背景:对于质子治疗,1.1的相对生物学有效性(RBE)在临床上被广泛应用。然而,由于体外存在大量的RBE变量的证据,正如对患者预后的研究所建议的那样,RBE可能会在质子轨道结束时增加,如几个提出的变量RBE模型所述。通常,剂量平均线性能量转移(LETd$\\text{LET}_d$)已被用作这些模型的辐射质量度量(RQM)。然而,RQM的最优选择尚未得到充分探索。
目的:本研究旨在提出新型RQM,可有效地对不同能量的质子进行加权,并评估其在质子治疗中对可变RBE的预测能力。总体目标是确定RQM,该RQM更好地描述了单个粒子对质子束RBE的贡献。
方法:利用SHIELD-HIT12A蒙特卡罗粒子传输代码模拟了用于质子RBE测定的体外细胞存活研究的高通量实验装置。对于每个数据点,模拟质子能谱,允许通过对LET或有效Q$Q$(Qeff$Q_\\mathrm{eff}$)值的光谱应用不同的功率水平来计算新的RQM。然后将现象学的基于线性二次的RBE模型应用于体外数据,使用各种RQM作为输入变量,并且通过每个数据点的细胞存活分数的对数的均方根误差(RMSE)来评估模型性能。
结果:提高功率水平,也就是说,在构建RQM时,对更高的LET粒子施加更高的权重通常与增加的模型性能相关,剂量平均LET3$\\text{LET}^3$(即,剂量平均立方LET,cLETd$\\mathrm{cLET}_d$)导致RMSE值0.31,而基于(线性加权)LETd$\\text{LET}_d$的模型为0.45,轨道平均和Qeff$Q_\mathrm{eff}$为基础的RQMs也观察到类似的趋势。
结论:结果表明,假设单个质子的非线性RBE(LET)关系,可以构建改进的质子变量RBE模型。如果类似的趋势也适用于体外环境,cLETd$\\mathrm{cLET}_d$或跟踪的平均立方LET(cLETt$\\mathrm{cLET}_t$)可能更好地描述了可变RBE效果,或相应的Qeff$Q_\\mathrm{eff}基于$的RQM,而不是今天常规应用的线性加权LETd$\\text{LET}_d$或LETt$\\text{LET}_t$。
BACKGROUND: For
proton therapy, a relative biological effectiveness (RBE) of 1.1 is widely applied clinically. However, due to abundant evidence of variable RBE in vitro, and as suggested in studies of patient outcomes, RBE might increase by the end of the
proton tracks, as described by several proposed variable RBE models. Typically, the dose averaged linear energy transfer ( LET d $\\text{LET}_d$ ) has been used as a radiation quality metric (RQM) for these models. However, the optimal choice of RQM has not been fully explored.
OBJECTIVE: This study aims to propose novel RQMs that effectively weight protons of different energies, and assess their predictive power for variable RBE in proton therapy. The overall objective is to identify an RQM that better describes the contribution of individual particles to the RBE of
proton beams.
METHODS: High-throughput experimental set-ups of in vitro cell survival studies for
proton RBE determination are simulated utilizing the SHIELD-HIT12A Monte Carlo particle transport code. For every data point, the
proton energy spectra are simulated, allowing the calculation of novel RQMs by applying different power levels to the spectra of LET or effective Q $Q$ ( Q eff $Q_\\mathrm{eff}$ ) values. A phenomenological linear-quadratic-based RBE model is then applied to the in vitro data, using various RQMs as input variables, and the model performance is evaluated by root-mean-square-error (RMSE) for the logarithm of cell surviving fractions of each data point.
RESULTS: Increasing the power level, that is, putting an even higher weight on higher LET particles when constructing the RQM is generally associated with an increased model performance, with dose averaged LET 3 $\\text{LET}^3$ (i.e., dose averaged cubed LET, cLET d $\\mathrm{cLET}_d$ ) resulting in a RMSE value 0.31, compared to 0.45 for a model based on (linearly weighted) LET d $\\text{LET}_d$ , with similar trends also observed for track averaged and Q eff $Q_\\mathrm{eff}$ -based RQMs.
CONCLUSIONS: The results indicate that improved proton variable RBE models can be constructed assuming a non-linear RBE(LET) relationship for individual protons. If similar trends hold also for an in vitro-environment, variable RBE effects are likely better described by cLET d $\\mathrm{cLET}_d$ or tracked averaged cubed LET ( cLET t $\\mathrm{cLET}_t$ ), or corresponding Q eff $Q_\\mathrm{eff}$ -based RQM, rather than linearly weighted LET d $\\text{LET}_d$ or LET t $\\text{LET}_t$ which is conventionally applied today.