Biochemistry Publications
Document Type
Article
Publication Date
1-9-2019
Journal
Radiation protection dosimetry
URL with Digital Object Identifier
10.1093/rpd/ncy282
Abstract
Accuracy 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. The process iteratively searches a pool of selection model candidates by modifying statistical and filter cut-offs to rank the best candidates according to their respective evaluation scores. Evaluation scores minimize the sum of squared errors relative to the actual radiation dose of the calibration samples. For one laboratory, the minimum score for the curve fit residual method was 0.0475 Gy2, compared to 1.1975 Gy2 without image selection. Application of optimal selection models using samples of unknown exposure produced estimated doses within 0.5 Gy of physical dose. Model optimization standardizes image selection among samples and provides relief from manual DC scoring, improving accuracy and consistency of dose estimation.
Citation of this paper:
Yanxin Li, Ben C Shirley, Ruth C Wilkins, Farrah Norton, Joan H M Knoll, Peter K Rogan, RADIATION DOSE ESTIMATION BY COMPLETELY AUTOMATED INTERPRETATION OF THE DICENTRIC CHROMOSOME ASSAY, Radiation Protection Dosimetry, , ncy282, https://doi.org/10.1093/rpd/ncy282
Included in
Biochemistry Commons, Bioinformatics Commons, Genetics Commons, Radiation Medicine Commons
Notes
Available open access in Radiation Protection Dosymetry, available at https://doi.org/10.1093/rpd/ncy282