Radiation dose estimation with time-since-exposure uncertainty using the γ -H2AX biomarker

Dorota Młynarczyk*, Pedro Puig, Carmen Armero, Virgilio Gómez-Rubio, Joan F. Barquinero, Mònica Pujol-Canadell

*Autor correspondiente de este trabajo

Producción científica: Contribución a una revistaArtículoInvestigaciónrevisión exhaustiva

2 Citas (Scopus)


To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker, phosphorylated γ-H2AX protein, is used to evaluate cell damage and is thus suitable for the dose estimation process. In this paper, we present new Bayesian methods that, in contrast to approaches where estimation is carried out at predetermined post-irradiation times, allow for uncertainty regarding the time since radiation exposure and, as a result, produce more precise results. We also use the Laplace approximation method, which drastically cuts down on the time needed to get results. Real data are used to illustrate the methods, and analyses indicate that the models might be a practical choice for the γ-H2AX biomarker dose estimation process.

Idioma originalInglés
Número de artículo19877
Número de páginas8
EstadoPublicada - 18 nov 2022


Profundice en los temas de investigación de 'Radiation dose estimation with time-since-exposure uncertainty using the γ -H2AX biomarker'. En conjunto forman una huella única.

Citar esto