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Biological dosimetry is a key technique for retrospective radiation dosimetry that provides individual estimates of absorbed dose of ionizing radiation, applicable for use in a large scale radiological/nuclear event. Current techniques for biodosimetry are labor intensive and time consuming and not high through-put. In this proof-of-concept study, we developed a new approach for detecting irradiated blood based on Raman spectroscopy of blood combined with multivariate analysis. Peripheral blood samples from 8 healthy male and female, anonymous donors, were exposed to either 5 Gy X ray radiation or unirradiated (0 Gy). At 3 h postirradiation, the blood was immediately frozen at –80°C. Raman spectra were measured from thawed blood using a portable spectrometer system. Data were preprocessed and analyzed using principal component analysis (PCA) to observe trends in the data, and by using partial least squares-discriminant analysis (PLS-DA) to build a model to discriminate between Raman spectra of control (0 Gy) and irradiated (5 Gy) blood. We found strong evidence of inter-donor variability in the form of donor-wise clustering of PCA scores corresponding to the control Raman spectra, in addition to the poor separation of PLS-DA scores associated with Raman intensities of 0 Gy vs. 5 Gy spectra. However, after adjustment for donor covariates using a linear mixed-effects model, we obtained a better separation between control and irradiated blood using PLS-DA. Evaluation of the coefficients of the PLS-DA loading vectors indicated radiation-induced changes in proteins, lipids and hemoglobin to be major contributors for this discrimination. This pilot study demonstrates the potential of application of Raman spectroscopy to support biodosimetry of blood and blood components.

Purpose The purpose of this work is to develop a new approach for high spatial resolution dosimetry based on Raman micro‐spectroscopy scanning of radiochromic film (RCF). The goal is to generate dose calibration curves over an extended dose range from 0 to 50 Gy and with improved sensitivity to low (<2 Gy) doses, in addition to evaluating the uncertainties in dose estimation associated with the calibration curves. Methods Samples of RCF (EBT3) were irradiated at a broad dose range of 0.03–50 Gy using an Elekta Synergy clinical linear accelerator. Raman spectra were acquired with a custom‐built Raman micro‐spectroscopy setup involving a 500 mW, multimode 785 nm laser focused to a lateral spot diameter of 30 µm on the RCF. The depth of focus of 34 µm enabled the concurrent collection of Raman spectra from the RCF active layer and the polyester laminate. The preprocessed Raman spectra were normalized to the intensity of the 1614 cm−1 Raman peak from the polyester laminate that was unaltered by radiation. The mean intensities and the corresponding standard deviation of the active layer Raman peaks at 696, 1445, and 2060 cm−1 were determined for the 150 × 100 µm2 scan area per dose value. This was used to generate three calibration curves that enabled the conversion of the measured Raman intensity to dose values. The experimental, fitting, and total dose uncertainty was determined across the entire dose range for the dosimetry system of Raman micro‐spectroscopy and RCF. Results In contrast to previous work that investigated the Raman response of RCFs using different methods, high resolution in the dose response of the RCF, even down to 0.03 Gy, was obtained in this study. The dynamic range of the calibration curves based on all three Raman peaks in the RCF extended up to 50 Gy with no saturation. At a spatial resolution of 30 × 30 µm2, the total uncertainty in estimating dose in the 0.5–50 Gy dose range was [6–9]% for all three Raman calibration curves. This consisted of the experimental uncertainty of [5–8]%, and the fitting uncertainty of [2.5–4.5]%. The main contribution to the experimental uncertainty was determined to be from the scan area inhomogeneity which can be readily reduced in future experiments. The fitting uncertainty could be reduced by performing Raman measurements on RCF samples at further intermediate dose values in the high and low dose range. Conclusions The high spatial resolution experimental dosimetry technique based on Raman micro‐spectroscopy and RCF presented here, could become potentially useful for applications in microdosimetry to produce meaningful dose estimates in cellular targets, as well as for applications based on small field dosimetry that involve high dose gradients.

The risk of large-scale radiological/nuclear events has notably increased in recent years. Biodosimetry is considered an essential tool for emergency management following such unplanned exposures to ionizing radiation. For example, by assessing an individual's received dose to blood, biodosimetry can support medical screening and individual health management. Current biodosimetry techniques, such as the dicentric chromosome assay, are based on the analysis of chromosomal aberrations Although highly accurate, these methods are time-consuming and labour-intensive. We recently developed a new high-throughput approach based on Raman spectroscopy of blood combined with covariate-adjusted multivariate analysis for the detection of irradiated blood. We found that the protein bands in the Raman spectra were the main sources of discrimination between unirradiated (control) and irradiated blood. In this follow up work, we explored the application of Raman spectroscopy and multivariate analysis to blood plasma to avoid dominant hemoglobin contributions. Peripheral blood drawn from a healthy volunteer was irradiated at 0 (control), 5 and 20 Gy using 250 kV Xrays. After a 4 hour incubation time, plasma centrifuged from the blood sample was immediately frozen at -80 deg C. Raman measurements were performed in triplicate on thawed blood plasma samples. Partial least squares-discriminant analysis (PLS-DA) was utilized for multi-class differentiation between Raman spectra of 0, 5 and 20 Gy irradiated plasma. Sparse PLS-DA (sPLS-DA) provided improved dose classification after combining Raman spectral data from different batches. Biomarker information related to radiation-induced changes in blood plasma was also extracted from sPLS-DA. The outcomes of these initial studies highlight the value of Raman spectroscopy to support biodosimetry.

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