Fitting the Generalized Target Model to Cell Survival Data of Proton Radiation Reveals Dose-Dependent RBE and Inspires an Alternative Method to Estimate RBE in High-Dose Regions.

Abstract

The imprecise estimation of the relative biological effectiveness (RBE) of proton radiation has been one of the main challenges to further calculating the biologically effective dose in proton therapy. Since dose levels can greatly influence the proton RBE, the relationship between the two should be clarified first. In addition, since the dose-response curves are usually too complex to readily assess RBE in high-dose regions, a reliable and simple method is needed to predict the RBE of proton radiation accurately in clinically relevant doses. The standard linear-quadratic (LQ) model is widely used to determine the RBE of particles for clinical applications. However, there has been some debate over its use when modeling the cell survival curves in high-dose regions, since those survival curves usually show linear behavior in the semilogarithmic plot. By considering both cellular repair effects and indirect effects of radiation, we have proposed a generalized target model with linear-quadratic linear (LQL) characteristics. For the more accurate evaluation of proton RBE in radiotherapy, here we used this generalized target model to fit the cell survival data in V79 and C3H 10T1/2 cells exposed to proton radiation with different LETs. The fitting results show that the generalized target model works as well as the LQ model in general. Based on the fitting parameters of the generalized target model, the RBE of six given doses DT (RBET) could be calculated in the corresponding cell lines with different LETs. The results show that the RBET gradually decreases with increased dose in both cell types. In addition, inspired by the calculation method of the RBEM in the low-dose region, a novel method was proposed for estimating the RBE in the high-dose region (RBEH) based on the slope ratio of the dose-response curves in this region. Linear regression analysis indicated a significant linear correlation between the proposed RBEH and the RBET in high-dose regions, which suggests that the current method can be used as an alternative tool, which is both simple and robust, to estimate RBE in high-dose regions.