Numerical simulations of particle behaviour in a realistic human airway model with varying inhalation patterns

Abstract

Objectives For dry powder inhalers, the airflow properties in the airways could affect the deposition of inhaled particles; the flow patterns vary inherently between patients. This paper provides an evaluation of the effects of six airflow patterns on the behaviour of inhaled particles, as determined by using numerical simulations. Methods Constant‐velocity and unsteady inhalation flows were employed. The unsteady inhalation flow was set as an inhalation curve with a peak inspiratory flow rate. Under a constant flow of 28.3 l/min, the total flow rates were calculated to confirm the validity of the numerical simulation. The effects of different inhalation patterns on the particle behaviour in a realistic human airway model were revealed via numerical simulation. Key findings Different flow rates affected the behaviour and deposition of the inhaled particles. Under an inhalation flow pattern, different airflow tendencies were observed between the right and left bronchi. Particle deposition in the airways was promoted by a vortex following terminal‐velocity‐like breath‐holding. The inhalation flow pattern affected the behaviour and deposition of inhaled particles in the airway. Conclusions Our results indicated that particle deposition in a realistic human airway model was promoted by a vortex formation following the terminal‐velocity‐like breath‐holding. Moreover, the inhalation flow pattern significantly influenced the behaviour and deposition of inhaled particles in the airways. Additionally, the effect of flow patterns on the particle deposition in each airway position was quantitatively evaluated by numerical simulations for a realistic human airway model.

Salbutamol transport and deposition in healthy cat airways under different breathing conditions and particle sizes

“…We also found that some microparticles may travel and deposit in the sinus area, due to turbulent dispersion and secondary flow as described in rabbits (35). But in humans, the inhaled particles of 1 μm are effectively delivered distally (21), contrary to our results. In rodents, the maxilloturbinate region has been recognized as a very important and highly complex structure, accounting for over 50% airways resistance, bifurcating in several branches, and, in rabbits, acting as a filter for inhaled particles (35,36).…”

“…Li and co-workers in 2007 demonstrated that deposition of micro-particle is due to impaction, secondary flow convection, and turbulent dispersion (46,47). For this reason, in humans particles tend to deposit mainly at stagnation points (oral cavity, pharynx, larynx, and trachea) and rarely reach the deep bronchial region (21). In this study, deposition tends to be higher in the muzzle and in the nasal turbinates region due to its complex structure and the deposition was lower in the oropharynx and tracheal region.…”

“…The transport and distribution of particles are mainly affected by their size and the flow patterns during inhalation in humans (16). But the velocity, relative humidity (19), devices used to apply them, or the anatomy (20,21) also play roles. Spacers are chamber extensions to the pMDI attached to a mask that allow the inhalation of the drug without synchronization with the actuation of the inhaler (22).…”

A multiscale modeling method incorporating spatial coupling and temporal coupling into transient simulations of the human airways

“…Another trend of the human airway simulations is to use time-varied breath rates rather than steady breath rates. 7,17,18 Temporal scaling for application to transient airway modeling has not been investigated in the literature prior. Another challenge for the large-scale airway simulations would be the application of appropriate physics.…”

“…If not handled in a multiscale way, the upper coarse zones may waste numerous computational resources by using smaller timesteps. Another trend of the human airway simulations is to use time‐varied breath rates rather than steady breath rates 7,17,18 . Temporal scaling for application to transient airway modeling has not been investigated in the literature prior.…”