & Technology, 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 assess if 3D Vane MRI can accurately depict the motion of the target volume and OARs.
Methods: This retrospective study included 54 liver cancer patients who underwent both 3D Vane MRI ...

Validation of an Ivim Tool for Liver Hypoxia Assessment for an Online Adaptive MR-Linac System

Authors: Jean-Pierre Bissonnette, Catherine Coolens, Laura Dawson, Ryan A Kuhn, Michael Maddalena, Teo Stanescu

Affiliation: Princess Margaret Hospital, The Princess Margaret Cancer Centre - UHN, University of Toronto, Princess Margaret Cancer Centre

Abstract Preview: Purpose: To investigate the generation and reproducibility of 3D hypoxia maps in liver hepatocellular carcinoma (HCC) patients using data derived from an Intravoxel Incoherent Motion (IVIM) MR sequenc...