Laboratory of Experimental Radiotherapy, Department of Oncology, KU Leuven, Leuven, Belgium. Current address: Université Libre de Bruxelles, Avenue Franklin Roosevelt 50, 1050 Bruxelles, Belgium. Author to whom any correspondence should be addressed.
Phys Med Biol. 2019 Apr 29;64(9):095021. doi: 10.1088/1361-6560/ab120c.
Irradiation log-files store useful information about the plan delivery, and together with independent Monte Carlo dose engine calculations can be used to reduce the time needed for patient-specific quality assurance (PSQA). Nonetheless, machine log-files carry an uncertainty associated to the measurement of the spot position and intensity that can influence the correct evaluation of the quality of the treatment delivery. This work addresses the problem of the inclusion of these uncertainties for the final verification of the treatment delivery. Dedicated measurements performed in an IBA Proteus Plus gantry with a pencil beam scanning (PBS) dedicated nozzle have been carried out to build a 'room-dependent' model of the spot position uncertainties. The model has been obtained through interpolation of the look-up tables describing the systematic and random uncertainties, and it has been tested for a clinical case of a brain cancer patient irradiated in a dry-run. The delivered dose has been compared with the planned dose with the inclusion of the errors obtained applying the model. Our results suggest that the accuracy of the treatment delivery is higher than the spot position uncertainties obtained from the log-file records. The comparison in terms of DVHs shows that the log-reconstructed dose is compatible with the planned dose within the 95% confidence interval obtained applying our model. The initial mean dose difference between the calculated dose to the patient based on the plan and recorded data is around 1%. The difference is essentially due to the log-file uncertainties and it can be removed with a correct treatment of these errors. In conclusion our new PSQA protocol allows for a fast verification of the dose delivered after every treatment fraction through the use of machine log-files and an independent Monte Carlo dose engine. Moreover, the inclusion of log-file uncertainties in the dose calculation allows for a correct evaluation of the quality of the treatment plan delivery.
辐照日志文件存储有关计划交付的有用信息，并且与独立的蒙特卡罗剂量引擎计算一起使用，可以减少患者特定质量保证 (PSQA) 的时间。尽管如此，机器日志文件携带与测量斑点位置和强度相关的不确定性，这可能会影响治疗交付质量的正确评估。这项工作解决了将这些不确定性纳入最终治疗交付验证的问题。已经在配备专用笔束扫描 (PBS) 喷嘴的 IBA Proteus Plus 龙门架中进行了专用测量，以构建斑点位置不确定性的“房间相关”模型。该模型是通过描述系统和随机不确定性的查找表进行插值获得的，并且已经针对在干运行中照射脑癌患者的临床病例进行了测试。已经将递送剂量与包括应用模型获得的误差在内的计划剂量进行了比较。我们的结果表明，治疗交付的准确性高于从日志文件记录中获得的斑点位置不确定性。在包括应用我们的模型获得的 95%置信区间内的剂量体积直方图 (DVH) 比较表明，日志重建剂量与计划剂量兼容。基于计划和记录数据计算的患者剂量的初始平均剂量差异约为 1%。差异主要是由于日志文件的不确定性，并且可以通过正确处理这些误差来消除。总之，我们的新 PSQA 协议允许通过使用机器日志文件和独立的蒙特卡罗剂量引擎，在每次治疗后快速验证递送的剂量。此外，在剂量计算中包含日志文件不确定性可以正确评估治疗计划交付的质量。
