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Results for "feasibility machine": 21 found

A Predictive Tool for Optimizing Treatment System Allocation in Hypofractionated Whole-Breast Radiotherapy

Authors: Zhenzhen Dai, Anthony J. Doemer, Ryan Hall, Kenneth Levin, Bing Luo, Benjamin Movsas, Karen C. Snyder, Kundan S Thind, Eleanor Walker

Affiliation: Henry Ford Health, HFHS

Abstract Preview: Purpose: To investigate the feasibility of a predictive tool for efficient allocation of hypofractionated whole-breast irradiation patients between Varian Truebeam and Ethos systems.
Methods: A ful...

An International Multi-Institutional Espresso Study of Developing the Specialized-Equipment-Free Remote Audit for Single-Isocenter Multi-Target Stereotactic Radiosurgery

Authors: Juan-Francisco Calvo-Ortega, Andrew Cousins, Ashley Cullen, Andrew Dipulia, Peter B. Greer, Seng Boh Gary Lim, Shih-Chi Lin, D. Michael Lovelock, Conor McGarry, Victoria Robinson, Cameron Stanton, Baozhou Sun, Ching-Ling Teng, Gemma Warner, Benjamin J. Zwan

Affiliation: Northern Ireland Cancer Centre, Baylor College of Medicine, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Christchurch Hospital, Northwell, Central Coast Cancer Centre, Calvary Mater Hospital, Hospital Quironsalud Barcelona, Icahn School of Medicine at Mount Sinai, Chris O'Brien Lifehouse, University of Newcastle

Abstract Preview: Purpose: This multi-institution Electronic Silicon-based Remote Survey of Small-field Output (ESPRESSO) study aims to develop the remote audit process to evaluate the safety of single-isocenter multi-...

Clinical Implementation of Automated Contour Quality Assurance in Head and Neck Radiotherapy

Authors: Sam Armstrong, Jamison Louis Brooks, Nicole Johnson, Douglas John Moseley, Cassie Sonnicksen, Erik J. Tryggestad

Affiliation: Mayo Clinic

Abstract Preview: Purpose: To evaluate the feasibility of a shallow learning-based quality assurance (QA) tool designed to assist human reviewers in assessing organ-at-risk (OAR) contours for head and neck radiotherapy...

Convergence Speed Advantages of a Machine Learning Assisted Framework in IMRT Fluence Map Optimization โ€“ 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...

Could Synthetic CTs Simulating Patient Anatomical Changes Help Improve the Robustness of Head-and-Neck Proton Plans?

Authors: Nrusingh C. Biswal, Matthew J Ferris, Michael J. MacFarlane, Jason K Molitoris, Byong Yong Yi, Mark J. Zakhary

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, University of Maryland

Abstract Preview: Purpose: Proton head-and-neck treatment plans often struggle to maintain plan quality over the course of treatment due to tumor response, weight-loss, and setup variability. Plan robustness to these c...

Dual Energy Cone Beam Computed Tomography for Artifact Reduction and Enhanced Image Quality Using Existing Hardware in Radiation Therapy

Authors: Michael J. Choi, Vindu Wathsala Kathriarachchi, Christopher L. Nelson, Andrew P. Soderstrom, Yawei Zhang

Affiliation: The University of Texas MD Anderson Cancer Center, MD Anderson, UF Health Proton Therapy Institute

Abstract Preview: Purpose: Cone Beam Computed Tomography (CBCT) is widely used in image-guided radiation therapy for patient positioning. While kV photons offer high image contrast, they are prone to artifacts caused b...

Enhanced Lung Function Assessment through Machine Learning Analysis of 4DCT Subregional Respiratory Dynamics

Authors: Jing Cai, Zhi Chen, Hong Ge, Yu-Hua Huang, Bing Li, Zihan Li, Ge Ren

Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital

Abstract Preview: Purpose: Algorithms based on subregional respiratory dynamics (SRD) capture spatiotemporal heterogeneity in the ventilation process, though rely on empirical modelings to map surrogate ventilation. Gi...

Estimation of Heart Dose in Left Breast Cancer Radiotherapy: Assessment of Vdibh Feasibility Using the Supervised Machine Learning Algorithm

Authors: Rajeev Gupta, Shriram Ashok Rajurkar, Teerthraj Verma

Affiliation: King George's Medical University, King George's Medical University, UP

Abstract Preview: Purpose:
The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and...

Evaluation of an Offline Adaptive CBCT Planning Workflow for Halcyon with Hypersight

Authors: Michelle Alonso-Basanta, Joshua Bryer, Lei Dong, Barbara Garcia, Elissa Khoudary, Brandon M. Koger, Taoran Li, Michael Salerno, Karen Tang, Boon-Keng Kevin Teo

Affiliation: University of Pennsylvania

Abstract Preview: Purpose: The Varian HyperSight imaging solution features a workflow for planning on CBCT images (CBCTp). This study evaluates the feasibility of CBCTp images in the setting of an offline adaptive plan...

FMEA for Direct to Unit Adaptive Radiotherapy

Authors: Haleem Azmy, Robbie Beckert, Farnoush Forghani, Dean Hobbis, Dan Hong, Hyun Kim, Eric Laugeman, Silpa Raju-Salicki, Domenic Sievert

Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine in St. Louis, Washington University School of Medicine, Wash U Medicine, Washington University in St. Louis

Abstract Preview: Purpose: A novel radiation therapy (RT) workflow has recently emerged with the advent of online adaptive RT systems, direct-to-unit (DTU). DTU utilizes online adaptive platforms (MR and CT based) to o...

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...

Free-Breathing Spirometer-Gated Proton Pencil Beam Scanning Delivery Maintains Tumor Coverage with Improved Organ-at-Risk Sparing: A Motion Phantom Validation

Authors: Uriel Aura, Qing Chen, Arpit M. Chhabra, J Isabelle Choi, Chanda Guha, Meng Wei Ho, Sheng Huang, Minglei Kang, Stanislav Lazarev, Nancy Y Lee, Yang Lei, Haibo Lin, Hang Qi, Mahbubur Rahman, Charles B. Simone, Shouyi Wei, Irini Yacoub, Francis Yu, Anna Zhai, Ajay Zheng

Affiliation: DYN'R Medical System, New York Proton Center, Montefiore Medical Center and Albert Einstein College of Medicine, Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Tianjin Medical University Cancer Institute&Hospital, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Managing tumor motion during pencil beam scanning proton therapy remains challenging. This study investigated the feasibility and dosimetric benefits of Free-Breathing Respiratory-Gated Deliv...

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...

Inter-Patient Adaptive Radiotherapy (IPART): A CT Simulation and Planning Free Approach Enabling Immediate Treatment Access for Patients.

Authors: Bin Cai, Andrew R. Godley, Brian A. Hrycushko, Heejung Kim, Mu-han Lin, David D.M. Parsons, Justin D. Visak, Da Wang, Tingliang Zhuang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: The standard radiation therapy workflow requires CT-simulation and planning, whether for initial treatments or re-planning due to significant anatomical changes. IPART instead uses one patien...

Learning from Failures โ€“ Case Studies into Failing Patient Specific Quality Assurance Plans

Authors: Christopher S. Melhus, Elizabeth Meyer, Cassandra Stambaugh

Affiliation: Tufts Medical Center

Abstract Preview: Purpose: To investigate the clinical treatment planning parameters that impact patient-specific quality assurance (PSQA) passing rates for hippocampal avoidance whole brain (HAWB) treatment plans.
...

Log File-Based Patient-Specific QA As a Viable Alternative to Measurement-Based QA in IMPT

Authors: Sina Mossahebi, Pouya Sabouri, Kayla Schneider, James W Snider

Affiliation: University of Maryland School of Medicine, Proton International, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiation Oncology, University of Arkansas for Medical Sciences

Abstract Preview: Purpose:
Conventional patient-specific QA (PSQA) for intensity-modulated proton therapy (IMPT) requires extensive measurements, straining resources in single-room proton centers. This study evaluat...

Mid-Range Planning for Efficient and Robust Proton Arc Therapy

Authors: Mingli Chen, Xuejun Gu, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, Kangning Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: Delivery efficiency and robustness are critical in spot-scanning proton arc therapy (SPAT), yet the conventional use of redundant energy layers (ELs) prolongs switching times and reduces effi...

Multi-Variat, Multi-Model, and Multi-Patient: From Pure Feasibility to Generalizability in Machine Learning Outcome Prediction Model-Based Treatment Plan Optimization

Authors: Martin Frank, Oliver Jรคkel, Niklas Wahl

Affiliation: Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Karlsruhe Institute of Technology (KIT)

Abstract Preview: Purpose: Machine learning (ML) models on normal tissue complication and tumor control probability ((N)TCP) exploiting e.g. dosiomic and radiomic features are playing an increasingly important role in ...

Respiratory Monitoring in Human Subjects Using a Low-Cost Optical Imaging System Prototype

Authors: Marian Axente, Mandeep Kaur

Affiliation: Emory University

Abstract Preview: Purpose: To validate a low-cost optical imaging system for respiratory monitoring by comparing its accuracy and feasibility against the clinical gold standard in human subjects.
Methods: Following ...

Unidose: A Universal Framework for IMRT Dose Prediction

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, 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: Dose prediction (DP) is essential in guiding radiotherapy planning. However, current DP models for intensity-modulated radiation therapy (IMRT) primarily rely on fixed-beam orientations and a...

โ€œSeeโ€ through Surface: Transforming Surface Imaging into a Real-Time Three-Dimensional Imaging Solution for Intra-Treatment Image Guidance

Authors: Steve B. Jiang, Ruiqi Li, Hua-Chieh Shao, Kenneth Westover, You Zhang, Tingliang Zhuang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, 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:
Respiratory motion is a long-standing challenge for lung SBRT, particularly for centrally-located lung tumors where increased toxicity demands more precise motion management during treatme...