Automated bidirectional coupling of multiscale models of aerosol dosimetry: validation with subject-specific deposition data.

Assessing the toxicity of airborne particulate matter or the efficacy of inhaled drug depends upon accurate estimates of deposited fraction of inhaled materials. In silico approaches can provide important insights into site- or airway-specific deposition of inhaled aerosols in the respiratory system. In this study, we improved on our recently developed 3D/1D model that simulate aerosol transport and deposition in the whole lung over multiple breath cycles (J. Aerosol Sci 151:105647). A subject-specific multiscale lung model of a healthy male subject using computational fluid-particle dynamics (CFPD) in a 3D model of the oral cavity through the large bronchial airways entering each lobe was bidirectionally coupled with a recently improved Multiple Path Particle Dosimetry (MPPD) model to predict aerosol deposition over the entire respiratory tract over multiple breaths for four conditions matching experimental aerosol exposures in the same subject from which the model was developed. These include two particle sizes (1 and 2.9 µm) and two subject-specific breathing rates of ~300 ml/s (slow breathing) and ~750 ml/s (fast breathing) at a target tidal volume of 1 L. In silico predictions of retained fraction were 0.31 and 0.29 for 1 µm and 0.66 and 0.62 for 2.9 µm during slow and fast breathing, respectively, and compared well with experimental data (1 µm: 0.31±0.01 (slow) and 0.27±0.01 (fast), 2.9 µm: 0.63±0.03 (slow) and 0.68±0.02 (fast)). These results provide a great deal of confidence in the validity and reliability of our approach.

Influence of alveolar mixing and multiple breaths of aerosol intake on particle deposition in the human lungs.

Predictive dosimetry models play an important role in assessing health effect of inhaled particulate matter and in optimizing delivery of inhaled pharmaceutical aerosols. In this study, the commonly used 1D Multiple-Path Particle Dosimetry model (MPPD) was improved by including a mechanistically based model component for alveolar mixing of particles and by extending the model capabilities to account for multiple breaths of aerosol intake. These modifications increased the retained fraction of particles and consequently particle deposition predictions in the deep lung during tidal breathing. Comparison with an existing dataset (J. Aerosol Sci., 99:27-39, 2016) obtained under two breathing conditions referred to as slow and fast breathing showed significant differences in 1 µm particle deposition between predictions based on subject-specific breathing patterns and lung volume (slow: 30 ± 1%, fast: 21 ± 1%, (average ± standard deviation), N = 7) and measurements (slow: 43 ± 9%, fast: 30 ± 5%) when the prior version of MPPD (single breath and no mixing, J. Aerosol Sci., 151:105647, 2021) was used. Adding a mixing model and multiple breaths moved the predictions (slow: 34 ± 2%, fast:25 ± 2%) closer to the range of deposition measurements. For 2.9 µm particles, predictions from both the original (slow: 70 ± 2%, fast: 57 ± 2%) and the revised MPPD model (slow: 71 ± 2%, fast: 59 ± 3%) compared well with experiments (slow: 67 ± 8%, fast: 58 ± 10%). This was expected as suspended fraction of 2.9 µm particles was small and thus the addition of alveolar mixing and multi breath capability only slightly increased the retained fraction for particles of this size and greater. The revised 1D model improves dose predictions in the deep lung and support human risk assessment from exposure to airborne particles.

Efficient bi-directional coupling of 3D Computational Fluid-Particle Dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry.

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. As a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 µm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFPD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. These methods can be used as the foundation for multi-scale modeling of the full respiratory system.

Computational fluid dynamics modeling of Bacillus anthracis spore deposition in rabbit and human respiratory airways.

Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived respectively from computed tomography (CT) and µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. Two different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Due to the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the nasal sinus compared to the human at the same air concentration of anthrax spores. In contrast, higher spore deposition was predicted in the lower conducting airways of the human compared to the rabbit lung due to differences in airway branching pattern. This information can be used to refine published and ongoing biokinetic models of inhalation anthrax spore exposures, which currently estimate deposited spore concentrations based solely upon exposure concentrations and inhaled doses that do not factor in species-specific anatomy and physiology for deposition.

A Bidirectional Coupling Procedure Applied to Multiscale Respiratory Modeling.

In this study, we present a novel multiscale computational framework for efficiently linking multiple lower-dimensional models describing the distal lung mechanics to imaging-based 3D computational fluid dynamics (CFD) models of the upper pulmonary airways in order to incorporate physiologically appropriate outlet boundary conditions. The framework is an extension of the Modified Newton's Method with nonlinear Krylov accelerator developed by Carlson and Miller [1, 2, 3]. Our extensions include the retention of subspace information over multiple timesteps, and a special correction at the end of a timestep that allows for corrections to be accepted with verified low residual with as little as a single residual evaluation per timestep on average. In the case of a single residual evaluation per timestep, the method has zero additional computational cost compared to uncoupled or unidirectionally coupled simulations. We expect these enhancements to be generally applicable to other multiscale coupling applications where timestepping occurs. In addition we have developed a "pressure-drop" residual which allows for stable coupling of flows between a 3D incompressible CFD application and another (lower-dimensional) fluid system. We expect this residual to also be useful for coupling non-respiratory incompressible fluid applications, such as multiscale simulations involving blood flow. The lower-dimensional models that are considered in this study are sets of simple ordinary differential equations (ODEs) representing the compliant mechanics of symmetric human pulmonary airway trees. To validate the method, we compare the predictions of hybrid CFD-ODE models against an ODE-only model of pulmonary airflow in an idealized geometry. Subsequently, we couple multiple sets of ODEs describing the distal lung to an imaging-based human lung geometry. Boundary conditions in these models consist of atmospheric pressure at the mouth and intrapleural pressure applied to the multiple sets of ODEs. In both the simplified geometry and in the imaging-based geometry, the performance of the method was comparable to that of monolithic schemes, in most cases requiring only a single CFD evaluation per time step. Thus, this new accelerator allows us to begin combining pulmonary CFD models with lower-dimensional models of pulmonary mechanics with little computational overhead. Moreover, because the CFD and lower-dimensional models are totally separate, this framework affords great flexibility in terms of the type and breadth of the adopted lower-dimensional model, allowing the biomedical researcher to appropriately focus on model design. Research funded by the National Heart and Blood Institute Award 1RO1HL073598.

Magnetic resonance imaging and computational fluid dynamics (CFD) simulations of rabbit nasal airflows for the development of hybrid CFD/PBPK models.

The percentages of total airflows over the nasal respiratory and olfactory epithelium of female rabbits were calculated from computational fluid dynamics (CFD) simulations of steady-state inhalation. These airflow calculations, along with nasal airway geometry determinations, are critical parameters for hybrid CFD/physiologically based pharmacokinetic models that describe the nasal dosimetry of water-soluble or reactive gases and vapors in rabbits. CFD simulations were based upon three-dimensional computational meshes derived from magnetic resonance images of three adult female New Zealand White (NZW) rabbits. In the anterior portion of the nose, the maxillary turbinates of rabbits are considerably more complex than comparable regions in rats, mice, monkeys, or humans. This leads to a greater surface area to volume ratio in this region and thus the potential for increased extraction of water soluble or reactive gases and vapors in the anterior portion of the nose compared to many other species. Although there was considerable interanimal variability in the fine structures of the nasal turbinates and airflows in the anterior portions of the nose, there was remarkable consistency between rabbits in the percentage of total inspired airflows that reached the ethmoid turbinate region (approximately 50%) that is presumably lined with olfactory epithelium. These latter results (airflows reaching the ethmoid turbinate region) were higher than previous published estimates for the male F344 rat (19%) and human (7%). These differences in regional airflows can have significant implications in interspecies extrapolations of nasal dosimetry.

An Anisotropic Fluid-Solid Model of the Mouse Heart.

A critical challenge in biomechanical simulations is the spatial discretization of complex fluid-solid geometries created from imaging. This is especially important when dealing with Lagrangian interfaces, as there must be at a minimum both geometric and topological compatibility between fluid and solid phases, with exact matching of the interfacial nodes being highly desirable. We have developed a solution to this problem and applied the approach to the creation of a 3D fluid-solid mesh of the mouse heart. First, a 50 micron isotropic MRI dataset of a perfusion-fixed mouse heart was segmented into blood, tissue, and background using a customized multimaterial connected fuzzy thresholding algorithm. Then, a multimaterial marching cubes algorithm was applied to produce two compatible isosurfaces, one for the blood-tissue boundary and one for the tissue-background boundary. A multimaterial smoothing algorithm that rigorously conserves volume for each phase simultaneously smoothed the isosurfaces. Next we applied novel automated meshing algorithms to generate anisotropic hybrid meshes with the number of layers and the desired element anisotropy for each material as the only input parameters. As the meshes are scale-invariant within a material and include boundary layer prisms, fluid-structure interaction computations would have a relative error equilibrated over the entire mesh. The resulting model is highly detailed mesh representation of the mouse heart, including features such as chordae and coronary vasculature, that is also maximally efficient to produce the best simulation results for the computational resources available.

Bridging simulations and experiments in microstructure evolution.

We demonstrate the importance of anisotropic interface properties in microstructure evolution by comparing computed evolved microstructures to final experimental microstructures of 5170 grains in 19 thin aluminum foil samples. This is the first time that a direct experimental validation of simulation has been performed at the level of individual grains. We observe that simulated microstructures using curvature-driven grain boundary motion and anisotropic interface properties agree well with experimentally evolved microstructures, whereas agreement is poor when isotropic properties are used.