Development and evaluation of an automated report-based chart checking tool in external beam radiotherapy

Area of Science:

• Medical Physics
• Radiation Oncology
• Radiotherapy Quality Assurance

Background:

• Computerized tools enhance radiotherapy chart checking by verifying plan parameters rapidly.
• Existing tools often access live databases, posing risks to integrity and performance.
• There is a need for safe and efficient automated chart checking solutions.

Purpose of the Study:

• To develop and evaluate an Automated AURA Report-based Chart Checking Tool (AARCCT).
• To utilize AURA reports and the reporting database for error detection in external beam radiotherapy plans.
• To improve the accuracy and efficiency of treatment plan preparation.

Main Methods:

• Developed the AARCCT using Python within the RayStation treatment planning system.
• Verified physics check items against TG-275 recommendations using TPS and ARIA ROS data via AURA reports.
• Tested the tool on over 600 diverse patient treatment plans, including 3D-CRT, IMRT, and electron therapies.

Main Results:

• The AARCCT analyzed over fifty plan parameters in near real-time.
• Approximately 48.6% of plans had errors before physics review, and 37.1% after.
• Common errors included inaccuracies in patient setup imaging, prescription, and written directives.

Conclusions:

• The AARCCT is essential for reducing errors post-manual physics checks.
• Its automated nature and avoidance of live database access ensure seamless clinical integration.
• The tool can aid in staff training evaluation and standardizing practices for improved quality and efficiency.