A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay

Einbeck, Jochen; Ainsbury, Elizabeth A.; Sales, Rachel; Barnard, Stephen; Kaestle, Felix; Higueras, Manuel

doi:10.1371/journal.pone.0207464

A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay

Einbeck, Jochen; Ainsbury, Elizabeth A.; Sales, Rachel; Barnard, Stephen; Kaestle, Felix; Higueras, Manuel

Authors

Professor Jochen Einbeck jochen.einbeck@durham.ac.uk
Professor

Elizabeth A. Ainsbury

Rachel Sales

Stephen Barnard

Felix Kaestle

Manuel Higueras

Abstract

Over the last decade, the γ–H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double–strand–breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure to ionizing radiation. While the existing literature has convincingly demonstrated a dose–response effect, and also presented approaches to dose estimation based on appropriately defined calibration curves, a more widespread practical use is still hampered by a certain lack of discussion and agreement on the specific dose–response modelling and uncertainty quantification strategies, as well as by the unavailability of implementations. This manuscript intends to fill these gaps, by stating explicitly the statistical models and techniques required for calibration curve estimation and subsequent dose estimation. Accompanying this article, a web applet has been produced which implements the discussed methods.

Citation

Einbeck, J., Ainsbury, E. A., Sales, R., Barnard, S., Kaestle, F., & Higueras, M. (2018). A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay. PLoS ONE, 13(11), https://doi.org/10.1371/journal.pone.0207464

Journal Article Type	Article
Acceptance Date	Oct 31, 2018
Online Publication Date	Nov 28, 2018
Publication Date	Nov 28, 2018
Deposit Date	Dec 13, 2018
Publicly Available Date	Dec 13, 2018
Journal	PLoS ONE
Publisher	Public Library of Science
Peer Reviewed	Peer Reviewed
Volume	13
Issue	11
DOI	https://doi.org/10.1371/journal.pone.0207464

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Copyright Statement
Copyright: © 2018 Einbeck et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
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reproduction in any medium, provided the original
author and source are credited.