Stochastic model of particle clearance in human bronchial airways.

A stochastic bronchial clearance model, based on a stochastic morphometric model of the human bronchial tree, has been developed, which simulates the combined action of fast and slow bronchial clearance mechanisms by Monte Carlo methods. To model fast bronchial clearance, mucus velocities in individual airways were based on a correlation between mucus velocity and airway diameter, considering conservation of mucus flow. In addition, mucus transport was assumed to be delayed at bronchial bifurcation zones. The size dependence of the slow bronchial clearance phase was considered by a linear relationship between the slow bronchial clearance fraction, f(s), and the geometric particle diameter, derived from bolus inhalation experiments. Potential variations of f(s) from proximal to distal airway generations were simulated by five different scenarios, which allocated slow bronchial clearance to successively peripheral bronchial regions. Alveolar clearance, which contributes only to longterm particle retention, was modeled by transfer rates supplied by the ICRP respiratory tract model. To test the different components of the clearance model, modeling predictions were compared with experimental retention data from bolus inhalation experiments, using various particle sizes and bolus front depths, as well as from slow inhalation experiments, with a flow rate of only 0.045 L sec(-1). The overall good agreement between modeling results and experimental data indicate that the present model correctly predicts bronchial clearance, suggesting that slow bronchial clearance mechanisms are most effective in smaller bronchial airways.