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Anatomical and physiological changes alter airflow characteristics and aerosol distribution in the developing lung. Correlation between age and aerosol dosimetry is needed, specifically because youth are more susceptible to medication side effects. In this study, we estimate aerosol dosages (particle diameters of 1, 3, and 5 [Formula: see text]m) in a 3 month-old infant, a 6 year-old child, and a 36 year-old adult by performing whole lung subject-specific particle simulations throughout respiration. For 3 [Formula: see text]m diameter particles we estimate total deposition as 88, 73, and [Formula: see text] and the conducting versus respiratory deposition ratios as 4.0, 0.5, and 0.4 for the infant, child, and adult, respectively. Due to their lower tidal volumes and functional residual capacities the deposited mass is smaller while the tissue concentrations are larger in the infant and child subjects, compared to the adult. Furthermore, we find that dose cannot be predicted by simply scaling by tidal volumes. These results highlight the need for additional clinical and computational studies that investigate the efficiency of treatment, while optimizing dosage levels in order to alleviate side effects, in youth.

Little is known about transport throughout the respiration cycle in the conducting airways. It is challenging to appropriately describe the time-dependent number of particles entering back into the model during exhalation. Modeling the entire lung is not feasible; therefore, multidomain methods must be used. Here, we present a new framework that is designed to simulate particles throughout the respiration cycle, incorporating realistic airway geometry and respiration. This framework is applied for a healthy rat lung exposed to  ∼ 1μm diameter particles, chosen to facilitate parameterization and validation. The flow field is calculated in the conducting airways (3D domain) by solving the incompressible Navier-Stokes equations with experimentally derived boundary conditions. Particles are tracked throughout inspiration by solving a modified Maxey-Riley equation. Next, we pass the time-dependent particle concentrations exiting the 3D model to the 1D volume conservation and advection-diffusion models (1D domain). Once the 1D models are solved, we prescribe the time-dependent number of particles entering back into the 3D airways to again solve for 3D transport. The coupled simulations highlight that about twice as many particles deposit during inhalation compared to exhalation for the entire lung. In contrast to inhalation, where most particles deposit at the bifurcation zones, particles deposit relatively uniformly on the gravitationally dependent side of the 3D airways during exhalation. Strong agreement to previously collected regional experimental data is shown, as the 1D models account for lobe-dependent morphology. This framework may be applied to investigate dosimetry in other species and pathological lungs., (Copyright © 2016 John Wiley & Sons, Ltd.)

There has been relatively little attention given on predicting particle deposition in the respiratory zone of the diseased lungs despite the high prevalence of chronic obstructive pulmonary disease (COPD). Increased alveolar volume and deterioration of alveolar septum, characteristic of emphysema, may alter the amount and location of particle deposition compared to healthy lungs, which is particularly important for toxic or therapeutic aerosols. In an attempt to shed new light on aerosol transport and deposition in emphysematous lungs, we performed numerical simulations in models of healthy and emphysematous acini motivated by recent experimental lobar-level data in rats (Oakes et al., 2014a). Compared to healthy acinar structures, models of emphysematous subacini were created by removing inter-septal alveolar walls and enhancing the alveolar volume in either a homogeneous or heterogeneous fashion. Flow waveforms and particle properties were implemented to match the experimental data. The occurrence of flow separation and recirculation within alveolar cavities was found in proximal generations of the healthy zones, in contrast to the radial-like airflows observed in the diseased regions. In agreement with experimental data, simulations point to particle deposition concentrations that are more heterogeneously distributed in the diseased models compared with the healthy one. Yet, simulations predicted less deposition in the emphysematous models in contrast to some experimental studies, a likely consequence due to the shallower penetration depths and modified flow topologies in disease compared to health. These spatial-temporal particle transport simulations provide new insight on deposition in the emphysematous acini and shed light on experimental observations., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

In silico models of airflow and particle deposition in the lungs are increasingly used to determine the therapeutic or toxic effects of inhaled aerosols. While computational methods have advanced significantly, relatively few studies have directly compared model predictions to experimental data. Furthermore, few prior studies have examined the influence of emphysema on particle deposition. In this work we performed airflow and particle simulations to compare numerical predictions to data from our previous aerosol exposure experiments. Employing an image-based 3D rat airway geometry, we first compared steady flow simulations to coupled 3D-0D unsteady simulations in the healthy rat lung. Then, in 3D-0D simulations, the influence of emphysema was investigated by matching disease location to the experimental study. In both the healthy unsteady and steady simulations, good agreement was found between numerical predictions of aerosol delivery and experimental deposition data. However, deposition patterns in the 3D geometry differed between the unsteady and steady cases. On the contrary, satisfactory agreement was not found between the numerical predictions and experimental data for the emphysematous lungs. This indicates that the deposition rate downstream of the 3D geometry is likely proportional to airflow delivery in the healthy lungs, but not in the emphysematous lungs. Including small airway collapse, variations in downstream airway size and tissue properties, and tracking particles throughout expiration may result in a more favorable agreement in future studies., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Image-based in silico modeling tools provide detailed velocity and particle deposition data. However, care must be taken when prescribing boundary conditions to model lung physiology in health or disease, such as in emphysema. In this study, the respiratory resistance and compliance were obtained by solving an inverse problem; a 0D global model based on healthy and emphysematous rat experimental data. Multi-scale CFD simulations were performed by solving the 3D Navier-Stokes equations in an MRI-derived rat geometry coupled to a 0D model. Particles with 0.95 μm diameter were tracked and their distribution in the lung was assessed. Seven 3D-0D simulations were performed: healthy, homogeneous, and five heterogeneous emphysema cases. Compliance (C) was significantly higher (p = 0.04) in the emphysematous rats (C = 0.37 ± 0.14 cm(3)/cmH2O) compared to the healthy rats (C = 0.25 ± 0.04 cm(3)/cmH2O), while the resistance remained unchanged (p = 0.83). There were increases in airflow, particle deposition in the 3D model, and particle delivery to the diseased regions for the heterogeneous cases compared to the homogeneous cases. The results highlight the importance of multi-scale numerical simulations to study airflow and particle distribution in healthy and diseased lungs. The effect of particle size and gravity were studied. Once available, these in silico predictions may be compared to experimental deposition data.