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.

In Silico Quantification of Intersubject Variability on Aerosol Deposition in the Oral Airway

The extrathoracic oral airway is not only a major mechanical barrier for pharmaceutical aerosols to reach the lung but also a major source of variability in lung deposition. Using computational fluid dynamics, deposition of 1−30 µm particles was predicted in 11 CT-based models of the oral airways of adults. Simulations were performed for mouth breathing during both inspiration and expiration at two steady-state flow rates representative of resting/nebulizer use (18 L/min) and of dry powder inhaler (DPI) use (45 L/min). Consistent with previous in vitro studies, there was a large intersubject variability in oral deposition. For an optimal size distribution of 1−5 µm for pharmaceutical aerosols, our data suggest that >75% of the inhaled aerosol is delivered to the intrathoracic lungs in most subjects when using a nebulizer but only in about half the subjects when using a DPI. There was no significant difference in oral deposition efficiency between inspiration and expiration, unlike subregional deposition, which shows significantly different patterns between the two breathing phases. These results highlight the need for incorporating a morphological variation of the upper airway in predictive models of aerosol deposition for accurate predictions of particle dosimetry in the intrathoracic region of the lung.

New Approach Methodology for Assessing Inhalation Risks of a Contact Respiratory Cytotoxicant: Computational Fluid Dynamics-Based Aerosol Dosimetry Modeling for Cross-Species and In Vitro Comparisons

Regulatory agencies are considering alternative approaches to assessing inhalation toxicity that utilizes in vitro studies with human cells and in silico modeling in lieu of additional animal studies. In support of this goal, computational fluid-particle dynamics models were developed to estimate site-specific deposition of inhaled aerosols containing the fungicide, chlorothalonil, in the rat and human for comparisons to prior rat inhalation studies and new human in vitro studies. Under bioassay conditions, the deposition was predicted to be greatest at the front of the rat nose followed by the anterior transitional epithelium and larynx corresponding to regions most sensitive to local contact irritation and cytotoxicity. For humans, simulations of aerosol deposition covering potential occupational or residential exposures (1-50 µm diameter) were conducted using nasal and oral breathing. Aerosols in the 1-5 µm range readily penetrated the deep region of the human lung following both oral and nasal breathing. Under actual use conditions (aerosol formulations >10 µm), the majority of deposited doses were in the upper conducting airways. Beyond the nose or mouth, the greatest deposition in the pharynx, larynx, trachea, and bronchi was predicted for aerosols in the 10-20 µm size range. Only small amounts of aerosols >20 µm penetrated past the pharyngeal region. Using the ICRP clearance model, local retained tissue dose metrics including maximal concentrations and areas under the curve were calculated for each airway region following repeated occupational exposures. These results are directly comparable with benchmark doses from in vitro toxicity studies in human cells leading to estimated human equivalent concentrations that reduce the reliance on animals for risk assessments.

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.

Relative permeability for water and gas through fractures in cement

Relative permeability is an important attribute influencing subsurface multiphase flow. Characterization of relative permeability is necessary to support activities such as carbon sequestration, geothermal energy production, and oil and gas exploration. Previous research efforts have largely neglected the relative permeability of wellbore cement used to seal well bores where risks of leak are significant. Therefore this study was performed to evaluate fracturing on permeability and relative permeability of wellbore cement. Studies of relative permeability of water and air were conducted using ordinary Portland cement paste cylinders having fracture networks that exhibited a range of permeability values. The measured relative permeability was compared with three models, 1) Corey-curve, often used for modeling relative permeability in porous media, 2) X-curve, commonly used to represent relative permeability of fractures, and 3) Burdine model based on fitting the Brooks-Corey function to fracture saturation-pressure data inferred from x-ray computed tomography (XCT) derived aperture distribution results. Experimentally-determined aqueous relative permeability was best described by the Burdine model. Though water phase tended to follow the Corey-curve for the simple fracture system while air relative permeability was best described by the X-curve.

Comparison of realistic and idealized breathing patterns in computational models of airflow and vapor dosimetry in the rodent upper respiratory tract

CONTEXT

Computational fluid dynamics (CFD) simulations of airflows coupled with physiologically based pharmacokinetic (PBPK) modeling of respiratory tissue doses of airborne materials have traditionally used either steady-state inhalation or a sinusoidal approximation of the breathing cycle for airflow simulations despite their differences from normal breathing patterns.

OBJECTIVE

Evaluate the impact of realistic breathing patterns, including sniffing, on predicted nasal tissue concentrations of a reactive vapor that targets the nose in rats as a case study.

MATERIALS AND METHODS

Whole-body plethysmography measurements from a free-breathing rat were used to produce profiles of normal breathing, sniffing and combinations of both as flow inputs to CFD/PBPK simulations of acetaldehyde exposure.

RESULTS

For the normal measured ventilation profile, modest reductions in time- and tissue depth-dependent areas under the curve (AUC) acetaldehyde concentrations were predicted in the wet squamous, respiratory and transitional epithelium along the main airflow path, while corresponding increases were predicted in the olfactory epithelium, especially the most distal regions of the ethmoid turbinates, versus the idealized profile. The higher amplitude/frequency sniffing profile produced greater AUC increases over the idealized profile in the olfactory epithelium, especially in the posterior region.

CONCLUSIONS

The differences in tissue AUCs at known lesion-forming regions for acetaldehyde between normal and idealized profiles were minimal, suggesting that sinusoidal profiles may be used for this chemical and exposure concentration. However, depending upon the chemical, exposure system and concentration and the time spent sniffing, the use of realistic breathing profiles, including sniffing, could become an important modulator for local tissue dose predictions.

Numerical Simulation of Permeability Change in Wellbore Cement Fractures after Geomechanical Stress and Geochemical Reactions Using X-ray Computed Tomography Imaging

X-ray microtomography (XMT) imaging combined with three-dimensional (3D) computational fluid dynamics (CFD) modeling technique was used to study the effect of geochemical and geomechanical processes on fracture permeability in composite Portland cement-basalt caprock core samples. The effect of fluid density and viscosity and two different pressure gradient conditions on fracture permeability was numerically studied by using fluids with varying density and viscosity and simulating two different pressure gradient conditions. After the application of geomechanical stress but before CO2-reaction, CFD revealed fluid flow increase, which resulted in increased fracture permeability. After CO2-reaction, XMT images displayed preferential precipitation of calcium carbonate within the fractures in the cement matrix and less precipitation in fractures located at the cement-basalt interface. CFD estimated changes in flow profile and differences in absolute values of flow velocity due to different pressure gradients. CFD was able to highlight the profound effect of fluid viscosity on velocity profile and fracture permeability. This study demonstrates the applicability of XMT imaging and CFD as powerful tools for characterizing the hydraulic properties of fractures in a number of applications like geologic carbon sequestration and storage, hydraulic fracturing for shale gas production, and enhanced geothermal systems.

Comparative Risks of Aldehyde Constituents in Cigarette Smoke Using Transient Computational Fluid Dynamics/Physiologically Based Pharmacokinetic Models of the Rat and Human Respiratory Tracts

Computational fluid dynamics (CFD) modeling is well suited for addressing species-specific anatomy and physiology in calculating respiratory tissue exposures to inhaled materials. In this study, we overcame prior CFD model limitations to demonstrate the importance of realistic, transient breathing patterns for predicting site-specific tissue dose. Specifically, extended airway CFD models of the rat and human were coupled with airway region-specific physiologically based pharmacokinetic (PBPK) tissue models to describe the kinetics of 3 reactive constituents of cigarette smoke: acrolein, acetaldehyde and formaldehyde. Simulations of aldehyde no-observed-adverse-effect levels for nasal toxicity in the rat were conducted until breath-by-breath tissue concentration profiles reached steady state. Human oral breathing simulations were conducted using representative aldehyde yields from cigarette smoke, measured puff ventilation profiles and numbers of cigarettes smoked per day. As with prior steady-state CFD/PBPK simulations, the anterior respiratory nasal epithelial tissues received the greatest initial uptake rates for each aldehyde in the rat. However, integrated time- and tissue depth-dependent area under the curve (AUC) concentrations were typically greater in the anterior dorsal olfactory epithelium using the more realistic transient breathing profiles. For human simulations, oral and laryngeal tissues received the highest local tissue dose with greater penetration to pulmonary tissues than predicted in the rat. Based upon lifetime average daily dose comparisons of tissue hot-spot AUCs (top 2.5% of surface area-normalized AUCs in each region) and numbers of cigarettes smoked/day, the order of concern for human exposures was acrolein > formaldehyde > acetaldehyde even though acetaldehyde yields were 10-fold greater than formaldehyde and acrolein.

3D imaging of microbial biofilms: integration of synchrotron imaging and an interactive visualization interface

Understanding the structure of microbial biofilms and other complex microbial communities is now possible through x-ray microtomography imaging. Feature detection and image processing for this type of data focuses on efficiently identifying and segmenting biofilm biomass in the datasets. These datasets are very large and segmentation often requires manual interventions due to low contrast between objects and high noise levels. New software is required for the effectual interpretation and analysis of such data. This work specifies the evolution and ability to analyze and visualize high resolution x-ray microtomography datasets. Major functionalities include read/write with multiple popular file formats, down-sampling large datasets to generate quick-views on low-power computers, image processing, and generating high quality output images and videos. These capabilities have been wrapped into a new interactive software toolkit, BiofilmViewer. A major focus of our work is to facilitate data transfer and to utilize the capabilities of existing powerful visualization and analytical tools including MATLAB, ImageJ, Paraview, Chimera, Vaa3D, Cell Profiler, Icy, BioImageXD, and Drishti.

Detecting distance between injected microspheres and target tumor via 3D reconstruction of tissue sections

One treatment increasing in use for solid tumors in the liver is radioembolization via the delivery of (90)Y microspheres to the vascular bed within or near the location of the tumor. It is desirable as part of the treatment for the microspheres to embed preferentially in or near the tumor. This work details an approach for analyzing the deposition of microspheres with respect to the location of the tumor. The approach used is based upon thin-slice serial sectioning of the tissue sample, followed by high resolution imaging, microsphere detection, and 3-D reconstruction of the tumor surface. Distance from the microspheres to the tumor was calculated using a fast deterministic point inclusion method.

Visualization of high resolution spatial mass spectrometric data during acquisition

Mass Spectrometric Imaging (MSI) allows the generation of 2D ion density maps that help visualize molecules present in sections of tissues and cells. The combination of spatial resolution and mass resolution results in very large and complex data sets. New capabilities are necessary for efficient analysis and interpretation of this data. This work details the development and application of the capability to process, visualize, query, and analyze spatial mass spectrometry data. Applications include the generation of 2D maps for selected spectra, the manipulation of the heat maps, and the identification of spectral peaks. Heat maps are generated by projecting the sum of intensity vs. time spectra of each pixel for selected m/z value or range. These capabilities take the form of a new interactive software toolkit, MSI QuickView. This software approach is a significant advance over the previous state-of-the art methods that required the conversion of the RAW data using one software, manual assembly of the data, and visualization in another software.

An efficient algorithm for mapping imaging data to 3D unstructured grids in computational biomechanics

Geometries for organ scale and multiscale simulations of organ function are now routinely derived from imaging data. However, medical images may also contain spatially heterogeneous information other than geometry that are relevant to such simulations either as initial conditions or in the form of model parameters. In this manuscript, we present an algorithm for the efficient and robust mapping of such data to imaging-based unstructured polyhedral grids in parallel. We then illustrate the application of our mapping algorithm to three different mapping problems: (i) the mapping of MRI diffusion tensor data to an unstructured ventricular grid; (ii) the mapping of serial cyrosection histology data to an unstructured mouse brain grid; and (iii) the mapping of computed tomography-derived volumetric strain data to an unstructured multiscale lung grid. Execution times and parallel performance are reported for each case.

Phase-contrast MRI and CFD modeling of apparent ³He gas flow in rat pulmonary airways

Phase-contrast (PC) magnetic resonance imaging (MRI) with hyperpolarized ³He is potentially useful for developing and testing patient-specific models of pulmonary airflow. One challenge, however, is that PC-MRI provides apparent values of local ³He velocity that not only depend on actual airflow but also on gas diffusion. This not only blurs laminar flow patterns in narrow airways but also introduces anomalous airflow structure that reflects gas-wall interactions. Here, both effects are predicted in a live rat using computational fluid dynamics (CFD), and for the first time, simulated patterns of apparent ³He gas velocity are compared with in vivo PC-MRI. Results show (1) that correlations (R²) between measured and simulated airflow patterns increase from 0.23 to 0.79 simply by accounting for apparent ³He transport, and (2) that remaining differences are mainly due to uncertain airway segmentation and partial volume effects stemming from relatively coarse MRI resolution. Higher-fidelity testing of pulmonary airflow predictions should therefore be possible with future imaging improvements.

A multiscale bidirectional coupling framework

The lung is geometrically articulated across multiple scales from the trachea to the alveoli. A major computational challenge is to tightly link ODEs that describe lower scales to 3D finite element or finite volume models of airway mechanics using iterative communication between scales. In this study, we developed a novel multiscale computational framework for bidirectionally coupling 3D CFD models and systems of lower order ODEs. To validate the coupling framework, a four and eight generation Weibel lung model was constructed. For the coupled CFD-ODE simulations, the lung models were truncated at different generations and a RL circuit represented the truncated portion. The flow characteristics from the coupled models were compared to untruncated full 3D CFD models at peak inhalation and peak exhalation. Results showed that at no time or simulation was the difference in mass flux and/or pressure at a given location between uncoupled and coupled models was greater than 2.43%. The flow characteristics at prime locations for the coupled models showed good agreement to uncoupled models. Remarkably, due to reuse of the Krylov subspace, the cost of the ODE coupling is not much greater than uncoupled full 3D-CFD computations with simple prescribed pressure values at the outlets.

Comparative computational modeling of airflows and vapor dosimetry in the respiratory tracts of rat, monkey, and human

Computational fluid dynamics (CFD) models are useful for predicting site-specific dosimetry of airborne materials in the respiratory tract and elucidating the importance of species differences in anatomy, physiology, and breathing patterns. We improved the imaging and model development methods to the point where CFD models for the rat, monkey, and human now encompass airways from the nose or mouth to the lung. A total of 1272, 2172, and 135 pulmonary airways representing 17±7, 19±9, or 9±2 airway generations were included in the rat, monkey and human models, respectively. A CFD/physiologically based pharmacokinetic model previously developed for acrolein was adapted for these anatomically correct extended airway models. Model parameters were obtained from the literature or measured directly. Airflow and acrolein uptake patterns were determined under steady-state inhalation conditions to provide direct comparisons with prior data and nasal-only simulations. Results confirmed that regional uptake was sensitive to airway geometry, airflow rates, acrolein concentrations, air:tissue partition coefficients, tissue thickness, and the maximum rate of metabolism. Nasal extraction efficiencies were predicted to be greatest in the rat, followed by the monkey, and then the human. For both nasal and oral breathing modes in humans, higher uptake rates were predicted for lower tracheobronchial tissues than either the rat or monkey. These extended airway models provide a unique foundation for comparing material transport and site-specific tissue uptake across a significantly greater range of conducting airways in the rat, monkey, and human than prior CFD models.

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.

Fluid-Structure Interactions of the Mitral Valve and Left Heart: Comprehensive Strategies, Past, Present and Future

The remodeling that occurs after a posterolateral myocardial infarction can alter mitral valve function by creating conformational abnormalities in the mitral annulus and in the posteromedial papillary muscle, leading to mitral regurgitation (MR). It is generally assumed that this remodeling is caused by a volume load and is mediated by an increase in diastolic wall stress. Thus, mitral regurgitation can be both the cause and effect of an abnormal cardiac stress environment. Computational modeling of ischemic MR and its surgical correction is attractive because it enables an examination of whether a given intervention addresses the correction of regurgitation (fluid-flow) at the cost of abnormal tissue stress. This is significant because the negative effects of an increased wall stress due to the intervention will only be evident over time. However, a meaningful fluid-structure interaction model of the left heart is not trivial; it requires a careful characterization of the in-vivo cardiac geometry, tissue parameterization though inverse analysis, a robust coupled solver that handles collapsing Lagrangian interfaces, automatic grid-generation algorithms that are capable of accurately discretizing the cardiac geometry, innovations in image analysis, competent and efficient constitutive models and an understanding of the spatial organization of tissue microstructure. In this manuscript, we profile our work toward a comprehensive fluid-structure interaction model of the left heart by reviewing our early work, presenting our current work and laying out our future work in four broad categories: data collection, geometry, fluid-structure interaction and validation.

Adaptive generation of multimaterial grids from imaging data for biomedical Lagrangian fluid-structure simulations

Spatial discretization of complex imaging- derived fluid-solid geometries, such as the cardiac environment, is a critical but often overlooked challenge in biomechanical computations. This is particularly true in problems with Lagrangian interfaces, where the fluid and solid phases share a common interface geometrically. For simplicity and better accuracy, it is also highly desirable for the two phases to have a matching surface mesh at the interface between them. We outline a method for solving this problem, and illustrate the approach with a 3D fluid-solid mesh of the mouse heart. An MRI dataset of a perfusion-fixed mouse heart with 50 microm isotropic resolution was semi-automatically segmented using a customized multimaterial connected-threshold approach that divided the volume into non-overlapping regions of blood, tissue, and background. Subsequently a multimaterial marching cubes algorithm was applied to the segmented data to produce two detailed, compatible isosurfaces, one for blood and one for tissue. Both isosurfaces were simultaneously smoothed with a multimaterial smoothing algorithm that exactly conserves the volume for each phase. Using these two isosurfaces, we developed and applied novel automated meshing algorithms to generate anisotropic hybrid meshes on arbitrary biological geometries with the number of layers and the desired element anisotropy for each phase as the only input parameters. Since our meshes adapt to the local feature sizes and include boundary layer prisms, they are more efficient and accurate than non-adaptive, isotropic meshes, and the fluid-structure interaction computations will tend to have relative error equilibrated over the whole mesh.

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.

An anisotropic scale-invariant unstructured mesh generator suitable for volumetric imaging data

We present a boundary-fitted, scale-invariant unstructured tetrahedral mesh generation algorithm that enables registration of element size to local feature size. Given an input triangulated surface mesh, a feature size field is determined by casting rays normal to the surface and into the geometry and then performing gradient-limiting operations to enforce continuity of the resulting field. Surface mesh density is adjusted to be proportional to the feature size field and then a layered anisotropic volume mesh is generated. This mesh is "scale-invariant" in that roughly the same number of layers of mesh exist in mesh cross-sections, between a minimum scale size L(min) and a maximum scale size L(max). We illustrate how this field can be used to produce quality grids for computational fluid dynamics based simulations of challenging, topologically complex biological surfaces derived from magnetic resonance images. The algorithm is implemented in the Pacific Northwest National Laboratory (PNNL) version of the Los Alamos grid toolbox LaGriT[14]. Research funded by the National Heart and Blood Institute Award 1RO1HL073598-01A1.

An automated self-similarity analysis of the pulmonary tree of the Sprague-Dawley rat

We present the results of an automated analysis of the morphometry of the pulmonary airway trees of the Sprague-Dawley rat. Our work is motivated by a need to inform lower-dimensional mathematical models to prescribe realistic boundary conditions for multiscale hybrid models of rat lung mechanics. Silicone casts were made from three age-matched, male Sprague-Dawley rats, immersed in a gel containing a contrast agent and subsequently imaged with magnetic resonance (MR). From a segmentation of this data, we extracted a connected graph, representing the airway centerline. Segment statistics (lengths and diameters) were derived from this graph. To validate this MR imaging/digital analysis method, airway segment measurements were compared with nearly 1,000 measurements collected by hand using an optical microscope from one of the rat lung casts. To evaluate the reproducibility of the MR imaging/digital analysis method, two lung casts were each imaged three times with randomized orientations in the MR bore. Diameters and lengths of randomly selected airways were compared among each of the repeated imaging datasets to estimate the variability. Finally, we analyzed the morphometry of the airway tree by assembling individual airway segments into structures that span multiple generations, which we call branches. We show that branches not segments are the fundamental repeating unit in the rat lung and develop simple mathematical relationships describing these structures for the entire lung. Our analysis shows that airway diameters and lengths have both a deterministic and stochastic character.

Application of Magnetic Resonance (MR) Imaging for the Development and Validation of Computational Fluid Dynamic (CFD) Models of the Rat Respiratory System

Computational fluid dynamic (CFD) models of the respiratory system provide a quantitative basis for extrapolating the localized dose of inhaled materials and improving human health risk assessments based upon inhalation studies conducted in animals. Nevertheless, model development and validation have historically been tedious and time-consuming tasks. In recognition of this, we previously reported on the use of proton (1H) magnetic resonance (MR) imaging for visualizing nasal-sinus passages in the rat, and for speeding computational mesh generation. Here, the generation and refinement of meshes for rat nasal airways are described in more detail and simulated airflows are presented. To extend the CFD models to the complete respiratory tract, three-dimensional (3D) 1H MR imaging of rat pulmonary casts was also utilized to construct pulmonary airway meshes using procedures developed for the nasal airways. Furthermore, the feasibility of validating CFD predictions with MR was tested by imaging hyperpolarized 3He gas at physiological flow rates in a straight pipe with a diameter comparable to the rat trachea. Results from these diverse studies highlight the potential utility of MR imaging not only for speeding CFD development but also possibly for model validation.

MR imaging of apparent 3He gas transport in narrow pipes and rodent airways

High sensitivity makes hyperpolarized (3)He an attractive signal source for visualizing gas flow with magnetic resonance (MR) imaging. Its rapid Brownian motion, however, can blur observed flow lamina and alter measured diffusion rates when excited nuclei traverse shear-induced velocity gradients during data acquisition. Here, both effects are described analytically, and predicted values for measured transport during laminar flow through a straight, 3.2-mm diameter pipe are validated using two-dimensional (2D) constant-time images of different binary gas mixtures. Results show explicitly how measured transport in narrow conduits is characterized by apparent values that depend on underlying gas dynamics and imaging time. In ventilated rats, this is found to obscure acquired airflow images. Nevertheless, flow splitting at airway branches is still evident and use of 3D vector flow mapping is shown to reveal surprising detail that highlights the correlation between gas dynamics and lung structure.

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.