Although the major mechanisms of aerosol deposition in the lung are known, detailed quantitative data in anatomically realistic models are still lacking, especially in the acinar airways. In this study, an algorithm was developed to build multigenerational three-dimensional models of alveolated airways with arbitrary bifurcation angles and spherical alveolar shape. Using computational fluid dynamics, the deposition of 1- and 3-μm aerosol particles was predicted in models of human alveolar sac and terminal acinar bifurcation under rhythmic wall motion for two breathing conditions (functional residual capacity = 3 liter, tidal volume = 0.5 and 0.9 liter, breathing period = 4 s). Particles entering the model during one inspiration period were tracked for multiple breathing cycles until all particles deposited or escaped from the model. Flow recirculation inside alveoli occurred only during transition between inspiration and expiration and accounted for no more than 1% of the whole cycle. Weak flow irreversibility and convective transport were observed in both models. The average deposition efficiency was similar for both breathing conditions and for both models. Under normal gravity, total deposition was ∼33 and 75%, of which ∼67 and 96% occurred during the first cycle, for 1- and 3-μm particles, respectively. Under zero gravity, total deposition was ∼2–5% for both particle sizes. These results support previous findings that gravitational sedimentation is the dominant deposition mechanism for micrometer-sized aerosols in acinar airways. The results also showed that moving walls and multiple breathing cycles are needed for accurate estimation of aerosol deposition in acinar airways.
A Self-Consistent Scheme for Understanding Particle Impact and Adhesion in the Aerosol Deposition Process
