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Results for "computational framework": 23 found

A Deep Learning-Based Method for Rapid Generation of Spot Weights in Single Field Optimization for Proton Therapy in Prostate Cancer

Authors: Yu Chang, Mei Chen

Affiliation: Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine

Abstract Preview: Purpose: Spot weights optimization, as a critical step in the proton therapy, is often time-consuming and labor-intensive. Deep learning, with its powerful learning and computational efficiency, can e...

A Framework for Automated Selection of Dose-Volume Objectives to Improve Radiation-Induced Immune Suppression (RIIS)-Related Overall Survival (OS) Following Chemo-Radiotherapy

Authors: Gabriel Lucas Andrade de Sousa, Einsley-Marie Janowski, Cam Nguyen, Krishni Wijesooriya

Affiliation: Department of Radiation Oncology, University of Virginia, Department of Physics, University of Virginia

Abstract Preview: Purpose: Optimizing radiation therapy (RT) to spare the immune system may improve Overall Survival (OS) in cancer patients. This study develops a computational algorithm to identify optimal dose-volum...

A Monte Carlo Simulation Framework for Investigating the Effect of Inter-Track Coupling on H2O2 Productions at Ultra-High Dose Rates

Authors: Ramin Abolfath, Sedigheh Fardirad, Abbas Ghasemizad, Houda Kacem, Marie Catherine Vozenin

Affiliation: University of Guilan, Universite de Lausanne, University Hospital, Geneva, Howard University

Abstract Preview: Purpose: Lower production of H2O2 in water is a hallmark of ultra-high dose rate (UHDR) compared to the conventional dose rate (CDR). The current computational models are in the opposite of the experi...

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

Authors: Amir Abdollahi, Oliver Jäkel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome

Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH

Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...

An Experimentally Derived Microscale Blood and Lymphatic Vasculature Model for Applications to Radiopharmaceutical Dosimetry

Authors: Peter Balogh, Wesley E. Bolch, Mir Md Nasim Hossain, Nien-Wen Hu, Walter Murfee, Wyatt Smither, Julia D. Withrow

Affiliation: New Jersey Institute of Technology, University of Florida

Abstract Preview: Purpose: To develop 3D computational, tissue-representative models incorporating physiologically relevant microvascular network patterns for calculating local alpha particle and electron dosimetry eff...

An Ultra-High Parallel Performance (UHPP) Framework for Highly Complex Radiotherapy Planning

Authors: Lu Jiang, Shusen Jing, Qihui Lyu, Dan Ruan, Ke Sheng, Qifan Xu

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: In radiotherapy, the conformity and compactness of dose distribution are vital to patient outcomes. The introduction of highly complex planning, such as 4π radiotherapy, has provided a system...

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...

Beam Orientation Optimization in IMRT Using Sparse Mixed Integer Programming and Non-Convex IMRT Fluence Map Optimization

Authors: Yabo Fu, Yang Lei, Yu Lei, Haibo Lin, Ruirui Liu, Tian Liu, Kenneth Rosenzweig, Charles B. Simone, Shouyi Wei, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York Proton Center

Abstract Preview: Purpose: Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is traditionally a complex, non-convex problem tackled with heuristic methods. This study benchmarks global...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Cloud Workflow AI Apps for Radiotherapy Image Analysis Using Pycerr and Seven Bridges-Cancer Genomics Cloud

Authors: Aditya P. Apte, Joseph O. Deasy, Sharif F. 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 publicly shareable applications (apps) for AI-based radiotherapy segmentation workflows with pyCERR on Seven Bridges Cancer Genomics Cloud-based platform (CGC-SB)
Methods: Runni...

Convergence Speed Advantages of a Machine Learning Assisted Framework in IMRT Fluence Map Optimization – a Comparison Study Using Multiple Convergence Criteria

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose: Convergence speed is crucial for an optimizer. Faster convergence leads to better solutions with fewer iterations and less time. Recently, a machine learning (ML)-assisted framework employing...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity

Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...

Development and Clinical Validation of an Analytical Approach for 3D Positron Emitter Distribution Prediction in Carbon Ion Therapy

Authors: Julia Bauer, Tianxue Du, Katia Parodi, Marco Pinto, Thomas Tessonnier

Affiliation: Department of Medical Physics, Ludwig-Maximilians-Universität (LMU) München, Heidelberg Ion Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich)

Abstract Preview: Purpose:
Carbon ion therapy could benefit from range verification due to its sensitivity to range uncertainties. Positron emission tomography (PET) aids in this and comparing irradiation-induced PE...

Evaluating Tumor Shrinkage Using Fractionated Radiotherapy: A Mixed Finite Element Method (FEM) for Free Boundary Problem

Authors: Xianjin Dai, PhD, Xiang Wan, Lei Xing, Qiuyun Xu, Lewei Zhao, Zeyu Zhou

Affiliation: Department of Radiation Oncology, Stanford University, Carl Zeiss X-ray Microscopy, Department of Mathematics and Statistics, Loyola University Chicago, Department of Radiation Oncology, City of Hope National Medical Center

Abstract Preview: Purpose: The purpose of this study is to examine and quantify tumor shrinkage over time in response to fractionated radiotherapy. We seek to establish a predictive model that can provide a systematic ...

Film-Based Method for Accurate Radiation Isocenter Determination in Linear Accelerators Using 3D Starshot

Authors: Robert A. Corns, Mohammad Kanber

Affiliation: East Carolina University, East Carolina University Brody School of Medicine

Abstract Preview: Purpose:
Accurate determination of the radiation isocenter is crucial for precise radiotherapy treatments, directly impacting patient safety and treatment quality. This study presents a computation...

First Demonstration of Prostate Radiotherapy Plan Optimization on an IBM Quantum Computer

Authors: Keisuke Fujii, Masahiro Kitagawa, Arezoo Modiri, Yuichiro Nakano, Ken N. Okada, Robabeh Rahimi, Akira SaiToh, Amit Sawant, Satoyuki Tsukano, Baoshe Zhang

Affiliation: University of Maryland, University of Maryland in Baltimore, Department of Computer and Information Sciences, Sojo University, Center for Quantum Information and Quantum Biology, Osaka University, Maryland University Baltimore, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Fully personalized radiotherapy requires computational resources far exceeding those of conventional CPU/GPU systems. This study explores the use of quantum computing (QC) in radiotherapy pla...

Implementation of Radiochemotherapy Applied to Virtual Spheroids Using an Open-Source Multiscale Computational Framework

Authors: Ignacio Espinoza, Ignacio Narea, Beatriz Sanchez-Nieto

Affiliation: Institute of Physics, Pontificia Universidad Católica de Chile

Abstract Preview: Purpose: This study aims to evaluate the tumor response to combined radiochemotherapy on MCF7 spheroids using an open-source multiscale computational framework. The model provides a platform to simula...

Implementing a Learning-to-Optimize Machine Learning Framework to Accelerate VMAT Treatment Planning Optimization for Prostate Cancer

Authors: Ara Alexandrian, Sadiki Daniel

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: To develop a learning-to-optimize machine learning model that accelerates optimization in VMAT treatment planning by training on prostate patient data.
Methods: A treatment plan dataset of...

Investigating X-Ray Flash Effect on Plasmid DNA with Combined Microscopic Monte Carlo and Analytical Simulations

Authors: Xun Jia, Youfang Lai

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

Abstract Preview: Purpose: Ultrahigh dose rate FLASH (>40 Gy/s) radiotherapy (RT) has attracted significant attention. The mechanism remains unclear, hindering clinical translation. This study investigated the behavior...

Leveraging Codex-Based Spatial Profiling of the Tumor Microenvironment in Concurrent Radiation Therapy and Immunotherapy

Authors: Todd A Aguilera, Bassel Dawod, Sebastian Diegeler, Eslam Elghonaimy, Purva Gopal, Jiaqi Liu, Hao Peng, Arely Perez Rodriguez, Nina N. Sanford, Robert Timmerman, Megan B Wachsmann, 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, UT Southwestern Medical Center

Abstract Preview: Purpose: This study pioneers the integration of CODEX (co-detection by indexing)-based spatial profiling and advanced computational techniques to investigate the tumor immune microenvironment (TIME) i...

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...

Rectangular Aperture-Based Beam Orientation Optimization for 4π Non-Coplanar Small Animal IMRT Delivery

Authors: Dante PI Capaldi, Lu Jiang, Qihui Lyu, Ke Sheng

Affiliation: Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose:
Preclinical small animal studies help understand radiation-induced biological responses, toxicities, and mechanisms, facilitating the translation of new therapies to patient treatment. Int...

Synthesizing High-Quality Hepatic Vascular Tree Segmentation Datasets to Improve Segmentation Model Performance

Authors: Trevor McKeown, Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose: Accurate delineation of liver blood vascular structures is crucial for planning and executing therapeutic interventions in liver-related medical procedures. However, current auto-segmentation...