Abstract

Purpose

The linear-quadratic (LQ) model represents a simple and robust approximation for many mechanistically-motivated models of radiation effects. We believe its tendency to overestimate cell killing at high doses derives from the usual assumption that radiogenic lesions are distributed according to Poisson statistics.

Materials and methods

In that context, we investigated the effects of overdispersed lesion distributions, such as might occur from considerations of microdosimetric energy deposition patterns, differences in DNA damage complexities and repair pathways, and/or heterogeneity of cell responses to radiation. Such overdispersion has the potential to reduce dose response curvature at high doses, while still retaining LQ dose dependence in terms of the number of mean lethal lesions per cell. Here we analyze several irradiated mammalian cell and yeast survival data sets, using the LQ model with Poisson errors, two LQ model variants with customized negative binomial (NB) error distributions, the Padé-linear-quadratic, and Two-component models. We compared the performances of all models on each data set by information-theoretic analysis, and assessed the ability of each to predict survival at high doses, based on fits to low/intermediate doses.

Results

Changing the error distribution, while keeping the LQ dose dependence for the mean, enables the NB LQ model variants to outperform the standard LQ model, often providing better fits to experimental data than alternative models.

Conclusions

The NB error distribution approach maintains the core mechanistic assumptions of the LQ formalism, while providing superior estimates of cell survival following high doses used in radiotherapy. Importantly, it could also be useful in improving the predictions of low dose/dose rate effects that are of major concern to the field of radiation protection.

中文翻译：

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考虑到线性二次模型中致死病变的过度分散，可以提高高辐射剂量和低辐射剂量下的性能。

摘要

目的

线性二次 (LQ) 模型代表了许多受机械驱动的辐射效应模型的简单而稳健的近似。我们认为，其高估高剂量细胞杀伤的趋势源于通常的假设，即放射损伤是根据泊松统计分布的。

材料和方法

在这种情况下，我们研究了过度分散的病变分布的影响，例如可能由于微剂量能量沉积模式、DNA 损伤复杂性和修复途径的差异和/或细胞对辐射反应的异质性的考虑而发生。这种过度分散有可能降低高剂量下的剂量反应曲率，同时仍保持 LQ 剂量依赖的平均数量每个细胞的致死病变。在这里，我们使用具有泊松误差的 LQ 模型、具有自定义负二项式 (NB) 误差分布的两个 LQ 模型变体、Padé-线性二次型和双分量模型分析了几个辐照哺乳动物细胞和酵母存活数据集。我们通过信息理论分析比较了所有模型在每个数据集上的性能，并根据对低/中剂量的拟合来评估每个模型在高剂量下预测存活率的能力。

结果

改变误差分布，同时保持 LQ 对平均值的剂量依赖性，使 NB LQ 模型变体能够胜过标准 LQ 模型，通常比替代模型更适合实验数据。

结论

NB 误差分布方法保持了 LQ 形式的核心机制假设，同时提供了对放射治疗中使用的高剂量后细胞存活率的卓越估计。重要的是，它还可用于改进辐射防护领域主要关注的低剂量/剂量率效应的预测。