Optimizing dose rate to minimize delivery time in proton pencil beam dose-driven continuous scanning

Dose-driven continuous scanning (DDCS) enhances the efficiency and precision of proton pencil beam delivery by reducing beam pauses inherent in discrete spot scanning (DSS). However, current DDCS optimization studies using traveling salesman problem (TSP) formulations often rely on fixed beam intensity and computationally expensive interpolation for move spot generation, limiting efficiency and methodological robustness.

This study introduces a Break Spot-Guided (BSG) method, combined with two acceleration strategies-dose rate skipping and bounding-to optimize beam intensity while minimizing beam delivery time (BDT). In addition, a $\sigma$ -method is proposed for efficient move spot generation, aiming to balance computational efficiency and dose calculation accuracy.

The BSG framework simplifies the original mixed-integer nonlinear programming (MINLP) problem by transforming it into a series of TSP evaluations using break-spot dose rates. The two acceleration strategies are integrated to reduce computational complexity. The $\sigma$ -method is introduced to efficiently generate move spots without compromising dose fidelity. The performance of the BSG method, with and without the acceleration strategies, and the $\sigma$ -method, was evaluated across multiple clinical cases.

By jointly optimizing the scan path and dose rate, the proposed BSG-S-B method offered the most efficient delivery, achieving a 64% reduction in BDT compared to DSS and a 57% reduction compared to Liu's method in the prostate case. These gains were consistently observed across all cases. Utilizing acceleration strategies, BSG-S-B significantly reduced computation time from hours to minutes (e.g., from 10 525.7 to 108.5 s in the prostate case, and from 6202.4 to 129.8 s in the head-and-neck case). When combined with the $\sigma$ -method, it reduced the number of move spots by more than 50%, while still ensuring dosimetric quality.

The proposed framework significantly improves computational efficiency, making scan path optimization with dose rate selection feasible for clinical DDCS delivery. The $\sigma$ -method effectively reduces computational complexity while maintaining dose calculation accuracy, demonstrating strong potential for clinical adoption in proton therapy treatment planning.