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Related Experiment Video

Updated: Jul 12, 2025

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

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

Laurence Edward Court¹, Ajay Aggarwal², Hester Burger³

¹The University of Texas MD Anderson Cancer Center; lecourt@mdanderson.org.

Journal of Visualized Experiments : Jove

|October 23, 2023

Summary

Limited access to radiotherapy is addressed by the Radiation Planning Assistant (RPA), a web-based tool providing automated treatment planning for resource-limited clinics to help more cancer patients.

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Area of Science:

Oncology
Medical Physics
Health Informatics

Background:

Global access to radiotherapy, a crucial cancer treatment, is significantly limited, particularly in resource-constrained settings.
This disparity hinders equitable cancer care and necessitates innovative solutions to expand treatment reach.
Automated tools are emerging to address workflow inefficiencies in radiation oncology.

Purpose of the Study:

To introduce the Radiation Planning Assistant (RPA), a novel, fully automated, web-based tool designed to streamline radiotherapy treatment planning.
To enable clinics with limited resources to scale their planning capabilities and increase patient access to radiotherapy.
To facilitate the adoption of advanced planning techniques in underserved regions.

Main Methods:

The RPA is a web-based platform accessible via a webpage.
Users submit a Service Request with prescription details and upload patient CT image sets.
The system offers two automated planning modes: one-step (fully automated contouring and planning) and two-step (user review/edit of contours before automated plan generation).

Main Results:

The RPA generates radiotherapy treatment plans, including contours and Volume-Modulated Arc Therapy (VMAT) plans.
The system supports both fully automated and semi-automated planning workflows.
Final plans are downloadable for integration into local treatment planning systems for dose recalculation and clinical approval.

Conclusions:

The Radiation Planning Assistant (RPA) offers a scalable solution to improve radiotherapy access in resource-limited settings.
Automated treatment planning through the RPA can enhance efficiency and potentially increase the number of cancer patients receiving radiotherapy.
Web-based, automated tools represent a promising avenue for democratizing advanced cancer treatment planning globally.