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BreastWatch: A Varian Eclipse script tool for Community-Based automatic evaluation of breast treatment plans
Stefano Agostinelli1, Daniele Zefiro1, Stefania Garelli1
1UO Fisica Sanitaria, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Journal of Applied Clinical Medical Physics
|April 2, 2025
Summary
BreastWatch, a new script for External Beam Breast Treatment (EBBT) planning, speeds up and improves plan quality using automatic protocol and community-based evaluations. This tool enhances consistency and robustness in radiation oncology.
Area of Science:
- Radiation Oncology
- Medical Physics
- Computational Biology
Background:
- External Beam Breast Treatment (EBBT) planning requires meticulous adherence to protocol dose-constraints.
- Current methods for evaluating EBBT plans can be time-consuming and may have limitations in capturing real-world plan variations.
Purpose of the Study:
- To introduce BreastWatch, a Varian Eclipse script tool for automated inspection and improvement of EBBT plans.
- To enhance EBBT plan evaluation through automatic assessment of protocol dose-constraints and a novel Community-Based approach.
Main Methods:
- BreastWatch automatically evaluates EBBT plans and plan sums against international protocol dose-constraints (e.g., NRG RTOG1005, ICR FAST).
- A Community-Based (CB) approach exports plan data to create a library, enabling comparison against statistical distributions of similar plans.
- The script provides visual feedback (traffic lights, BW-SCORE) and a CB-SCORE to complement protocol-based evaluations.
Main Results:
- BreastWatch significantly speeds up the EBBT planning process.
- The tool improves treatment plan quality, including PTV coverage, OAR sparing, and inter-planner consistency.
- Preliminary analysis suggests the CB approach leads to improved and more consistent dose-constraint values.
Conclusions:
- BreastWatch is an effective tool for the automatic evaluation of Varian Eclipse EBBT plans.
- The integration of protocol-based and Community-Based features offers a simple yet powerful automation strategy for optimizing EBBT planning.

