Vassiliev Oleg N, Peterson Christine B, Grosshans David R, Mohan Radhe
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Br J Radiol. 2020 Aug;93(1112):20190949. doi: 10.1259/bjr.20190949. Epub 2020 Jun 4.
The relative biological effectiveness (RBE) of X-rays and γ radiation increases substantially with decreasing beam energy. This trend affects the efficacy of medical applications of this type of radiation. This study was designed to develop a model based on a survey of experimental data that can reliably predict this trend.
In our model, parameters and of a cell survival curve are simple functions of the frequency-average linear energy transfer () of delta electrons. The choice of these functions was guided by a microdosimetry-based model. We calculated by using an innovative algorithm in which is associated with only those electrons that reach a sensitive-to-radiation volume (SV) within the cell. We determined model parameters by fitting the model to 139 measured () pairs.
We tested nine versions of the model. The best agreement was achieved with [Formula: see text] and β being linear functions of [Formula: see text] .The estimated SV diameter was 0.1-1 µm. We also found that , , and the ratio increased with increasing [Formula: see text] .
By combining an innovative method for calculating [Formula: see text] with a microdosimetric model, we developed a model that is consistent with extensive experimental data involving photon energies from 0.27 keV to 1.25 MeV.
We have developed a photon RBE model applicable to an energy range from ultra-soft X-rays to megaelectron volt γ radiation, including high-dose levels where the RBE cannot be calculated as the ratio of values. In this model, the ionization density represented by [Formula: see text] determines the RBE for a given photon spectrum.
X射线和γ辐射的相对生物效应(RBE)会随着束流能量的降低而大幅增加。这种趋势会影响此类辐射在医学应用中的疗效。本研究旨在基于对实验数据的调查开发一个模型,该模型能够可靠地预测这种趋势。
在我们的模型中,细胞存活曲线的参数α和β是δ电子的频率平均线能量转移(LET)的简单函数。这些函数的选择以基于微剂量学的模型为指导。我们通过使用一种创新算法来计算LET,在该算法中,LET仅与那些在细胞内到达辐射敏感体积(SV)的电子相关联。我们通过将模型拟合到139对测量的(α,β)数据来确定模型参数。
我们测试了该模型的九个版本。当α和β是LET的线性函数时,模型与实验数据的吻合度最佳。估计的SV直径为0.1 - 1μm。我们还发现,α、β以及α/β比值会随着LET的增加而增大。
通过将一种计算LET的创新方法与微剂量学模型相结合,我们开发了一个与大量实验数据一致的模型,这些实验数据涉及从0.27 keV到1.25 MeV的光子能量。
我们开发了一个光子RBE模型,该模型适用于从超软X射线到兆电子伏特γ辐射的能量范围,包括无法将RBE计算为D0值之比的高剂量水平。在这个模型中,由LET表示的电离密度决定了给定光子谱的RBE。