Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden.
Acta Oncol. 2013 Apr;52(3):580-8. doi: 10.3109/0284186X.2012.705892. Epub 2012 Aug 22.
The biological effects of particles are often expressed in relation to that of photons through the concept of relative biological effectiveness, RBE. In proton radiotherapy, a constant RBE of 1.1 is usually assumed. However, there is experimental evidence that RBE depends on various factors. The aim of this study is to develop a model to predict the RBE based on linear energy transfer (LET), dose, and the tissue specific parameter α/β of the linear-quadratic model for the reference radiation. Moreover, the model should capture the basic features of the RBE using a minimum of assumptions, each supported by experimental data.
The α and β parameters for protons were studied with respect to their dependence on LET. An RBE model was proposed where the dependence of LET is affected by the (α/β)phot ratio of photons. Published cell survival data with a range of well-defined LETs and cell types were selected for model evaluation rendering a total of 10 cell lines and 24 RBE values.
A statistically significant relation was found between α for protons and LET. Moreover, the strength of that relation varied significantly with (α/β)phot. In contrast, no significant relation between β and LET was found. On the whole, the resulting RBE model provided a significantly improved fit (p-value < 0.01) to the experimental data compared to the standard constant RBE. By accounting for the α/β ratio of photons, clearer trends between RBE and LET of protons were found, and our results suggest that late responding tissues are more sensitive to LET changes than early responding tissues and most tumors. An advantage with the proposed RBE model in optimization and evaluation of treatment plans is that it only requires dose, LET, and (α/β)phot as input parameters. Hence, no proton specific biological parameters are needed.
粒子的生物学效应通常通过相对生物学效应(RBE)的概念与光子的生物学效应相关联。在质子放射治疗中,通常假设 RBE 为常数 1.1。然而,有实验证据表明 RBE 取决于各种因素。本研究的目的是开发一种基于线性能量传递(LET)、剂量和参考辐射的线性二次模型的组织特异性参数α/β来预测 RBE 的模型。此外,该模型应使用最少的假设来捕获 RBE 的基本特征,每个假设都得到实验数据的支持。
研究了质子的α和β参数与其与 LET 的关系。提出了一种 RBE 模型,其中 LET 的依赖性受光子的(α/β)phot 比值的影响。选择了具有一系列明确定义的 LET 和细胞类型的已发表的细胞存活数据来评估模型,共涉及 10 种细胞系和 24 个 RBE 值。
发现质子的α与 LET 之间存在显著的关系。此外,这种关系的强度随(α/β)phot 而显著变化。相比之下,没有发现β与 LET 之间存在显著关系。总的来说,与标准常数 RBE 相比,所得到的 RBE 模型对实验数据提供了显著改善的拟合(p 值<0.01)。通过考虑光子的α/β 比值,可以发现 RBE 与质子的 LET 之间更清晰的趋势,并且我们的结果表明,晚期反应组织比早期反应组织和大多数肿瘤对 LET 变化更敏感。与所提出的 RBE 模型相比,在治疗计划的优化和评估方面具有优势,因为它只需要剂量、LET 和(α/β)phot 作为输入参数。因此,不需要质子特异性生物学参数。