A Geant4-DNA Evaluation of Radiation-Induced DNA Damage on a Human Fibroblast

Accurately modeling the radiobiological mechanisms responsible for the induction of DNA damage remains a major scientific challenge, particularly for understanding the effects of low doses of ionizing radiation on living beings, such as the induction of carcinogenesis. A computational approach based on the Monte Carlo technique to simulate track structures in a biological medium is currently the most reliable method for calculating the early effects induced by ionizing radiation on DNA, the primary cellular target of such effects. The Geant4-DNA Monte Carlo toolkit can simulate not only the physical, but also the physico-chemical and chemical stages of water radiolysis. These stages can be combined with simplified geometric models of biological targets, such as DNA, to assess direct and indirect early DNA damage. In this study, DNA damage induced in a human fibroblast cell was evaluated using Geant4-DNA as a function of incident particle type (gammas, protons, and alphas) and energy. The resulting double-strand break yields as a function of linear energy transfer closely reproduced recent experimental data. Other quantities, such as fragment length distribution, scavengeable damage fraction, and time evolution of damage within an analytical repair model also supported the plausibility of predicting DNA damage using Geant4-DNA.The complete simulation chain application molecularDNA , an example for users of Geant4-DNA, will soon be distributed through Geant4.

Automated summary

Accurately modeling radiobiological mechanisms for DNA damage induction is a major challenge, with the Monte Carlo method being the most reliable for calculating early effects of ionizing radiation on DNA. The Geant4-DNA toolkit can simulate physical, physico-chemical, and chemical stages of water radiolysis to assess direct and indirect DNA damage. Studies have shown that Geant4-DNA can closely reproduce experimental data on double-strand break yields and support the prediction of DNA damage.