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BACKGROUND:The human respiratory airway undergoes dramatic growth during infancy and childhood, which induces substantial variability in air flow pattern and particle deposition. However, deposition studies have typically focused on adult subjects, the results of which cannot be readily extrapolated to children. We developed models to quantify the growth of human nasallaryngeal airways at early ages, and to evaluate the impact of that growth on breathing resistance and aerosol deposition. METHODS: Four image-based nasal-laryngeal models were developed from 4 children, ages 10 days, 7 months, 3 years, and 5 years, and were compared to a nasallaryngeal model of a 53-year-old adult. The airway dimensions were quantified in terms of different parameters (volume, cross-section area, and hydraulic diameter) and of different anatomies (nose, pharynx, and larynx). Breathing resistance and aerosol deposition were computed using a highfidelity fluid-particle transport model, and were validated against the measurements made with the 3-dimensional models fabricated from the same airway computed tomography images. RESULTS: Significant differences in nasal morphology were observed among the 5 subjects, in both morphology and dimension. The turbinate region appeared to experience the most noticeable growth during the first 5 years of life. The nasal airway volume ratios of the 10-day, 7-month, 3-year, and 5-year-old subjects were 6.4%, 18.8%, 24.2%, and 40.3% that of the adult, respectively. Remarkable inter-group variability was observed in air flow, pressure drop, deposition fraction, and particle accumulation. The computational fluid dynamics predicted pressure drops and deposition fractions were in close agreement with in vitro measurements. CONCLUSIONS: Age effects are significant in both breathing resistance and micrometer particle deposition. The image/computational-fluid-dynamics coupled method provides an efficient and effective approach in understanding patient-specific air flows and particle deposition, which have important implications in pediatric inhalation drug delivery and respiratory disorder diagnosis.

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The objective of this study is to systematically assess the influences of the larynopharyneal anatomical details on airflow and particle behaviors during exhalation by means of image-based modeling. A physiologically realistic nose-throat airway was developed with medical images. Individual airway anatomy such as uvula, pharynx, and larynx were then isolated for examination by progressively simplifying this image-based model geometry. Low Reynolds number (LRN) k- model and Langrangian tracking model were used to simulate the dynamics of airflow and particle transport for a wide range of exhalation conditions (4-45 L/min) and particle sizes (1 nm-1 μm). Results showed that pharyngeal anatomical details exerted a significant impact on breathing resistance and particle profiles. Abrupt pressure drop resulting from the uvula-related airway obstruction was observed. Even though the total deposition rate in the nasal airway is largely unaffected by the upstream effect, the local deposition patterns vary notably. Results of this study also indicate that the pressure drop appears to be an appropriate parameter to characterize the geometric variations for diffusive depositions. Inclusion of pressure drop (D 0.5 Q −0.62 dp 0.07) gives an improved correlation than using the conventional diffusion factor (D 0.5 Q −0.28).

Accurate knowledge of the delivery of locally acting drug products, such as metered-dose inhaler (MDI) formulations, to large and small airways is essential to develop reliable in vitro/in vivo correlations (IVIVCs). However, challenges exist in modeling MDI delivery, due to the highly transient multiscale spray formation, the large variability in actuation–inhalation coordination, and the complex lung networks. The objective of this study was to develop/validate a computational MDI-releasing-delivery model and to evaluate the device actuation effects on the dose distribution with the newly developed model. An integrated MDI–mouth–lung (G9) geometry was developed. An albuterol MDI with the chlorofluorocarbon propellant was simulated with polydisperse aerosol size distribution measured by laser light scatter and aerosol discharge velocity derived from measurements taken while using a phase Doppler anemometry. The highly transient, multiscale airflow and droplet dynamics were simulated by using large eddy simulation (LES) and Lagrangian tracking with sufficiently fine computation mesh. A high-speed camera imaging of the MDI plume formation was conducted and compared with LES predictions. The aerosol discharge velocity at the MDI orifice was reversely determined to be 40 m/s based on the phase Doppler anemometry (PDA) measurements at two different locations from the mouthpiece. The LES-predicted instantaneous vortex structures and corresponding spray clouds resembled each other. There are three phases of the MDI plume evolution (discharging, dispersion, and dispensing), each with distinct features regardless of the actuation time. Good agreement was achieved between the predicted and measured doses in both the device, mouth–throat, and lung. Concerning the device–patient coordination, delayed MDI actuation increased drug deposition in the mouth and reduced drug delivery to the lung. Firing MDI before inhalation was found to increase drug loss in the device; however, it also reduced mouth–throat loss and increased lung doses in both the central and peripheral regions.