The Cut-Sort-Group algorithm for efficient delivery of collimated step-and-shoot proton arc therapy.

Abstract

Background: Proton arc therapy is an emerging technology offering considerably more geometric flexibility than traditional multi-field treatments, thereby enhancing potential for more conformal proton treatments. The Dynamic Collimation System (DCS) offers energy-specific collimation during pencil beam scanning to further improve target conformity and reduce dose to normal tissues. Collimation with the DCS during arc delivery is referred to as dynamically collimated proton arc therapy (DC-PAT). The time required for energy switching, gantry movement during step-and-shoot arc delivery, and trimmer movement associated with dynamic collimation necessitates careful planning to create DC-PAT plans efficient enough to fit within a typical clinical workflow.

Purpose: To demonstrate a post-processing algorithm to improve the delivery efficiency of DC-PAT plans while maintaining plan quality.

Methods: A genetic optimizer was used to create baseline DC-PAT plans for three intracranial cases. These plans were then modified in the post-processing stage with the Cut-Sort-Group (CSG) algorithm. Specifically, each plan was modified through low-weight control point removal ("Cut"), a novel approach to energy layer sorting ("Sort"), and efficient DCS-trimmer reconfiguration ("Group"). The components of CSG were evaluated individually and in combination for changes in efficiency, plan quality, and robustness when compared to baseline plans.

Results: After applying the CSG algorithm, the beam delivery time (BDT) for the three patients was reduced to between 10 and 14 min, more than 64% faster than the reference baseline plans. These efficiency gains were achieved with minimal impact on plan quality. The dose coverage to the PTV of the CSG-derived plans was comparable to the baseline plans for each patient, with the PTV D_2% remaining under 10% of the prescription and a Homogeneity Index (HI) ranging from 0.09 and 0.12. Dose to non-target structures and overall plan robustness was also minimally impacted by the implementation of the CSG algorithm.

Conclusions: The CSG algorithm demonstrates a relatively simple approach to modifying step-and-shoot proton arc therapy plans to be more efficient in the post-processing stage regardless of the treatment planning system or optimization algorithm used to generate the initial plans and with minimal impact on plan quality. The overall BDT was reduced to just over 10 min, approaching plans produced using other advanced optimization algorithms in previous investigations, and fast enough for potential clinical implementation.