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Results for "multi path": 12 found

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...

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...

Cross Characterization of a 3D Gamma Camera and Ring Brachytherapy Applicator

Authors: Zachary R. Grelewicz, Kevin C. Jones, Yixiang Liao, Andrew Ogilvy, Julius V. Turian

Affiliation: Rush University Medical Center

Abstract Preview: Purpose: To demonstrate the accuracy and QA application of a time-resolved 3D gamma camera, we measured the path traversed by the Ir-192 High-Dose-Rate (HDR) brachytherapy source passing through a rin...

Development of a Radiomics-Dosiomics Mcode Ontology Extension for Radiotherapy

Authors: John Kildea, Odette Rios-Ibacache, Amal Zouaq

Affiliation: McGill University, Polytechnique MontrΓ©al

Abstract Preview: Purpose:
Even though Electronic medical records (EHRs) are now in widespread use in healthcare, and Artificial Intelligence tools incorporating radiomics are used to identify tumors in medical imag...

Evaluation of Hybrid Dynamic Conformal Arc Planning for SRS and SBRT Treatment

Authors: Pat Esposito, Ashley Klein, Carmine Verna, Ling Zhuang

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: To evaluate dosimetric parameters and treatment delivery efficiency between volumetric modulated arc therapy (VMAT) and hybrid dynamic conformal arc (HDCA) on SRS and SBRT planning through st...

Interpretable Deep Learning Predicts Metastasis-Free Survival (MFS) from Conventional Imaging for Oligometastatic Castration-Sensitive Prostate Cancer (omCSPC) Using Multi-Modality PSMA PET and CT Imaging.

Authors: Yufeng Cao, Luigi Marchionni, William Silva Mendes, Cem Onal, Lei Ren, Amit Sawant, Nicole L Simone, Philip Sutera, Phuoc Tran

Affiliation: University of Maryland School of Medicine, 9Department of Radiation Oncology, Thomas Jefferson University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, University of Maryland, Baltimore, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine, Maryland University Baltimore, 8Department of Pathology and Laboratory Medicine, Weill Cornell Medicine

Abstract Preview: Purpose: This study aims to predict 2-yr Metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) patients treated by metastasis-directed therapy (MDT) by devel...

Multi-Center Evaluation of an AI Beam Angle Prediction Model for Liver Treatments Using Pencil Beam Scanning Proton Therapy

Authors: Christopher Ackerman, Chang Chang, Yan-Cheng Huang, Robert Kaderka, Che Lin, Hsin-Chih Lo, Iain MacEwan, Yi-Chin Tu, James Urbanic

Affiliation: University of California San DIego, Taiwan AI Labs, National Taiwan University, California Protons Cancer Therapy Center, University of Miami, Sylvester Comprehensive Cancer Center

Abstract Preview: Purpose: To investigate the performance of an existing AI beam angle prediction model on external patient datasets for liver proton treatments. The AI model was trained on datasets exclusively from on...

Multi-Path Deep Learning Model for Predicting Post-Radiotherapy Functional Liver Imaging in Patients with Hepatocellular Carcinoma

Authors: Smith Apisarnthanarax, Stephen R. Bowen, Sunan Cui, Jie Fu, Clemens Grassberger, Yulun He, Yejin Kim, Matthew J. Nyflot, Sharon Pai

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Washington, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Physics, University of Washington, University of Washington and Fred Hutchinson Cancer Center

Abstract Preview: Purpose: 99mTc-sulfur colloid SPECT imaging enables quantitative assessment of voxel-wise liver function in patients with hepatocellular carcinoma (HCC). Accurately predicting post-radiotherapy (RT) l...

Noise Sensitivity of Benchmark Whole-Body CT Segmentation Models: Totalsegmentator and Vista3D Performance on an Independent Dataset

Authors: Samuel L. Brady, Shruti Hegde, Alexander Knapp, Usman Mahmood, Joseph G. Meier, Elanchezhian Somasundaram, Zachary Taylor

Affiliation: Cincinnati Children's Hospital Medical Ctr, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Cincinnati Children's Hospital Medical Center, Cincinnati Childrens Hospital Med Ctr

Abstract Preview: Purpose:
To assess how two benchmark multi-organ CT segmentation models respond to varying image noise levels.
Methods:
This study utilized the pediatric CT dataset from The Cancer Imaging Ar...

Optimized Dosimetric Planning for Trigeminal Neuralgia Using Cyberknife S7 Precision TPS with Volo Optimizer

Authors: Amy Fitzpatrick, Kim Howard, Julius G. Ojwang, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: This study evaluates the dosimetric advantages and workflow improvements of the CyberKnife S7 Precision Treatment Planning System (TPS) with the VOLO optimizer for stereotactic radiosurgery (...

Reinforcement Learning Based Machine Parameter Optimization for Two-Arc Prostate VMAT Planning

Authors: William T. Hrinivich, Junghoon Lee, Lina Mekki

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

Abstract Preview: Purpose: Volumetric modulated arc therapy (VMAT) planning is a computationally expensive process. In this work, we propose a reinforcement learning (RL) framework to automatically optimize dose rate a...

Water-Equivalent Thickness Mapping (WET-MAP) – a Potential Alternative to 4D Robust Optimization for Motion Management in Proton Treatment Planning

Authors: Duncan Henry Bohannon, Pretesh Patel, Sibo Tian, Yinan Wang, Xiaofeng Yang, Ahmal Jawad Zafar, Jun Zhou

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

Abstract Preview: Purpose:
4D robust optimization, incorporating additional images (e.g., maximum inhale/exhale phases), is commonly used to account for target motion in proton treatment planning. However, the incre...