Purpose: In case of a mass-casualty radiological event, there would be a need for networking to overcome surge limitations and to quickly obtain homogeneous results (reported aberration frequencies or estimated doses) among biodosimetry laboratories. These results must be consistent within such network. Inter-laboratory comparisons (ILCs) are widely accepted to achieve this homogeneity.
View Article and Find Full Text PDFCells exposed to fast neutrons often exhibit a non-Poisson distribution of chromosome aberrations due to the high ionization density of the secondary reaction products. However, it is unknown whether lymphocytes exposed to californium-252 (252Cf) spectrum neutrons, of mean energy 2.1 MeV, demonstrate this same dispersion effect at low doses.
View Article and Find Full Text PDFCells exposed to fast neutrons often exhibit a non-Poisson distribution of chromosome aberrations due to the high ionization density of the secondary reaction products. However, it is unknown whether lymphocytes exposed to californium-252 (252Cf) spectrum neutrons, of mean energy 2.1 MeV, demonstrate this same dispersion effect at low doses.
View Article and Find Full Text PDFPurpose: Inhomogeneous exposures to ionizing radiation can be detected and quantified with the dicentric chromosome assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole-body irradiation has significantly improved throughput without compromising accuracy, however, low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial-body exposure determination.
Materials And Methods: We describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells.
Humans are exposed to both natural (e.g. soil, cosmic rays) and human-made radiation sources (e.
View Article and Find Full Text PDFAccuracy of the automated dicentric chromosome (DC) assay relies on metaphase image selection. This study validates a software framework to find the best image selection models that mitigate inter-sample variability. Evaluation methods to determine model quality include the Poisson goodness-of-fit of DC distributions for each sample, residuals after calibration curve fitting and leave-one-out dose estimation errors.
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