The effect of different lower detection thresholds in microdosimetric spectra and their mean values

Research on the applications of microdosimetry to particle therapy is spreading worldwide with a rapid increase of publications in the last years. In order to be able to perform an intercomparison of data acquired with different detectors in different clinical centres it is important to analyse data with a standard procedure. Often microdosimetric spectra are presented with different lower detection thresholds, in relation with different detection sensitivity and noise levels. The purpose of this paper is to analyse the influence of the lower detection threshold on the dose-mean lineal energy values, which are used as an assessment of the average LET of the radiation field. Furthermore, the dose distribution of the lineal energy can be used in combination with biological weighting functions to estimate the biological RBE at different positions along the penetration depths of therapeutic proton or carbon ion beams. Microdosimetric spectra cut at different lower thresholds lead in principle to different RBE values. It was an additional purpose of this work to analyse and discuss this effect both for proton and carbon ion irradiations. Spectra in proton and carbon ion beams gathered with a miniaturized TEPC developed at the Legnaro National Laboratories of the Italian Institute for Nuclear Physics (LNL-INFN) have been used to perform this study. Linear extrapolation of the microdosimetric spectra to a common value of 0.01 keV/mu m significantly reduces the deviations in the mean values due to different lower thresholds. It is advisable to perform this procedure to have uniformity in data analysis and facilitate the intercomparison of data.

Automated summary

Research on the applications of microdosimetry in particle therapy is increasing globally, requiring the analysis of data with a standard procedure. The lower detection threshold affects dose-mean lineal energy values and can lead to different RBE values. Linear extrapolation to a common value significantly reduces deviations in mean values due to different lower thresholds.