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Results for "brain lesions": 28 found

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 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 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...

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 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...

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...

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 ...

Compressed Sensing Enhanced Radiomic Feature Selection for 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 new treatment paradigm pioneered by our institution. But the early decision-making process in PULSAR is challe...

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...

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...

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 Deep Learning Model for Accurate Brain Dose Prediction in Multi-Target Stereotactic Radiosurgery Plan Evaluation

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Wenyin Shi, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Multi-target stereotactic radiosurgery (SRS) planning poses challenges due to complex geometries, small target volumes, and steep dose gradients. Achieving a balance between target coverage a...

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 Variations Induced By Inaccurate Collimator Angles in Single-Isocenter SRS Plan for Multi-Lesion Brain Metastases

Authors: Makunda Aryal, Gregory Bartlett, David D. Campos, Ke Colin Huang, Sook Kien Ng, Christopher F. Njeh, Oluwaseyi Oderinde, Edwin Quashie, Ashok Tiwari, Yong Yue

Affiliation: Purdue University, Department of Radiation Oncology, Indiana University, Indiana University, Indiana University School of Medicine, Department of Radiation Oncology

Abstract Preview: Purpose:
Linear accelerator-based single-isocenter Stereotactic Radiosurgery (SRS) is widely used for treating brain metastases due to its efficiency, reduced treatment time, and lower imaging dose...

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...

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...

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...

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 40-44Β°C and is a potent radio- and chemosensitizer for treating solid tumors. Current clinical strategies to heat deep-seat...

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...

Retrospective Analysis of Treatment Pauses Due to Intrafraction Movement for Frameless Single Fraction Gamma Knife Icon Radiosurgery

Authors: Nina Burbure, Tawfik G. Giaddui, Shidong Li, Curtis Miyamoto, Jeremy Price, Bin Wang

Affiliation: FCCC at Temple University Hospital

Abstract Preview: Purpose: Frameless gamma knife (GK) treatments use a thermoplastic mask coupled with high-definition motion management system that utilizes an infrared camera, and a reflective marker placed on the pa...

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...

To Establish Local Diagnostic Reference Levels (DRLs) for Head and Neck Computed Tomography (CT) Exams in Abuja, Nigeria, and to Investigate the Performance of Brain Metastasis (BM) and Brain Lesion (BL) Segmentation Techniques Using U-Net Models.

Authors: Nuraddeen Nasiru Garba, Kalpana M Kanal, Abdullahi Mohammed, Rabiu Nasiru, Muhammad SHAFIU Shehu, Daniel Vergara, Joseph Everett Wishart

Affiliation: AHMADU BELLO UNIVERSITY, ZARIA, University of Washington

Abstract Preview: Purpose: To establish local Diagnostic Reference Levels (DRLs) for head and neck computed tomography (CT) exams in Abuja, Nigeria, and to investigate the performance of brain metastasis (BM) and brain...

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 ...