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Incorporating plan complexity into the statistical process control of volumetric modulated arc therapy pre-treatment
Serenella Russo1, Jordi Saez2, Marco Esposito1,3
1Medical Physics Unit, Azienda USL Toscana Centro, Florence, Italy.
Medical Physics
|April 17, 2024
Summary
Statistical process control (SPC) for Volumetric Modulated Arc Therapy (VMAT) quality assurance is improved by accounting for plan complexity. Adjusting tolerance limits based on complexity ensures accurate process monitoring and identifies issues in complex treatment plans.
Area of Science:
- Medical Physics
- Radiation Oncology
- Statistical Quality Control
Background:
- Statistical process control (SPC) is recommended for radiation therapy quality assurance (QA), particularly for Volumetric Modulated Arc Therapy (VMAT) pre-treatment verification.
- The AAPM TG-218 report highlighted the need to adjust SPC tolerance limits based on treatment plan complexity.
- Quantifying and integrating plan complexity into SPC remains a significant challenge in clinical practice.
Purpose of the Study:
- To investigate methods for incorporating treatment plan complexity into the SPC framework for VMAT pre-treatment verifications.
- To evaluate different strategies for integrating plan complexity, assessing their advantages and limitations.
- To provide recommendations for the clinical application of complexity-adjusted SPC in VMAT QA.
Main Methods:
- Retrospective analysis of 309 VMAT plans from diverse anatomical sites using PTW OCTAVIUS 4D for QA measurements.
- Calculation of Gamma Passing Rates (GPR) and computation of lower control limits using conventional and heuristic methods (Shewhart, scaled weighted variance, weighted standard deviations, skewness correction).
- Assessment of eight complexity metrics and two strategies for incorporating plan complexity: site-specific control limits and complexity-dependent control limits.
Main Results:
- SPC control limits are significantly influenced by treatment plan complexity.
- Both strategies demonstrated an inverse correlation between tolerance limits and plan complexity.
- Complexity-adjusted SPC correctly classified highly complex plans as in control, unlike conventional methods that identified them as out-of-control.
Conclusions:
- Integrating plan complexity into SPC for VMAT verifications requires careful and thorough analysis.
- Minimizing and controlling treatment plan complexity is crucial for overall process control, especially when adjusting control limits.
- Complexity-adjusted SPC offers a more accurate approach to VMAT QA by tailoring tolerance limits to individual plan characteristics.
