EPR Dosimetry in Human Fingernails: Investigation of the Origin of the Endogenous Signal and Implications for Estimating Dose from Nail Signals

Human nails have been studied for many years for potential use for dosimetry, based on the EPR signals induced by ionizing radiation, but a fully validated protocol to measure doses retrospectively has not yet been developed. The major problem is that the EPR spectrum of irradiated nails is complex and its radiation-induced signals (RIS) overlap with an endogenous signal called the background signal (BKS). RIS and BKS have similar spectral parameters. Therefore, detailed characterization of the BKS is required to develop a method for measuring the amount of RIS by removing the signal due to BKS from the total spectrum of irradiated nails. Effects of reducing and oxidizing treatments of fingernail samples on the BKS were studied. Numerical simulations of the observed BKSs were performed. Common features of the EPR spectra in fingernails are discussed. We also found that BKS can be generated in the fingernail clippings by oxidation in ambient air with dioxygen. Results support the hypothesis that BKS is an o-semiquinone radical anion. Comparison of the chemical and spectral properties of the BKS and with the RIS 5 (the stable signal suitable for dose assessment) suggests that both sets of radicals underlying these signals are o-semiquinone radicals. Given the common chemical properties of the BKS and RIS 5, it is unlikely that chemical treatment methods will provide a way to differentiate these two signals in irradiated nail spectra. Instead, other methods (i.e., dose-additive methods, population-derived BKS means) may be necessary to selectively estimate the content of BKS and RIS 5 in irradiated nail spectra.

Automated summary

Human nails have been studied for their potential use in dosimetry using EPR signals induced by ionizing radiation. However, no fully validated protocol for retrospective dose measurement has been developed. The complexity of the EPR spectrum and the overlap between radiation-induced signals and background signals pose a major challenge. Detailed characterization of background signals is required to measure the radiation-induced signals accurately.