Search Submissions 🔎

Results for "contrast mri": 69 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...

3D Topological Features for Outcome Assessment of Therapeutic Responses to Neoadjuvant Chemoradiotherapy (NCRT) with and without Anti-CD40 Immunotherapy in Local Advanced Rectal Cancer (LARC)

Authors: Todd A Aguilera, Gaurav Khatri, Jiaqi Liu, Hao Peng, Nina N. Sanford, Robert Timmerman, Haozhao Zhang

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

Abstract Preview: Purpose:
This study first integrates 3D topological data analysis with radiomics from local advanced rectal cancer T2-weighted MRI to evaluate therapeutic responses and quantify treatment-induced c...

3D Wideband Late Gadolinium-Enhanced MRI for Radiotherapy of Ventricular Tachycardia: A Preliminary Study in Healthy Participants and Patient

Authors: Arash Bedayat, Jason Bradfield, Minsong Cao, Robert K Chin, Huiming Dong, J Paul Finn, Fei Han, Justin Hayase, Shu-Fu Shih, Xiaodong Zhong

Affiliation: Cardiac Electrophysiology, University of California, Los Angeles, Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of California, Los Angeles, Siemens Healthineers

Abstract Preview: Purpose: Cardiac SBRT is a promising treatment for ventricular tachycardia (VT). Success depends on accurate target delineation, for which 2D narrowband late gadolinium-enhanced (LGE) MRI offers valua...

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 Novel Margin-Based Focal Distance Loss for Lesion Segmentation in Medical Imaging

Authors: Weiguo Lu, 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

Abstract Preview: Purpose:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...

A Vision-Language Deep Learning Model for Predicting Survival Outcomes in Glioblastoma Patients

Authors: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan

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

Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...

A Vision-Language Model for T1-Contrast Enhanced MRI Generation for Glioma Patients

Authors: Zachary Buchwald, Zach Eidex, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu

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

Abstract Preview: Purpose: Gadolinium-based contrast agents (GBCA) are commonly used for patients with gliomas to delineate and characterize the brain tumors using T1-weighted (T1W) MRI. However, there is a rising conc...

AI-Based Registration-Free 3T T2-Weighted MRI Synthesis Using Truefisp MRI Acquired on a 0.35T MR-Linac System

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Cynthia Fu-Yu Chuang, Yu Gao, Dimitre Hristov, Lianli Liu, Lawrie Skinner, Lei Xing

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

Abstract Preview: Purpose:
MR-guided radiation therapy has introduced a significant leap in cancer treatment by allowing adaptive treatment. The low-field MR-guided system predominantly uses the TrueFISP sequence, w...

AI-Driven Drug Discovery through an Interactive Analysis of Radiomics and Biological Insights in Glioblastoma

Authors: Nobuki Imano, Yuzuha Kadooka, Daisuke Kawahara, Misato Kishi, Yuji Murakami, Shumpei Onishi

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

Abstract Preview: Purpose: Radiomics has proven useful in predicting overall survival in glioblastoma (GBM) patients, but consistent molecular correlations remain unidentified, leaving its biological basis unclear. Thi...

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

Authors: Amir Abdollahi, Oliver JĂ€kel, 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...

Advancing Magnetic Resonance Imaging (MRI) Safety Clearance: Utilizing Dual-Energy CT (DECT) Material Decomposition for Foreign Object Assessment

Authors: Anzi Zhao

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: This study investigates the utility of Dual-Energy Computed Tomography (DECT) material decomposition in resolving Magnetic Resonance Imaging (MRI) safety concerns for patients with unidentifi...

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

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

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

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

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

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

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

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

Assessing Breast Cancer Tumor Segmentability on an Investigational, Double-Bolus, Prone-to-Supine Breast MRI Protocol for Surgical Guidance.

Authors: Richard J Barth, Brook Kennedy Byrd, Roberta DiFlorio-Alexander, Misty J Fox, Venkat Krishnaswamy, Keith D. Paulsen, Timothy B Rooney

Affiliation: Cairn Surgical Inc., Dartmouth Health, Thayer School of Engineering, Dartmouth Hitchcock Medical Center, University of Virginia Health, CairnSurgical Inc.

Abstract Preview: Purpose: Supine breast MRI enables precise surgical planning with demonstrated benefit in decreasing positive margin rates during BCS. However, acquiring supine breast MRI scans in a secondary imaging...

Assessing the Risks of Synthetic MRI Data in Deep Learning: A Study on U-Net Segmentation Accuracy

Authors: Chuangxin Chu, Haotian Huang, Tianhao Li, Jingyu Lu, Zhenyu Yang, Fang-Fang Yin, Tianyu Zeng, Chulong Zhang, Yujia Zheng

Affiliation: The Hong Kong Polytechnic University, Nanyang Technological University, Australian National University, Medical Physics Graduate Program, Duke Kunshan University, North China University of Technology, Duke Kunshan University

Abstract Preview: Purpose: Deep learning segmentation models, such as U-Net, rely on high-quality image-segmentation pairs for accurate predictions. However, the recent increasing use of generative networks for creatin...

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...

BEST IN PHYSICS IMAGING: Cross-Contrast Diffusion: A Synergistic Approach for Simultaneous Multi-Contrast MRI Super-Resolution

Authors: Yifei Hao, Wenxuan Li, Xiang Li, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Yaogong Zhang

Affiliation: Duke University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Diffusion-based deep-learning frameworks have been recently used in MRI resolution enhancement, or super-resolution. Multi-contrast MRI share common anatomical structures while holding comple...

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...

Brain Tumor Segmentation from Multi-Parametric MRI with Integrated Evidential Uncertainty Estimation

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki

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

Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...

Brain Vessel Segmentation and Tracking in Longitudinal Glioblastoma MRI Scans

Authors: Evan Calabrese, Edward Robert Criscuolo, Deshan Yang

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

Abstract Preview: Purpose: Glioblastoma (GBM) is the most common and aggressive form of brain cancer. Deformable image registration (DIR) is a powerful tool to compute anatomical changes in longitudinal MRI scans, whic...

Cerebellar Mutism Syndrome Prediction with 3D Residual Convolutional Neural Network

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki, Bohua Wan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Department of Computer Science, Johns Hopkins University

Abstract Preview: Purpose: Cerebellar mutism syndrome (CMS) is the most frequently observed complication in children undergoing surgical resection of posterior fossa tumors. Previous work explored lesion to symptom map...

Clinical Outcomes of Gamma Knife Stereotactic Radiosurgery Treatments for Intracranial Arteriovenous Malformations & Fistulas: A Single Institutional Retrospective Study

Authors: Madeleine Arbogast, David Dorndos, Denise E Foltz, Justin Fraser, Damodar Pokhrel, William St Clair

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

Abstract Preview: Purpose: For stereotactic radiosurgery (SRS) treatments of intracranial arteriovenous malformations (AVM) and fistulas (AVF), same-day Leksell Gamma Knife (GK) is the preferred modality. Long-term cli...

Comparison of Image Quality and Radiation Dose Among Four Vendors of Mobile Digital Radiography Systems

Authors: Nathalie Correa, Janet Ching-Mei Feng, Chun-Han Huang, Jimmy Huynh

Affiliation: UTHealth McGovern Medical School

Abstract Preview: Purpose: To compare the image quality and the dose-area product (DAP) of four mobile digital radiography (DR) systems—Canon (Soltus 500), Shimadzu (MobileDaRt Evolution MX8), Solution for Tomorrow (M1...

Comparison of Optimized Magnetic Resonance Sequences in the Treatment Planning of Surface Brachytherapy

Authors: Ivan M. Buzurovic, Phillip M. Devlin, Evangelia Kaza, Michael John Lavelle

Affiliation: Department of Radiation Oncology, Dana-Farber/Brigham and Women’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 work in surface brachytherapy (SBT) has demonstrated the feasibility of using magnetic resonance (MR)-guidance in place of Computer Tomography (CT) in SBT planning. The purpose of this...

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...

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

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

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

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

Deep Learning-Driven Comparative Analysis of CNN-Based Architectures and High-Order Vision Mamba U-Net (H-vMUNet) for MRI-Based Brain Tumor Segmentation

Authors: Sang Hee Ahn, Nalee Kim, Do Hoon Lim

Affiliation: Samsung Medical Center, Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine

Abstract Preview: Purpose: MRI offers superior soft-tissue contrast, aiding tumor localization and segmentation in radiation therapy, which traditionally relies on oncologists' expertise. This study compares CNN-based ...

Deep-Learning Based Spectral Artifact Removal with In Vivo 7T Proton MRSI Data

Authors: Anke Henning, Mahrshi Jani, Tianyu Wang, Andrew Wright, Xinyu Zhang

Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center

Abstract Preview: Purpose: Proton MRSI offers critical metabolic insights into diseased brain processes but is prone to artifacts, and current post-processing methods are often insufficient, resulting in low-quality da...

Demystifying Magnetic Resonance Imaging: Targeted Educational Initiatives for Medical Physicists in TĂŒrkiye and Preclinical Medical Students in the United States

Authors: Samuel A. Einstein, Jesutofunmi Fajemisin, Evren O. Göksel, Görkem O. GĂŒngör, Marthony Robins, Travis C. Salzillo, Charles R. Thomas, Turgay Toksay, Joseph Weygand, Yue Yan

Affiliation: Acibadem MAA University, Department of Radiation Oncology and Applied Science, Dartmouth Health, Dartmouth College, Moffitt Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Penn State College of Medicine, Bursa Ali Osman Sönmez Oncology Hospital

Abstract Preview: Purpose: Magnetic resonance imaging (MRI) is an indispensable clinical tool, offering unparalleled soft tissue contrast critical for diagnosing and managing a wide range of conditions. However, its co...

Development of a Cadmium Zinc Telluride (CdZnTe) Detector-Based Neutron Imaging System

Authors: Soo Hyun Byun, Troy Farncombe, Edcer Jerecho DC Laguda

Affiliation: McMaster University

Abstract Preview: Purpose: We present the adaptation of a Cadmium Zinc Telluride (CdZnTe) detector, initially designed for SPECT-MR applications, to neutron imaging. This study explores a novel technique that utilizes ...

Development of an MRI Guided Precision Small Animal Radiotherapy System

Authors: Yaowen Cao, Yunwen Huang, Yidong Yang, Xiaogang Yuan, Ning Zhao, Cheng Zheng

Affiliation: Department of Life Sciences and Medicine, University of Science and Technology of China, Department of Engineering and Applied Physics, University of Science and Technology of China, University of Science and Technology of China

Abstract Preview: Purpose: MRI has better soft tissue contrast than cone beam CT which is commonly used in image guided radiotherapy. This study aims to develop a low-field MRI system for precision small animal radiati...

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...

Enhancing CNN-Based Brain Metastasis Detection in MRI By Integrating Locoregional 3D Deformation Technique

Authors: Minbin Chen, Ke Lu, Kaizhong Shi, Chunhao Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao

Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University

Abstract Preview: Purpose: MRI-based automatic detection of brain metastases is often challenged by the small size and subtle nature of metastases. This study aimed to develop a novel deep learning-based brain metastas...

Enhancing T2-Weighted Brain MRI Resolution across Orientations Using AI-Based Volumetric Reconstruction

Authors: Mengqi Shen, Meghna Trivedi, Tony J.C. Wang, Andy (Yuanguang) Xu, Yading Yuan

Affiliation: Columbia University Medical Center, Dept of Med Hematology & Oncology, Data Science Institute at Columbia University, Columbia University Irving Medical Center, Department of Radiation Oncology, Columbia University Irving Medical Center

Abstract Preview: Purpose: T2-weighted (T2w) images are critical for identifying pathological changes due to their superior contrast in differentiating tissue types. However, they often lack detailed anatomical resolut...

Enhancing Urethral Visualization for Prostate SBRT Using Post-Void T2-Weighted Imaging on a Low-Field 0.35T MR-Linac System

Authors: Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Tino Romaguera, Nishan Shrestha, Somol Sunny

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

Abstract Preview: Purpose: Accurate delineation of the urethra is critical for optimizing tumor control and minimizing urethral toxicity in prostate stereotactic body radiation therapy (SBRT). The purpose of this study...

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 MR Proton Density Fat Fraction (PDFF) for Bone Marrow Protection in RT

Authors: Li Tong, Chuyan Wang, Zhengkui Wang, Yingli Yang, Jie Zhang

Affiliation: Shanghai United imaging Healthcare Advanced Technology Research Institute, Shanghai United Imaging Healthcare Co., LTD, Department of Radiology, Ruijin Hospital, Institute for Medical Imaging Technology, Ruijin Hospital

Abstract Preview: Purpose:
Pelvic radiotherapy (RT)-induced bone marrow (BM) damage affects patient prognosis by causing hematologic toxicity. However, consensus on BM-sparing (BMS) RT is still lacking, owing to the...

Evaluation of the Reflexion X1 As a Standalone PET/CT Simulator for Treatment Planning and Treatment Adaptation

Authors: Chunhui Han, An Liu, William T. Watkins, Qiuyun Xu

Affiliation: Department of Radiation Oncology, City of Hope National Medical Center

Abstract Preview: Purpose: To evaluate the RefleXion X1 imaging system as a standalone positron emission tomography and computed tomography (PET/CT) simulator for radiotherapy treatment planning and adaptive re-plannin...

From Noisy Signals to Accurate Maps: Transforming Look-Locker MRI with an Intelligent T₁ Estimation

Authors: Prabhu C. Acharya, Hassan Bagher-Ebadian, Stephen L. Brown, James R. Ewing, Mohammad M. Ghassemi, Benjamin Movsas, Farzan Siddiqui, Kundan S Thind

Affiliation: Michigan State University, Oakland University, Henry Ford Health

Abstract Preview: Purpose: Accurate T1 quantification using T One by Multiple Read Out Pulse (TOMROP) sequences is essential for physiological assessments in dynamic-contrast-enhanced (DCE) MRI and T1 mapping studies. ...

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...

Functional MRI Guided Partial Tumor Irradiation to Improve Tumor Control and Spare Tumor Microenvironment

Authors: Bingqi Guo, Ping Xia

Affiliation: Cleveland Clinic

Abstract Preview: Purpose:
Spatially fractionated radiation therapy (SFRT) delivers a “GRID” or “lattice” of high and low doses to tumors to increase tumor control, minimize normal tissue damage, and preserve the im...

Generalizable 7T T1 Map Synthesis from 1.5T and 3T T1W MRI for High-Resolution MRI-Guided Radiation Therapy

Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Hui Mao, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu

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

Abstract Preview: Purpose: MRI-guided radiation therapy (MRgRT) benefits significantly from enhanced soft-tissue contrast and spatial resolution, which aid in accurately delineating tumors and organs at risk. Although ...

Immobilization and Optimization of Pulse Sequences for 0.23T MRI

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:
It has been challenging to acquire clinically useful MR images of pediatric cancer patients without anesthesia, and MR contrast agents. Custom-made immobilization devices and optimization ...

Improving Quantitative Accuracy of Maximum-a-Posteriori Expectation Maximization Reconstruction By Optimizing Gibbs Prior Parameters in SPECT

Authors: Krishnendu Saha

Affiliation: Cleveland Clinic Foundation

Abstract Preview: Purpose: The goal is to improve quantitative accuracy of a Maximum-a-posteriori expectation maximization (MAPEM) reconstruction of SPECT phantom images by optimizing Gibbs prior parameters.
Methods...

Improving the Robustness of AI-Based Detection and Segmentation for Brain Metastasis By Optimizing Loss Function and Multi-Dataset Training

Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte

Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine

Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...

Investigating Interstitial Fluid Pressure and Hydraulic Conductivity By Examining the Biophysical Properties of Drug Transport Using Cross Voxel Exchange Model and Dynamic Contrast Enhanced MRI

Authors: Catherine Coolens, Janny Yeyoung Kim, Michael Milosevic, Noha Sinno

Affiliation: Princess Margaret Hospital, University of Toronto

Abstract Preview: Purpose: In solid tumors, Interstitial fluid pressure (IFP) acts as a barrier to molecular transport to the tumor center and serves as a predictor of cancer patients’ treatment responsiveness. The nov...

JACK KROHMER EARLY-CAREER INVESTIGATOR COMPETITION WINNER: Direct Measurement of an Early Change in Tumor Oxygenation in Response to Radiation with Oxygen Enhanced Electron Paramagnetic Resonance Imaging (OE-EPRI)

Authors: Jorge De La Cerda, Andrew Joseph Fanning, Tianzhe Li, Xiaofei Liang, Grace Murley, Mark Pagel, William Schuler, Renee Tran, Shuo Wang, Su-Min Zhou

Affiliation: University of Wisconsin Madison, University of Nebraska Medical Center, University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Electron paramagnetic resonance imaging (EPRI) can be used to image partial pressure of oxygen (pO2) in tumor models. The goal of this study is to develop an Oxygen Enhanced EPRI protocol to ...

NA-Unetr: A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery

Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu

Affiliation: Wayne State University, 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: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...

Next Generation Nanoparticles for Fractionated MRI-Guided Radiation Therapy

Authors: Stephanie Bennett, Ross I. Berbeco, Guillaume Bort, Needa Brown, Lena Carmes, Sandrine Dufort, Michael John Lavelle, Geraldine Le Duc, Francois Lux, Toby Morris, Zeinaf Muradova, Andrea Protti, Olivier Tillement

Affiliation: University de Lyon, NH TherAGuIX, University of Massachsetts Lowell and Dana-Farber Cancer Institute Boston, Department of Radiation & Cellular Oncology, University of Chicago, University of Central Florida, Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, NH TherAguix, Universite de Lyon, Brigham and Women's Hospital, Dana-Farber Cancer Institute

Abstract Preview: Purpose: AGuIX is a theranostic Gd-based nanoparticle currently under phase-2 clinical testing where patients receive 2-3 doses at 1-week intervals prior to imaging and irradiation. AGuIX-Bi is a new ...

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...

Patient-Specific Ultra-Sparse k-Space Reconstruction Using Motion Decomposition and Sinusoidal Representation Networks for Dynamic Volumetric MRI in Radiotherapy

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Charlotte Elizabeth Read, Jing Wang, Qian Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Beth Israel Deaconess Medical Center

Abstract Preview: Purpose: Accurate motion management in MRI-guided radiotherapy (MRIgRT) relies on real-time volumetric MRI to track intra-fractional anatomical changes. Dense k-space sampling, while capable of produc...

Patterns of Nanoparticle Uptake for Patients with Multiple Brain Metastases: Similarities and Differences to Standard Gbca

Authors: Stephanie Bennett, Ross I. Berbeco, Ning Jin, Sonal Josan, Justin Michael Sheetz, Atchar Sudhyadhom

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Massachusetts - Lowell, Siemens Healthineers, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School,, Brigham and Women's Hospital

Abstract Preview: Purpose: AGuIX, a Gadolinium-based theranostic radiosensitizing nanoparticle, is currently under clinical evaluation in Europe and the US. Using patients from the double-blinded NanoBrainMets trial, u...

Performance Evaluation of an Upright, Short-Scan, Cone-Beam, Dedicated Breast CT System.

Authors: Stephen Araujo, Jing-Tzyh Alan Chiang, Cynthia E. Davis, Eri Haneda, Andrew Karellas, Thomas C Larsen, William Ross, Hsin Wu Tseng, Srinivasan Vedantham, Pengwei Wu

Affiliation: Department of Biomedical Engineering, The University of Arizona, GE Aerospace Research, Department of Medical Imaging, The University of Arizona, GE HealthCare Technology & Innovation Center

Abstract Preview: Purpose: The purpose of this work is to describe the design and development of a newly developed upright-geometry dedicated breast CT system and to quantitatively and qualitatively evaluate its imagin...

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...

Research on Glioma MRI Image Generation Based on Large Language Model and Diffusion Model

Authors: Xiangli Cui, Chi Han, Man Hu, Wanli Huo, Xunan Wang, Jianguang Zhang, Yingying Zhang

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

Abstract Preview: Purpose:
Medical image generation has broad application prospects in deep learning, but the model training effect is often limited due to the lack of real image data. This study aims to explore the...

Signal-to-Noise Ratio Estimation from Polynomial Fitting of Acr MRI Phantom Images

Authors: Alex Lindgren-Ruby, Jeffrey M. Moirano, Joseph Everett Wishart

Affiliation: University of Washington

Abstract Preview: Purpose:
To evaluate polynomial fitting of signal intensity for signal-to-noise ratio (SNR) estimation from weekly QC ACR MRI phantom images and compare against other SNR estimation methods as well...

Small Fields Output Factor Measurements in 1.5 MR-Linac

Authors: Thomas I. Banks, Tsuicheng D. Chiu, Viktor M. Iakovenko, Christopher Kabat, Chang-Shiun Lin, Mu-Han Lin, Arnold Pompos

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

Abstract Preview: Purpose: The superior soft-tissue contrast provided by MR imaging offers favorable conditions for the effective application of stereotactic body radiation therapy (SBRT). Accurate small field dosimetr...

Spatially Informed Auto-Segmentation of Cardiac Nodes for Radiotherapy Treatment Planning

Authors: Ming Dong, Carri K. Glide-Hurst, Joshua Pan, Nicholas R. Summerfield

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Radiation dose to the cardiac nodes is more strongly associated with conduction disorders and arrythmias than whole heart (WH) metrics. However, node segmentation is challenging due to comple...

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 ...

Synthetic CT Generation from a Cycle Diffusion Model Based Framework for Ultrasound-Based Prostate HDR Brachytherapy

Authors: Michael Baine, Charles Enke, Yang Lei, Yu Lei, Ruirui Liu, Su-Min Zhou

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Radiation Oncology, University of Nebraska Medical Center

Abstract Preview: Purpose: This study presents a framework for generating synthetic CT images using a Cycle Diffusion model, which can be utilized to enhance needle conspicuity in ultrasound-guided prostate HDR brachyt...

Synthetic Vs. Conventional Planar Imaging: Performance and Clinical Feasibility

Authors: Jennifer Kwak, Chelsea Manica, Justin K. Mikell, Michael Silosky, Wendy Siman

Affiliation: Washington University School of Medicine in St. Louis, University of Colorado Anschutz Medical Campus, School of Medicine, Rocky Vista University

Abstract Preview: Purpose:
This study evaluates synthetic planar imaging (synP) from SPECT projections against conventional planar imaging, focusing on detectability, spatial resolution, and feasibility. SynP allows...

Towards Penile Small Vessel Imaging with Ferumoxytol-Enhanced MRI

Authors: Darren Fang, Amar Kishan, Justin McWilliams, Dan Ruan, Xiaodong Zhong

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

Abstract Preview: Purpose: Prostate radiotherapy can malform penile vasculature, contributing to erectile dysfunction and compromising quality of life. To detect, quantify, and preferably avoid such occurrences, this p...

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...

Use of Edge-Driven Modified Fuzzy C-Means Algorithm in DCE-MRI Image Sequences for Prostate Cancer Lesion Segmentation

Authors: Ilias Gatos, Stavros Grigoriadis, George C. Kagadis, Maria Karamesini, Paraskevi Katsakiori, Dimitris N. Mihailidis, Stavros Spiliopoulos, Efstratios Syrmas, Ioannis Theotokas, Stavros Tsantis, Pavlos Zoumpoulis

Affiliation: Diagnostic Echotomography, University of Pennsylvania, University of Athens, University of Patras

Abstract Preview: Purpose: To detect prostate lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images which is a particularly difficult task due to the heterogeneous and inconsistent representa...

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, PeopleÊŒs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, PeopleÊŒs 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...

Web-Based Tool for CT Ring Artifact Identification Using Streamlit and Python

Authors: Sarah Huo, David Zander, Wei Zhou

Affiliation: Cherry Creek High School, University of Colorado Anschutz Medical Campus, University of Colorado Anschutz Medical Campus, School of Medicine

Abstract Preview: Purpose:
Ring artifact is commonly seen in CT, and it is usually caused by detector element failure or miscalibration. Although many ring artifacts are apparent and easy to recognize, those origina...