Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates
Vu Khac Hoang Bui, Ju‐Young Moon, Minhe Chae, Duckshin Park, Young‐Chul Lee
Abstract
The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches’ many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.