Targeting inhaled aerosol delivery to upper airways in children: Insight from computational fluid dynamics (CFD)

Abstract

Despite the prevalence of inhalation therapy in the treatment of pediatric respiratory disorders, most prominently asthma, the fraction of inhaled drugs reaching the lungs for maximal efficacy remains adversely low. By and large drug delivery devices and their inhalation guidelines are typically derived from adult studies with child dosages adapted according to body weight. While it has long been recognized that physiological (e.g. airway sizes, breathing maneuvers) and physical transport (e.g. aerosol dynamics) characteristics are critical in governing deposition outcomes, such knowledge has yet to be extensively adapted to younger populations. Motivated by such shortcomings, the present work leverages in a first step in silico computational fluid dynamics (CFD) to explore opportunities for augmenting aerosol deposition in children based on respiratory physiological and physical transport determinants. Using an idealized, anatomically-faithful upper airway geometry, airflow and aerosol motion are simulated as a function of age, spanning a five year old to an adult. Breathing conditions mimic realistic age-specific inhalation maneuvers representative of Dry Powder Inhalers (DPI) and nebulizer inhalation. Our findings point to the existence of a single dimensionless curve governing deposition in the conductive airways via the dimensionless Stokes number (Stk). Most significantly, we uncover the existence of a distinct deposition peak irrespective of age. For the DPI simulations, this peak (∼ 80%) occurs at Stk ≈ 0.06 whereas for nebulizer simulations, the corresponding peak (∼ 45%) occurs in the range of Stk between 0.03-0.04. Such dimensionless findings hence translate to an optimal window of micron-sized aerosols that evolves with age and varies with inhalation device. The existence of such deposition optima advocates revisiting design guidelines for optimizing deposition outcomes in pediatric inhalation therapy.

Computational Fluid Dynamic Models as Tools to Predict Aerosol Distribution in Tracheobronchial Airways

“…4a) (1). As expected, a laryngeal jet appears in the glottis region, where the noticeable constriction of the larynx forces the airflow to accelerate (16,20). The static pressure distribution in Fig.…”

“…A characteristic model, as the one described in this paper, reproduces all geometrical features of an average subject while neglecting unnecessary patient-specific details that could decrease the predictive efficiency of the model. Considering the domain extension, these models can be further categorized as single (4), double (5), or multiple (6,7) bifurcation models, complete tracheobronchial (TB) tree models (8)(9)(10), upper airways models (11)(12)(13), and complete airways models (3,(14)(15)(16)(17)(18)(19)(20).…”

“…Flow is computed by means of numerical models of the Navier-Stokes equation. The effects of air fluid dynamics and particle properties can usually be assessed considering various combinations of Reynolds and Stokes numbers (3,15,20,(26)(27)(28)(29)(30). Reynolds is a dimensionless number, ratio between inertial and viscous forces, and is it used to define the laminar/turbulent regime of flow in the model.…”

In Silico Optimization of Fiber-Shaped Aerosols in Inhalation Therapy for Augmented Targeting and Deposition across the Respiratory Tract

“…In turn, our strategy revolves around in silico numerical simulations of ellipsoid-shaped fibers of varying equivalent diameters (d p ) and aspect ratios (AR) in an upper airways model and a bronchial tree, adopting a multiscale approach in the footsteps of Koullapis et al [23]. In particular, the upper airways domain (see Figure 1a) follows recent work [25] on the fate of inhaled spherical aerosols in upper airway models (i.e., from the mouth to the 6th generation of the tracheobronchial respiratory tree). The mouth-throat region is modelled following the work of [26], and the first seven generations of the bronchial airway tree are modelled according to the seminal morphometric studies [27,28].…”

“…Here, we consider a simulated breathing maneuver that mimics a DPI profile (see Figure 1c) as a potential method to deliver non-spherical particles as a dry powder. The tidal volume (TV) is estimated as 2.95 L, the peak inspiration flow rate (PIFR) is estimated as 90 L/min, and the total inspiration period is 3 s [25] for an average human adult.…”