A biomathematical model of particle clearance and retention in the lungs of coal miners.
To understand better the factors influencing the relationships among airborne particle exposure, lung burden, and fibrotic lung disease, we developed a biologically based kinetic model to predict the long-term retention of particles in the lungs of coal miners. This model includes alveolar, interstitial, and hilar lymph node compartments. The 131 miners in this study had worked in the Beckley, West Virginia, area and died during the 1960s. The data used to develop this model include exposure to respirable coal mine dust by intensity and duration within each job, lung and lymph node dust burdens at autopsy, pathological classification of fibrotic lung disease, and smoking history. Initial parameter estimates for this model were based on both human and animal data of particle deposition and clearance and on the biological and physical factors influencing these processes. Parameter estimation and model fit to the data were determined using least squares. Results show that the end-of-life lung dust burdens in these coal miners were substantially higher than expected from first-order clearance kinetics, yet lower than expected from the overloading of alveolar clearance predicted from rodent studies. The best-fitting and most parsimonious model includes processes for first-order alveolar-macrophage-mediated clearance and transfer of particles to the lung interstitium. These results are consistent with the particle retention patterns observed previously in the lungs of primates. The findings indicate that rodent models extrapolated to humans, without adjustment for the kinetic differences in particle clearance and retention, would be inadequate for predicting lung dust burdens in humans. Also, this human lung kinetic model predicts greater retained lung dust burdens from occupational exposure than predicted from current human models based on lower exposure data. This model is useful for risk assessment of particle-induced lung diseases, by estimating equivalent internal doses in rodents and humans and predicting lung burdens in humans with occupational dust exposures.