The first investigation of spot-scanning proton arc (SPArc) delivery time and accuracy with different delivery tolerance window settings.
Gang LiuLewei ZhaoPeilin LiuRiao DaoYujia QianXiaoda CongGuillaume JanssensXiaoqiang LiXuanfeng DingPublished in: Physics in medicine and biology (2023)
To investigate the impact of various delivery tolerance window settings on the treatment delivery time and dosimetric accuracy of spot-scanning proton arc (SPArc) therapy.
Approach: SPArc plans were generated for three representative disease sites (brain, head neck, and liver cancer) with an angle sampling frequency of 2.5 degrees. An in-house dynamic arc controller was used to simulate the arc treatment delivery with various tolerance windows (±0.25, ±0.5, ±1, and ±1.25 degrees). The controller generates virtual logfiles during the arc delivery simulation, such as gantry speed, acceleration and deceleration, spot position, and delivery sequence, similar to machine logfiles. The virtual logfile was then imported to the treatment planning system (TPS) to reconstruct the delivered dose distribution and compare it to the initial SPArc nominal plan. A three-dimensional gamma index was used to quantitatively assess delivery accuracy. Total treatment delivery time and relative lost time (dynamic arc delivery time - fix beam delivery time)/fix beam delivery time) were reported.
Main Results: The 3D Gamma Passing Rate (GPR) was greater than 99% for all cases when using 3%/3mm and 2%/2mm criteria and the GPR (1%/1mm criteria) degraded as the tolerance window opens. The total delivery time for dynamic arc delivery increased with the decreasing delivery tolerance window length. The average delivery time and the relative lost time (%) were 630±212s (253%±68%), 322±101s (81%±31%), 225±60s (27%±16%), 196±41s (11%±6%), 187±29s (6%±1%) for tolerance windows ±0.25, ±0.5, ±1, and ±1.25 degrees respectively.
Significance: The study quantitatively analyzed the dynamic SPArc delivery time and accuracy with different delivery tolerance window settings, which offer a critical reference in the future SPArc plan optimization and delivery controller design.
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