Room: AAPM ePoster Library
Purpose: Secondary neutrons produced in radiotherapy pose an energy-dependent carcinogenic risk to patients and staff, as evidenced by the ICRP neutron weighting factors. Although the underlying biophysical phenomena for the energy-dependence are not well characterized, it is generally accepted that clustered DNA damage induced by ionizing radiation significantly impairs DNA repair pathways and can lead to mutations and carcinogenesis. This investigation aims to evaluate the energy-dependence of neutron RBE for mutagenesis by scoring clustered DNA damage in a geometric DNA model via Monte Carlo simulations.
Methods: Our group has previously used the Monte Carlo toolkit, Geant4 to generate the energy spectra of secondary particles produced by monoenergetic neutrons in a tissue phantom as a function of energy and depth. The secondary spectra produced by reference 250 keV x-rays were also generated in order to facilitate calculations of RBE. In this work, these spectra are stochastically sampled to generate particle tracks in Geant4-DNA simulations, which are imposed upon an open-source model of nuclear DNA. To characterize DNA damage induced by the sampled secondary particles tracks, we are developing a novel algorithm to quantify clustering of individual DNA lesions (base damages, single-strand breaks, double-strand breaks) that occur within 1-2 turns of the DNA double helix.
Results: We intend to present neutron RBE for clustered DNA damage (a proxy for mutagenic RBE) as a function of energy and compare with the ICRP neutron weighting factors. Our data will be made compatible with the recently-published standard DNA damage (SDD) data format and released publicly along with our simulation and clustering code.
Conclusion: We aim to enhance the understanding of the energy-dependent carcinogenic risk associated with secondary neutron radiation using an open-source computational approach. Future comparison and cross-validation with experimental analyses of neutron-induced mutation signatures may aid in improving risk estimates for radiotherapy patients.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) (Alexander Graham Bell Canada Graduate Scholarship-Doctoral: L. Montgomery, Discovery Grant: J. Kildea) and the McGill Faculty of Medicine (James O. and Maria Meadows Fellowship: L. Montgomery).