Abstract
Exposure of lung airways to detrimental suspended aerosols in the environment increases the vulnerability of the respiratory and cardiovascular systems. In addition, recent developments in therapeutic inhalation devices magnify the importance of particle transport. In this manuscript, particle transport and deposition patterns in the upper tracheobronchial (TB) tree were studied where the inertial forces are considerable for microparticles. Wall shear stress divergence (WSSdiv) is proposed as a wall-based parameter that can predict particle deposition patterns. WSSdiv is proportional to near-wall normal velocity and can quantify the strength of flow towards and away from the wall. Computational fluid dynamics (CFD) simulations were performed to quantify airflow velocity and WSS vectors for steady inhalation in one case-control and unsteady inhalation in six subject-specific airway trees. Turbulent flow simulation was performed for the steady case using large eddy simulation to study the effect of turbulence. Magnetic resonance velocimetry (MRV) measurements were used to validate the case-control CFD simulation. Inertial particle transport was modeled by solving the Maxey-Riley equation in a Lagrangian framework. Deposition percentage (DP) was quantified for the case-control model over five particle sizes. DP was found to be proportional to particle size in agreement with previous studies in the literature. A normalized deposition concentration (DC) was defined to characterize localized deposition. A relatively strong correlation (Pearson value > 0.7) was found between DC and positive WSSdiv for physiologically relevant Stokes (St) numbers. Additionally, a regional analysis was performed after dividing the lungs into smaller areas. A spatial integral of positive WSSdiv over each division was shown to maintain a very strong correlation (Pearson value > 0.9) with cumulative spatial DC or regional dosimetry. The conclusions were generalized to a larger population in which two healthy and four asthmatic patients were investigated. This study shows that WSSdiv could be used to predict the qualitative surface deposition and relative regional dosimetry without the need to solve a particle transport problem.