Airflow and particle deposition simulations in health and emphysema: from in vivo to in silico animal experiments

A coupled model for the dynamics of gas exchanges in the human lung with Haldane and Bohr's effects

We propose an integrated dynamical model for oxygen and carbon dioxide transfer from the lung into the blood, coupled with a lumped mechanical model for the ventilation process, for healthy patients as well as in pathological cases. In particular, we take into account the nonlinear interaction between oxygen and carbon dioxide in the blood volume, referred to as the Bohr and Haldane effects. We also propose a definition of the physiological dead space volume (the lung volume that does not contribute to gas exchange) which depends on the pathological state and the breathing scenario. This coupled ventilation-gas diffusion model is driven by the sole action of the respiratory muscles. We analyse its sensitivity with respect to characteristic parameters: the resistance of the bronchial tree, the elastance of the lung tissue and the oxygen and carbon dioxide diffusion coefficients of the alveolo-capillary membrane. Idealized pathological situations are also numerically investigated. We obtain realistic qualitative tendencies, which represent a first step towards classification of the pathological behaviours with respect to the considered input parameters.

Magnetic Resonance Imaging of Aerosol Deposition

Nuclear magnetic resonance imaging (MRI) uses non-ionizing radiation and offers a host of contrast mechanisms with the potential to quantify aerosol deposition. This chapter introduces the physics of MRI, its use in lung imaging, and more specifically, the methods that are used for the detection of regional distributions of inhaled particles. The most common implementation of MRI is based on imaging of hydrogen atoms (1H) in water. The regional deposition of aerosol particles can be measured by the perturbation of the acquired 1H signals via labeling of the aerosol with contrast agents. Existing in vitro human and in vivo animal model measurements of regional aerosol deposition in the respiratory tract are described, demonstrating the capability of MRI to assess aerosol deposition in the lung.

A path forward in the development of new aerosol drug delivery devices for pediatrics

Inhaled medications are widely accepted as being the optimal route for treating pediatric respiratory diseases, a leading cause of hospitalization and death. Despite jet nebulizers being the preferred inhalation device for neonates and infants, current devices face performance issues with most of the drug never reaching the target lung location. Previous work has aimed to improve pulmonary drug deposition, yet nebulizer efficiency remains low. The development of an inhalant therapy that is efficacious and safe for pediatrics depends on a well-designed delivery system and formulation. To accomplish this, the field needs to rethink the current practice of basing pediatric treatments on adult studies. The rapidly evolving pediatric patient (i.e. neonates to eighteen) needs to be considered because they are different from adults with respect to airway anatomy, breathing patterns, and adherence. Previous research approaches to improve deposition efficiency have been limited due to the complexity of combining physics, which drives aerosol transport and deposition, and biology, especially within the area of pediatrics. To address these critical knowledge gaps, we need a better understanding of how patient age and disease state affect deposition of aerosolized drugs. The complexity of the multiscale respiratory system makes scientific investigation very challenging. The authors have simplified the complex problem into five components with these three areas as ones to address first: how the aerosol is (i) generated in a medical device, (ii) delivered to the patient, and (iii) deposited inside the lung. In this review, we discuss the technological advances and innovations made from experiments, simulations, and predictive models in each of these areas. In addition, we discuss the impact on patient treatment efficacy and recommend a clinical direction, with a focus on pediatrics. In each area, a series of research questions are posed and steps for future research to improve efficacy in aerosol drug delivery are outlined.

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.

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challenging to detect using current techniques due to the diseases’ location (inaccessibility to biopsy) and size (below normal CT/MRI resolution). In this review, we present a new method for lung disease detection and treatment in small airways based on exhaled aerosols, whose patterns are uniquely related to the health of the lungs. Proof-of-concept studies are first presented in idealized lung geometries. We subsequently describe the recent developments in feature extraction and classification of the exhaled aerosol images to establish the relationship between the images and the underlying airway remodeling. Different feature extraction algorithms (aerosol density, fractal dimension, principal mode analysis, and dynamic mode decomposition) and machine learning approaches (support vector machine, random forest, and convolutional neural network) are elaborated upon. Finally, future studies and frequent questions related to clinical applications of the proposed aerosol breath testing are discussed from the authors’ perspective. The proposed breath testing has clinical advantages over conventional approaches, such as easy-to-perform, non-invasive, providing real-time feedback, and is promising in detecting symptomless lung diseases at early stages.

Inhalation dosimetry of nasally inhaled respiratory aerosols in the human respiratory tract with locally remodeled conducting lungs

Objective: Respiratory diseases are often accompanied by alterations to airway morphology. However, inhalation dosimetry data in remodeled airways are scarce due to the challenges in reconstructing diseased respiratory morphologies. This study aims to study the airway remodeling effects on the inhalation dosimetry of nasally inhaled nanoparticles in a nose-lung geometry that extends to G9 (ninth generation).Materials and methods: Statistical shape modeling was used to develop four diseased lung models with varying levels of bronchiolar dilation/constriction in the left-lower (LL) lobe (i.e. M1-M4). Respiratory airflow and particle deposition were simulated using a low Reynolds number k-ω turbulence model and a Lagrangian tracking approach.Results: Significant discrepancies were observed in the flow partitions between the left and right lungs, as well as between the lower and upper lobes of the left lung, which changed by 10-fold between the most dilated and constricted models.Much lower doses were predicted on the surface of the constricted LL bronchioles G4-G9, as well as into the peripheral airways beyond G9 of the LL lung. However, the LL lobar remodeling had little effect on the dosimetry in the nasopharynx, as well as on the total dosimetry in the nose-lung geometry (up to G9).Conclusion: It is suggested that airway remodeling may pose a higher viral infection risk to the host by redistributing the inhaled viruses to healthy lung lobes. Airway remodeling effects should also be considered in the treatment planning of inhalation therapies, not only because of the dosimetry variation from altered lung morphology but also its evolution as the disease progresses.

Realizing Lobe-Specific Aerosol Targeting in a 3D-Printed In Vitro Lung Model

Background: Delivery of aerosols to isolated lobes of the lungs would be beneficial for diseases that have lobe-specific effects, such as cancer, pneumonia, and chronic obstructive pulmonary disorder. Recent computational fluid-particle dynamic (CFPD) modeling has demonstrated that in low flow rates, the inlet location of a particle at the mouth dictates the lobe into which it will deposit. However, realization of this lobe-specific deposition has yet to be attempted experimentally or in the clinic. To address this, we sought to develop a proof-of-concept in vitro model and targeting device for achieving lobe-specific delivery. Methods: Using 3D printing, a lung replica was created from a computed tomography scan of a healthy 47-year-old male volunteer and connected to a flow setup to control inlet flow rate and outlet airflow distribution to each lobe. A device was designed and fabricated that directs particles to an inlet location that is 5% of the total inlet area and described by radial coordinates (r,θ). Filter paper at sampling ports for each lobe was used to capture fluorescent polystyrene particles to quantify particle collection. We evaluated lobe-specific targeting at varied inlet coordinates, particle diameters, inlet flow rates, and disease lobe flow rate distribution profiles. Results: Guided by CFPD modeling, inlet locations were identified that increased particle collection to a target lobe between 63% and 90%. For example, release of fluorescent particles at the inlet location r = 4.67 mm, θ = 252° with respect to the center of the inlet using 1 μm particles, 1 L/min inlet flow rate, and healthy subject lobe flow distribution profile yielded 90% of the aerosol dose to the right upper lobe, corresponding to an increase of 4.6 × above the non-targeted percent particle collection. Particle size, inlet flow rate, and disease airflow distributions were all shown to generally decrease the efficiency of lobe-specific targeting. Conclusions: Our results indicate that aerosol targeting of a specific lobe is possible in vitro under optimized conditions and that controlling inlet locations could be a potentially useful method for treatment of lobe-specific diseases. This is the first demonstration of lobe-specific particle collection in a physical lung model and illuminates numerous challenges that will be faced as this method is translated to clinical applications.

Innovative preclinical models for pulmonary drug delivery research

Introduction: Pulmonary drug delivery is a complex field of research combining physics which drive aerosol transport and deposition and biology which underpins efficacy and toxicity of inhaled drugs. A myriad of preclinical methods, ranging from in-silico to in-vitro, ex-vivo and in-vivo, can be implemented.Areas covered: The present review covers in-silico mathematical and computational fluid dynamics modelization of aerosol deposition, cascade impactor technology to estimated drug delivery and deposition, advanced in-vitro cell culture methods and associated aerosol exposure, lung-on-chip technology, ex-vivo modeling, in-vivo inhaled drug delivery, lung imaging, and longitudinal pharmacokinetic analysis.Expert opinion: No single preclinical model can be advocated; all methods are fundamentally complementary and should be implemented based on benefits and drawbacks to answer specific scientific questions. The overall best scientific strategy depends, among others, on the product under investigations, inhalation device design, disease of interest, clinical patient population, previous knowledge. Preclinical testing is not to be separated from clinical evaluation, as small proof-of-concept clinical studies or conversely large-scale clinical big data may inform preclinical testing. The extend of expertise required for such translational research is unlikely to be found in one single laboratory calling for the setup of multinational large-scale research consortiums.

Particle transport and deposition correlation with near-wall flow characteristic under inspiratory airflow in lung airways

Exposure of lung airways to detrimental suspended aerosols in the environment increases the vulnerability of the respiratory and cardiovascular systems. In addition, recent developments in therapeutic inhalation devices magnify the importance of particle transport. In this manuscript, particle transport and deposition patterns in the upper tracheobronchial (TB) tree were studied where the inertial forces are considerable for microparticles. Wall shear stress divergence (WSSdiv) is proposed as a wall-based parameter that can predict particle deposition patterns. WSSdiv is proportional to near-wall normal velocity and can quantify the strength of flow towards and away from the wall. Computational fluid dynamics (CFD) simulations were performed to quantify airflow velocity and WSS vectors for steady inhalation in one case-control and unsteady inhalation in six subject-specific airway trees. Turbulent flow simulation was performed for the steady case using large eddy simulation to study the effect of turbulence. Magnetic resonance velocimetry (MRV) measurements were used to validate the case-control CFD simulation. Inertial particle transport was modeled by solving the Maxey-Riley equation in a Lagrangian framework. Deposition percentage (DP) was quantified for the case-control model over five particle sizes. DP was found to be proportional to particle size in agreement with previous studies in the literature. A normalized deposition concentration (DC) was defined to characterize localized deposition. A relatively strong correlation (Pearson value > 0.7) was found between DC and positive WSSdiv for physiologically relevant Stokes (St) numbers. Additionally, a regional analysis was performed after dividing the lungs into smaller areas. A spatial integral of positive WSSdiv over each division was shown to maintain a very strong correlation (Pearson value > 0.9) with cumulative spatial DC or regional dosimetry. The conclusions were generalized to a larger population in which two healthy and four asthmatic patients were investigated. This study shows that WSSdiv could be used to predict the qualitative surface deposition and relative regional dosimetry without the need to solve a particle transport problem.

Assessing Airflow Sensitivity to Healthy and Diseased Lung Conditions in a Computational Fluid Dynamics Model Validated In Vitro

Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry (PIV). The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy and one COPD) and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root-mean-square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates but markedly different for COPD (minimum R, 0.26; maximum Drms, ten times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contributes to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.

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.

Use of computational fluid dynamics deposition modeling in respiratory drug delivery

INTRODUCTION

Respiratory drug delivery is a surprisingly complex process with a number of physical and biological challenges. Computational fluid dynamics (CFD) is a scientific simulation technique that is capable of providing spatially and temporally resolved predictions of many aspects related to respiratory drug delivery from initial aerosol formation through respiratory cellular drug absorption.

AREAS COVERED

This review article focuses on CFD-based deposition modeling applied to pharmaceutical aerosols. Areas covered include the development of new complete-airway CFD deposition models and the application of these models to develop a next-generation of respiratory drug delivery strategies.

EXPERT OPINION

Complete-airway deposition modeling is a valuable research tool that can improve our understanding of pharmaceutical aerosol delivery and is already supporting medical hypotheses, such as the expected under-treatment of the small airways in asthma. These complete-airway models are also being used to advance next-generation aerosol delivery strategies, like controlled condensational growth. We envision future applications of CFD deposition modeling to reduce the need for human subject testing in developing new devices and formulations, to help establish bioequivalence for the accelerated approval of generic inhalers, and to provide valuable new insights related to drug dissolution and clearance leading to microdosimetry maps of drug absorption.

A mathematical model to investigate the key drivers of the biogeography of the colon microbiota

The gut microbiota, mainly located in the colon, is engaged in a complex dialogue with the large intestinal epithelium through which important regulatory processes for the health and well-being of the host take place. Imbalances of the microbial populations, called dysbiosis, are related to several pathological status, emphasizing the importance of understanding the gut bacterial ecology. Among the ecological drivers of the microbiota, the spatial structure of the colon is of special interest: spatio-temporal mechanisms can lead to the constitution of spatial interactions among the bacterial populations and of environmental niches that impact the overall colonization of the colon. In the present study, we introduce a mathematical model of the colon microbiota in its fluid environment, based on the explicit coupling of a population dynamics model of microbial populations involved in fibre degradation with a fluid dynamics model of the luminal content. This modeling framework is used to study the main drivers of the spatial structure of the microbiota, specially focusing on the dietary fibre inflow, the epithelial motility, the microbial active swimming and viscosity gradients in the digestive track. We found 1) that the viscosity gradients allow the creation of favorable niches in the vicinity of the mucus layer; 2) that very low microbial active swimming in the radial direction is enough to promote bacterial growth, which sheds a new light on microbial motility in the colon and 3) that dietary fibres are the main driver of the spatial structure of the microbiota in the distal bowel whereas epithelial motility is preponderant for the colonization of the proximal colon; in the transverse colon, fibre levels and chemotaxis have the strongest impact on the distribution of the microbial communities.

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.

Simulation of Airflow in an Idealized Emphysematous Human Acinus

Emphysema is the permanent enlargement of air spaces in the respiratory regions of the lung due to destruction of the inter-alveolar septa. The progressive coalescence of alveoli and alveolar ducts into larger airspaces leads to the disruption of normal airway wall motion and airflow rates within the pulmonary acinus. To contribute to the understanding of the individual effects of emphysema during its earliest stages, computational fluid dynamics (CFD) simulations of airflow in mathematically derived models of the pulmonary acinus were performed. The here generated computational domain consists of two generations of alveolar ducts within the pulmonary acinus, with alveolar geometries approximated as closely packed, 14-sided polygons. Physiologically realistic airflow rates and wall motions were used to study airflow patterns within subsequent generations of alveolar ducts during the inspiratory and expiratory phases of the breathing cycle. The effects of progressive emphysema on the airway wall motion and flow rates were simulated by sequentially removing all alveolar septa within each alveolar duct. Parametric studies were presented to independently assess the relative influence of progressive septal destruction of airway motion and flow rates. The results illustrate that septal destruction lowers the flow resistance through the alveolar ducts but has little influence on the mass transport of oxygen into the alveoli. Septal destruction has a net effect on the flow field by favoring the development of recirculatory flow patterns in individual alveoli.

Benchmark problems for numerical treatment of backflow at open boundaries

In computational fluid dynamics, incoming velocity at open boundaries, or backflow, often yields unphysical instabilities already for moderate Reynolds numbers. Several treatments to overcome these backflow instabilities have been proposed in the literature. However, these approaches have not yet been compared in detail in terms of accuracy in different physiological regimes, in particular because of the difficulty to generate stable reference solutions apart from analytical forms. In this work, we present a set of benchmark problems in order to compare different methods in different backflow regimes (with a full reversal flow and with propagating vortices after a stenosis). The examples are implemented in FreeFem++, and the source code is openly available, making them a solid basis for future method developments.

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.

Computational fluid dynamics evaluation of excessive dynamic airway collapse

BACKGROUND

Excessive dynamic airway collapse, which is often caused by the collapse of the posterior membrane wall during exhalation, is often misdiagnosed with other diseases; stents can provide support for the collapsing airways. The standard pulmonary function tests do not necessarily show change in functional breathing condition for evaluation of these type of diseases.

METHODS

Flow characteristics through a patient's airways with excessive dynamic airway collapse have been numerically investigated. A stent was placed to support the collapsing airway and to improve breathing conditions. Computed tomography images of the patient's pre- and post-stenting were used for generating 3-Dimensional models of the airways, and were imported into a computational fluid dynamics software for simulation of realistic air flow behavior. Unsteady simulations of the inspiratory phase and expiratory phase were performed with patient-specific boundary conditions for pre- and post-intervention cases to investigate the effect of stent placement on flow characteristic and possible improvements.

FINDINGS

Results of post-stent condition show reduced pressure, velocity magnitude and wall shear stress during expiration. The variation in wall shear stress, velocity magnitude and pressure drop is negligible during inspiration.

INTERPRETATION

Although Spirometry tests do not show significant improvements, computational fluid dynamics results show significant improvements in pre- and post-treatment results, suggesting improvement in breathing condition.

Particulate Deposition in a Patient With Tracheal Stenosis

The presence of obstructions such as tracheal stenosis has important effects on respiratory functions. Tracheal stenosis impacts the therapeutic efficacy of inhaled medications as a result of alterations in particle transport and deposition pattern. This study explores the effects of the presence and absence of stenosis/obstruction in the trachea on air flow characteristics and particle depositions. Computational fluid dynamics (CFD) simulations were performed on three-dimensional (3D) patient-specific models created from computed tomography (CT) images. The analyzed model was generated from a subject with tracheal stenosis and includes the airway tree up to eight generations. CT scans of expiratory and inspiratory phases were used for patient-specific boundary conditions. Pre- and post-intervention CFD simulations' comparison reveals the effect of the stenosis on the characteristics of air flow, transport, and depositions of particles with diameters of 1, 2.5, 4, 6, 8, and 10 μm. Results indicate that the existence of the stenosis inflicts a major pressure force on the flow of inhaled air, leading to an increased deposition of particles both above and below the stenosis. Comparisons of the decrease in pressure in each generation between pre- and post-tracheal stenosis intervention demonstrated a significant reduction in pressure following the stenosis, which was maintained in all downstream generations. Good agreements were found using experimental validation of CFD findings with a model of the control subject up to the third generation, constructed via additive layer manufacturing from CT images.

One (sub-)acinus for all: Fate of inhaled aerosols in heterogeneous pulmonary acinar structures

Computational Fluid Dynamics (CFD) have offered an attractive gateway to investigate in silico respiratory flows and aerosol transport in the depths of the lungs. Yet, not only do existing models lack sufficient anatomical realism in capturing the heterogeneity and morphometry of the acinar environment, numerical simulations have been widely restricted to domains capturing a mere few percent of a single acinus. Here, we present to the best of our knowledge the most detailed and comprehensive in silico simulations to date on the fate of aerosols in the acinar depths. Our heterogeneous acinar domains represent complete sub-acinar models (i.e. 1/8th of a full acinus) based on the recent algorithm of Koshiyama & Wada (2015), capturing statistics of human acinar morphometry (Ochs et al. 2004). Our simulations deliver high-resolution, 3D spatial-temporal data on aerosol transport and deposition, emphasizing how variances in acinar heterogeneity only play a minor role in determining general deposition outcomes. With such tools at hand, we revisit whole-lung deposition predictions (i.e. ICRP) based on past 1D lung models. While our findings under quiet breathing substantiate general deposition trends obtained with past predictions in the alveolar regions, we underscore how deposition fractions are anticipated to increase, in particular during deep inhalation. For such inhalation maneuver, our simulations support the notion of significantly augmented deposition for all aerosol sizes (0.005-5.0μm). Overall, our efforts not only help consolidate our mechanistic understanding of inhaled aerosol transport in the acinar depths but also continue to bridge the gap between "bottom-up" in silico models and regional deposition predictions from whole-lung models. Such quantifications provide what is deemed more accurate deposition predictions in morphometrically-faithful models and are particularly useful in assessing inhalation strategies for deep airway deposition (e.g. systemic delivery).

Aerosol transport throughout inspiration and expiration in the pulmonary airways

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

Aging effects on airflow dynamics and lung function in human bronchioles

Background and objective

The mortality rate for patients requiring mechanical ventilation is about 35% and this rate increases to about 53% for the elderly. In general, with increasing age, the dynamic lung function and respiratory mechanics are compromised, and several experiments are being conducted to estimate these changes and understand the underlying mechanisms to better treat elderly patients.

Materials and methods

Human tracheobronchial (G1 ~ G9), bronchioles (G10 ~ G22) and alveolar sacs (G23) geometric models were developed based on reported anatomical dimensions for a 50 and an 80-year-old subject. The aged model was developed by altering the geometry and material properties of the model developed for the 50-year-old. Computational simulations using coupled fluid-solid analysis were performed for geometric models of bronchioles and alveolar sacs under mechanical ventilation to estimate the airflow and lung function characteristics.

Findings

The airway mechanical characteristics decreased with aging, specifically a 38% pressure drop was observed for the 80-year-old as compared to the 50-year-old. The shear stress on airway walls increased with aging and the highest shear stress was observed in the 80-year-old during inhalation. A 50% increase in peak strain was observed for the 80-year-old as compared to the 50-year-old during exhalation. The simulation results indicate that there is a 41% increase in lung compliance and a 35%-50% change in airway mechanical characteristics for the 80-year-old in comparison to the 50-year-old. Overall, the airway mechanical characteristics as well as lung function are compromised due to aging.

Conclusion

Our study demonstrates and quantifies the effects of aging on the airflow dynamics and lung capacity. These changes in the aging lung are important considerations for mechanical ventilation parameters in elderly patients. Realistic geometry and material properties need to be included in the computational models in future studies.

Multi-resolution classification of exhaled aerosol images to detect obstructive lung diseases in small airways

Exhaled aerosol patterns have been used to detect obstructive respiratory diseases in the upper airways. Signals from small airway diseases are weak and may not manifest themselves in the exhaled aerosol patterns. Therefore, it will be more challenging to detect abnormalities in small airways. The objective of this study is to develop a simulation-based classification model that can accurately classify small airway diseases. The model performance was evaluated in five obstructed models that are located in lung bifurcations G7-9. The exhaled aerosol images were quantified using local fractal dimensions at different sampling resolutions (n × n). The datasets were classified using both the random forest (RF) and support vector machine (SVM) algorithms. Results show that RF performs slightly and persistently better than SVM. The sampling resolution of 12 × 12 gave the optimal classification for both algorithms. Based on the lung models with predefined obstructive levels, the optimal classification accuracy is 87.0% for 5-class classification, and is 92.5% for 4-class classification by regrouping the mislabeled samples. The proposed model with multi-resolution fractal feature extraction and RF algorithm appears to be sensitive enough to accurately distinguish airway abnormalities in small airways beyond G7 with healthy bronchiole diameter <4 mm. This aerosol-based breath test is promising to develop into an alternative or supplemental tool to the low-dose CT scanning for lung cancer screening.

Atomization method for verifying size effects of inhalable particles on lung damage of mice

To explore the size effects of inhalable particles on lung damage, aqueous aerosol containing cadmium was studied as a model to design a new type of two-stage atomization device that was composed of two adjustable parts with electronic ultrasonic atomization and pneumatic atomization. The working parameters and effectiveness of this device were tested with H₂O atomization and CdCl₂ inhalation, respectively. By gravimetrically detecting the mass concentrations of PM_2.5 and PM₁₀ and analysing the particle size with a laser sensor, we confirmed the particle size distribution of the aqueous aerosol produced by the new device under different working conditions. Then, we conducted experiments in male Kunming mice that inhaled CdCl₂ to determine the size effects of inhalable particles on lung damage and to confirm the effectiveness of the device. The new device could effectively control the particle size in the aqueous aerosol. The inhaled CdCl₂ entered and injured the lungs of the mice by causing tissue damage, oxidative stress, increasing endoplasmic reticulum stress and triggering an inflammatory response, which might be related to where the particles deposited. The smaller particles in the aqueous aerosol atomized by the new two-stage atomization device deposited deeper into lung causing more damage. This device could provide a new method for animal experiments involving inhalation with water-soluble toxins.

Nanoparticle transport and delivery in a heterogeneous pulmonary vasculature

Quantitative understanding of nanoparticles delivery in a complex vascular networks is very challenging because it involves interplay of transport, hydrodynamic force, and multivalent interactions across different scales. Heterogeneous pulmonary network includes up to 16 generations of vessels in its arterial tree. Modeling the complete pulmonary vascular system in 3D is computationally unrealistic. To save computational cost, a model reconstructed from MRI scanned images is cut into an arbitrary pathway consisting of the upper 4-generations. The remaining generations are represented by an artificially rebuilt pathway. Physiological data such as branch information and connectivity matrix are used for geometry reconstruction. A lumped model is used to model the flow resistance of the branches that are cut off from the truncated pathway. Moreover, since the nanoparticle binding process is stochastic in nature, a binding probability function is used to simplify the carrier attachment and detachment processes. The stitched realistic and artificial geometries coupled with the lumped model at the unresolved outlets are used to resolve the flow field within the truncated arterial tree. Then, the biodistribution of 200nm, 700nm and 2µm particles at different vessel generations is studied. At the end, 0.2-0.5% nanocarrier deposition is predicted during one time passage of drug carriers through pulmonary vascular tree. Our truncated approach enabled us to efficiently model hemodynamics and accordingly particle distribution in a complex 3D vasculature providing a simple, yet efficient predictive tool to study drug delivery at organ level.

SimVascular: An Open Source Pipeline for Cardiovascular Simulation

Patient-specific cardiovascular simulation has become a paradigm in cardiovascular research and is emerging as a powerful tool in basic, translational and clinical research. In this paper we discuss the recent development of a fully open-source SimVascular software package, which provides a complete pipeline from medical image data segmentation to patient-specific blood flow simulation and analysis. This package serves as a research tool for cardiovascular modeling and simulation, and has contributed to numerous advances in personalized medicine, surgical planning and medical device design. The SimVascular software has recently been refactored and expanded to enhance functionality, usability, efficiency and accuracy of image-based patient-specific modeling tools. Moreover, SimVascular previously required several licensed components that hindered new user adoption and code management and our recent developments have replaced these commercial components to create a fully open source pipeline. These developments foster advances in cardiovascular modeling research, increased collaboration, standardization of methods, and a growing developer community.

Validating Whole-Airway CFD Predictions of DPI Aerosol Deposition at Multiple Flow Rates

BACKGROUND

The objective of this study was to compare aerosol deposition predictions of a new whole-airway CFD model with available in vivo data for a dry powder inhaler (DPI) considered across multiple inhalation waveforms, which affect both the particle size distribution (PSD) and particle deposition.

METHODS

The Novolizer DPI with a budesonide formulation was selected based on the availability of 2D gamma scintigraphy data in humans for three different well-defined inhalation waveforms. Initial in vitro cascade impaction experiments were conducted at multiple constant (square-wave) particle sizing flow rates to characterize PSDs. The whole-airway CFD modeling approach implemented the experimentally determined PSDs at the point of aerosol formation in the inhaler. Complete characteristic airway geometries for an adult were evaluated through the lobar bronchi, followed by stochastic individual pathway (SIP) approximations through the tracheobronchial region and new acinar moving wall models of the alveolar region.

RESULTS

It was determined that the PSD used for each inhalation waveform should be based on a constant particle sizing flow rate equal to the average of the inhalation waveform's peak inspiratory flow rate (PIFR) and mean flow rate [i.e., AVG(PIFR, Mean)]. Using this technique, agreement with the in vivo data was acceptable with <15% relative differences averaged across the three regions considered for all inhalation waveforms. Defining a peripheral to central deposition ratio (P/C) based on alveolar and tracheobronchial compartments, respectively, large flow-rate-dependent differences were observed, which were not evident in the original 2D in vivo data.

CONCLUSIONS

The agreement between the CFD predictions and in vivo data was dependent on accurate initial estimates of the PSD, emphasizing the need for a combination in vitro-in silico approach. Furthermore, use of the AVG(PIFR, Mean) value was identified as a potentially useful method for characterizing a DPI aerosol at a constant flow rate.

The role of anisotropic expansion for pulmonary acinar aerosol deposition

Lung deformations at the local pulmonary acinar scale are intrinsically anisotropic. Despite progress in imaging modalities, the true heterogeneous nature of acinar expansion during breathing remains controversial, where our understanding of inhaled aerosol deposition still widely emanates from studies under self-similar, isotropic wall motions. Building on recent 3D models of multi-generation acinar networks, we explore in numerical simulations how different hypothesized scenarios of anisotropic expansion influence deposition outcomes of inhaled aerosols in the acinar depths. While the broader range of particles acknowledged to reach the acinar region (dp=0.005-5.0μm) are largely unaffected by the details of anisotropic expansion under tidal breathing, our results suggest nevertheless that anisotropy modulates the deposition sites and fractions for a narrow band of sub-micron particles (dp~0.5-0.75μm), where the fate of aerosols is greatly intertwined with local convective flows. Our findings underscore how intrinsic aerosol motion (i.e. diffusion, sedimentation) undermines the role of anisotropic wall expansion that is often attributed in determining aerosol mixing and acinar deposition.

INHALED AEROSOL DOSIMETRY: SOME CURRENT RESEARCH NEEDS

After the presentation of 60 papers at the conference "Advancing Aerosol Dosimetry Research" (October 24-25, 2014 in Irvine, CA, USA), attendees submitted written descriptions of needed research. About 40 research needs were submitted. The suggestions fell into six broad categories: 1) Access to detailed anatomic data; 2) Access to subject-specific aerosol deposition datasets; 3) Improving current inhaled aerosol deposition models; 4) Some current experimental data needs and hot topics; 5) Linking exposure and deposition modeling to health endpoints; and 6) Developing guidelines for appropriate validation of dosimetry and risk assessment models. Summaries of suggestions are provided here as an update on research needs related to inhaled aerosol dosimetry modeling. Taken together, the recommendations support the overarching need for increased collaborations between dose modelers and those that use the models for risk assessments, aerosol medicine applications, design of toxicology experiments, and extrapolation across species. This paper is only a snapshot in time of perceived research needs from the conference attendees; it does not carry the approval of any agency or other group that plans research priorities or that funds research.

Bridging the Gap Between Science and Clinical Efficacy: Physiology, Imaging, and Modeling of Aerosols in the Lung

Development of a new drug for the treatment of lung disease is a complex and time consuming process involving numerous disciplines of basic and applied sciences. During the 2015 Congress of the International Society for Aerosols in Medicine, a group of experts including aerosol scientists, physiologists, modelers, imagers, and clinicians participated in a workshop aiming at bridging the gap between basic research and clinical efficacy of inhaled drugs. This publication summarizes the current consensus on the topic. It begins with a short description of basic concepts of aerosol transport and a discussion on targeting strategies of inhaled aerosols to the lungs. It is followed by a description of both computational and biological lung models, and the use of imaging techniques to determine aerosol deposition distribution (ADD) in the lung. Finally, the importance of ADD to clinical efficacy is discussed. Several gaps were identified between basic science and clinical efficacy. One gap between scientific research aimed at predicting, controlling, and measuring ADD and the clinical use of inhaled aerosols is the considerable challenge of obtaining, in a single study, accurate information describing the optimal lung regions to be targeted, the effectiveness of targeting determined from ADD, and some measure of the drug's effectiveness. Other identified gaps were the language and methodology barriers that exist among disciplines, along with the significant regulatory hurdles that need to be overcome for novel drugs and/or therapies to reach the marketplace and benefit the patient. Despite these gaps, much progress has been made in recent years to improve clinical efficacy of inhaled drugs. Also, the recent efforts by many funding agencies and industry to support multidisciplinary networks including basic science researchers, R&D scientists, and clinicians will go a long way to further reduce the gap between science and clinical efficacy.

Aerosols in healthy and emphysematous in silico pulmonary acinar rat models

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

Numerical simulation of particle transport and deposition in the pulmonary vasculature

To quantify the transport and adhesion of drug particles in a complex vascular environment, computational fluid particle dynamics (CFPD) simulations of blood flow and drug particulate were conducted in three different geometries representing the human lung vasculature for steady and pulsatile flow conditions. A fully developed flow profile was assumed as the inlet velocity, and a lumped mathematical model was used for the calculation of the outlet pressure boundary condition. A receptor-ligand model was used to simulate the particle binding probability. The results indicate that bigger particles have lower deposition fraction due to less chance of successful binding. Realistic unsteady flow significantly accelerates the binding activity over a wide range of particle sizes and also improves the particle deposition fraction in bifurcation regions when comparing with steady flow condition. Furthermore, surface imperfections and geometrical complexity coupled with the pulsatility effect can enhance fluid mixing and accordingly particle binding efficiency. The particle binding density at bifurcation regions increases with generation order and drug carriers are washed away faster in steady flow. Thus, when studying drug delivery mechanism in vitro and in vivo, it is important to take into account blood flow pulsatility in realistic geometry. Moreover, tissues close to bifurcations are more susceptible to deterioration due to higher uptake.

Distribution of aerosolized particles in healthy and emphysematous rat lungs: comparison between experimental and numerical studies

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

MRI-based measurements of aerosol deposition in the lung of healthy and elastase-treated rats

Aerosolized drugs are increasingly being used to treat chronic lung diseases or to deliver therapeutics systemically through the lung. The influence of disease, such as emphysema, on particle deposition is not fully understood. With the use of magnetic resonance imaging (MRI), the deposition pattern of iron oxide particles with a mass median aerodynamic diameter of 1.2 μm was assessed in the lungs of healthy and elastase-treated rats. Tracheostomized rats were ventilated with particles, at a tidal volume of 2.2 ml, and a breathing frequency of 80 breaths/min. Maximum airway pressure was significantly lower in the elastase-treated (P_aw = 7.71 ± 1.68 cmH₂O) than in the healthy rats (P_aw = 10.43 ± 1.02 cmH₂O; P < 0.01). This is consistent with an increase in compliance characteristic of an emphysema-like lung structure. Following exposure, lungs were perfusion fixed and imaged in a 3T MR scanner. Particle concentration in the different lobes was determined based on a relationship with the MR signal decay rate, R₂^*. Whole lung particle deposition was significantly higher in the elastase-treated rats (C_E,part = 3.03 ± 0.61 μm/ml) compared with the healthy rats (C_H,part = 1.84 ± 0.35 μm/ml; P < 0.01). However, when particle deposition in each lobe was normalized by total deposition in the lung, there was no difference between the experimental groups. However, the relative dispersion [RD = standard deviation/mean] of R₂^* was significantly higher in the elastase-treated rats (RD_E = 0.32 ± 0.02) compared with the healthy rats (RD_H = 0.25 ± 0.02; P < 0.01). These data show that particle deposition is higher and more heterogeneously distributed in emphysematous lungs compared with healthy lungs.