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

Errington, Adam; Einbeck, Jochen; Cumming, Jonathan

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
• Public URL: https://durham-repository.worktribe.com/output/1646041