Monte Carlo simulations of energy deposition and DNA damage using TOPAS-nBio

Monte Carlo (MC) track structure codes are commonly used for predicting energy deposition and radiation-induced DNA damage at the nanometer scale. Various simulation parameters such as physics model, DNA model, and direct damage threshold have been developed. The differences in adopted parameters lead to disparity in calculation results, which requires quantitative evaluation.

Three simulation configurations were implemented in TOPAS-nBio MC toolkit to investigate the impact of physics models, DNA model, and direct damage threshold on the prediction of energy deposition and DNA damage. Dose point kernels (DPKs) of electrons and nanometer-sized volumes irradiated with electrons, protons, and alpha particles were utilized to evaluate the impact of physics models on energy deposition. Proton irradiation of plasmid DNA was used to investigate the disparity in single-strand break and double-strand break (DSB) yields caused by differences in physics models, DNA models, and direct damage thresholds.

Electron DPKs obtained with different physics models show similar trends but different diffusiveness and maximums. Energy deposition distributions in nanometer-sized volumes irradiated with electrons, protons, and alpha particles calculated using different physics models have the same trend although discrepancies can be observed at the lowest and highest energy deposits. Strand breaks from incident protons in DNA plasmids vary with adopted parameters. For the configurations in this study, changing physics model, DNA model, and direct damage threshold can cause differences of up to 57%, 69%, and 15% in DSB yields, respectively. All these simulation results are essentially in agreement with previously published simulation or experimental studies.

All the physics models, DNA models, and direct damage thresholds investigated in this study are applicable to predict energy deposition and DNA damage. Although the choice of parameters can lead to disparity in simulation results, which serves as a reference for future studies.