radiation-planning-assistant-web-based-tool-to-support-high-quality

Radiation Planning Assistant - A Web-based Tool to Support High-quality Radiotherapy in Clinics with Limited Resources

Access to radiotherapy worldwide is limited. The Radiation Planning Assistant (RPA) is a fully automated, web-based tool that is being developed to offer ...

The University of Texas MD Anderson Cancer Center

To develop a checklist that improves the rate of error detection during the plan review of automatically generated radiotherapy plans.

Development and validation of a checklist for use with automatically generated radiotherapy plans.

Knowledge-based planning (KBP) has been shown to be an effective tool in quality control for intensity-modulated radiation therapy treatment planning and generating high-quality plans. Previous studies have evaluated its ability to create consistent plans across institutions and between planners within the same institution as well as its use as teaching tool for inexperienced planners. This study evaluates whether planning quality is consistent when using a KBP model to plan across different treatment machines.

Assessing the practicality of using a single knowledge-based planning model for multiple linac vendors.

To investigate the use of statistical process control (SPC) for quality assurance of an integrated web-based autoplanning tool, Radiation Planning Assistant (RPA).

Statistical process control to monitor use of a web-based autoplanning tool.

To develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning-based auto-contouring and customizable landmark-based field aperture design.

Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning.

Hazard scenarios were created to assess and reduce the risk of planning errors in automated planning processes. This was accomplished through iterative testing and improvement of examined user interfaces.

Hazard testing to reduce risk in the development of automated planning tools.

Automation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).

Article	Year
Development and validation of a checklist for use with automatically generated radiotherapy plans. Journal of applied clinical medical physics\| PubMed ID: 35775105	2022
Assessing the practicality of using a single knowledge-based planning model for multiple linac vendors. Journal of applied clinical medical physics\| PubMed ID: 35791594	2022
Statistical process control to monitor use of a web-based autoplanning tool. Journal of applied clinical medical physics\| PubMed ID: 36300872	2022
Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning. Journal of applied clinical medical physics\| PubMed ID: 36412092	2023
Hazard testing to reduce risk in the development of automated planning tools. Journal of applied clinical medical physics\| PubMed ID: 37073484	2023
Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant. JCO global oncology\| PubMed ID: 37471671	2023

Raphael Douglas

Biography

JoVE Journal Publications

Other Publications