Coupling Radiation Transport and Track-Structure Simulations: Strategy Based on Analytical Formulas Representing DNA Damage Yields

Existing radiation codes for biomedical applications face the challenge of dealing with largely different spatial scales, from nanometer scales governing individual energy deposits to macroscopic scales of dose distributions in organs and tissues in radiotherapy. Event-by-event track-structure codes are needed to model energy deposition patterns at cellular and subcellular levels. In conjunction with DNA and chromatin models, they predict radiation-induced DNA damage and subsequent biological effects. Describing larger-scale effects is the realm of radiation transport codes and dose calculation algorithms. A coupling approach with a great potential consists in implementing into radiation transport codes the results of track-structure simulations captured by analytical formulas. This strategy allows extending existing transport codes to biologically relevant endpoints, without the need of developing dedicated modules and running new computationally expensive simulations. Depending on the codes used and questions addressed, alternative strategies can be adopted, reproducing DNA damage in dependence on different parameters extracted from the transport code, e.g., microdosimetric quantities, average linear energy transfer (LET), or particle energy. Recently, a comprehensive database on DNA damage induced by ions from hydrogen to neon, at energies from 0.5 GeV/u down to their stopping, has been created with PARTRAC biophysical simulations. The results have been captured as a function of average LET in the cell nucleus. However, the formulas are not applicable to slow particles beyond the Bragg peak, since these can have the same LET as faster particles but in narrower tracks, thus inducing different DNA damage patterns. Particle energy distinguishes these two cases. It is also more readily available than LET from some transport codes. Therefore, a set of new analytical functions are provided, describing how DNA damage depends on particle energy. The results complement the analysis of the PARTRAC database, widening its potential of application and use for implementation in transport codes.