Search Submissions πŸ”Ž

Results for "multiple brain": 32 found

A Clinically Aligned Embedding Model for Glioma Prognostication Via Radiology-Pathology Report Matching

Authors: Steve Braunstein, Yannet Interian, Hui Lin, Bo Liu, Janine Lupo, Olivier Morin, Benedict Neo

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 Data Science, University of San Francisco, University of San Francisco

Abstract Preview: Purpose: Large Language Models (LLMs) demonstrate strong general text comprehension but remain limited in oncology due to insufficient contextual alignment. We pilot embedding alignment through radiol...

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 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...

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

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

Affiliation: Kaiser Permanente

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

Assessment of the Radiological Features of 3D-Printed Polylactic Acid Composites for Creating Personalized Dosimetric Phantoms

Authors: Ashish Binjola, Raj Kishore Bisht, Natanasabapathi Gopishankar, Pratik Kumar, Daya Nand Kishore Sharma, Sukhvir Kishore Singh, Subramani Vellaiyan

Affiliation: Medical Physics Unit, All India Institute of Medical Sciences, All India Institute of Medical Sciences, Department of Radiological Safety, Institute of Nuclear Medicine and Allied Sciences, Department of Radiation Oncology, All India Institute of Medical Sciences

Abstract Preview: Purpose: Additive manufacturing is increasingly being explored to create dosimetry phantoms. Commercial anthropomorphic phantoms represent an average patient and lack anatomical variations due to obes...

Asymmetrical High Performance Brain Dedicated PET System: Design Optimization and Performance Evaluation

Authors: Yuemeng Feng, Hamid Sabet

Affiliation: Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: We propose a novel brain-dedicated PET system comprising elliptical cylinder with a neck cut-out, supplemented by front and back panels to improve sensitivity and line-of-response sampling. T...

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...

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 Auto Segmentation of Oars in Head and Neck Radiation Therapy

Authors: Laila A Gharzai, Bharat B Mittal, Poonam Yadav

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

Abstract Preview: Purpose: Multiple studies have shown the increasing role of deep learning in segmenting regions of interest. This work presents the feasibility of auto-segmenting the critical structures for head and ...

Design and Testing of a Portable Microwave Scanner for Imaging Soft Tissue and Tumors in Cancer Patients

Authors: Imad M. Ali, Nesreen Alsbou, Sakeeneh Majeed

Affiliation: University of Central Oklahoma, University of Oklahoma Health Sciences Center

Abstract Preview: Purpose: to design and assess a microwave imaging system equipped with multiple antennas for generating high-resolution 3D images of phantom models that simulate abdominal, thoracic, and brain tissues...

Development and Clinical Validation of a Tissue Maximum Ratio (TMR)-Based Monitor Units Second Check Script for Dynamic Conformal-Based Hyperarc Brain Radiosurgery Plans Via Scatter Correction Factors

Authors: Jacob Gooslin, Ellis Lee Johnson, Damodar Pokhrel

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

Abstract Preview: Purpose: HyperArc radiosurgery permits treatment of multiple brain lesions using a single-isocenter improving treatment planning efficiency and workflow. A key stereotactic planning aspect is an indep...

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...

Dose Evaluation of Multiple Gammatiles in Heterogeneous Brain Models Using Egs_Brachy

Authors: Fatemeh Akbari, Artemis Dalby, Nelson A. Miksys, Prarthana Pasricha, Rowan M. Thomson

Affiliation: Ackerman Cancer Center, Carleton University

Abstract Preview: Purpose: To investigate dose evaluations for GammaTile brachytherapy, a novel treatment for brain malignancies. The analysis focuses on the impact of tissue heterogeneities, including the presence of ...

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...

Dual-Branch Attention-Driven Network for Enhanced Sparse-View CBCT Reconstruction Using Planning CT As Prior Knowledge

Authors: Xiaoyi Dai, Manju Liu, Weiwei Sang, Pulin Sun, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
Current deep learning-based sparse-view CBCT reconstruction methods are prone to hallucinatory artifacts, as they rely on inferred image details that may not correspond to true anatomical ...

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...

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. ...

Investigation of the Correlation between Proton Linear Energy Transfer and Treatment Field Hinge Angles in Brain Tumor Patients Treated with Intensity Modulated Proton Therapy

Authors: Omer Gal, Alonso N. Gutierrez, Matthew D. Hall, Rupesh Kotecha, Minesh P. Mehta, Andrew J. Wroe, Jen Yu

Affiliation: Miami Cancer Institute, Baptist Health South Florida

Abstract Preview: Purpose: Linear energy transfer (LET) is directly related to relative-biological-effectiveness dose in proton therapy. This study aims to investigate how the treatment field hinge angles affect LET of...

Investigation of the Impact of Dlg Changes on Plan Quality and Patient Specific QA

Authors: Nicole C. Detorie, Steven M. Kirsner, Remy Y. Manigold

Affiliation: Scripps Cancer Center

Abstract Preview: Purpose:
Dosimetric Leaf Gap (DLG) is an important factor in obtaining the proper beam model in the Eclipse treatment planning system. The purpose of this study was to investigate the dosimetric im...

Isocenter Optimization for Linear Accelerator-Based Radiosurgical Treatment Planning for Multiple Brain Metastases

Authors: J. Daniel Bourland, Christina K Cramer, Justin M. Napolitano, James D. Ververs

Affiliation: Wake Forest University School of Medicine

Abstract Preview: Purpose:
Brain metastases (BM) can be treated with linear accelerator (LINAC)-based stereotactic radiosurgery (SRS). Treatment planning for this modality has evolved over time; treatment plans typi...

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...

Multiple x-Ray Source Array (MXA) System Development for Better Ray Sampling in Large Coverage Axial CT Imaging

Authors: Craig K Abbey, John M. Boone, Richard E. Colbeth, Andrew M. Hernandez, Sarah E. McKenney, Vance Robinson, Paul Schwoebel, Jeffrey H. Siewerdsen, Alejandro Sisniega, Wojciech B. Zbijewski

Affiliation: UC Santa Barbara, University of California, UT MD Anderson Cancer Center, Johns Hopkins University, University of New Mexico Albuquerque, UC Davis Health, Varex Imaging Corporation

Abstract Preview: Purpose:
While wide coverage (160 mm) CT scanners can image whole organs (e.g. heart, brain, kidneys, etc.) in one axial scan, the peripheral regions of the field of view (along z) suffer from cons...

Neutron Dose Measurements with Multiple Dosimetry Techniques for Fetal Dose Estimation

Authors: Ahmet S. Ayan, Estelle Batin, Austin M. Faught, Peter E. Klages, Eunsin Lee, Collin Nappi, Mina Okello, Meghana Ramani, Zachary X. Richards, Parisa Sadeghi

Affiliation: Department of Radiation Oncology, The Ohio State University Wexner Medical Center, The Ohio State University Wexner Medical Center, Ohio State University, The Ohio State University

Abstract Preview: Purpose: Neutron doses are not modelled in proton treatment planning systems, so measurements were taken with two independent dosimeter types to quantify representative neutron fetal doses in pencil b...

Novel AI-Powered Tool to Objectively Evaluate Brain Dose for Multi-Met Stereotactic Radiosurgery Optimization

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Richard A. Popple, Wenyin Shi, Rodney J. Sullivan, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

Affiliation: Thomas Jefferson University, The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: Objectively evaluating brain sparing as a plan-quality indicator for patients receiving stereotactic radiosurgery (SRS) to multiple metastases (multi-met) is complicated by variability in tar...

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...

Predicting Brain V60% in Linac-Based Single-Isocenter-Multiple-Targets (SIMT) Stereotactic Radiosurgery Using Machine Learning

Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...

Pulse-Based Method of Electrometer Calibration for High Instantaneous Currents Produced in Ultra-High Dose per-Pulse Electron Beams

Authors: Wesley S. Culberson, Miguel Angel Flores Mancera, Jeff Radtke

Affiliation: Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison

Abstract Preview: Purpose: Electrometers are fundamental instruments for absorbed dose determination, and their accuracy is strongly dependent on their calibration. The standard procedure of electrometer calibration is...

QA Your Way: A Customizable 3D Printed CT Simulator Monthly QA Phantom

Authors: Paul J. Black, Jordan B Lunsford, James D. Ververs, India Wood

Affiliation: Atrium Health Wake Forest Baptist, Wake Forest University School of Medicine, Wake Forest School of Medicine

Abstract Preview: Purpose:
To develop a 3D-printed modular CT simulator phantom that allows the assessment of all AAPM TG-66 recommended monthly quality assurance (QA) tests.
Methods:
A modular CT simulator mo...

Robust and Radiobiologically Accurate Dose Summation Strategy for Multiple Courses of Stereotactic Re-Irradiation of Metastatic Brain Cancer Patients with Previous WBRT

Authors: Garrett Russell Hamilton, Joshua Misa, Damodar Pokhrel, William St. Clair

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

Abstract Preview: Purpose: Recurrent brain metastasis is very common, and patients who previously received whole-brain radiotherapy (WBRT) may receive an additional course(s) of stereotactic radiosurgery (SRS) to selec...

Target Region-Specific Dose-Volume Parameters for Estimate of Brain Toxicity in Single-Isocenter Multiple-Metastases Linac-Based Stereotactic Radiosurgery

Authors: David L. Barbee, Jose R. Teruel Antolin, Jinyu Xue

Affiliation: NYU Langone Health

Abstract Preview: Purpose: This work introduces a method of regional dose evaluation of normal brain tissue using local target-specific evaluation and compares to global dose evaluation for linac-based single-isocenter...

Uncertainty Analysis of Hyperarc VMAT Plans for Stereotactic Radiosurgery Patients with Multiple Brain Metastases

Authors: Shifeng Chen, Yannick P. Poirier, Huijun Xu, Byong Yong Yi, Baoshe Zhang, Hong Zhang, Jinghao Zhou

Affiliation: University of Maryland School of Medicine, University of Maryland Shore Regional Cancer Center, Vanderbilt University Medical Center, Department of Radiation Oncology, University of Maryland School of Medicine, Capital Region Medical Center

Abstract Preview: Purpose: To thoroughly assess the resilience of HyperArc VMAT plans for multiple brain metastases (MBT) in relation to (i) high-definition MLC leaf positional inaccuracies and (ii) patient rotational ...

Using a-Si 1200 Epid Portal Dosimetry for VMAT Commissioning

Authors: Ryan Burri, Nazanin Hoshyar, Jerry W. McCoy, Yulin Song, Huma Syed

Affiliation: Bay Pines VA Medical Center

Abstract Preview: Purpose: The study aimed to streamline traditionally manual, iterative, and time-consuming VMAT commissioning process. The goal was to identify an optimal set of MLC dosimetric parameters that minimiz...