A Novel Spot Sparsity Optimization Algorithm For an Efficent Proton Arc Therapy

Document Type

Conference Proceeding

Publication Date

6-2024

Publication Title

International Journal of Particle Therapy

Abstract

Background and aims: The outstanding challenge of utilizing Spot-scanning Proton Arc therapy (SPArc) in routine clinic is the delivery efficiency. One of the major components of delivery time is the spot switching time, which is proportional to the total number of spots. Therefore, spot reduction plays a crucial role in improving treatment efficiency. This study aims to develop a novel spot sparsity optimization (SSO) algorithm to reduce the number of spots for optimal dosimetric plan quality and treatment delivery efficiency. Methods: SSO is based on the least-square dose fidelity term with regularized L0-minimization. In this study, the alternating directions method of multipliers (ADMM), is introduced to solve the optimization problem, denoted SSO-ADMM. A state-of-the-art SSO method, the primal-dual-active-set with continuation (PDASC) algorithm published previously, noted as SSO-PDASC was utilized as a reference. Two plan groups with the same beam-assignment and clinical constraint were generated. Three different disease sites (brain, lung, and liver cancer) were used for testing. The performance of algorithm were evaluated based on the level of spot sparsity, spot switching time (SSWT), spot spill time (SSPT) and dosimetric plan quality. Results: Compared to the SSO-PDASC plan, the SSO-ADMM plan has better sparsity (means fewer spots) while maintaining a good plan quality (Figure 1 and Table 1). Specifically, for the liver case, the sparsity was increased from 70.84% (SSO-PDASC) to 88.91% (SSO-ADMM) and the dose objective was decreased from 1.59 to 0.72. Besides, compared to SSO-PDASC plan, SSO-ADMM reduced SSWT by 46% and SSPT by 62%. Similar phenomena were observed in the other two cases. Conclusions: This study developed a novel spot sparsity optimization algorithm for SPArc. Such an algorithm could reduce the number of spots further while maintaining the dosimetric plan quality. Table 1. Evaluation indicators for two plan groups.

Volume

12

Issue

Suppl

First Page

25

Comments

62nd Annual Conference of the Particle Therapy Cooperative Group (PTCOG), June 10-15, 2024, Singapore

DOI

10.1016/j.ijpt.2024.100166

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