Speaker
Description
Background: Therapeutic and accidental radiation exposure contexts typically focus on absorbed dose as the figure of merit for assessing tissue damage. However, physical processes underlying genetic damage are primarily mediated by secondary electrons with energies near the ionization threshold energy of DNA. This has motivated efforts to push Monte Carlo simulations of radiation transport to lower energies. Below 1 keV, however, the wavelength of the electron becomes comparable to interatomic distances, and therefore the semi-classical picture of localized interactions breaks down. Although quantum effects have been studied for systems involving purely absorptive inelastic interactions, the ionization cascade that ultimately induces biological effects has not been modelled in a similar quantum manner.
Purpose: To introduce a quantum model of low energy electron scattering that includes ionization events and focuses on classic microdosimetry quantities.
Methods: Building on a previous simplified quantum model of elastic scattering and absorption in a system of point scatterers, we propose a novel approach that further includes ionization events. Assuming rapid decoherence following ionization, our treelike branching model of a quantum history provides an accessible method to predict microdosimetry observables. We compare to analogous semi-classical simulations to estimate the bias of ignoring quantum effects. Included in our analysis is the probability distribution for the number of ionizations, the mean distance between ionizations, and the radial energy deposition profile.
Results: Using the same cross section inputs in both the quantum and the semi-classical models to highlight algorithmic differences, we find that the classical transport algorithm consistently overestimates the number of ionizations while also underestimating the energy deposited in each shell of a nanoscopic sphere. For DNA-like binding energies, the relative error of the shellwise energy deposition grows from 5% at an incident kinetic energy of 256 eV, up to 25% at 16 eV. No similar trend exists for the number of ionizations or the distance between ionizations.
Conclusions: Results suggest that there is no single scaling law for the relative error in all microdosimetric observables. Future work will expand the set of observables and geometries relevant to nanoscale energy deposition.
| Keyword-1 | Computational medical physics |
|---|---|
| Keyword-2 | Low-energy electron transport |
| Keyword-3 | Quantum simulations |