Americium biodistribution in rats after wound contamination with different physicochemical forms in the presence or absence of plutonium: analyses using STATBIODIS

Abstract

Americium (Am) biodistribution data obtained after wound contamination in rats were analysed to evaluate and quantify the influence of different physicochemical forms of Am in the presence or absence of plutonium (Pu). The biodistribution data were individual Am daily urinary excretion and tissue retention. The data were analysed with STATBIODIS, a statistical tool developed in the laboratory and based on the R language. Non-parametric methods were selected to comply with the data characteristics. Am systemic tissue retention and urinary excretion data were much greater for contamination with soluble physicochemical forms than insoluble forms. Meanwhile, Am relative biodistribution between the main retention tissues (skeleton, liver and kidney) remained the same. Hence, after absorption into blood the radionuclide behaviour was independent of the physicochemical form. The presence of Pu did not change the Am biodistribution. Comparisons of the biodistribution data from the laboratory with mean values published by other laboratories showed that soluble to moderately soluble forms of Am resulted in similar urine excretion after contamination, whether it was intravenous, intramuscular, subcutaneous injection or incision. Findings from this work will contribute to improve the understanding and interpretation of wound contamination cases with different physicochemical forms and mixtures of actinides including Am.

DTPA Treatment of Wound Contamination in Rats with Americium: Evaluation of Urinary Profiles Using STATBIODIS Shows Importance of Prompt Administration

“…The 24-h urinary excretion of Am was fitted using non-linear regression with a sum of two exponential terms for untreated and treated rats (Table 4). Regression coefficients for untreated groups, e.g., r 1 = 3.7 ± 0.2 d −1 and r 2 = 0.3 ± 0.03 d −1 , remained similar to those published with wound contamination data obtained up until 2016, r 1 = 3.6 ± 0.2 d −1 and r 2 = 0.3 ± 0.03 d −1 (Lamart et al 2019). This observation confirmed that recent wound experiments were consistent with those carried out previously.…”

“…Prior to running comparison tests, data and effects of interest were identified and characterized in terms of sample size, paired or unpaired data, and fixed or random effects. Nonparametric rank-based methods adapted to small and uneven samples, independent or paired data, and mixed effects were applied (Lamart et al 2019). Overall effects were evaluated using the f1.LD.f1 function from the {nparLD} R package (Noguchi et al 2012).…”

“…Experimental data from the wound experiments were analyzed using the statistical tool STATBIODIS, based on the R language (Lamart et al 2017, Lamart et al 2019, R Core Team 2019.…”

“…It enables manipulation of a large set of individual data, adjustment of urinary excretion with sum of exponential terms, and comparison of data that accounts for small sample sizes, longitudinal data and mixed effects. STATBIODIS was used previously to analyse biodistribution data of Am obtained after wound contamination with Am nitrate, deposited alone or with Pu nitrate, or with MOX, with presence of Am as a decay product of 241 Pu (Lamart et al 2019).…”

“…To facilitate the overall analysis of these large biodistribution datasets, the statistical tool STATBIODIS was developed in the laboratory (Lamart et al 2017(Lamart et al , 2019. It enables manipulation of a large set of individual data; adjustment of urinary excretion with sum of exponential terms; and comparison of data that account for small sample sizes, longitudinal data, and mixed effects.…”