Pilot study reveals Raman spectroscopy classifies ionizing radiation exposure in blood plasma, indicating its utility as a biodosimetry technique.
Biodosimetry is a key technique for retrospective radiation dosimetry that provides individual estimates of the absorbed dose of ionizing radiation based on the detection of biological indicators. A critical challenge confronting current biodosimetry methods is the time and technical expertise needed in processing and analyzing samples, therefore new high-throughput techniques are required. In this pilot study, we demonstrate a technique based on RS and multivariate analysis of peripheral blood plasma from nine healthy male and female anonymous donors for the classification and biomarker identification of ex vivo irradiated blood exposed to 0 (control), 5 and 20 Gy of X-ray dose. After 4 hours post-exposure, the blood was centrifuged, and the blood plasma samples were immediately frozen at -80 ºC. Raman spectra were measured from thawed blood plasma using a custom benchtop Raman micro-spectroscopy setup. Data were preprocessed and analyzed using partial least squares-discriminant analysis (PLS-DA). We applied a method based on a linear mixed-effects model to compensate for the differences in covariates such as gender, age and complete blood count between donors. After covariate adjustment, the application of PLS-DA to the residual Raman spectral intensities provided improved separation in the binary classification results (0 vs 5 and 0 vs 20 Gy). Raman spectral biomarkers responsible for the discrimination were extracted by evaluating the coefficients of the PLS-DA loading vectors. Sparse PLS-DA was demonstrated to be a promising method that offers the potential to further narrow down the regions in the Raman spectra that are dose discriminatory.
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Beausoleil-Morrison et al. (2025) studied this question.
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