Numerical simulations of aerosol delivery to the human lung with an idealized laryngeal model, image-based airway model, and automatic meshing algorithm.

The authors proposed a new method to automatically mesh computed tomography (CT)-based three-dimensional human airway geometry for computational fluid dynamics (CFD)-based simulations of pulmonary gas-flow and aerosol delivery. Traditional methods to construct and mesh realistic geometry were time-consuming, because they were done manually using image-processing and mesh-generating programs. Furthermore, most of CT thoracic image data sets do not include the upper airway structures. To overcome these issues, the proposed method consists of CFD grid-size distribution, an automatic meshing algorithm, and the addition of a laryngeal model along with turbulent velocity inflow boundary condition attached to the proximal end of the trachea. The method is based on our previously developed geometric model with irregular centerlines and cross-sections fitted to CT segmented airway surfaces, dubbed the "fitted-surface model." The new method utilizes anatomical information obtained from the one-dimensional tree, e.g., skeleton connectivity and branch diameters, to efficiently generate optimal CFD mesh, automatically impose boundary conditions, and systematically reduce simulation results. The aerosol deposition predicted by the proposed method agreed well with the prediction by a traditional CT-based model, and the laryngeal model generated a realistic level of turbulence in the trachea. Furthermore, the computational time was reduced by factor of two without losing accuracy by using the proposed grid-size distribution. The new method is well suited for branch-by-branch analyses of gas-flow and aerosol distribution in multiple subjects due to embedded anatomical information.

Effect of static vs. dynamic imaging on particle transport in CT-based numerical models of human central airways.

Advances in quantitative computed tomography (CT) has provided methods to assess the detailed structure of the pulmonary airways and parenchyma, providing the means of applying computational fluid dynamics-based modeling to better understand subject-specific differences in structure-to-function relationships. Most of the previous numerical studies, seeking to predict patterns of inhaled particle deposition, have considered airway geometry and regional ventilation derived from static images. Because geometric alterations of the airway and parenchyma associated with regional ventilation may greatly affect particle transport, we have sought to investigate the effect of rigid vs. deforming airways, linear vs. nonlinear airway deformations, and step-wise static vs. dynamic imaging on particle deposition with varying numbers of intermediate lung volume increments. Airway geometry and regional ventilation at different time points were defined by four-dimensional (space and time) dynamic or static CT images. Laminar, transitional, and turbulent air flows were reproduced with a three-dimensional eddy-resolving computational fluid dynamics model. Finally, trajectories of particles were computed with the Lagrangian tracking algorithm. The results demonstrated that static-imaging-based models can contribute 7% uncertainty to overall particle distribution and deposition primarily due to regional flow rate (ventilation) differences as opposed to geometric alterations. The effect of rigid vs. deforming airways on serial distribution of particles over generations was significantly smaller than reported in a previous study that used the symmetric Weibel geometric model with smaller flow rate. Rigid vs. deforming airways were also shown to affect parallel particle distribution over lobes by 8% and the differences associated with use of static vs. dynamic imaging was 18%. These differences demonstrate that estimates derived from static vs. dynamic imaging can significantly affect the assessment of particle distribution heterogeneity. The effect of linear vs. nonlinear airway deformations was within the uncertainty due to mesh size.

Aerosol deposition predictions in computed tomography-derived skeletons from severe asthmatics: A feasibility study.

BACKGROUND: The authors numerically investigated the correlation between airway skeletons of severe asthmatic human subjects and predicted aerosol deposition to shed light on the effect of environmental factors on asthma risk. We hypothesized that there are asthmatic subjects whose airway skeletal structure can expose the subject to a risk of higher local aerosol deposition compared to subjects with a more common/normal branching pattern. METHODS: From a population of severe asthmatics studied at total lung capacity via computed tomography we randomly selected 8 subjects whose Forced Expiratory Volume in 1s, percent predicted fell below 45% predicted. To simulate aerosol motion in the human lungs, we employed in-house three-dimensional eddy-resolving computational fluid dynamics and particle tracking models utilizing 3 of the 8 severe asthmatic subjects. One of the 3 subjects was found to have a distinct, localized airway narrowing chosen for further investigation. In the simulation, we controlled flow rate and luminal area, i.e., Reynolds and Stokes numbers, in each branch of the computed tomography-derived airway skeletons. FINDINGS: We found a distinct enhancement of aerosol deposition associated with the narrowed branches of one subject even when the luminal area was numerically adjusted from its narrowed state to that of a non-asthmatic subject. The branching angle, freed of luminal narrowing persisted in demonstrating a marginally significant increase in local particle deposition compared with the subjects without the initial constriction. INTERPRETATION: These results demonstrate the possibility that inherent airway structure may influence localized constriction found in severe asthmatics.

A Feasible Computational Fluid Dynamics Study for Relationships of Structural and Functional Alterations with Particle Depositions in Severe Asthmatic Lungs.

This study aims to investigate the effect of altered structures and functions in severe asthma on particle deposition by using computational fluid dynamics (CFD) models. Airway geometrical models of two healthy subjects and two severe asthmatics were reconstructed from computed tomography (CT) images. Subject-specific flow boundary conditions were obtained by image registration to account for regional functional alterations of severe asthmatics. A large eddy simulation (LES) model for transitional and turbulent flows was applied to simulate airflows, and particle transport simulations were then performed for 2.5, 5, and 10 µm particles using CFD-predicted flow fields. Compared to the healthy subjects, the severe asthmatics had a smaller air-volume change in the lower lobes and a larger air-volume change in the upper lobes. Both severe asthmatics had smaller airway circularity (Cr), but one of them had a significant reduction of hydraulic diameter (Dh). In severe asthmatics, the larger air-volume change in the upper lobes resulted in more particles in the upper lobes, especially for the small 2.5 µm particles. The structural alterations measured by Cr and Dh were associated with a higher particle deposition. Dh was found to be the most important metric which affects the specific location of particle deposition. This study demonstrates the relationship of CT-based structural and functional alterations in severe asthma with flow and particle dynamics.

Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface.

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11 % of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches.

A 4DCT imaging-based breathing lung model with relative hysteresis.

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry.

A Numerical Study of Water Loss Rate Distributions in MDCT-Based Human Airway Models.

Both three-dimensional (3D) and one-dimensional (1D) computational fluid dynamics methods are applied to study regional water loss in three multi-detector row computed-tomography-based human airway models at the minute ventilations of 6, 15 and 30 L/min. The overall water losses predicted by both 3D and 1D models in the entire respiratory tract agree with available experimental measurements. However, 3D and 1D models reveal different regional water loss rate distributions due to the 3D secondary flows formed at bifurcations. The secondary flows cause local skewed temperature and humidity distributions on inspiration acting to elevate the local water loss rate; and the secondary flow at the carina tends to distribute more cold air to the lower lobes. As a result, the 3D model predicts that the water loss rate first increases with increasing airway generation, and then decreases as the air approaches saturation, while the 1D model predicts a monotonic decrease of water loss rate with increasing airway generation. Moreover, the 3D (or 1D) model predicts relatively higher water loss rates in lower (or upper) lobes. The regional water loss rate can be related to the non-dimensional wall shear stress (τ (*)) by the non-dimensional mass transfer coefficient (h 0 (*) ) as [Formula: see text].

Early airway structural changes in cystic fibrosis pigs as a determinant of particle distribution and deposition.

The pathogenesis of cystic fibrosis (CF) airway disease is not well understood. A porcine CF model was recently generated, and these animals develop lung disease similar to humans with CF. At birth, before infection and inflammation, CF pigs have airways that are irregularly shaped and have a reduced caliber compared to non-CF pigs. We hypothesized that these airway structural abnormalities affect airflow patterns and particle distribution. To test this hypothesis we used computational fluid dynamics (CFD) on airway geometries obtained by computed tomography of newborn non-CF and CF pigs. For the same flow rate, newborn CF pig airways exhibited higher air velocity and resistance compared to non-CF. Moreover we found that, at the carina bifurcation, particles greater than 5-µm preferably distributed to the right CF lung despite almost equal airflow ventilation in non-CF and CF. CFD modeling also predicted that deposition efficiency was greater in CF compared to non-CF for 5- and 10-µm particles. These differences were most significant in the airways included in the geometry supplying the right caudal, right accessory, left caudal, and left cranial lobes. The irregular particle distribution and increased deposition in newborn CF pig airways suggest that early airway structural abnormalities might contribute to CF disease pathogenesis.

Effect of carrier gas properties on aerosol distribution in a CT-based human airway numerical model.

The effect of carrier gas properties on particle transport in the human lung is investigated numerically in an imaging based airway model. The airway model consists of multi-detector row computed tomography (MDCT)-based upper and intra-thoracic central airways. The large-eddy simulation technique is adopted for simulation of transitional and turbulent flows. The image-registration-derived boundary condition is employed to match regional ventilation of the whole lung. Four different carrier gases of helium (He), a helium-oxygen mixture (He-O(2)), air, and a xenon-oxygen mixture (Xe-O(2)) are considered. A steady inspiratory flow rate of 342 mL/s is imposed at the mouthpiece inlet to mimic aerosol delivery on inspiration, resulting in the Reynolds number at the trachea of Re( t ) ≈ 190, 460, 1300, and 2800 for the respective gases of He, He-O(2), air, and Xe-O(2). Thus, the flow for the He case is laminar, transitional for He-O(2), and turbulent for air and Xe-O(2). The instantaneous and time-averaged flow fields and the laminar/transitional/turbulent characteristics resulting from the four gases are discussed. With increasing Re( t ), the high-speed jet formed at the glottal constriction is more dispersed around the peripheral region of the jet and its length becomes shorter. In the laminar flow the distribution of 2.5-µm particles in the central airways depends on the particle release location at the mouthpiece inlet, whereas in the turbulent flow the particles are well mixed before reaching the first bifurcation and their distribution is strongly correlated with regional ventilation.