Purpose: To quantitatively model a precise spot-scanning proton arc(SPArc) delivery sequence and assess its efficiency improvement in the routine proton clinical operation.
Methods: The SPArc delivery sequence model(DSMSPArc) includes two kinds of parameters:(1) mechanical parameters(the maximum gantry velocity, acceleration, and deceleration speed).(2) irradiation parameters (tolerance window and buffer, spot scanning speed, energy layer switching time, and burst switching time). An independent gantry inclinometer was used to measure mechanical parameters. Log files were used to derive the irradiation parameters through a series of SPArc test plans. The in-house DSMSPArc was established by fitting both mechanical and irradiation parameters.Eight SPArc plans from different disease sites(brain, HN, lung, and liver cancer) were used to validate the model's accuracy. To quantitatively assess the treatment efficiency improvement compared to the clinical IMPT, a random clinical operation date of our proton center(total 21 cases on Jan 6th 2021) was selected, and SPArc plans were generated for all the cases. The DSMSPArc was used to simulate the SPArc treatment delivery sequence and compared to the clinical IMPT treatment logfiles.
Results: The relative difference of treatment time between log files and DSMSPArc‘s prediction was 6.1%±3.9% on average, and the gantry angle vs. delivery time showed a good agreement between the DSMSPArc and log file. Additionally, the SPArc plan could effectively save two hours out of 10 hours of clinical operation by simplifying the treatment workflow for a single room proton therapy center. The average treatment delivery time (including gantry rotation and irradiation) per patient was reduced to 226±149s using SPArc compared to 665±407s using IMPT(p<0.01).
Conclusion: This is the first modeling of the SPArc delivery sequence, which paves the roadmap for implementing the delivery speed and time into the SPArc optimization algorithm. Additionally, SPArc can offer a superior delivery efficiency to improve clinical treatment throughput, compared to IMPT.
Funding Support, Disclosures, and Conflict of Interest: This study was supported by the research fundings from Ion Beam Application Inc.(IBA) and Beaumont Health Herb and Betty Fisher Research Seed Grant Award.Xuanfeng Ding, Xiaoqiang Li, and Di Yan have a patent related to the Particle Arc Therapy (WO2017156419). The patent has been licensed to Ion Beam Application, Belgium.
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