A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery

Authors

  • Gang Liu Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China; Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Xiaoqiang Li Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Lewei Zhao Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Weili Zheng Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • An Qin Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Sheng Zhang Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, PR China
  • Craig Stevens Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Di Yan Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Peyman Kabolizadeh Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA
  • Xuanfeng Ding Department of Radiation Oncology, Beaumont Health System, Royal Oak, MI, USA

DOI:

https://doi.org/10.1080/0284186X.2020.1765415

Abstract

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 (BDTfixed) and 2. An in-house dynamic arc scanning controller simulation which considered of gantry rotation speed, acceleration and deceleration (BDTarc).

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 vs.115), 70% (16 vs. 64), 82% (19 vs. 104), 80% (19 vs. 94) and 70% (9 vs. 30), which effectively shortened the BDTfixed by 65% (386 vs. 1091 s), 61% (235 vs. 609 s), 64% (336 vs. 928 s), 48% (787 vs.1521 s) and 25% (384 vs. 511 s) and shortened BDTarc by 54% (522 vs.1128 s), 52% (310 vs.645 s), 53% (443 vs. 951 s), 49% (803 vs.1583 s) and 26% (398 vs. 534 s) in prostate, lung, brain, HNC and breast cancer, respectively.

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.

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Published

2020-05-18

How to Cite

Liu, G., Li, X., Zhao, L., Zheng, W., Qin, A., Zhang, S., … Ding, X. (2020). A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery. Acta Oncologica, 59(10), 1178–1185. https://doi.org/10.1080/0284186X.2020.1765415