Unfolding the background of secondary ions in measured nanodosimetric ionisation cluster size distributions

Abstract

Nanodosimetry is a methodology for quantifying the effects of ionising radiation on matter by determining the frequency distributions of the cluster size of ionisations in nanometric target volumes. In previous investigations with the Ion Counter nanodosimeter operated at PTB, significant deviations for large cluster sizes were found in the comparison between measured and simulated data of ionisation cluster size distributions. These deviations could be explained by a background of secondary ions, which are produced within the transport system of the ionised target molecules. In this paper, two different approaches were investigated to correct for the background of secondary ions in the measured data to obtain the “true” cluster size distribution to be used, e. g., in predictions of biological effectiveness. In the first approach, the correction of the background was treated as a minimising problem. In the second approach, an iterative unfolding algorithm using Bayes statistics was employed. In all cases where the convolution of the background-corrected results with the secondary ion background agrees well with the corresponding measured cluster size distribution, the background-correction led to an improved agreement between measurement and simulation. For the removal of a background of secondary ions from measured cluster size distributions, the unfolding algorithm using Bayes statistics is the preferred method as it proved to be the most effective and the least sensitive to boundary conditions. Moreover, it was considerably less time consuming.