Robust Estimation of Lung Retention in Animals Exposed to α-Emitting Radionuclides

Abstract

Assessing human health risk using data from inhalation toxicology studies in laboratory animals exposed to α-emitting radionuclides requires estimating the temporal pattern of accumulation of lung dose in individual animals. Three quantities are required to estimate lung dose: a function describing lung retention, a function describing lung growth, and an estimate of initial lung burden.

To determine accurately the lung retention function for an individual animal, repeated measurements of the radionuclide content in the lung would need to be made over time and described by estimating appropriate parameters in the function for that animal. However, direct measurements of lung content can be made only at necropsy, so parameters in a lung retention function must be estimated from measurements on different animals. Thus, variability in data used for estimation of the lung retention function includes variability both within and between animals. Often the substantial observed variation causes problems in obtaining convergence of nonlinear algorithms and thus in obtaining stable parameter estimates.

In this paper, an iterative statistical reweighting approach based on residuals, in which functions of residuals from successive iterations are used as weights, is proposed to obtain robust estimates of the parameters of a lung retention function using data from different animals. This approach assumes that all animals have a similar lung retention function. The approach is illustrated and evaluated by estimating a lung retention function in rats exposed to ²³⁹PuO₂. Finally, data from another laboratory experiment in rats, in which the a-emitter is tagged with a γ-emitter, are shown to substantiate the validity of using a common lung retention function for different animals.