A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery.
Acta oncologica (Stockholm, Sweden)
BACKGROUND: Spot-scanning proton arc therapy (SPArc) has been proposed to improve dosimetric outcome and to simplify treatment workflow. To efficiently deliver a SPArc plan, it's crucial to minimize the number of energy layer switches (ELS) a sending because of the magnetic hysteresis effect. In this study, we introduced a new SPArc energy sequence optimization algorithm (SPArc_seq) to reduce ascended ELS and to investigate its impact on the beam delivery time (BDT).
METHOD AND MATERIALS: An iterative energy layer sorting and re-distribution mechanism following the direction of the gantry rotation was implemented in the original SPArc algorithm (SPArc_orig). Five disease sites, including prostate, lung, brain, head neck cancer (HNC) and breast cancer were selected to evaluate this new algorithm. Dose-volume histogram (DVH) and plan robustness were used to assess the plan quality for both SPArc_seq and SPArc_orig plans. The BDT evaluations were analyzed through two methods: 1. fixed gantry angle delivery (BDT
RESULTS: With a similar total number of energy layers, SPArc_seq plans provided a similar nominal plan quality and plan robustness compared to SPArc_orig plans. SPArc_seq significantly reduced the number of ascended ELS by 83% (19
CONCLUSIONS: The SPArc_seq optimization algorithm could effectively reduce the BDT compared to the original SPArc algorithm. The improved efficiency of the SPArc_seq algorithm has the potential to increase patient throughput, thereby reducing the operation cost of proton therapy.
Liu G, Li X, Zhao L, Zheng W, Qin A, Zhang S, Stevens C, Yan D, Kabolizadeh P, Ding X. A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery. Acta Oncol. 2020 Oct;59(10):1178-1185. doi: 10.1080/0284186X.2020.1765415. Epub 2020 May 18. PMID: 32421375.