Abstract
If individuals are exposed to ionising radiation, due to some radiation accident, for medical reasons, or during spaceflight, there is often a need to estimate the contracted radiation dose. The field of biodosimetry is concerned with estimating the dose retrospectively, using certain biomarkers, which are typically based on counts of some cytogenetic or biomolecular features of the cell arising after radiation-induced double-strand-breaks. Such techniques face particular challenges when the exposure is only partial rather than whole-body, which, when unaccounted for, may lead to grossly inaccurate dose estimates. For biomarkers which are overdispersed, there are currently no procedures available for the detection of partial-body exposures. We consider the question of estimating the exposure fraction as well as quantifying its uncertainty, using Bayesian and frequentist methods, by means of simulation scenarios which are motivated by overdispersed count data (nuclear foci) as arising for the γ −H2AX protein biomarker.
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Acknowledgements
We thank Dr David Endesfelder, BfS, Neuherberg, Germany, for providing some rjags code for zero-inflated models. We also thank the Cytogenetics Group at PHE, Didcot, UK, for providing the γ-H2AX data used in Sect. 4.
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Appendix
Appendix
The following R code (used with package rjags) details the prior configurations used in Sect. 3. If the covariance matrix (betacov) is not available from the calibration curve (as in our case), it can be estimated from simulated data generated from that curve.
# Prior distribution for lambda f1 <- beta[1] + beta[2]∗D di[1] <- 1 di[2] <- D v <- inprod(di[1:2], betacov[1:2, 1:2] %∗% di[1:2]) lambda ~ dgamma(pow(f1, 2)/v,f1/v) # Prior distribution for alpha alpha ~ dgamma(0.005,0.01) # mean = 0.5, var = 50 # Prior distribution for dose D ~ dunif(0, 50) F ~ dbeta(1, 1) p <- (1-F) # F = 1-p assumption
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Errington, A., Einbeck, J., Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In: Vasile, M., Quagliarella, D. (eds) Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications. UQOP 2020. Space Technology Proceedings, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-030-80542-5_24
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DOI: https://doi.org/10.1007/978-3-030-80542-5_24
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