Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, BT9 7AE, United Kingdom.
Phys Med Biol. 2021 Feb 17;66(4):04NT02. doi: 10.1088/1361-6560/abda98.
Uncertainties in the relative biological effectiveness (RBE) of protons remains a major barrier to the biological optimisation of proton therapy. While a constant value of 1.1 is widely used in treatment planning, extensive preclinical in vitro and in vivo data suggests that proton RBE is variable, depending on proton energy, target tissue, and endpoint. A number of phenomenological models have been developed to try and explain this variation, but agreement between these models is often poor. This has been attributed to both the models' underlying assumptions and the data to which they are fit. In this brief note, we investigate the underlying trends in these models by comparing their predictions as a function of relevant biological and physical parameters, to determine where models are in conceptual agreement or disagreement. By doing this, it can be seen that the primary differences between models arise from how they handle biological parameters (i.e. [Formula: see text] and [Formula: see text] from the linear-quadratic model for photon exposures). By contrast, when specifically explored for linear energy transfer-dependence, all models show extremely good correlation. These observations suggest that there is a pressing need for more systematic exploration of biological variation in RBE across different cells in well-controlled conditions to help distinguish between these different models and identify the true behaviour.
质子的相对生物学效应(RBE)的不确定性仍然是质子治疗生物学优化的主要障碍。虽然在治疗计划中广泛使用 1.1 的恒定值,但广泛的临床前体外和体内数据表明,质子 RBE 是可变的,取决于质子能量、靶组织和终点。已经开发了许多唯象模型来试图解释这种变化,但这些模型之间的一致性往往很差。这归因于模型的基本假设和它们所适应的数据。在这篇简短的说明中,我们通过比较这些模型作为相关生物和物理参数的函数的预测,来研究这些模型的基本趋势,以确定模型在概念上是一致还是不一致。通过这样做,可以看出模型之间的主要区别在于它们如何处理生物参数(即线性二次模型中用于光子暴露的 [Formula: see text] 和 [Formula: see text])。相比之下,当专门针对线性能量转移依赖性进行探索时,所有模型都显示出非常好的相关性。这些观察结果表明,迫切需要在良好控制的条件下对不同细胞的 RBE 中的生物学变异性进行更系统的探索,以帮助区分这些不同的模型并确定真实的行为。