Aerosol transport throughout inspiration and expiration in the pulmonary airways

Analysis of the effect of inert gas on alveolar/venous blood partial pressure by using the operator splitting method

This study aims to investigate how inert gas affects the partial pressure of alveolar and venous blood using a fast and accurate operator splitting method (OSM). Unlike previous complex methods, such as the finite element method (FEM), OSM effectively separates governing equations into smaller sub-problems, facilitating a better understanding of inert gas transport and exchange between blood capillaries and surrounding tissue. The governing equations were discretized with a fully implicit finite difference method (FDM), which enables the use of larger time steps. The model employed partial differential equations, considering convection-diffusion in blood and only diffusion in tissue. The study explores the impact of initial arterial pressure, breathing frequency, blood flow velocity, solubility, and diffusivity on the partial pressure of inert gas in blood and tissue. Additionally, the effects of anesthetic inert gas and oxygen on venous blood partial pressure were analyzed. Simulation results demonstrate that the high solubility and diffusivity of anesthetic inert gas lead to its prolonged presence in blood and tissue, resulting in lower partial pressure in venous blood. These findings enhance our understanding of inert gas interaction with alveolar/venous blood, with potential implications for medical diagnostics and therapies.

The utility of hybrid in silico models of airflow and aerosol dosimetry in the lung

The development and application of multi-scale models of the lung has significantly increased in recent years. These hybrid models merge realistic representations of the larger airways with lower-dimensional descriptions of the bronchioles and respiratory airways. Due to recent advancements, it is possible to calculate airflow and dosimetry throughout the entire lung, enabling model validation with human or animal data. Here, we present a hybrid modeling pipeline and corresponding characteristic airflow and particle deposition hotspots. Next, we discuss the limitations of current hybrid models, including the need to update lower-dimensional deposition function descriptions to better represent realistic airway geometries. Future directions should include modeling diseased lungs and use of machine learning to predict whole lung dosimetry maps for a wider population.

Impact of Wildfires on Cardiovascular Health

Wildfire smoke (WFS) is a mixture of respirable particulate matter, environmental gases, and other hazardous pollutants that originate from the unplanned burning of arid vegetation during wildfires. The increasing size and frequency of recent wildfires has escalated public and occupational health concerns regarding WFS inhalation, by either individuals living nearby and downstream an active fire or wildland firefighters and other workers that face unavoidable exposure because of their profession. In this review, we first synthesize current evidence from environmental, controlled, and interventional human exposure studies, to highlight positive associations between WFS inhalation and cardiovascular morbidity and mortality. Motivated by these findings, we discuss preventative measures and suggest interventions to mitigate the cardiovascular impact of wildfires. We then review animal and cell exposure studies to call attention on the pathophysiological processes that support the deterioration of cardiovascular tissues and organs in response to WFS inhalation. Acknowledging the challenges of integrating evidence across independent sources, we contextualize laboratory-scale exposure approaches according to the biological processes that they model and offer suggestions for ensuring relevance to the human condition. Noting that wildfires are significant contributors to ambient air pollution, we compare the biological responses triggered by WFS to those of other harmful pollutants. We also review evidence for how WFS inhalation may trigger mechanisms that have been proposed as mediators of adverse cardiovascular effects upon exposure to air pollution. We finally conclude by highlighting research areas that demand further consideration. Overall, we aspire for this work to serve as a catalyst for regulatory initiatives to mitigate the adverse cardiovascular effects of WFS inhalation in the community and alleviate the occupational risk in wildland firefighters.

A revision of the multiple-path particle dosimetry model focusing on tobacco product aerosol dynamics

To assess the health impact of inhaled aerosols, it is necessary to understand aerosol dynamics and the associated dosimetry in the human respiratory tract. Although several studies have measured or simulated the dosimetry of aerosol constituents, the respiratory tract focus areas have been limited. In particular, the aerosols generated from tobacco products are complex composites and simulating their dynamics in the respiratory tract is challenging. To assess the dosimetry of the aerosol constituents of tobacco products, we developed a revised version of the Multiple-Path Particle Dosimetry (MPPD) model, which employs (1) new geometry based on CT-scanned human respiratory tract data, (2) convective mixing in the oral cavity and deep lung, and (3) constituent partitioning between the tissue and air, and clearance. The sensitivity analysis was conducted using aerosols composed of four major constituents of electronic cigarette (EC) aerosols to investigate the parameters that have a significant impact on the results. In addition, the revised model was run with 4 and 10 constituents in ECs and conventional cigarettes (CCs), respectively. Sensitivity analysis revealed that the new modeling and the physicochemical properties of constituents had a considerable impact on the simulated aerosol concentration and dosimetry. The simulations could be carried out within 3 min even when 10 constituents of CC aerosols were analyzed simultaneously. The revised model based on MPPD is an efficient and easy-to-use tool for understanding the aerosol dynamics of CC and EC constituents and their effect on the human body.

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks

For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.

Dry Powder Formulations for Inhalation Require a Smaller Aerodynamic Diameter for Usage at High Altitude

BACKGROUND

High Altitude Pulmonary Edema (HAPE) seriously threatens the health of people at high altitudes. There are drug treatments for HAPE, and dry powder formulations (DPFs) represent a rapid and accessible delivery vehicle for these drugs. However, there are presently no reports on the inhalability of DPFs in low-pressure environments. Given the reduced atmospheric pressure typical at high altitudes, conventional DPFs might not be suitable for inhalation. Therefore, it is necessary to elucidate the deposition behaviors of dry powder in the respiratory tract at low pressure, as well as to improve their pulmonary deposition efficiency via adjustments to their formulation and design.

METHODS

The effect of air pressure, inspiratory velocity, and particle properties (such as size, density, and aerodynamic diameter) on pulmonary deposition of DPFs was calculated by a computational fluid dynamics (CFD)-coupled discrete phase model. DPFs of various aerodynamic diameters were prepared by spray drying, and the inhalability of these DPFs in a low-pressure environment was evaluated in mice. Finally, a mouse model of HAPE was established, and the treatment of HAPE by nifedipine-loaded DPFs with small aerodynamic diameter was validated.

RESULTS

CFD results showed that low pressure decreased the deposition of DPFs in the lungs. At 0.5 standard atmosphere, DPFs with aerodynamic diameter of ∼2.0 μm could not enter the lower respiratory tract; however, a decrease in the physical diameter, density, and, consequently, the aerodynamic diameter of the DPFs was able to enhance pulmonary deposition of these powders. To validate the CFD results, three kinds of dry powder with aerodynamic diameters of 0.66, 0.98, and 2.00 μm were prepared by spray drying. Powders with smaller aerodynamic diameter could be inhaled into the lungs of mice more effectively, and, consequently could ameliorate the progression of HAPE more effectively than conventional powders. These results were consistent with the CFD results.

CONCLUSIONS

Low atmospheric pressure can prevent the pulmonary deposition of DPFs at high altitudes. Compared with conventional DPFs, powders with smaller aerodynamic diameter can be effectively inhaled at these pressures and thus might be more suitable for the treatment the HAPE.

Dosimetry Sensitivity in a Lower Dimensional Model of Patient-Specific Asthma Subjects

OBJECTIVE

Experimental uncertainty will impact in silico model calculations of aerosol delivery and deposition. Patient-specific dosimetry models are often parameterized based on medical imaging data, which contain inherent experimental variability.

METHODS

Here, we created and parameterized 1D models of three subject-specific asthmatic subjects and randomly assigned perturbations of up to 15 % on airway diameter, segmental volume, and defected volume. Sensitivity of imaging data experimental variability on dosimetry metrics were quantified.

RESULTS

Lobar particle delivery primarily depended on the distal segmental volumes; 15 % range of noise resulted in delivery to the upper right lobe to vary at most from 15.2 and 18.2 % for one of the severe subjects. Particle deposition was most sensitive to airway diameter; 95 % confidence intervals spanned from 8 to 10.6 % in the mild/moderate subject for 15 % variation on input metrics for 5 [Formula: see text] diameter particles. While these results provide possible ranges of dosimetry calculations for a specific subject, the perturbations were not sufficient to model the large observed inter-subject variability (8.9, 19, and 14.5 % deposition, subjects 1--3, respectively, 5 [Formula: see text] diameter particles).

CONCLUSION

This study highlights that in silico model predictions are robust in the presence of experimental uncertainty and that it continues to be necessary to perform subject-specific simulations, especially within the presence of heterogeneous airway disease.

SIGNIFICANCE

Sensitivity analysis provides confidence in calculating deposition in the airways of asthmatic subjects within the presence of experimental uncertainty.

Prolonged smoldering Douglas fir smoke inhalation augments respiratory resistances, stiffens the aorta, and curbs ejection fraction in hypercholesterolemic mice

While mounting evidence suggests that wildland fire smoke (WFS) inhalation may increase the burden of cardiopulmonary disease, the occupational risk of repeated exposure during wildland firefighting remains unknown. To address this concern, we evaluated the cardiopulmonary function in mice following a cumulative exposure to lab-scale WFS equivalent to a mid-length wildland firefighter (WLFF) career. Dosimetry analysis indicated that 80 exposure hours at a particulate concentration of 22 mg/m3 yield in mice the same cumulative deposited mass per unit of lung surface area as 3600 h of wildland firefighting. To satisfy this condition, male Apoe-/- mice were whole-body exposed to either air or smoldering Douglas fir smoke (DFS) for 2 h/day, 5 days/week, over 8 consecutive weeks. Particulate size in DFS fell within the respirable range for both mice and humans, with a count median diameter of 110 ± 20 nm. Expiratory breath hold in mice exposed to DFS significantly reduced their minute volume (DFS: 27 ± 4; Air: 122 ± 8 mL/min). By the end of the exposure time frame, mice in the DFS group exhibited a thicker (DFS: 109 ± 3; Air: 98 ± 3 μm) and less distensible (DFS: 23 ± 1; Air: 28 ± 1 MPa-1) aorta with reduced diastolic blood augmentation capacity (DFS: 53 ± 2; Air: 63 ± 2 kPa). Cardiac magnetic resonance imaging further revealed larger end-systolic volume (DFS: 14.6 ± 1.1; Air: 9.9 ± 0.9 μL) and reduced ejection-fraction (DFS: 64.7 ± 1.0; Air: 75.3 ± 0.9 %) in mice exposed to DFS. Consistent with increased airway epithelium thickness (DFS: 10.4 ± 0.8; Air: 7.6 ± 0.3 μm), airway Newtonian resistance was larger following DFS exposure (DFS: 0.23 ± 0.03; Air: 0.20 ± 0.03 cmH2O-s/mL). Furthermore, parenchyma mean linear intercept (DFS: 36.3 ± 0.8; Air: 33.3 ± 0.8 μm) and tissue thickness (DFS: 10.1 ± 0.5; Air: 7.4 ± 0.7 μm) were larger in DFS mice. Collectively, mice exposed to DFS manifested early signs of cardiopulmonary dysfunction aligned with self-reported events in mid-career WLFFs.

A Numerical Simulation of the Airflow and Aerosol Particle Deposition in a Realistic Airway Model of a Healthy Adult

Determining the behavior of aerosol drug particles is of vital importance in the treatment of respiratory tract diseases. Despite the development of imaging techniques in the pulmonary region in recent years, current imaging techniques are insufficient to detect particle deposition. Computational fluid dynamics (CFD) methods can fill the gap in this field as they take into account the very different physical processes that occur during aerosol transport. This study aims to numerically investigate the airflow and the aerosol particle dynamics on a realistic human respiratory tract model during multiple breathing cycles. The simulations were conducted on the different breathing conditions for people under light, normal, and heavy physical activities, and the aerosol particles with different aerodynamic diameters (i.e., dp=2, 5, and 7 µm). The numerical results were validated by comparing extensively with experimental and numerical results. The results indicated that the airflow during inspiration and expiration was characteristically different from each other and changed with the inspiration flow rate. It was determined that small-sized particles followed the streamlines and moved towards the distal of the lung under low respiratory conditions. On the other hand, larger particles tended to deposit in higher generations due to the higher inertia. It was found that with the increase of inspiration flow rate the deposition of particles increased for all particles during multiple breaths. For light breathing conditions, low deposition efficiencies were obtained because the particles followed the streamlines and moved towards the distal part of the lung. The particle deposition efficiency under heavy breathing conditions was 28.2% for 2 µm, 33.05% for 5 µm, and 38.4% for 7 µm particles. The results showed that inertial impaction plays an active role in particle deposition.

Pharmacological and physiological response in Apoe-/- mice exposed to cigarette smoke or e-cigarette aerosols

OBJECTIVE

Electronic cigarettes (e-cigs) are popular nicotine delivery devices, yet the health effects remain unclear. To determine equivalent biomarkers, we characterized the immediate response in Apoe^-/- mice exposed to tank/box-mod e-cig (e-cig_tank), pod e-cig (e-cig_pod), or cig smoke.

MATERIALS AND METHODS

Reproducible puff profiles were generated for each aerosol and delivered to Apoe^-/- mice via a nose-only exposure system. Serum cotinine levels were quantified at various time points through ELISA and utilized to model cotinine pharmacokinetics. In addition, particle size measurements and mouse respiratory function were characterized to calculate particle dosimetry.

RESULTS AND DISCUSSION

Cig and e-cig_tank particles were lognormally distributed with similar count median diameters (cig: 178 ± 2, e-cig_tank: 200 ± 34nm), while e-cig_pod particles were bimodally distributed and smaller (116 ± 13 and 13.3 ± 0.4 nm). Minute volumes decreased with cig exposure (5.4 ± 2.7 mL/min) compared to baseline (90.8 ± 11.6 mL/min), and less so with e-cig_tank (45.2 ± 9.2 mL/min) and e-cig_pod exposures (58.6 ± 6.8 mL/min), due to periods of apnea in the cig exposed groups. Cotinine was absorbed and eliminated most rapidly in the e-cig_pod group (tmax = 14.5; t1/2' = 51.9 min), whereas cotinine was absorbed (cig: 50.4, e-cig_tank: 40.1 min) and eliminated (cig: 104.6, e-cig_tank: 94.1 min) similarly in the cig and e-cig_tank groups. For exposure times which equate the area under the cotinine-concentration curve, ∼6.4× (e-cig_tank) and 4.6× (e-cig_pod) more nicotine deposited in e-cig compared to cig exposed mice.

CONCLUSIONS

This study provides a basis for incorporating cotinine pharmacokinetics into preclinical exposure studies, allowing for longitudinal studies of structural and functional changes due to exposure.

Development of a rat capnoperitoneum phantom to study drug aerosol deposition in the context of anticancer research on peritoneal carcinomatosis

Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC) is a promising approach with a high optimization potential for the treatment of peritoneal carcinomatosis. To study the efficacy of PIPAC and drugs, first rodent cancer models were developed. But inefficient drug aerosol supply and knowledge gaps concerning spatial drug distribution can limit the results based on such models. To study drug aerosol supply/deposition, computed tomography scans of a rat capnoperitoneum were used to deduce a virtual and a physical phantom of the rat capnoperitoneum (RCP). RCP qualification was performed for a specific PIPAC method, where the capnoperitoneum is continuously purged by the drug aerosol. In this context, also in-silico analyses by computational fluid dynamic modelling were conducted on the virtual RCP. The physical RCP was used for ex-vivo granulometric analyses concerning drug deposition. Results of RCP qualification show that aerosol deposition in a continuous purged rat capnoperitoneum depends strongly on the position of the inlet and outlet port. Moreover, it could be shown that the droplet size and charge condition of the drug aerosol define the deposition efficiency. In summary, the developed virtual and physical RCP enables detailed in-silico and ex-vivo analyses on drug supply/deposition in rodents.

A whole lung in silico model to estimate age dependent particle dosimetry

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.

Effect of Particle-Wall Interaction and Particle Shape on Particle Deposition Behavior in Human Respiratory System

Dry powder inhalation (DPI) has attracted much attention as a treatment for respiratory diseases owing to the large effective absorption area in a human respiratory system. Understanding the drug particle motion in the respiratory system and the deposition behavior is necessary to improve the efficiency of DPI. We conducted computer simulations using a model coupling a discrete element method and a computational fluid dynamics method (DEM-CFD) to evaluate the particle deposition in human respiratory system. A simple artificial respiratory model was developed, which numerically investigated the effect of particle properties and inhalation patterns on the particle deposition behavior. The DEM-CFD simulations demonstrated that the smaller- and lower-density particles showed higher reachability into the simple respiratory model, and the particle arrival ratio to the deep region strongly depended on the aerodynamic diameter. The particle arrival ratio can be described as an exponential function of the aerodynamic diameter. Furthermore, the exponential relationship between the particle reachability into the depth of the simple respiratory model and the aerodynamic diameter predicted the particle aerodynamic diameter based on the required reachability. The particle shape also had an impact on the particle deposition behavior. The rod-like particles with a larger aspect ratio indicated higher reachability into the depth of the simple respiratory model. This was attributed to the high velocity motion of the particles whose long axis was in the direction of the deep region.

Euler–Lagrange approach to investigate respiratory anatomical shape effects on aerosol particle transport and deposition

An accurate knowledge of the pulmonary aerosol particle transport in the realistic lung is essential to deliver the therapeutic particle to the targeted site of the bifurcating airways. The available in silico studies have enriched the knowledge of the aerosol transport and deposition (TD) in the lung; however, the absolute TD data in the realistic lung airway are still elusive. Therefore, in this study, a 3-D geometry of the human lung central airway is developed from the computed tomography (CT) images. A CT scan-based modified lung geometry with a smooth surface and nonrealistic Weibel’s lung geometry is also generated. The coal mine exhausted aerosol TD in the upper airway is investigated. The Euler–Lagrange (E-L) method for particle tracking and ANSYS Fluent solver are used to carry out the entire investigation. The effective diameter method is employed to define the shape-specific particles and is integrated with the E-L method. The anatomical shape effects on the deposition patterns are investigated for different deposition parameter. The numerical results illustrated that the airway geometry, particle shape, particle diameter, and breathing flow rates significantly influence the aerosol TD pattern in the upper airway. The present study reports that airway tracheal wall is the new deposition hot spot for the CT-based geometry instead of bifurcating area for the idealized model, which might be helpful for zone-specific drug delivery to the respiratory airways.

Mechanics of pulmonary airways: Linking structure to function through constitutive modeling, biochemistry, and histology

Breathing involves fluid-solid interactions in the lung; however, the lack of experimental data inhibits combining the mechanics of air flow to airway deformation, challenging the understanding of how biomaterial constituents contribute to tissue response. As such, lung mechanics research is increasingly focused on exploring the relationship between structure and function. To address these needs, we characterize mechanical properties of porcine airways using uniaxial tensile experiments, accounting for bronchial orientation- and location- dependency. Structurally-reinforced constitutive models are developed to incorporate the role of collagen and elastin fibers embedded within the extrafibrillar matrix. The strain-energy function combines a matrix description (evaluating six models: compressible NeoHookean, unconstrained Ogden, uncoupled Mooney-Rivlin, incompressible Ogden, incompressible Demiray and incompressible NeoHookean), superimposed with non-linear fibers (evaluating two models: exponential and polynomial). The best constitutive formulation representative of all bronchial regions is determined based on curve-fit results to experimental data, accounting for uniqueness and sensitivity. Glycosaminoglycan and collagen composition, alongside tissue architecture, indicate fiber form to be primarily responsible for observed airway anisotropy and heterogeneous mechanical behavior. To the authors' best knowledge, this study is the first to formulate a structurally-motivated constitutive model, augmented with biochemical analysis and microstructural observations, to investigate the mechanical function of proximal and distal bronchi. Our systematic pulmonary tissue characterization provides a necessary foundation for understanding pulmonary mechanics; furthermore, these results enable clinical translation through simulations of airway obstruction in disease, fluid-structure interaction insights during breathing, and potentially, predictive capabilities for medical interventions. STATEMENT OF SIGNIFICANCE: The advancement of pulmonary research relies on investigating the biomechanical response of the bronchial tree. Experiments demonstrating the non-linear, heterogeneous, and anisotropic material behavior of porcine airways are used to develop a structural constitutive model representative of proximal and distal bronchial behavior. Calibrated material parameters exhibit regional variation in biomaterial properties, initially hypothesized to originate from tissue constituents. Further exploration through biochemical and histological analysis indicates mechanical function is primarily governed by microstructural form. The results of this study can be directly used in finite element and fluid-structure interaction models to enable physiologically relevant and more accurate computational simulations aimed to help diagnose and monitor pulmonary disease.

Patient-specific modeling of aerosol delivery in healthy and asthmatic adults

The magnitude and regional heterogeneity of airway obstructions in severe asthmatics is likely linked to insufficient drug delivery, as evidenced by the inability to mitigate exacerbations with inhaled aerosol medications. To understand the correlation between morphometric features, airflow distribution, and inhaled dosimetry, we perform dynamic computational simulations in two healthy and four asthmatic subjects. Models incorporate computed tomography-based and patient-specific central airway geometries and hyperpolarized ³He MRI-measured segmental ventilation defect percentages (SVDPs), implemented as resistance boundary conditions. Particles [diameters (d_p) = 1, 3, and 5 μm] are simulated throughout inhalation, and we record their initial conditions, both spatially and temporally, with their fate in the lung. Predictions highlight that total central airway deposition is the same between the healthy subjects (26.6%, d_p = 3 μm) but variable among the asthmatic subjects (ranging from 5.9% to 59.3%, d_p = 3 μm). We found that by preferentially releasing the particles during times of fast or slow inhalation rates we enhance either central airway deposition percentages or peripheral particle delivery, respectively. These predictions highlight the potential to identify with simulations patients who may not receive adequate therapeutic dosages with inhaled aerosol medication and therefore identify patients who may benefit from alternative treatment strategies. Furthermore, by improving regional dose levels, we may be able to preferentially deliver drugs to the airways in need, reducing associated adverse side effects.NEW & NOTEWORTHY Although it is evident that exacerbation mitigation is unsuccessful in some asthmatics, it remains unclear whether or not these patients receive adequate dosages of inhaled therapeutics. By coupling MRI and computed tomography data with patient-specific computational models, our predictions highlight the large intersubject variability, specifically in severe asthma.

Regional flow and deposition variability in adult female lungs: A numerical simulation pilot study

BACKGROUND

Despite the promise of respiratory simulations improving diagnosis and treatment of pulmonary diseases, model predictions have yet to be translated into the clinical setting. Current state-of-the-art in silico models have not yet incorporated subject variability in their predictions of airflow distributions and extent of deposited particles. Until inter-subject variability is accounted for in lung modeling, it will remain impossible to translate model predictions into clinical practice.

METHODS

Airflow and particle trajectories (d_p=1,3,5μm) are calculated in three subject-specific female adults by performing physiologically-based simulations. The computation framework features the ability to track air and particles throughout the respiration cycle and in the entire lung. Airway resistances, air velocities, and local deposition sites are correlated to airway anatomical features.

FINDINGS

Smaller airway diameters are correlated to larger airway resistances and pressure gradients in one subject compared to the other two. Irregular shape of the airway and flow direction (e.g. inspiration or expiration) correspond with peak velocities and secondary flow motions. Largest subject variability in deposition between conducting and respiratory zones is seen for 1 μm diameter particles. Little difference in total deposition is found among subjects. Localized deposited particle concentration hotspots are linked to airway anatomy and flow motion.

INTERPRETATION

Simulation predictions provide a first look into the correlation of anatomical features with airflow characteristics and deposited particle concentrations. Global deposition percentages ranged (at most, by 20%) between subjects and variances in localized deposition hotspots are correlated to variances in flow characteristics.

Airway morphology and inspiratory flow features in the early stages of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic Obstructive Pulmonary Disease (COPD) is among the leading causes of death worldwide. Inhaled pollutants are the prime risk factor, but the pathogenesis and progression of the diseased is poorly understood. Most studies on the disease onset and trajectory have focused on genetic and molecular biomarkers. Here we investigate the role of the airway anatomy and the consequent respiratory fluid mechanics on the development of COPD.

METHODS

We segmented CT scans from a five-year longitudinal study in three groups of smokers (18 subjects each) having: (i) minimal/mild obstruction at baseline with declining lung function at year five; (ii) minimal/mild obstruction at baseline with stable function, and (iii) normal and stable lung function over the five year period. We reconstructed the bronchial trees up to the 7th generation, and for one subject in each group we performed MRI velocimetry in 3D printed models.

FINDINGS

The subjects with airflow obstruction at baseline have smaller airway diameters, smaller child-to-parent diameter ratios, larger length-to-diameter ratios, and smaller fractal dimensions. The differences are more significant for subjects that develop severe decline in pulmonary function. The secondary flows that characterize lateral dispersion along the airways are found to be less intense in the subjects with airflow obstruction.

INTERPRETATION

These results indicate that morphology of the conducting airways and inspiratory flow features are correlated with the status and progression of COPD already at an early stage of the disease. This suggests that imaging-based biomarkers may allow a pre-symptomatic diagnosis of disease progression.

Models of deposition, pharmacokinetics, and intersubject variability in respiratory drug delivery

INTRODUCTION

Aerosol drug delivery to the lungs via inhalation is widely used in the treatment of respiratory diseases. The deposition pattern of inhaled particles within the airways of the respiratory tract is key in determining the initial delivered dose. Thereafter, dose-dependent processes including drug release or dissolution, clearance, and absorption influence local and systemic exposure to inhaled drugs over time.

AREAS COVERED

Empirical correlations, numerical simulation, and in vitro airway geometries that permit improved prediction of extrathoracic and lung deposition fractions in a variety of age groups and breathing conditions are described. Efforts to link deposition models with pharmacokinetic models predicting lung and systemic exposure to inhaled drugs over time are then reviewed. Finally, new methods to predict intersubject variability in extrathoracic deposition, capturing variability in both size and shape of the upper airways, are highlighted.

EXPERT OPINION

Recent work has been done to expand in vitro deposition experiments to a wide range of age groups and breathing conditions, to link regional lung deposition models with pharmacokinetic models, and to improve prediction of intersubject variability. These efforts are improving predictive understanding of respiratory drug delivery, and will aid the development of new inhaled drugs and delivery devices.

Patient-Specific Computational Simulations of Hyperpolarized 3He MRI Ventilation Defects in Healthy and Asthmatic Subjects

Combined, medical imaging data and respiratory computer simulations may facilitate novel insight into pulmonary disease phenotypes, including the structure/function relationships within the airways. This integration may ultimately enable improved classification and treatment of asthma. Severe asthma (15% of asthmatics) is particularly challenging to treat, as these patients do not respond well to inhaled therapeutics.

METHODS

This study combines medical image data with patient-specific computational models to predict gas distributions and airway mechanics in healthy and asthmatic subjects. We achieve this by integrating segmental volume defect percent (SVDP), measured from hyperpolarized 3He MRI and CT images, to create models of patient-specific gas flow within the conducting airways. Predicted and measured SVDP distributions are achieved when the prescribed resistances are increased systematically.

RESULTS

Because of differences in airway morphology and regional function, airway resistances and flow structures varied between the asthmatic subjects. Specifically, while mean SVDP was similar between the severe asthmatics (4.30±5.22 versus 3.54±5.98%), one subject exhibited abnormal flow structures, high near wall flow gradients, and enhanced conducting airway resistances (17.3E-3versus 1.1E-3 cmH2O-s/mL) in comparison to the other severe asthmatic subject.

CONCLUSION

By coupling medical imaging data with computer simulations, we provide detailed insight into pathological flow characteristics and airway mechanics in asthmatics, beyond what could be inferred independently.

Construction of analysis suitable vascular models using axis-aligned polycubes

Image-based modeling is an active and growing area of biomedical research that utilizes medical imaging to create patient-specific simulations of physiological function. Under this paradigm, anatomical structures are segmented from a volumetric image, creating a geometric model that serves as a computational domain for physics-based modeling. A common application is the segmentation of cardiovascular structures to numerically model blood flow or tissue mechanics. The segmentation of medical image data typically results in a discrete boundary representation (surface mesh) of the segmented structure. However, it is often desirable to have an analytic representation of the model, which facilitates systematic manipulation. For example, the model then becomes easier to union with a medical device, or the geometry can be virtually altered to test or optimize a surgery. Furthermore, to employ increasingly popular isogeometric analysis methods the parameterization must be analysis suitable. Converting a discrete surface model to an analysis suitable model remains a challenge, especially for complex branched structures commonly encountered in cardiovascular modeling. To address this challenge, we present a framework to convert discrete surface models of vascular geometries derived from medical image data into analysis suitable non-uniform rational B-splines representation. This is achieved by decomposing the vascular geometry into a polycube structure that can be used to form a globally-valid parameterization. We provide several practical examples and demonstrate the accuracy of the methods by quantifying the fidelity of the parameterization with respect to the input geometry.

Mechanical properties of the airway tree: heterogeneous and anisotropic pseudoelastic and viscoelastic tissue responses

Airway obstruction and pulmonary mechanics remain understudied despite lung disease being the third cause of death in the United States. Lack of relevant data has led computational pulmonary models to infer mechanical properties from available material data for the trachea. Additionally, the time-dependent, viscoelastic behaviors of airways have been largely overlooked, despite their potential physiological relevance and utility as metrics of tissue remodeling and disease progression. Here, we address the clear need for airway-specific material characterization to inform biophysical studies of the bronchial tree. Specimens from three airway levels (trachea, large bronchi, and small bronchi) and two orientations (axial and circumferential) were prepared from five fresh pig lungs. Uniaxial tensile tests revealed substantial heterogeneity and anisotropy. Overall, the linear pseudoelastic modulus was significantly higher axially than circumferentially (30.5 ± 3.1 vs. 8.4 ± 1.1 kPa) and significantly higher among circumferential samples for small bronchi than for the trachea and large bronchi (12.5 ± 1.9 vs. 6.0 ± 0.6 and 6.6 ± 0.9 kPa). Circumferential samples exhibited greater percent stress relaxation over 300 s than their axial counterparts (38.0 ± 1.4 vs. 23.1 ± 1.5%). Axial and circumferential trachea samples displayed greater percent stress relaxation (26.4 ± 1.6 and 42.5 ± 1.7%) than corresponding large and small bronchi. This ex vivo pseudoelastic and viscoelastic characterization reveals novel anisotropic and heterogeneous behaviors and equips us to construct airway-specific constitutive relations. Our results establish necessary fundamentals for airway mechanics, laying the groundwork for future studies to extend to clinical questions surrounding lung injury, and further directly enables computational tools for lung disease obstruction predictions. NEW & NOTEWORTHY Understanding the mechanics of the lung is necessary for investigating disease progression. Trachea mechanics comprises the vast majority of ex vivo airway tissue characterization despite distal airways being the site of disease manifestation and occlusion. Furthermore, viscoelastic studies are scarce, whereas time-dependent behaviors could be potential physiological metrics of tissue remodeling. In this study, the critical need for airway-specific material properties is addressed, reporting bronchial tree anisotropic and heterogeneous material properties.

Airflow Simulations in Infant, Child, and Adult Pulmonary Conducting Airways

The airway structure continuously evolves from birth to adulthood, influencing airflow dynamics and respiratory mechanics. We currently know very little about how airflow patterns change throughout early life and its impact on airway resistance, namely because of experimental limitations. To uncover differences in respiratory dynamics between age groups, we performed subject-specific airflow simulations in an infant, child, and adult conducting airways. Airflow throughout the respiration cycle was calculated by coupling image-based models of the conducting airways to the global respiratory mechanics, where flow was driven by a pressure differential. Trachea diameter was 19, 9, and 4.5 mm for the adult (36 years, female), child (6 years, male), and infant (0.25 years, female), respectively. Mean Reynolds number within the trachea was nearly the same for each subject (1100) and Womersley number was above unity for all three subjects and largest for the adult, highlighting the significance of transient effects. In general, air speeds and airway resistances within the conducting airways were inversely correlated with age; the 3D pressure drop was highest in the infant model. These simulations provide new insight into age-dependent flow dynamics throughout the respiration cycle within subject-specific airways.