Clinical Development of an Automated Raystation Scripting Tool for Osteoarthritis Treatment Planning
Abstract
Purpose
To develop and clinically implement a Python-based RayStation scripting tool that automates three-dimensional radiotherapy planning for osteoarthritis (OA) in a single execution.
Methods
A Python-based automated script was developed within the RayStation (RaySearch) scripting environment and implemented clinically to standardize knee OA treatment planning. The script replaces manual forward planning tasks with a single execution workflow. Upon execution, the script automatically determines treatment laterality, selects the appropriate treatment machine and prescription, places the isocenter within the joint space, and generates anterior-posterior and posterior-anterior beam arrangements. The script configures beam geometry, energy selection, jaw limits, dose calculation, and prescription scaling. The script includes optional support for control point implementation; however, following physician review and clinical approval, routine clinical use transitioned away from control points without compromising plan quality. The automated workflow was implemented on Varian TrueBeam and Edge systems using RayStation 11B. All generated plans were normalized to deliver at least 300cGy to the joint space in six fractions delivered every other day.
Results
The scripting tool consistently generated clinically acceptable knee OA treatment plans in a single execution with correct isocenter placement, beam geometry, energy selection, jaw limits, and prescription assignment. Automated plans met institutional planning criteria and demonstrated dose distributions consistent with established clinical practice. Elimination of routine control point usage did not adversely affect clinical acceptability following physician review. The automated workflow reduced reliance on manual planner input and improved planning efficiency while maintaining consistent plan quality.
Conclusion
This work demonstrates the successful development and clinical implementation of an automated RayStation scripting tool for knee OA treatment planning. The tool standardizes plan configuration, reduces manual user input, and produces consistent, clinically acceptable plans. This workflow is readily transferable and provides a foundation for extending automation to additional OA treatment sites and other radiotherapy applications.