Centre for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland. Department of Physics, ETH Zurich, Zurich, Switzerland.
Phys Med Biol. 2019 Jan 29;64(3):035014. doi: 10.1088/1361-6560/aaf82d.
Patient specific quality assurance is crucial to guarantee safety in proton pencil beam scanning. In current clinical practice, this requires extensive, time consuming measurements. Additionally, these measurements do not consider the influence of density heterogeneities in the patient and are insensitive to delivery errors. In this work, we investigate the use of log file based Monte Carlo calculations for dose reconstructions in the patient CT, which takes the combined influence of calculational and delivery errors into account. For one example field, 87%/90% of the voxels agree within ±3% when taking either calculational or delivery uncertainties into account (analytical versus Monte Carlo calculation/Monte Carlo from planned versus Monte Carlo from log file). 78% agree when considering both uncertainties simultaneously (nominal field versus Monte Carlo from log files). We then show the application of the log file based Monte Carlo calculations as a patient specific quality assurance tool for a set of five patients (16 fields) treated for different indications. For all fields, absolute dose scaling factors based on the log file Monte Carlo agree within ±3% to the measurement based absolute dose scaling. Relative comparison shows that more than 90% of the voxels agree within ± 5% between the analytical calculated plan and the Monte Carlo based on log files. The log file based Monte Carlo approach is an end-to-end test incorporating all requirements of patient specific quality assurance. It has the potential to reduce the workload and therefore to increase the patient throughput, while simultaneously enabling more accurate dose verification directly in the patient geometry.
患者特异性质量保证对于保证质子笔束扫描的安全性至关重要。在当前的临床实践中,这需要进行广泛的、耗时的测量。此外,这些测量没有考虑到患者中的密度不均匀性的影响,并且对输送误差不敏感。在这项工作中,我们研究了基于日志文件的蒙特卡罗计算在患者 CT 中的剂量重建中的应用,该方法考虑了计算和输送误差的综合影响。对于一个示例场,当考虑计算或输送不确定性时(分析与蒙特卡罗计算/计划的蒙特卡罗与日志文件的蒙特卡罗),90%/87%的体素在±3%以内一致。当同时考虑两个不确定性时,78%的体素一致(名义场与日志文件的蒙特卡罗)。然后,我们展示了基于日志文件的蒙特卡罗计算作为一组五名患者(16 个场)的患者特异性质量保证工具的应用,这些患者接受了不同适应症的治疗。对于所有的场,基于日志文件的蒙特卡罗的绝对剂量缩放因子与基于测量的绝对剂量缩放因子在±3%以内一致。相对比较表明,在分析计算的计划和基于日志文件的蒙特卡罗之间,超过 90%的体素在±5%以内一致。基于日志文件的蒙特卡罗方法是一种端到端测试,包含了患者特异性质量保证的所有要求。它有可能减少工作量,从而增加患者的吞吐量,同时能够直接在患者几何形状中进行更准确的剂量验证。