A5103134457- Advanced Radiotherapy Techniques
- Radiomics and Machine Learning in Medical Imaging
- Radiation Therapy and Dosimetry
- Advances in Oncology and Radiotherapy
- Radiation Dose and Imaging
- Advanced X-ray and CT Imaging
- Health and Medical Research Impacts
- Medical Imaging Techniques and Applications
- Head and Neck Cancer Studies
- Lung Cancer Diagnosis and Treatment
- Radiation Detection and Scintillator Technologies
- Tracheal and airway disorders
- Machine Learning in Bioinformatics
- Radiology practices and education
- Nuclear Physics and Applications
- Big Data and Business Intelligence
- Biomedical and Engineering Education
- Medical Imaging and Analysis
- History and advancements in chemistry
- Advanced MRI Techniques and Applications
- Infectious Disease Case Reports and Treatments
- Radiation Effects and Dosimetry
The University of Texas Southwestern Medical Center
2024-2025
The University of Texas MD Anderson Cancer Center
2019-2024
The University of Texas Health Science Center at Houston
2021-2024
Purpose Radiation therapy treatment planning is a time‐consuming and iterative manual process. Consequently, plan quality varies greatly between within institutions. Artificial intelligence shows great promise in improving reducing times. This technical note describes our participation the American Association of Physicists Medicine Open Knowledge‐Based Planning Challenge (OpenKBP), competition to accurately predict radiation dose distributions. Methods A three‐dimensional (3D) densely...
Purpose: This study aimed to use deep learning-based dose prediction assess head and neck (HN) plan quality identify suboptimal plans. Methods: A total of 245 VMAT HN plans were created using RapidPlan knowledge-based planning (KBP). subset 112 high-quality was selected under the supervision an radiation oncologist. We trained a 3D Dense Dilated U-Net architecture predict 3-dimensional distributions 3-fold cross-validation on 90 Model inputs included CT images, target prescriptions, contours...
This study aimed to investigate the feasibility of using a knowledge-based planning technique detect poor quality VMAT plans for patients with head and neck cancer. We created two dose-volume histogram (DVH) prediction models commercial system (RapidPlan, Varian Medical Systems, Palo Alto, CA) from generated by manual (MP) automated (AP) approaches. DVHs were predicted evaluation cohort 1 (EC1) 25 compared achieved MP AP evaluate accuracy. Additionally, we 2 (EC2) which intentionally...
Objective.To establish an open framework for developing plan optimization models knowledge-based planning (KBP).Approach.Our includes radiotherapy treatment data (i.e. reference plans) 100 patients with head-and-neck cancer who were treated intensity-modulated radiotherapy. That also high-quality dose predictions from 19 KBP that developed by different research groups using out-of-sample during the OpenKBP Grand Challenge. The input to four fluence-based mimicking form 76 unique pipelines...
Abstract Background In recent years, deep‐learning models have been used to predict entire three‐dimensional dose distributions. However, the usability of predictions improve plan quality should be further investigated. Purpose To develop a model high‐quality distributions for volumetric modulated arc therapy (VMAT) plans patients with gynecologic cancer and evaluate their in driving improvements. Methods A total 79 VMAT female pelvis were train (47 plans), validate (16 test plans) 3D dense...
Abstract Background Recent studies have shown deep learning techniques are able to predict three‐dimensional (3D) dose distributions of radiotherapy treatment plans. However, their use in prediction for treatments with varied prescription doses including simultaneous integrated boost (SIB), that is, using multiple within the same plan, and benefit improving plan quality should be validated. Purpose To investigate feasibility potential distribution volumetric modulated arc therapy (VMAT) SIB...
Abstract Objective:
To evaluate the impact of beam mask implementation and data aggregation on artificial intelligence-based dose prediction accuracy in proton therapy, with a focus scenarios involving limited or highly heterogeneous datasets.
Approach:
In this study, 541 prostate 632 head neck (H&N) therapy plans were used to train convolutional neural networks designed for task prediction. Datasets grouped by anatomical site configuration assess masks—graphical...
Objective. Robustness evaluation is critical in particle radiotherapy due to its susceptibility uncertainties. However, the customary method for robustness only considers a few uncertainty scenarios, which are insufficient provide consistent statistical interpretation. We propose an artificial intelligence-based approach that overcomes this limitation by predicting set of percentile dose values at every voxel and allows planning objectives specific confidence levels.Approach. built trained...
This report details curricular recommendations for graduate degrees in medical physics and serves as an update to Report No. 197. In this section, we review the history of American Association Physicists Medicine (AAPM) recommendations, present aims report, detail how these should be interpreted. The first AAPM publication on education was 44, published 1993, describing Master Science Degree Medical Physics.1 79 2002 established a core curriculum all training physics, well more specific...
To investigate the use of statistical process control (SPC) for quality assurance an integrated web-based autoplanning tool, Radiation Planning Assistant (RPA).Automatically generated plans were downloaded and imported into two treatment planning systems (TPSs), RayStation Eclipse, in which they recalculated using fixed monitor units. The then uploaded back to RPA, mean dose differences each contour between original RPA TPSs calculated. SPC was used characterize terms comparisons: TPS versus...
Dedicated precision orthovoltage small animal irradiators have become widely available in the past decade and are commonly used for radiation biology research. However, there is a lack of dosimetric standardization among these irradiators, which affects reproducibility radiation-based studies. The purpose this study was to develop mail-based, independent peer review system verify dose delivery institutions using X-RAD 225Cx (Precision X-Ray, North Branford, CT). A robust, user-friendly mouse...
This work of fiction is part a case study series developed by the Medical Physics Leadership Academy (MPLA). It intended to facilitate discussion how students and advisors can better communicate expectations navigate difficult conversations. In this case, fourth-year Ph.D. student Emma learns that her advisor Dr. So leaving institution has not arranged bring any with him. As meet discuss Emma's next steps, conversation reveals misunderstandings miscommunications expectations, including...
. Previous methods for robustness evaluation rely on dose calculation a number of uncertainty scenarios, which either fails to provide statistical meaning when the is too small (e.g., ∼8) or becomes unfeasible in daily clinical practice sufficiently large >100). Our proposed deep learning (DL)-based method addressed this issue by avoiding intermediate step and instead directly predicting percentile distribution from nominal using DL model. In study, we sought validate DL-based efficient...
This work of fiction is part a case study series developed by the Medical Physics Leadership Academy (MPLA). It intended to facilitate discussion managerial and leadership challenges faced clinical medical physicist. In this case, physicist David used in clinic where he thrived felt like leader, despite not having title. After job change, now officially "Lead Physicist" at hospital newly affiliated with large academic healthcare system. He believes will be equally successful. Yet struggles...
PURPOSE: Recent studies demonstrate deep learning dose prediction algorithms may produce results like those of traditional knowledge-based planning tools. In this exploratory study, we compared 2D DVH-based tools and METHODS: Pre-validated 3D models were applied to 58 patients with head neck cancer treated under RTOG 0522 obtained from The Cancer Imaging Archive (TCIA). model was used predict dose-volume histogram bands for seven organs at risk (OARs; brainstem, spinal cord, oral cavity,...
This guide provides a framework and general steps for writing case study the Medical Physics Leadership Academy (MPLA).1, 2 may be used as part of Request Proposal (RFP) studies in AAPM leadership-themed sessions. Consideration category learning objectives should maintained while developing synopsis, facilitators guide. A synopsis is high-level summary study. An example given Exhibit 1 Supplemental Materials. The following components included: setting, including information about technology...