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Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches

Errington, Adam; Einbeck, Jochen; Cumming, Jonathan

Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches Thumbnail


Authors

Adam Errington adam.errington@durham.ac.uk
PGR Student Doctor of Philosophy



Contributors

Massimiliano Vasile
Editor

Domenico Quagliarella
Editor

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.

Citation

Errington, A., Einbeck, J., & Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In M. Vasile, & D. Quagliarella (Eds.), Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications (393-405). Springer Verlag. https://doi.org/10.1007/978-3-030-80542-5_24

Online Publication Date Jul 16, 2021
Publication Date 2021
Deposit Date Feb 15, 2022
Publicly Available Date Jul 16, 2022
Publisher Springer Verlag
Pages 393-405
Series Title Proceedings of the 2020 UQOP International Conference
Series Number 8
Book Title Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications
DOI https://doi.org/10.1007/978-3-030-80542-5_24

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Accepted Book Chapter (227 Kb)
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Copyright Statement
This a post-peer-review, pre-copyedit version of a chapter published in Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-80542-5_24





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