Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.
Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, United Kingdom.
Biomed Phys Eng Express. 2021 Dec 17;8(1). doi: 10.1088/2057-1976/ac3f50.
The strongevidence that proton Relative Biological Effectiveness (RBE) varies with Linear Energy Transfer (LET) has led to an interest in applying LET within treatment planning. However, there is a lack of consensus on LET definition, Monte Carlo (MC) parameters or clinical methodology. This work aims to investigate how common variations of LET definition may affect potential clinical applications. MC simulations (GATE/GEANT4) were used to calculate absorbed dose and different types of LET for a simple Spread Out Bragg Peak (SOBP) and for four clinical PBT plans covering a range of tumour sites. Variations in the following LET calculation methods were considered: (i) averaging (dose-averaged LET (LET) & track-averaged LET); (ii) scoring (LETto water, to medium and to mass density); (iii) particle inclusion (LETto all protons, to primary protons and to particles); (iv) MC settings (hit type and Maximum Step Size (MSS)). LET distributions were compared using: qualitative comparison, LET Volume Histograms (LVHs), single value criteria (maximum and mean values) and optimised LET-weighted dose models. Substantial differences were found between LET values in averaging, scoring and particle type. These differences depended on the methodology, but for one patient a difference of ∼100% was observed between the maximum LETfor all particles and maximum LETfor all protons within the brainstem in the high isodose region (4 keVmand 8 keVmrespectively). An RBE model using LETincluding heavier ions was found to predict substantially different LET-weighted dose compared to those using other LET definitions. In conclusion, the selection of LET definition may affect the results of clinical metrics considered in treatment planning and the results of an RBE model. The authors' advocate for the scoring of dose-averaged LET to water for primary and secondary protons using a random hit type and automated MSS.
质子相对生物学效应（RBE）随线性能量转移（LET）变化的有力证据促使人们对治疗计划中的 LET 应用产生了兴趣。然而，在 LET 定义、蒙特卡罗（MC）参数或临床方法学方面，尚未达成共识。本工作旨在研究 LET 定义的常见变化如何可能影响潜在的临床应用。使用 MC 模拟（GATE/GEANT4）为简单的扩展布拉格峰（SOBP）和涵盖多种肿瘤部位的四个临床 PBT 计划计算吸收剂量和不同类型的 LET。考虑了以下 LET 计算方法的变化：（i）平均（剂量平均 LET（LET）和轨迹平均 LET）；（ii）评分（LET 到水、到中值和到质量密度）；（iii）粒子包含（LET 到所有质子、到初级质子和到粒子）；（iv）MC 设置（命中类型和最大步长（MSS））。使用定性比较、LET 体积直方图（LVHs）、单值标准（最大值和平均值）和优化的 LET 加权剂量模型比较 LET 分布。在平均、评分和粒子类型中发现 LET 值存在很大差异。这些差异取决于方法，但对于一名患者，在脑干高等剂量区域（分别为 4 keV/m 和 8 keV/m），所有粒子的最大 LET 和所有质子的最大 LET 之间观察到约 100%的差异。使用包括重离子的 LET 的 RBE 模型被发现与使用其他 LET 定义的模型相比，能够预测出明显不同的 LET 加权剂量。总之，LET 定义的选择可能会影响治疗计划中考虑的临床指标的结果和 RBE 模型的结果。作者提倡使用随机命中类型和自动 MSS 对初级和次级质子进行剂量平均 LET 到水的评分。
