Department of Medical Physics, Ludwig-Maximilians-Universität München, Munich, Germany. Author to whom any correspondence should be addressed.
Phys Med Biol. 2018 Oct 30;63(21):215025. doi: 10.1088/1361-6560/aae749.
Protons with modern pencil-beam scanning delivery are widely used in state-of-the-art radiotherapy. To reduce the unwanted effect of proton range uncertainties, prompt gamma (PG) monitoring is investigated and considered one of the most promising methods for real-time, in vivo range verification. Despite good correlation between the penetration depth of the PG signal and proton range in most cases, mismatch can occur especially because of tissue heterogeneities. Moreover, detectability and reproducibility of the prompt gamma signal critically depends on counting statistics. Nowadays, conventional treatment planning systems do not account for the degree of correlation between dose and PG signal nor the expected PG signal counting statistics, which considerably influences the possibility of a reliable verification of the intended beam range. Hence, in this project, we investigate a new treatment planning approach, in which the spot-by-spot conformities between PG and dose profiles (PG-dose correlation) as well as PG signal detectability and precision are taken into account based on a TPS optimizer. To investigate the feasibility of this idea, a research computational platform, combining Monte Carlo (MC, Geant4) pre-calculated pencil beams with the analytical Matlab-based TPS engine CERR, is used for treatment planning. Geant4 is employed for realistic simulation of the dose delivery and PG generation of all spots in the heterogeneous patient anatomy given by CT images. First of all, a treatment plan is created using a charged particle extension of CERR. Secondly, the PG fall-off positions of all individual pencil beams are evaluated and compared to the 80% distal dose fall-off positions. Thirdly, the PG-dose correlations of all spots are quantified. A new plan, in which a few spots with the best PG-dose correlation are boosted to ensure PG detectability with good precision, is then made. Finally, the optimized plan is fully recalculated on the same patient CT using Geant4, and the result is evaluated considering both plan quality and beam range monitorability. The evaluation shows that the re-optimized treatment plan is comparable to the initial plan in terms of dose distribution, dose averaged LET distribution and robustness, while fulfilling the set statistical conditions for reliable PG monitoring of the few automatically or manually selected spots. The method could thus complement, and for the selected pencil beams even overcome limitations of, alternative suggested approach such as pencil beam aggregation to provide sufficient counting statistics for precise PG range retrieval with good correlation to the treatment dose.
质子的现代笔形扫描输送被广泛应用于最先进的放射治疗中。为了减少质子射程不确定性的不良影响，人们研究了瞬发伽马（PG）监测，并认为这是实时体内射程验证最有前途的方法之一。尽管在大多数情况下，PG 信号的穿透深度与质子射程之间存在很好的相关性，但特别是由于组织不均匀性，可能会出现不匹配的情况。此外，瞬发伽马信号的可探测性和再现性严重依赖于计数统计。如今，传统的治疗计划系统不考虑剂量与 PG 信号之间的相关性程度，也不考虑预期的 PG 信号计数统计，这极大地影响了可靠验证预期射束射程的可能性。因此，在这个项目中，我们研究了一种新的治疗计划方法，该方法基于 TPS 优化器考虑了 PG 与剂量分布之间的逐点一致性（PG-剂量相关性）以及 PG 信号的可探测性和精度。为了研究这个想法的可行性，我们使用一个结合了蒙特卡罗（MC、Geant4）预计算笔形束与基于 Matlab 的分析性 TPS 引擎 CERR 的研究计算平台进行治疗计划。Geant4 用于对来自 CT 图像的异质患者解剖结构中的所有点的剂量输送和 PG 生成进行现实模拟。首先，使用 CERR 的带电粒子扩展创建治疗计划。其次，评估并比较所有单个笔形束的 PG 衰减位置与 80%远端剂量衰减位置。第三，量化所有点的 PG-剂量相关性。然后制作一个新的计划，其中几个具有最佳 PG-剂量相关性的点被提升，以确保具有良好精度的 PG 可探测性。最后，使用 Geant4 在同一患者 CT 上重新计算优化后的计划，并根据计划质量和束流范围可监测性进行评估。评估结果表明，重新优化的治疗计划在剂量分布、剂量平均 LET 分布和稳健性方面与初始计划相当，同时满足了为少数自动或手动选择的点进行可靠 PG 监测设定的统计条件。因此，该方法可以补充，甚至对于选定的笔形束，可以克服例如笔形束聚集等替代建议方法的限制，为精确的 PG 射程检索提供足够的计数统计，并与治疗剂量具有良好的相关性。
