The First Investigation of Spot Size and Its Impact on Treatment Planning Quality for Spot Scanning Proton Arc Therapy
Abstract
Purpose
Spot-scanning proton arc therapy(SPArc) delivers pencil beam scanning dose during continuous gantry rotation and its dosimetry depends on the underlying beam model particularly lateral spot size. This study evaluated the impact of spot size on SPArc plan quality using a standardized plan quality scoring rubric.
Methods
Three beam models were generated with different lateral spot size from 70MeV to 227.7MeV (Gaussian σ): small(1.7–4 mm), medium(3.4–8 mm), and large(6.8–16mm) using Raystation 2023B. Four clinical patient cases (brain, lung, liver, and pancreas; n=4) were replanned with SPArc using identical prescription, normalization, and optimization settings. Plan quality was assessed using the ProKnow standardized composite score based on target coverage/homogeneity and organ-at-risk(OAR) dose objectives. Delivery-related metrics, including total monitor units(MU), total number of spots, and delivery time, were compared.
Results
Across all four sites, the small spot beam model produced the highest overall plan-quality scores, reflecting improved target/OAR performance within the scoring rubric compared with medium and large spot models. Compared to the large spot model, total MU decreased by 30±13% and 22±10%, and the number of spots increased by 6.9±2.8 and 2.7±0.5 times for the small spot and medium spot models, respectively, while the difference of delivery time remains within 2% (n=4). These results indicate a tradeoff between plan quality and different delivery-related plan characteristics.
Conclusion
SPArc plan quality is sensitive to spot-size of the proton beam. Smaller spot size improved composite plan scores and reduced MU but required more planned spot positions, with minimal change in estimated delivery time. We expect this study to provide guidance on the trade-off between spot size and plan quality for proton arc therapy at existing spot-scanning proton therapy centers and future systems.