Purpose: Proton spot delivery sequence is critical to the accurate evaluation of motion interplay effect. We proposed an experimental approach to build an accurate beam delivery time (BDT) prediction model for normal delivery, volumetirc and layer repainting delivery using a cyclotron accelerator system.
Methods: Test fields and clinical treatment plans were used to investigate each beam delivery parameters that impacted BDT. The machine delivery log files, from an IBA ProteusPlus system, were retrospectively analyzed to quantitatively model energy layer switching time (ELST), spot switching time (SSWT), and spot drill time (SDT) as well as the threshold spot MU to divide a layer into repaintings. Total of 103 clinical treatment fields (including normal delivery, volumetric, and layer repainting delivery) were used to validate the model.
Results: The study found that ELST is not a constant; instead, it depends on the two kinds of data files transmitted between two sequential radiation energy layers. One of them is the machine delivery log file of the previous layer irradiation record, and the other is a command file, which is used to instruct the proton system to deliver the next radiation layer. The validation showed that the accuracy of each component of the BDT matches well between machine log files and BDT prediction model. More specifically, the difference of ELST , SSWT and SDT were -0.99±3.18%, 4.66±10.88% and -3.89%±10.30%, respectively. The average total BDT was about -0.68±3.41% difference compared to the treatment log files, which is significantly improved from the current commercial proton system prediction(67.22±26.19%).
Conclusion: An accurate BDT prediction model was established for a cyclotron proton therapy system, IBA ProteusPLUS®, including normal, volumetric, and layer repainting through the experiments. This method would help each institution model its own proton system and better assess the interplay effect in treating mobile targets.
Funding Support, Disclosures, and Conflict of Interest: This research is supported in part by Ion Beam Application, research grant.