Nanoparticle transport and deposition in a heterogeneous human lung airway tree: An efficient one path model for CFD simulations

Abstract

Understanding nano-particle inhalation in human lung airways helps targeted drug delivery for treating lung diseases. A wide range of numerical models have been developed to analyse nano-particle transport and deposition (TD) in different parts of airways. However, a precise understanding of nano-particle TD in large-scale airways is still unavailable in the literature. This study developed an efficient one-path numerical model for simulating nano-particle TD in large-scale lung airway models. This first-ever one-path numerical approach simulates airflow and nano-particle TD in generations 0–11 of the human lung, accounting for 93% of the whole airway length. The one-path model enables the simulation of particle TD in many generations of airways with an affordable time. The particle TD of 5 nm, 10 nm and 20 nm particles is simulated at inhalation flow rates for two different physical activities: resting and moderate activity. It is found that particle deposition efficiency of 5 nm particles is 28.94% higher than 20 nm particles because of the higher dispersion capacity. It is further proved that the diffusion mechanism dominates the particle TD in generations 0–11. The deposition efficiency decreases with the increase of generation number irrespective of the flow rate and particle size. The effects of the particle size and flow rate on the escaping rate of each generation are opposite to the corresponding effects on the deposition rate. The quantified deposition and escaping rates at generations 0–11 provide valuable guidelines for drug delivery in human lungs.