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Results for "mri brain": 79 found

23na Magnetic Resonance Imaging k-Space Denoising

Authors: Lorenzo Arsini, Andrea Ciardiello, Fabio Massimo D'Amore, Stefano Giagu, Federico Giove, Carlo Mancini-Terracciano, Cecilia Voena

Affiliation: Istituto Superiore di SanitĂ , Sapienza University of Rome, UniversitĂ  Sapienza Roma, Magnetic Resonance for Brain Investigation Laboratory, Museo Storico della Fisica e Centro di Studi e Ricerche Enrico Fermi

Abstract Preview: Purpose: To leverage newly developed heteronuclear magnetic resonance imaging (MRI) techniques, particularly sodium (23Na) imaging, for identifying potential biomarkers of Alzheimer's disease—such as ...

3D Bioprinted Brain Cancer Constructs for Experimental Synchrotron Radiotherapy

Authors: John Paul Ortiz Bustillo, Elette Engels, Elrick T. Inocencio, Michael Lerch, Julia Rebecca D Posadas, Anatoly Rosenfeld, Kiarn Roughley, Moeava Tehei, Gordon Wallace, Danielle Warren, Vincent de Rover

Affiliation: Centre for Medical Radiation Physics, University of Wollongong Australia, Department of Radiology, University of the Philippines- Philippine General Hospital, Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, University of Wollongong Australia, Centre for Medical Radiation Physics, University of Wollongong, Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, University of Wollongong, University of the Philippines Manila; Centre for Medical Radiation Physics, University of Wollongong Australia

Abstract Preview: Purpose: To compare the biological response through cell viability assay and fluorescence imaging of 3D bioprinted brain cancer (glioma) constructs relative to 2D monolayer and 3D spheroid culture for...

A Combination of Radiomics and Dosiomics for Gross Tumor Volume Regression in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR)

Authors: Hao Peng, Yajun Yu

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: Personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is a novel ablative radiation dosing scheme developed by our institution. This study aims to establish a regression...

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 Modular Approach to Reversible and Stackable Medical Imaging Translation Models: CBCT-Based Synthetic MRI with Multiple U-Nets in Series (MUNETs)

Authors: Eric Chang, Nguyen Phuong Dang, Andrew Lim, Lauren Lukas, Lijun Ma, Yutaka Natsuaki, Zhengzheng Xu, Hualin Zhang

Affiliation: Radiation Oncology, Keck School of Medicine of USC

Abstract Preview: Purpose: Harnessed the power of AI and Deep Learning (DL), Generalized Neural Network models for medical image transformation are trained to predict target images from reference images, often requirin...

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 Plan Complexity Comparison between Monaco and Eclipse - Meta Analysis of 17,000 Plans and 30,000 Beams

Authors: Christopher Colyer, Leon F Dunn, Jonathan Dunning, Simon Goodall, Andy Schofield

Affiliation: GenesisCare

Abstract Preview: Purpose: Modern radiotherapy is characterized by complex treatment plans utilizing dynamic MLCs, gantry positions and recently, collimator rotations. The purpose of this work was to compare the plan c...

A Retrospective Assessment of Proton Radiation Response in Brain Tumor Patients Using Diffusion-Weighted MR Imaging

Authors: Liu Hong, Wen C. Hsi, Faraz Kalantari, Romy Megahed, Ganesh Narayanasamy, Maida Ranjbar, Pouya Sabouri, Zhong Su

Affiliation: University of Arkansas for Medical Sciences, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)

Abstract Preview: Purpose: Quantitative apparent diffusion coefficients (ADC) in diffusion-weighted MRI (dMRI) reflect water diffusivity and thus provide tissue cellular density information. Functional diffusion mappin...

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 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...

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 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 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...

Application of a Conditional Diffusion Model to Improve Real-Time MR Imaging in Online Adaptive MR-Guided Radiotherapy

Authors: Hideaki Hirashima, Haruo Inokuchi, Nobutaka Mukumoto, Naruki Murahashi, Mitsuhiro Nakamura, Megumi Nakao, Keiko Shibuya, Linna Zhang

Affiliation: Kyoto University, Osaka Metropolitan University

Abstract Preview: Purpose:
To transform the quality of 2D cine MR images acquired during online adaptive MR-guided radiotherapy (OA-MRgRT) by utilizing a conditional diffusion model to achieve image quality comparab...

Artificial Intelligence Based Auto-Contouring for Organs at Risk in Head and Neck

Authors: Mylinh Dang, Laila A Gharzai, Xinlei Mi, Poonam Yadav

Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern Medicine

Abstract Preview: Purpose: Delineation of organs at risk (OAR) in the head/neck region requires substantial physician time. Many artificial intelligence (AI) based auto-contouring software are commercially available. T...

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 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...

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 IMAGING: Revolutionizing Neurocognitive Dynamic Pattern Discovery with Self-Supervised AI in Functional Brain Imaging

Authors: Lei Xing, Zixia Zhou

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

Abstract Preview: Purpose: Functional brain imaging techniques, such as functional magnetic resonance imaging (fMRI), generate high-dimensional, dynamic data reflecting complex neural processes. However, extracting rob...

BEST IN PHYSICS MULTI-DISCIPLINARY: Building a Cross-Modality Model to Integrate Bio-Clinical Features, Anatomical MRI, and White-Matter Pathlength Mapping for Personalized Glioblastoma RT Planning

Authors: Steve Braunstein, Angela Jakary, Hui Lin, Bo Liu, Janine Lupo, Tiffany Ngan, Ke Sheng, Nate Tran

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Radiology and Biomedical Imaging, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Current RT clinical target volumes (CTVs) for Glioblastoma (GBM) employ 2cm isotropic expansions of gross tumor volumes. However, studies showed patients still experience progression beyond t...

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

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

Affiliation: Dartmouth College

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

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

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

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

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

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...

Brain Structural Covariance Networks in Nicotine-Dependent Users: A Graph Analysis

Authors: Humberto Monsivais, Brian A. Taylor, Francesco Versace

Affiliation: Purdue University, Department of Behavioral Science, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: To identify possible signatures of altered brain morphometry in nicotine-dependency via a structural covariance network approach.

Methods: Fifty-one healthy controls (HC:27M, mean age=...

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 Assessment of Synthetic CT in MR-Only Brain Radiotherapy

Authors: Ergun E. Ahunbay, Colette Gage, Abdul Kareem Parchur, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: AI-generated synthetic CT (sCT) images address challenges with prior sCT approaches, including atlas- and threshold-based methods. Commercial AI-based sCT tools have been introduced. This wor...

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...

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 ...

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 ...

Deep Learning-Based Ventricular Auto-Segmentation for Dosimetric Analysis in Intraventricular Tumor SRS

Authors: John Byun, Juan J Cardona, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Yusuke Hori, Hao Jiang, Fred Lam, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang

Affiliation: Department of Radiation Oncology, Stanford University, Department of Neurosurgery, Stanford School of Medicine, Department of Neurosurgery, Stanford University, 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:
Intraventricular tumors pose significant challenges in neurosurgery due to their complex location. Therefore, brain SRS could be a better treatment option. At our institution, some patient...

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...

Design and Construction of a Geometrical and Head Phantom with Internal Carotid Inserts for Flow Simulation in Image-Derived Input Function with 3T and 7T MR-Brainpet Insert Studies.

Authors: Dirk Grunwald, Hans Herzog, Hidehiro Iida, N. Jon Shah, Usman Khalid, Manfred Lennartz, Philipp Lohmann, Ceren Memis, Tobias Meurer, Claudia Regio Brambilla, JĂŒrgen Scheins, Lutz Tellmann, Christoph W. Lerche, Martin Wiesmann, Karl Ziemons

Affiliation: FH Aachen University of Applied Sciences, Department of Chemistry and Biotechnology, Clinic for Diagnostic and Interventional Neuroradiology, Uniklinik Aachen,, Institute of Neuroscience and Medicine (INM-4), Forschungszentrum JĂŒlich GmbH, Institute of Neuroscience and Medicine (INM-4), Forschungszentrum JĂŒlich GmbH,, Central Institute for Engineering, Electronics and Analytics (ZEA-1), Forschungszentrum, Turku PET Center, Institute of Biomedicine, Faculty of Medicine, University of Turku,

Abstract Preview: Purpose: Quantitative brain studies with positron emission tomography (PET) often require an arterial input function (AIF), which traditionally requires arterial cannulation. However, this is invasive...

Developing Patient-Specific Functional Atlases with Inverse Distance Weighting of MR Images

Authors: Chibawanye I. Ene, Sherise D. Ferguson, Ping Hou, Vinodh A. Kumar, Ho-Ling Anthony Liu, Kyle R. Noll, Sujit S. Prabhu, Jian Ming Teo, Max Wintermark

Affiliation: Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
Functional brain atlases are used to guide clinical functional MRI (fMRI) analyses. Imprecise assertions may introduce the ecological fallacy as atlases are reflective of the constituent c...

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...

Development of Foundation Model for Analysis of Prostate Cancer with Mpmri

Authors: Ahmad Algohary, Adrian Breto, Quadre Emery, Radka Stoyanova

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

Abstract Preview: Purpose:
To develop a foundation model (U-Found) for multiparametric MRI (mpMRI) of the prostate by using self-supervised learning to prove the feasibility of a prostate-oriented foundation model u...

Development of a Brain-like Digital Reference Object of Resting-State Functional MRI

Authors: Henry Szu-Meng Chen, Mu-Lan Jen, Vinodh A. Kumar, Ho-Ling Anthony Liu, Jian Ming Teo

Affiliation: School of Medicine, University of Colorado Denver, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Resting-state (rs-) fMRI detects functional networks by measuring synchronization of low-frequency oscillations in blood-oxygenation-level-dependent (BOLD) signals between brain regions. Stan...

Diffusion Model-Based Motion Correction in Portable Computed Tomography for Brain: Human Observer Study

Authors: Rajiv Gupta, Rehab Naeem Khalid, Min Lang, Michael H Lev, Quirin Strotzer, Matthew Tivnan, Maryam Vejdani-Jahromi, Dufan Wu, Siyeop Yoon, Chen Zhennong

Affiliation: Massachusetts General Hospital

Abstract Preview: Purpose: Patient motion is a major source of artifacts in portable brain CT due to the slow scanning speed. A diffusion model was developed to reduce these motion artifacts. This work aims to assess t...

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 ...

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...

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

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

Affiliation: St. Jude Children's Research Hospital

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

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 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...

Generating 3D Brain in Volume (BRAVO) Images Using Attention-Gated Conditional Gan (AGC-GAN)

Authors: Nan Li, Shouping Xu, Gaolong Zhang, Xuerong Zhang

Affiliation: Department of Radiation Oncology, HeBei YiZhou proton center, School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
The 3D BRAVO sequence is an advanced magnetic resonance (MR) technique that allows for image reconstruction at any angle. It offers 1 mm gapless scanning and has a high signal-to-noise rat...

Generating Brain Pseudo-CT from PET-Only Images Using Deep Learning Method

Authors: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences, Tehran University of Medical Science

Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...

Geometrically Derived Density Compensation Function for 3D Non-Cartesian MRI Reconstruction

Authors: Oluyemi Bright Aboyewa, KyungPyo Hong, Daniel Kim

Affiliation: Department of Radiology, Northwestern University

Abstract Preview: Purpose: While non-Cartesian MRI is desirable for fast imaging with high spatial resolution and robustness to motion, it requires long post-processing times. Preconditioning with an adequate density c...

Gradient-Based Radiomics for Outcome Prediction and Decision-Making in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR): A Preliminary Study

Authors: Michael Dohopolski, Jiaqi Liu, Hao Peng, Robert Timmerman, Zabi Wardak, Haozhao 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:
This study introduces a gradient-based radiomics framework to enhance outcome prediction in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR) for brain metastases...

Imaging of Mn Washout in the Individual Welder Brain after Wearing Powered Air-Purifying Respirators (PAPRs)

Authors: Ulrike Dydak, Chia-Tien Hsu, Chang Geun Lee, Cora Mizimakoski, Humberto Monsivais, Jae Hong Park

Affiliation: Purdue University

Abstract Preview: Purpose: Overexposure to manganese (Mn) from inhaling welding fumes can lead to cognitive and motor deficits. We developed a whole-brain Mn-mapping approach to detect subtle but significant increases ...

Improving Post-SRS Brain Metastasis Radionecrosis Diagnosis Accuracy Via Deep Feature Space Analysis

Authors: Evan Calabrese, Scott R. Floyd, Kyle J. Lafata, Zachary J. Reitman, Eugene Vaios, Chunhao Wang, Lana Wang, Deshan Yang, Zhenyu Yang, Jingtong Zhao

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

Abstract Preview: Purpose:
This study proposes a novel neural ordinary differential equation (NODE) framework to distinguish post-SRS radionecrosis from recurrence in brain metastases (BMs). By integrating imaging f...

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 ...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

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

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

Inter-Fraction Monitoring of Brain Metastases Resection Cavities during Fractionated Stereotactic Radiosurgery on the 0.35 T MRI-Linac

Authors: Eyub Y. Akdemir, Gregory A Azzam, Rupesh Kotecha, Gregory J. Kubicek, Natalia Lutsik, Eric Mellon, Siamak P. Nejad-Davarani, Parag Parikh, Karen C. Snyder

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Department of Radiation Oncology, University of Miami, Henry Ford Health

Abstract Preview: Purpose: Resection cavity volumes shrink gradually over time after surgical resection of brain metastases. Fractionated stereotactic radiosurgery (fSRS) is often delivered to the cavity to prevent rec...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...

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...

Modality-Agnostic Image Cascade (MAGIC) for Multi-Modality Cardiac Substructure Segmentation

Authors: Ming Dong, Carri K. Glide-Hurst, Qisheng He, Anudeep Kumar, Alex Singleton Kuo, Joshua Pan, Chase Ruff, 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: Recent evidence highlights the importance of incorporating cardiac substructures (CS) into treatment planning for thoracic cancers, however current segmentation methods are limited to a singl...

Multi-Center Diffusion-Weighted MRI Validation for 0.35T MR-Linac: A Repeatability and Reproducibility Study

Authors: Tess Armstrong, Nema Bassiri, Alonso N. Gutierrez, Michael Kasper, Natalia Lutsik, Eric Mellon, Kathryn E. Mittauer, Siamak P. Nejad-Davarani, Shyam Pokharel, Suresh Rana, Hui Wang, Joseph Weygand

Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Miami Cancer Institute, Baptist Health South Florida, ViewRay, Inc., Miami Cancer Institute, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida, Department of Radiation Oncology, University of Miami

Abstract Preview: Purpose: Radiation treatments on the MR-linac (MRL) enable daily acquisition of anatomical and physiological images for adaptive treatment planning. The apparent diffusion coefficient (ADC) estimated ...

Multidimensional Diffusion MRI Based Microstructural Heterogeneity Model on a 5T MR System

Authors: Jiayi Chen, Shaolei Li, Fuhua Yan, Yingli Yang, Jie Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Institute for Medical Imaging Technology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai United imaging Healthcare Advanced Technology Research Institute, Department of Radiation Oncology, Ruijin Hospital

Abstract Preview: Purpose: The aim of this exploratory study is to investigate the feasibility of establishing a model to explore tissue component heterogeneity using multidimensional diffusion magnetic resonance imagi...

Multiparametric and Low-Field MRI for Biomimetic MRI-Readable Gel Dosimeters

Authors: Kaitlyn M Betz, David Dunkerley, Eric Johnson, Kalina V Jordanova, Kathryn E. Keenan, Samuel D Oberdick, Gregory P. Penoncello, Stephen E Russek

Affiliation: Dept of Radiology, Stanford, University of Colorado School of Medicine, NIST, College of Wooster

Abstract Preview: Purpose: Examine use of low-field MRI and multiparametric analysis for 3D MRI-readable biomimetic gel dosimetry. Low-field MRIs are compact, inexpensive, and portable. They could be located within rad...

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Authors: Houssam Abou Mourad, Christopher Ackerman, Stephen Adler, Kirk Aduddell, Muhammad K. Afghan, Hamid G. Aghdam, Diego Aguilar, Kang-Hyun Ahn, Francis Ai, Hua Ai, Ray Anthony Aikens, Manik Aima, Victoria Ainsworth, Erfan Akbari, Blessing Akinro, Rani Al-Senan, Khalid Alabbasi, Sam Alam, Daniel Alexander, Mohammed H. Aljallad, Mazin T. Alkhafaji, Ahmad K. Alkhatib, Scott J. Alleman, James Logan Allen, Ibtisam Almajnooni, Tiba Alnaqshabandi, Murat Alp, Stephen J. Amadon, Riska Amilia, Ala Amini, Shiho Amster, Mason R. Anders, Erin Angel, Ledi Anggara, John A. Antolak, Debora Antonio, Felicity Appiah, Haiqa Arain, Lahcen Arhjoul, Ali V. Aritkan, Muhammad Arshad, Mark E. Artz, Nathan S. Artz, Frank A Ascoli, John R. Ashburn, Benjamin Astarita, Masakazu Atsumi, Rex G. Ayers, Tara M. Bachman, Nina L. Bahar, Bing Bai, Michael J. Bailey, Chris Baird, Mohammad Bakhtiari, Andrew J. Ballesio, Isabel Balvoa, Qinan Bao, Jeffrey J. Barbarits, Joseph Barbiere, Philip C. Bardos, Gary T. Barnes, John C. Barrett, Divya Bartley, Steven J. Bartolac, Robert Barton, Christopher P. Bass, Loni Bates, Alan Baydush, John E. Bayouth, Stephen Beach, Kevin Beaudette, Kaelyn Becker, Natalie A. Beckmann, Colleen Beer, Sepideh Behinaein, Jake M. Bell, David M. Bellezza, Maria R. Bellon, Ahmed Benelfassi, Stephanie Louise Bennett, Todd Bernath, Kate Bevins, Nicholas B. Bevins, Brian J. Bismack, David Blaich, Anthony P. Blatnica, Joseph W. Blickenstaff, Steven Blum, Maggie Bobbett, Dayna Bodensteiner, Daniel Boedeker, Robert C. Boggs, Jason D. Bond, Sjirk N. Boon, Jennifer M. Borsavage, Ryan J. Bosca-Harasim, Ryan J. Bosca-Harasim, Satya R. Bose, Todd Bossenberger, Cristina Boswell, Djamal Boukerroui, Christopher M. Bowen, Aaron Brammer, Rich Brancaleoone, Eric Brass, Luis Bravo, William Breeden, Christina Breeze, Eric E. Brost, Justin L. Brown, Karen L. Brown, Marissa Brown, Norman Lee Brown, Payton Brown, Patrick V. Brunick, Ryan Brunkhorst, Gwendolyn P. Brunner, Camelia E. Bunaciu, Maria Bunta, Olwen Burton, Karim Butalag, Priscilla F. Butler, Angela Cagwin, Jeffrey L. Campbell, Warren G. Campbell, Tyler Cantrell, Xu Cao, Yanan Cao, Peter F. Caracappa, Amanda M. Caringi, Joe Caron, Joshua Carter, Kenneth W. Cashon, Sarah Castillo, Everett Cavanaugh, Suran Chae, Abhi Chakrabarti, PhD, Philip Chan, Jina Chang, Sha X. Chang, Youssef M. Charara, Pierre E. Charpentier, Priyanka Chaudhary, Senthamil Selvan Chelliah, Chen Chen, Doris Chen, Kuan Ling Chen, Max Chen, Mingyue Chen, Mu Chen, Xinan Chen, Yie Chen, Yong Chen, Caroline Cheney, Shyh-Shi R. Chern, Stephen Thomas Chesser, Kin Man Cheung, Pai-Chun Melinda Chi, Yuwei Chi, Omar Chibani, Hung Ching, Gwi Ae Cho, Jongmin Cho, David Choi, Wing Yan Choi, Nitish Chopra, Daniel Christ, Olav I. Christianson, Emmanuel Christodoulou, Heeteak Chung, Sophia Claudio, Arely Clavel, William J. Clouse, Gilad Cohen, Michael S. Cohen, Vladimir Collantes, Jason Collier, Jacob Collins, Daria C. Comsa, Charles Conduah, Virgil N. Cooper, Anita M. Corrao, Frank D. Corwin, Mihaela Cosma, Ben Coull-Neveu, Mary K. Cox, Daniel F. Craft, Steven D. Crawford, Troy M. Crawford, Charles E. Creagh, Beatrice Croteau, Camille Crumbley, Wilbert F. Cruz, Guoqiang Cui, J. Adam M. Cunha, Scott Cupp, Bruce H. Curran, Jordan McCauley Cutsinger, Alita D Almeida, Harold DSouza, Nana Dabo-Akoteng, Robert Dahl, Shaun W. Dahl, Ghayath Dakkouri, Malek Daneshvarnezhad, Mylinh Dang, Matt Daniels, George M. Daskalov, David A. Davenport, Amanda Davidek, Scott E. Davidson, Maria De Ornelas, Dylan A. DeAngelis, Mike Deady, Daniel Dean, Savannah Decker, Savannah Decker, Michael Delafuente, Omer Demirkaya, Logan Dempsey, Marc Dennis, Viv Dennis, Dana Derby, Garron A. Deshazer, Veronique Destombes, Ajaya K. Devabhaktuni, Suneetha Devpura, James A. Deye, Shalmali Dharmadhikari, Dominic J. DiCostanzo, Richard V. DiPietro, Emily Diller, Lei Ding, Nayha V. Dixit, Charles Dodge, David N. Dodoo Amoo, Shana Donchatz, Lei Dong, Elangovan Doraisamy, Jennifer E. Dorand, Sarah Driver, Jiayi Du, Michael Duax, Ibrahim M. Duhaini, Ibrahim Duhaini, Kristen Duke, Richard Dunia, Leon Dunn, Shannon R. Durfee, Brittany Earl, Behzad Ebrahimi, Colton Eckert, Hisham Elasmar, John G. Eley, Abdelhamid Elfaham, David C. Ellerbusch, Scott J. Emerson, Sara Endo, David Erickson, Freddy Escorcia, Caroline Esposito, Patrice Essien, Adam Evearitt, Benjamin Fahimian, Liliosa C. Fajardo, Kevin Fallon, Guoqing Fan, Jiahua Fan, Mingdong Fan, Pei Fan, Bing Fang, Jian Fang, Yile Fang, Marc A. Felice, Ye Feng, Michele Sutton Ferenci, Philippe Feru, Jade Alecia Fischer, Aaron Fishbein, Caitlyn M. Fitzherbert, Damian Fondevila, Grant Fong, Robert Wesley Foster, Luke Fourie, Jeffrey Brian Fowlkes, Alexandre Franca Velo, D. Jay Freedman, Ronald W. Frick, Jie Fu, Samuel Fulton, Kamalakar Gaddam, Justin D. Gagneur, Mariana Gallo, Mariana Gallo, David Gammel, Robert G. Gandy, Junfang Gao, Yiming Gao, Victor L. Garcia, Michael Garcia-Alcoser, Jeffrey Garrett, Steven Anthony Gasiecki, Keith Gatermann, Avinash Gautam, Bhoj Gautam, Olivier Gayou, Andrew J. Gearhart, Paul B. Geis, Renil B. George, David P. Gierga, Robert Gilliam, James Giltz, Eric L. Gingold, Frederic Girard, Garth Gladfelder, Sharon Glaze, Brendan K. Glennon, Steven P. Glennon, Guy Godwin, David Lloyd Goff, Lisa M. Goggin, Daniel Goldberg-Zimring, Edward Joseph Goldschmidt, Ehsan Golkar, Angel Gomez, Jason Gong, Manish K. Goyal, Frank Graeff, Royce L. Gragg, Jonathan Gray, Alexander D. Green, Olga L. Green, Andrew Christopher Greene, Travis Greene, Jared Grice, Kevin T. Grizzard, Suveena Guglani, Jeffrey B. Guild, Patrick P. Guo, Sandesh Gupta, Megan Gute, Jonathan Ha, Rachael L. Hachadorian, Christopher Haddad, Lubomir Hadjiiski, Scott W. Hadley, Tomoe Hagio, Kelsey Hall, Logan P. Hall, Klaus A. Hamacher, Amineh Hamad Khatib, Amineh O. Hamad Khatib, Brian R. Hames, Carnell Hampton, Samuel S. Hancock, Robyn S. Handschuh, Jeremy Hansen, Paul Harden, Joseph Harms, Daniel P. Harrington, Carley Harris, Jamie Marie Harris, Jennifer Hart, Richard P. Harvey, Jeremy Hawk, Naoki Hayashi, Maria Laura Haye, Katherine Hazelwood, David Hearshen, Bret H. Heintz, Adam Henry, Frank William Hensley, Michael Chris Hermansen, Marissa Hernandez, Nadia Hernandez, Dayadna Hernandez Perez, Sarah Hetherington, Emily Hewson, Maynard High, Brian P. Hill, Charles B. Hill, Yunsil Ho, Simeon Hodges, David M. Hoeprich, Michael N. Hoff, Robert F. Hoffman, Russell Holden, Clay Holdsworth, Scott Hollingsworth, John R. Holmes, Steve Holmes, Neal S. Holter, Thomas M. Holtschneider, Amirul Hoque, Sabbir Hossain, Tyler S. Howlin, Andrew Robert Hoy, An Ting Hsia, Hao-Yun Hsu, David Hu, Tom C. Hu, Yu-Chi Hu, Long Huang, Mi Huang, Joshua Hubbell, Michael J. Huberts, Julie C. Hudson, Geoffrey Hugo, Donglai Huo, Justin D. Hurley, Martina H. Hurwitz, Mohammad NASEEM Hussain, Andrew Hwang, Ui-Jung Hwang, Joe Ianni, Geoffrey Ibbott, Khalil Ibrahim, Ileana Iftimia, Mohammad Islam, Oleksandra Ivashchenko, Keyvan Jabbari, Joshua Jackson, Joshua Jackson, Ferenc Jacso, Mary Ellen Jafari, Karim Jaffer, Amit Jain, Ngoneh Jallow, Sachin R. Jambawalikar, Joshua A. James, Sunyoung Jang, Desiree Jangha, Tomaj Javidtash, Jun-Hsuang Jen, Peter Jenkins, Todd P. Jenkins, Andrew R. Jensen, Mads Lykke Jensen, Hosang Jin, Bowen Jing, Danielle Marie Johnson, Joshua D. Johnson, Holly Johnston, Kevin Jones, Badal R. Juneja, Nikhil Sriram Kabilan, Robert Kaderka, Jaclyn Kain, Faraz Kalantari, Maduka M. Kaluarachchi, Ali Kamen, Amrit Kaphle, Alireza Kassaee, Saravjeet Kaur, Vaiva Kaveckyte, Linda A. Kelley, Katelyn Kelly, Kathryn Elise Bales Kelly, Delsin B. Khan, Om Khanal, Maksud Khatri, William Steadman Kiger, Bryan Kim, Jong Oh Kim, Sangroh Kim, Sophia Kim, Brian W. King, Erica Kinsey, Assen S. Kirov, Marc T. Kleiman, Matic Knap, Robert J. Kobistek, Inger-Karine Kolkman-Deurloo, Erika Kathryn Kollitz, Dramane Konate, Xiang Kong, Walter Kopecky, Sandra Kos, Nataliya Kovalchuk, Shane Krafft, James A. Kraus, Robert Krauss, Deae-eddine Krim, Serguei Kriminski, Kerry T. Krugh, Lichung Ku, Esra Kucukmokroc, Randi Kudner, Andrew T. Kuhls-Gilcrist, Antti Juhani Kulmala, Akila D. Kumarasiri, Zacariah E. Labby, Taylor Lackey, Edcer Jerecho Laguda, Thang Lam, Michael A. S. Lamba, Kara Lambson, Laurel Zenaida Larramendi, Andy D. Lau, Wolfram Laub, Tyler Laugh, Robert P. Laureckas, Donald Laury, Patricia Lavey, Ashlie Laydon, Adam LeVay, Brandon Lee, Brian Lee, Dong-Chang Lee, Ji Hyun Lee, Jui-Min Lee, Bryan Lemieux, Matthew Lesher, Nicole Leslie, Etienne Lessard, Trish Lewis, Alan Li, Alexander N. Li, Hui Li, Jenny Li, Jiaxin Li, Qiongge Li, Taoran Li, Xiang Li, Yanlong Li, Zisheng Li, Xing Liang, Yun Liang, Chien-Yi Liao, Karisa Liaw, Sung-Yen Lin, Tiffany Lin, Holly M. Lincoln, Lin Ling, Chang Liu, Shaohua Liu, Yu Liu, Chih-Ming Mark Lo, Eric Lobb, Dilson Lobo, Virginia L. Lockamy, Lauren C. Long, Nelia S. Long, Troy Long, Michele Loscocco, Thomas Lowinger, Cynthia Lu, Minghui Lu, Winnie Lu, Yonggang Lu, Jianqiao Luo, Pei-Chin Luo, Xuhan Luo, Jan Luse, Daniel A. Lutterman, Dang Hoang Oanh Luu, Yulia Lyatskaya, Trina Lynd, Morgan Cervo Lyon, Chi Ma, Jingfei Ma, Tianjun Ma, Laurie Madden, Gregory E. Madison, Kurt Maffei, Michael J. Maffett, Nyasha G. Maforo, Dennise Magill, Emma Magness, Alphonso W. Magri, Dennis Mah, Usman Mahmood, Rebecca N. Mahon, Courage Mahuvava, Andrew D. Maidment, Gerassimos M. Makrigiorgos, Harish K. Malhotra, Kate Mallory, P. Scott Mange, Vivek Maradia, Jacob Marasco, Camilla Marino, Loren R. Marous, Wagner Marques, Craig M. Marsden, Edward I. Marshall, Jonathan Marshall, Caroline Martel, Colin Martin, Alejandro Martinez, Jeffrey P. Masten, Richard Mathew, Bobby Mathews, Anetia S. Matthews Jackson, Matthew R. Maynard, Joel R. McAllister, Rafe McBeth, James A. McCulloch, Kiernan T. McCullough, Keelin McGee, Kiaran P. McGee, Brian M. McGill, Christopher M. McGuinness, Robert McKoy, Steven M. McQuiggan, Lacey Medlock, Chirag D. Mehta, Nancy Meiler, Robert Meiler, Matthew A. Meineke, Caroline Melancon, Daniel S. Meleason, Carolyn Meltzer, Chunhua Men, Stephanie Merkl, Michael Merrick, Keith A. Michel, Georgeta Mihai, Ana Mihail, Devin A. Miles, Edward J. Miller, Elizabeth A. Miller, Ronaldo Minniti, Linda Minor, Filmon Misgina, Ajeet Kumar Mishra, Chad Mitchell, Drew P. Mitchell, Gregory S. Mitchell, Jessica Mitchell, Jacqueline Moga, Uwe Mollenhauer, Julien-Fabrice Ngoune Momo, Emi Mondragon, Nicholas Mongillo, Victor J. Montemayor, Scott Montgomery, Diego Luis Montufar Hidalgo, Mohammadamin Moradi, Serban Morcovescu, Jill Anna Moreau, Terrance Moretti, Toby Morris, Courtney K. Morrison, Alexander Albert Morrow, Jill Moton, Jonathon Mueller, Reshma Munbodh, Daniel W. Mundy, Daniela Murgulet, Scott A. Murphy, Benjamin C. Musall, Jana E. Musgrove, Samantha Musial, Yong Hum Na, Joel Nace, Paul Naine, Justin Napolitano, Vrinda Narayana, Ganesh Narayanasamy, Moulay Ali Nassiri, Muhammad Naveed, Richard D. Nawfel, Ritish Nedunoori, Aaron Nelson, Kristin J. Nelson, Aaron Nelson, MD, Neerajan Nepal, Emily Neubauer Sugar, Shree Neupane, David Newey, Mark Newpower, Susan Ng, Bau H. Nguyen, Daniel J. Nicewonger, Xingyu Nie, Ethan Nikolau, Kevin D. Nitzling, Kai Niu, John M. Noll, Prashanth K. Nookala, Khalid Noori, James T. Norweck, Hamidreza Nourzadeh, Jessica L. Nute, Sebastiaan Nysten, Kevin OGrady, Ceferino Obcemea, Keith Ober, Jacqueline Ogburn, Timilehin Ogunbeku, Mina Okello, Brian Olson, Martin Keane Ongeti, Savannah Orrill, Joseph Ott, Bahadir Ozus, Jan Pachon, Alexis Paige-Glenn, Jason Paisley, Farideh Pak, Randahl C. Palmer, Kiran Pant, Virginia Pappas, Abby Pardes, So-Yeon Park, Alexis Parker, Karla Parker, Homayon Parsai, Tommy O. Parsons, Pankaj Patel, Amy Patrick, Johnlly G. Pattaserial, Lindsey M. Patton, Taylor J. Patton, Nava R. Paudel, Timothy John Paul, Colin Paulbeck, Olga V. Pen, Cheng Peng, Yuanlin Peng, Carmelo Perez, Dominik Peruƥko, Alexander Pevsner, Douglas Pfeiffer, Melanie Piantino, Daniel Piatigorski, Rajesh Pidikiti, Natalie Piechowska, Greg Pierce, Tina Pike, Donika Plyku, Robert Pohlman, Mariela Adelaida Porras-Chaverri, Subechhya Pradhan, Guillem Pratx, Chris Proctor, Alexander Pryanichnikov, Diane Pugel, Yue Qiu, Adam C. Quinton, Todd Racine, Andrea Radine, Dustin K. Ragan, Balasubramanian Rajagopalan, Kishore Rajendran, Eric V. Ramirez, Mehdi Ramshad, Vijay K. Rana, Brianne Raulston, Amy K. Readshaw, Hailey Reaux, Ian Reineck, Xuemin Ren, Meral L. Reyhan, Davenport Ria, Matthew J. Riblett, Kenneth M. Richardson, Rebecca F Richardson, Matthew Richeson, Ashlyn Rickard, Adam Riegel, Lynn N. Rill, Miguel A. Rios, E. Russell Ritenour, Scott P. Robertson, Marthony L. Robins, Rebecca Robinson Rey, Steve Rodney, Priscila Rodrigues, Edgardo Rodriguez, Tino Romaguera, Emilie Roncali, Joseph E. Roring, Alison R. Roth, Lawrence N. Rothenberg, Nick Rothwein, Kricia Emilia Ruano Espinoza, Damian DG Rudder, Donald R. Ruegsegger, Erwin W. Ruff, Brandon J. Russell, Frederick Rustad, Narayan Sahoo, Jonathan H. Saleeby, Habeeb H. Saleh, Flavio Salinas Aranda, Steffen Sammet, Daniel Sandoval, Aman Sangal, Joseph P. Santoro, Maíra Santos, Alexis Marie Sanwick, Milind Sardesai, Vikren Sarkar, Duminda Satharasinghe, Jessica L. Saunders, Carmen Sawyers, Sarah B. Scarboro, James Scheuermann, Colleen G. Schinkel, Dale Schippers, Joshua William Schlegel, David J. Schlesinger, Charles Ross Schmidtlein, Erich Schmitz, Jose Schneider, Erich A. Schnell, Lisa Schober, Leah Schubert, Michelle L. Schwer, James Seekamp, Jennifer Seger-Paisley, J. Anthony Seibert, Balaji Selvaraj, Raj N. Selvaraj, Meredith A. Semon-Pomposelli, Lasitha Senadheera, Naima Senhou, Christopher F. Serago, Hananiel Setiawan, Shakil B. Shafique, Aarti Shah, Hina Shah, Alok Shankar, Ryan Shanks, Kritika Sharma, Sunil K. Sharma, Jennifer M. Shealy, Ron Sheen, Gina L. Shelton, Mohammad Ullah Shemanto, Zion Sheng, Andrew J. Shepard, Justin R. Sherman, Kaizhong Shi, Xiaolin Shi, J. Allen Shih, Taciana Soares Shiue, Deborah J. Shumaker, Noah Silverberg, Ramon Alfredo C. Siochi, Amogh Sirniirkar, Marlene Skopec, Michael G. Skowronski, Dana Smetherman, Erika Smith, Eileen Sneeden, Jesse Snyder, James C. So, Emilie Soisson, Nima Soltani, Kwang Hyun Song, Liang Song, Xiaoling Song, Jigar B. Soni, Yashvant C. Soni, Jagadeesh R. Sonnad, Michael A. Speidel, Michael P. Speiser, James D. Speitel, Tanya Spellman, Joseph Patrick Speth, Daniel J. Spitznagel, Sara T. St. James, Alexander Stanforth, George Starkschall, James Stebelton, James P. Steinman, Jonathan M. Stenbeck, Robin L. Stern, Patrick D. Stevens, Erika Stewart, Gary Stinnett, Sarah A. Strand, Keith J. Strauss, Kristen Stryker, Edward Sudentas, Kevinraj N. Sukumar, Orhan H. Suleiman, John L. Sullivan, Paul Robert Sullivan, Mei Sun, Peng Sun, Kumari Sunidhi, Jacob Sunnerberg, Elizabeth A. Swanson, William J. Swanson, Larry E. Sweeney, Sean Swiedom, Gregory Szalkowski, Katsuyuki Taguchi, MohammadAli Tajik-Mansoury, Reza Taleei, Derek Tang, Shengzhang Tang, Mahin Tariq, Jason S. Tavel, Neelima Tellapragada, Alexandra Tellez, Dawn Tellez, Juan Manuel Tellez, Xiaokun Teng, James A. Terry, Biniam Tesfamicael, Confex Test, Aapm Tester, Contex Tester, Namita Thakur, David J. Theel, Kathleen D. Thomas, Emily A. Thompson, Stephen K. Thompson, Daniela Thorwarth, Kevin Tierney, Anders Tingberg, Ragu S. Tirukonda, Robert A. Tokarz, Robert J. Tokarz, Naresh B. Tolani, Brian Tom, Shidong Tong, Ebrahim Torangan, Martin Tornai, Diana Tovmasian, Trung Tran, Bryan Traughber, Samuel Trichter, Sugata Tripathi, Petra Trnkova, Panagiotis Tsiamas, Ryan Tsiao, Haifeng Tu, Philip N Tubiolo, Jeff D. Turley, Adam Turner, PhD, DABR, Conner Ubert, Chibueze Zimuzo Uche, Vincent M. Ulizio, Gnanaprakasam Vadivelu, Hema Vaithianathan, Sunil Valaparla, Fabiola Vallejo Castañeda, Liesbeth Vancoillie, Matt Vanderhoek, Caroline Vanderstraeten, Nancy J. Vazquez, Linda A. Veldkamp, Trevor L. Vent, Anthony M. Ventura, Keith Ver Steeg, Irina Vergalasova, CHENG WANG, Christopher Waite-Jones, Matthew C. Walb, Reuben Waldron, Arlie Vester Walker, Jim Walsh, Alisa I. Walz-Flannigan, Cheng Wang, Helen H. Wang, Hui-Chuan Wang, Jiali Wang, Jian-xiong Wang, Kai Wang, Kyle Wang, Ning Wang, Yuntao Wang, Zhendong Wang, Zhixing Wang, Grace Ward, Sarah M. Way, Rachel L. Waymire, Melvin Weatherly, Charles Travis Webb, Lincoln J. Webb, Jia Wei, Wenbo Wei, Callie Weiant, Miriam S. Weiser, Eric M. Welch, Jered R Wells, Michelle C. Wells, S. Brock Westlund, Gerald A. White, John White, Darunee S. Whitt, David Wikler, Austin Wilkinson, Carly D. Williams, Mark Bennett Williams, Joshua M. Wilson, Keli C. Wilson, Nicholai Wingreen, Joseph Wishart, Alon Witztum, Katherine M. Woch Naheedy, Andy Wolf, Serkalem E. Wondimgezhu, Genevieve N. Wu, Wenhao Wu, Ye Wu, Yuxiang Xing, Li Xiong, Weijun Xiong, Xunyi Xu, Yan Xu, Tianyou Xue, Yanjie Xue, Girijesh K. Yadava, Derek Z. Yaldo, Kaiguo Yan, Yue Yan, Nathan E. Yanasak, Bowen Yang, Ray Yang, Xiaocheng Yang, Yun Yang, Yunze Yang, Bin Yao, Yuan (John) Yao, Anna N Yaroslavsky, Feng-Ju Yeh, Susanne Yerich, Michael V. Yester, Xiaofei Ying, Tekeste Yohannis, Tony Younes, Eyesha Younus, Jialu Yu, Justin Yu, Yan Yu, Pui Kuen Yuen, Joshua P. Yung, Steve Yuvan, Mehran Miron Zaini, Ramtin Zakikhani, Lee Anne Zarger, Merissa Zeman, Lisa Zent, Di Zhang, Dongqing Zhang, Hao Zhang, Jun Zhang, Lei Zhang, Lu Zhang, Maochen Zhang, Peng Zhang, Peng Zhang, Qingyun Zhang, Xin Zhang, Yi Zhang, Yinghui Zhang, Yongbin Zhang, Zhongwei Zhang, Bo Zhao, Xuandong Zhao, Yizhou Zhao, Weiping Zheng, Yi Zheng, Troy Zhou, Xiangzhi Zhou, Xiaohong Joe Zhou, Yuwei Zhou, Jin Zhu, Mingyao Zhu, Eric C. Zickgraf, John R. Zullo, Piotr Zygmanski, Leo van Battum

Affiliation: DTC Consultants, NL Health, Dartmouth Hitchcock Medical Center, ProCure Proton Therapy Center, Medical & Radiation Physics, Inc, Augusta University, Genesis Healthcare Partners, Michigan Medicine, Washington DC VA Medical Center, VA Medical Center, Mercy Southeast Hospital, Food And Drug Administration, University of Iowa, Advanced Radiation Physics Service, Inc, University of Pittsburgh, University of Wisconsin, Wellspan Health, Good Samaritan Hospital, Howard University Hospital, St. Mary's Memorial Health Center, Penn State Milton S. 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Abstract Preview: N/A...

Novel 915 MHz Annular Phased Array Applicator for Hyperthermia Treatment of Brain Lesions

Authors: Jason Ellsworth, Mark Mishra, Jason K Molitoris, Lei Ren, Dario B. Rodrigues, Paul Turner, Graeme Woodworth

Affiliation: University of Maryland School of Medicine, Department of Neurosurgery, University of Maryland School of Medicine, University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine, Pyrexar Medical

Abstract Preview: Purpose: Hyperthermia therapy (HT) involves increasing tumor temperatures to 40-44°C and is a potent radio- and chemosensitizer for treating solid tumors. Current clinical strategies to heat deep-seat...

Novel Use of 3D Printing for Pre-Operative Dose Estimation in the First Case of Gammatile Spine Implantation

Authors: Ali Al Asadi, Amanda Lynn DiCarlo, Anthony J. Doemer, Jessie Y. Huang, Ian Y Lee, Alexandra Moceri, Adam Robin, Lisa Scarpace, Mira Shah, Salim Siddiqui, Kundan S Thind

Affiliation: Henry Ford Innovations, Henry Ford Health

Abstract Preview: Purpose: For a patient who had two previous courses of external beam therapy for rectosigmoid adenocarcinoma and presented with painful, recurrent disease in the sacrum, this study describes the first...

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...

Physics and Geometry Input-Based Neural Network Dose Engine

Authors: Ricardo Garcia Santiago, Narges Miri, Daryl P. Nazareth, Ankit Pant, Mukund Seshadri

Affiliation: Roswell Park Comprehensive Cancer Center

Abstract Preview: Purpose: To develop a transformer-based deep learning network framework for predicting VMAT dose distributions. This can provide fast and efficient calculations with accuracies potentially comparable ...

Python-Native Cerr for Cloud-Based Medical Image Analyses

Authors: Aditya P. Apte, Joseph O. Deasy, Sharif Elguindi, Aditi Iyer, Jue Jiang, Eve Marie LoCastro, Jung Hun Oh, Amita Shukla-Dave, Harini Veeraraghavan

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

Abstract Preview: Purpose: We present port of popular Computational Environment for Radiological Research software platform to Python programming language to cater to cloud-based analyses.
Methods: The components of...

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

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

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

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

SRS Treatment Planning for Brain Metastases on Varian Truebeam and Elekta Gamma Knife Icon

Authors: Carl D. Elliston, Lawrence Koutcher, Michael J. Price, Adam C. Riegel, Michael B Sisti, Tony J.C. Wang, Andy (Yuanguang) Xu

Affiliation: Columbia University Irving Medical Center

Abstract Preview: Purpose: An inverse treatment planning software was recently introduced to Gamma Knife radiosurgery. The purpose of this study is to compare the plan quality of the Gamma Knife ”Lightning” with that o...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu

Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...

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...

Spherical Slicing and Convolutions for Accurate Glioma Tumor Segmentation Using Multi-Parametric MRI

Authors: Ke Lu, Chunhao Wang, Ruoxu Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lei Zhang, Rihui Zhang, Jingtong Zhao, Haiming Zhu

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

Abstract Preview: Purpose: The human brain’s spherical geometry offers unique opportunities for improving the segmentation of tiny and irregular anatomical structures. We hypothesize that representing the brain in sphe...

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...

Universal MR-to-Synthetic CT: A Streamlined Framework for MR-Only Radiotherapy Planning

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:
Converting MR images to synthetic CT (MR2sCT) is highly desirable as it streamlines the radiotherapy treatment planning workflow. This approach leverages the superior soft tissue visibilit...

Workflow for Same Day Linac-Based Stereotactic Radiosurgery

Authors: William Amestoy, Carolina Benjamin, Markus Bredel, Rodrigo Delgadillo, Nesrin Dogan, Michael E Ivan, Ricardo J Komotar, Gregory J. Kubicek, Eric Mellon, Ivaylo B. Mihaylov, Maria Irene Monterroso, Raymond A. Schulz, Ashish Shah, Robert M Starke

Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, Varian Medical Systems

Abstract Preview: Purpose: Stereotactic Radiosurgery (SRS) is a widely used treatment modality in radiation oncology, utilizing various technologies such as Gamma Knife (GK), Cyber Knife (CK) and Linac-based SRS with H...