'Dirty dose'-based proton variable RBE models - performance assessment on in vitro data

基于“脏剂量”的质子可变RBE模型——体外数据性能评估

阅读:1

Abstract

BACKGROUND: In clinical proton radiotherapy, a constant relative biological effectiveness (RBE) of 1.1 is typically applied. Due to abundant evidence of variable RBE effects from in vitro data, multiple variable RBE models have been suggested, typically by describing the α and β parameters in the linear quadratic (LQ) model as a function of dose averaged linear energy transfer ( LETd ). PURPOSE: This work introduces a new variable RBE model based on the dirty dose concept, where dose deposited in voxels with a corresponding LET exceeding a specific threshold is considered "dirty" in the sense that it has a biological effect above the one predicted by a constant RBE of 1.1. As only one LET level, corresponding to a specific energy for a given particle in a given medium, needs to be monitored, this offers several advantages, such as simplified calculations by removing the need for intricate end of range LET calculations and averaging procedures, as well as opening up for more efficient experimental assessment of the cell specific model parameters. METHODS: Previously published in vitro data were utilized, where surviving fraction (SF), dose and LETd were reported for a pristine proton beam with varying physical PMMA thicknesses placed upstream of the cells. The setup was re-simulated to extract dirty dose metrics for the corresponding reported LETd -values. Models were created by setting the α parameter of the LQ model as a function of the fraction of dirty dose and subsequently benchmarked against models based on other radiation quality metrics by comparing the root-mean-square-error (RMSE) of the predicted and actual cell surviving fraction. RESULTS: Variable RBE models based on dirty dose perform on par with conventional radiation quality metrics with a RMSE of 0.38 for a dirty dose-based model with a threshold of 7 keV/μm , compared to 0.42 and 0.36 for a LETd -based and Qeff,d -based model, respectively. Higher chosen LET thresholds typically performed better and lower performed worse. CONCLUSION: The results indicate that models based on dirty dose metrics perform equally well as conventional radiation quality metrics. Due to the simplified calculations involved and the potential for more efficient measurement techniques for data generation, dirty dose-based models might be the most conservative and practical approach for creating future proton variable RBE models.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。