Abstract
The knowledge of respiratory particle transport in the extra-thoracic pathways is essential for the estimation of lung health-risk and optimization of targeted drug delivery. The published literature reports that a significant fraction of the inhaled aerosol particles are deposited in the upper airways, and available inhalers can deliver only a small amount of drug particles to the deeper airways. To improve the targeted drug delivery efficiency to the lungs, it is important to reduce the drug particle deposition in the upper airways. This study aims to minimize the unwanted aerosol particle deposition in the upper airways by employing a gas mixture model for the aerosol particle transport within the upper airways. A helium–oxygen (heliox) mixture (80% helium and 20% oxygen) model is developed for the airflow and particle transport as the heliox mixture is less dense than air. The mouth–throat and upper airway geometry are extracted from CT-scan images. Finite volume based ANSYS Fluent (19.2) solver is used to simulate the airflow and particle transport in the upper airways. Tecplot software and MATLAB code are employed for the airflow and particle post-processing. The simulation results show that turbulence intensity for heliox breathing is lower than in the case of air-breathing. The less turbulent heliox breathing eventually reduces the deposition efficiency (DE) at the upper airways than the air-breathing. The present study, along with additional patient-specific investigation, could improve the understanding of particle transport in upper airways, which may also increase the efficiency of aerosol drug delivery.
Highlights
Our general understanding of the airflow and inhaled particle transport in the human lung is improved by a wide range of numerical studies published in literature [1,2,3,4]
Polydisperse aerosol particles were considered for the particle transport study as both atmospheric and drug delivery device-generated particles are polydisperse
Summary, aa modeling modeling framework was developed to a modeling framework for at airthe and a helium–oxygen gas mixture wasDifferent developed to to predict the airflow and aerosol transport mouth–throat and upper airways
Summary
Our general understanding of the airflow and inhaled particle transport in the human lung is improved by a wide range of numerical studies published in literature [1,2,3,4]. A numerical analysis on the triple bifurcation model of the tracheobronchial airways used the LRN k-ω model and reported turbulence affects the airflow up to the first 5 generations at 30 lpm [12] Another numerical study investigated the particle transport for the first 16 generations of a non-realistic model and used the LRN k-ω model [13]. A computational study employed a heliox mixture for airflow and aerosol transport analysis in a CT-based airway model and predicted the velocity flow field for different breathing conditions [26]. The above computational study did not consider the mouth–throat region in its overall calculations It is, important to consider the oral airways for a better understanding of aerosol transport to the tracheobronchial and terminal. Mesh of the tracheobronchial airways, and (d) inflation mesh at the inlet section of the trachea
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