Impact of Machine-Specific Parameters on Proton Beam Delivery Accuracy of Mevion Hyperscanning System: Lessons from One-Year Psqa Failure Analysis and Planning Strategy Refinement
Abstract
Purpose
To identify key factors influencing proton beam delivery accuracy with a Mevion Hyperscanning system equipped with Adaptive Aperture, and to address parameters contributing to patient-specific quality assurance (PSQA) failures through planning technique optimization.
Methods
We conducted a retrospective review of twelve treatment plans that failed PSQA over a one-year period. Each case was analyzed for common characteristics related to nozzle position, beam computation setting, adaptive aperture, optimization objectives and planning parameters. After identifying contributing factors, we implemented modifications to planning and optimization strategies and tested revised plans to evaluate their impact on PSQA pass rates.
Results
Our results revealed multiple factors, individually or collectively, with effects ranging from moderate to significant. Fully retracted or extended snout position was a major contributor to PSQA failures, it is due to slight nozzle walkout affecting adaptive aperture alignment. Use of beam-specific maximum dose limits and beam specific uniform dose objectives for multi-field optimization (MFO) plans were also identified as significant factors. Additionally, avoidance structures can introduce uncertainty in collimated beam delivery. Furthermore, static apertures demonstrated slightly higher gamma criteria compared to dynamic apertures, likely due to their design and the trimming of only peripheral spots rather than all spots.
Conclusion
Systematic evaluation of PSQA failures on the Mevion Hyperscanning system revealed that machine-specific characteristics—such as snout positioning, adaptive aperture, planning objectives and computation setting—play a critical role in proton beam delivery accuracy. Implementing strategic adjustments to planning and optimization maintain beam delivery accuracy and eliminate QA failures. This study emphasizes the importance of incorporating adaptive aperture and refining planning considerations into clinical workflows to enhance treatment reliability and improve delivery accuracy.