Microdosimetric considerations for radiation response studies using Raman spectroscopy.

Abstract

Recent Raman spectroscopy (RS) studies of radiation response involve subcellular (μm-scale) sampling volumes and macroscopic doses as low as 0.005 Gy. These studies ignore the stochastic nature of radiation transport and energy deposition, which can lead to considerable microdosimetric "spread" (i.e., variation in energy deposition). The goal of this work is to use Monte Carlo (MC) simulations to investigate the microdosimetric spread across populations of microscopic targets relevant for RS studies of cellular radiation response. Simulation geometries involve populations of 1600 cells, with two sizes of sampling volumes (representative of recent RS studies) considered within each nucleus, as well as averaging over multiple sampling volumes in the same nucleus. To investigate variation in microdosimetric spread as a function of dose and target size, simple cubic voxel geometries are also considered. MC simulations are used to score energy imparted per unit mass (specific energy, z) in targets (nuclei, sampling volumes, and voxels), considering doses from a few mGy to several Gy. Three photon spectra are considered: 120 kVp x-ray, cobalt-60, and a 6 MV medical linac. For μm-sized targets, there can be considerable variation in energy deposition across a population of targets: the specific energy distribution is skewed, a large fraction of targets receive no energy, and the standard deviation of the specific energy relative to the mean, , is considerable. These results vary with source energy and (macroscopic) dose: for 60 Co with cylindrical nuclei of 12.8 μm height and diameter, is 17% at 0.02 Gy, decreasing to 2% at 2 Gy. In contrast, for cylindrical sampling volumes with 1 μm diameter and 4 μm height, is 170% at 0.02 Gy and 18% at 2 Gy. Results of MC simulations involving cubic voxel geometries are fit to an equation relating the relative standard deviation of the specific energy to the target volume and dose; additionally, specific energy distributions are compared with normal distributions. Microdosimetric considerations are important for RS cellular radiation response studies, especially for low doses. The results of this work may motivate changes to current measurement and data analysis methods for RS experiments, and motivate future work comparing MC simulation results with RS measurements to advance understanding of radiation response.