A simulation approach for determining the spectrum of DNA damage induced by protons. (29th August 2018)

• Record Type: Journal Article
• Authors: Mokari, Mojtaba; Alamatsaz, Mohammad Hassan; Moeini, Hossein; Taleei, Reza
• Is Part Of: Physics in medicine & biology. Volume 63:Number 17(2018:Sep.)
• Publication Date: 2018-08-29
• Subjects: DNA damage -- Geant4-DNA -- Monte Carlo simulations -- double-strand break; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/aad7ee
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: To study the molecular damage induced in the form of single-strand and double-strand breaks by ionizing radiation at the DNA level, the Geant4-DNA Monte Carlo simulation code for complete transportation of primary protons and other secondary particles in liquid water has been employed in this work. To this aim, a B-DNA model and a thorough classification of the complexity of the DNA damage were used. Strand breaks were assumed to have primarily originated by direct physical interactions via energy depositions, assuming a threshold energy of 17.5 eV, or indirect chemical reactions of hydroxyl radicals, assuming a probability of 0.13. The simulation results on the complexity and frequency of various damages are computed for proton energies of 0.5–20 MeV. The yield results for a cell (Gy cell) −1 are presented, assuming 22 chromosomes per cell and a mean number of 245 Mbp per chromosome. The results show that for proton energies below 2 MeV, more than 50% of the energy depositions within the DNA volume resulted in strand breaks. For double-strand breaks (DSBs), there is considerable sensitivity of DSB frequency to the proton energy. A comparison of DSB frequencies predicted by different simulations and experiments is presented as a function of proton linear energy transfer (LET). We show that our yield results (Gy Gbp) −1 are generally comparable with various experimental data and there seems to be a better agreement between our results and a number of experimental studies when compared to other simulations.