Investigating distributions of inhaled aerosols in the lungs of post-COVID-19 clusters through a unified imaging and modeling approach.

BACKGROUND: Recent studies, based on clinical data, have identified sex and age as significant factors associated with an increased risk of long COVID. These two factors align with the two post-COVID-19 clusters identified by a deep learning algorithm in computed tomography (CT) lung scans: Cluster 1 (C1), comprising predominantly females with small airway diseases, and Cluster 2 (C2), characterized by older individuals with fibrotic-like patterns. This study aims to assess the distributions of inhaled aerosols in these clusters. METHODS: 140 COVID survivors examined around 112 days post-diagnosis, along with 105 uninfected, non-smoking healthy controls, were studied. Their demographic data and CT scans at full inspiration and expiration were analyzed using a combined imaging and modeling approach. A subject-specific CT-based computational model analysis was utilized to predict airway resistance and particle deposition among C1 and C2 subjects. The cluster-specific structure and function relationships were explored. RESULTS: In C1 subjects, distinctive features included airway narrowing, a reduced homothety ratio of daughter over parent branch diameter, and increased airway resistance. Airway resistance was concentrated in the distal region, with a higher fraction of particle deposition in the proximal airways. On the other hand, C2 subjects exhibited airway dilation, an increased homothety ratio, reduced airway resistance, and a shift of resistance concentration towards the proximal region, allowing for deeper particle penetration into the lungs. CONCLUSIONS: This study revealed unique mechanistic phenotypes of airway resistance and particle deposition in the two post-COVID-19 clusters. The implications of these findings for inhaled drug delivery effectiveness and susceptibility to air pollutants were explored.

CT-derived 3D-diaphragm motion in emphysema and IPF compared to normal subjects.

Image registration-based local displacement analysis enables evaluation of respiratory motion between two computed tomography-captured lung volumes. The objective of this study was to compare diaphragm movement among emphysema, idiopathic pulmonary fibrosis (IPF) and normal subjects. 29 normal, 50 emphysema, and 51 IPF subjects were included. A mass preserving image registration technique was used to compute displacement vectors of local lung regions at an acinar scale. Movement of the diaphragm was assumed to be equivalent to movement of the basal lung within 5 mm from the diaphragm. Magnitudes and directions of displacement vectors were compared between the groups. Three-dimensional (3D) and apico-basal displacements were smaller in emphysema than normal subjects (P = 0.003, P = 0.002). Low lung attenuation area on expiration scan showed significant correlations with decreased 3D and apico-basal displacements (r = - 0.546, P < 0.0001; r = - 0.521, P < 0.0001) in emphysema patients. Dorsal-ventral displacement was smaller in IPF than normal subjects (P < 0.0001). The standard deviation of the displacement angle was greater in both emphysema and IPF patients than normal subjects (P < 0.0001). In conclusion, apico-basal movement of the diaphragm is reduced in emphysema while dorsal-ventral movement is reduced in IPF. Image registration technique to multi-volume CT scans provides insight into the pathophysiology of limited diaphragmatic motion in emphysema and IPF.

Longitudinal Imaging-Based Clusters in Former Smokers of the COPD Cohort Associate with Clinical Characteristics: The SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).

PURPOSE: Quantitative computed tomography (qCT) imaging-based cluster analysis identified clinically meaningful COPD former-smoker subgroups (clusters) based on cross-sectional data. We aimed to identify progression clusters for former smokers using longitudinal data. PATIENTS AND METHODS: We selected 472 former smokers from SPIROMICS with a baseline visit and a one-year follow-up visit. A total of 150 qCT imaging-based variables, comprising 75 variables at baseline and their corresponding progression rates, were derived from the respective inspiration and expiration scans of the two visits. The COPD progression clusters identified were then associated with subject demography, clinical variables and biomarkers. RESULTS: COPD severities at baseline increased with increasing cluster number. Cluster 1 patients were an obese subgroup with rapid progression of functional small airway disease percentage (fSAD%) and emphysema percentage (Emph%). Cluster 2 exhibited a decrease of fSAD% and Emph%, an increase of tissue fraction at total lung capacity and airway narrowing over one year. Cluster 3 showed rapid expansion of Emph% and an attenuation of fSAD%. Cluster 4 demonstrated severe emphysema and fSAD and significant structural alterations at baseline with rapid progression of fSAD% over one year. Subjects with different progression patterns in the same cross-sectional cluster were identified by longitudinal clustering. CONCLUSION: qCT imaging-based metrics at two visits for former smokers allow for the derivation of four statistically stable clusters associated with unique progression patterns and clinical characteristics. Use of baseline variables and their progression rates enables identification of longitudinal clusters, resulting in a refinement of cross-sectional clusters.

Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability.

PURPOSE: With the help of quantitative computed tomography (QCT), it is possible to identify smoking-associated airway remodeling. However, there is currently little information on whether QCT-based airway metrics are sensitive to early airway wall remodeling in subclinical phases of smoking-associated airway disease. This study aimed to evaluate a predictive model that normalized airway parameters and investigate structural airway alterations in smokers with normal-looking CT using the normalization scheme. METHODS: In this retrospective analysis, 222 non-smokers (male 97, female 125) and 69 smokers (male 66, female 3) from January 2014 to December 2016 were included, and airway parameters were quantitatively analyzed. To control inter-subject variability, multiple linear regressions of tracheal wall thickness (WT), diameter (D), and luminal area (LA) were performed, adjusted for age, sex, and height. Using this normalization scheme, airway parameters with matched generation were compared between smokers and non-smokers. RESULTS: Using the normalization scheme, it was possible to assess generation-based structural alterations of the airways in subclinical smokers. Smokers showed diffuse luminal narrowing of airways for most generations (P < 0.05, except 3rd generation), no change in wall thickness of the proximal bronchi (1st-3rd generation), and a thinning of distal airways (P <0.05, ≥4th generation). CONCLUSION: QCT assessment for subclinical smokers can help identify minimal structural changes in airways induced by smoking.

Latent traits of lung tissue patterns in former smokers derived by dual channel deep learning in computed tomography images.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes.

Association of Dysanapsis With Chronic Obstructive Pulmonary Disease Among Older Adults.

Importance: Smoking is a major risk factor for chronic obstructive pulmonary disease (COPD), yet much of COPD risk remains unexplained. Objective: To determine whether dysanapsis, a mismatch of airway tree caliber to lung size, assessed by computed tomography (CT), is associated with incident COPD among older adults and lung function decline in COPD. Design, Setting, and Participants: A retrospective cohort study of 2 community-based samples: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study, which involved 2531 participants (6 US sites, 2010-2018) and the Canadian Cohort of Obstructive Lung Disease (CanCOLD), which involved 1272 participants (9 Canadian sites, 2010-2018), and a case-control study of COPD: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), which involved 2726 participants (12 US sites, 2011-2016). Exposures: Dysanapsis was quantified on CT as the geometric mean of airway lumen diameters measured at 19 standard anatomic locations divided by the cube root of lung volume (airway to lung ratio). Main Outcomes and Measures: Primary outcome was COPD defined by postbronchodilator ratio of forced expired volume in the first second to vital capacity (FEV1:FVC) less than 0.70 with respiratory symptoms. Secondary outcome was longitudinal lung function. All analyses were adjusted for demographics and standard COPD risk factors (primary and secondhand tobacco smoke exposures, occupational and environmental pollutants, and asthma). Results: In the MESA Lung sample (mean [SD] age, 69 years [9 years]; 1334 women [52.7%]), 237 of 2531 participants (9.4%) had prevalent COPD, the mean (SD) airway to lung ratio was 0.033 (0.004), and the mean (SD) FEV1 decline was -33 mL/y (31 mL/y). Of 2294 MESA Lung participants without prevalent COPD, 98 (4.3%) had incident COPD at a median of 6.2 years. Compared with participants in the highest quartile of airway to lung ratio, those in the lowest had a significantly higher COPD incidence (9.8 vs 1.2 cases per 1000 person-years; rate ratio [RR], 8.12; 95% CI, 3.81 to 17.27; rate difference, 8.6 cases per 1000 person-years; 95% CI, 7.1 to 9.2; P < .001) but no significant difference in FEV1 decline (-31 vs -33 mL/y; difference, 2 mL/y; 95% CI, -2 to 5; P = .30). Among CanCOLD participants (mean [SD] age, 67 years [10 years]; 564 women [44.3%]), 113 of 752 (15.0%) had incident COPD at a median of 3.1 years and the mean (SD) FEV1 decline was -36 mL/y (75 mL/y). The COPD incidence in the lowest airway to lung quartile was significantly higher than in the highest quartile (80.6 vs 24.2 cases per 1000 person-years; RR, 3.33; 95% CI, 1.89 to 5.85; rate difference, 56.4 cases per 1000 person-years; 95% CI, 38.0 to 66.8; P<.001), but the FEV1 decline did not differ significantly (-34 vs -36 mL/y; difference, 1 mL/y; 95% CI, -15 to 16; P=.97). Among 1206 SPIROMICS participants (mean [SD] age, 65 years [8 years]; 542 women [44.9%]) with COPD who were followed up for a median 2.1 years, those in the lowest airway to lung ratio quartile had a mean FEV1 decline of -37 mL/y (15 mL/y), which did not differ significantly from the decline in MESA Lung participants (P = .98), whereas those in highest quartile had significantly faster decline than participants in MESA Lung (-55 mL/y [16 mL/y ]; difference, -17 mL/y; 95% CI, -32 to -3; P = .004). Conclusions and Relevance: Among older adults, dysanapsis was significantly associated with COPD, with lower airway tree caliber relative to lung size associated with greater COPD risk. Dysanapsis appears to be a risk factor associated with COPD.

Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects.

BACKGROUND: Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs. This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure. METHODS: To reduce confounding factors, subjects with normal spirometry without fibrosis, asthma and pneumonia histories were only selected, and a propensity score matching was applied to match age, sex, height, smoking status, and pack-years. Thus, from a larger data set (N = 609), only 41 cement dust-exposed subjects were compared with 164 non-cement dust-exposed subjects. QCT imaging metrics of airway hydraulic diameter (Dh), wall thickness (WT), and bifurcation angle (θ) were extracted at total lung capacity (TLC) and functional residual capacity (FRC), along with their deformation ratios between TLC and FRC. RESULTS: In TLC scan, dust-exposed subjects showed a decrease of Dh (airway narrowing) especially at lower-lobes (p < 0.05), an increase of WT (wall thickening) at all segmental airways (p < 0.05), and an alteration of θ at most of the central airways (p < 0.001) compared with non-dust-exposed subjects. Furthermore, dust-exposed subjects had smaller deformation ratios of WT at the segmental airways (p < 0.05) and θ at the right main bronchi and left main bronchi (p < 0.01), indicating airway stiffness. CONCLUSIONS: Dust-exposed subjects with normal spirometry demonstrated airway narrowing at lower-lobes, wall thickening at all segmental airways, a different bifurcation angle at central airways, and a loss of airway wall elasticity at lower-lobes. The airway structural alterations may indicate different airway pathophysiology due to cement dusts.

Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS).

BACKGROUND: Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. METHODS: An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. RESULTS: We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. CONCLUSIONS: QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.

Imaging-based clusters in current smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS).

BACKGROUND: Classification of COPD is usually based on the severity of airflow, which may not sensitively differentiate subpopulations. Using a multiscale imaging-based cluster analysis (MICA), we aim to identify subpopulations for current smokers with COPD. METHODS: Among the SPIROMICS subjects, we analyzed computed tomography images at total lung capacity (TLC) and residual volume (RV) of 284 current smokers. Functional variables were derived from registration of TLC and RV images, e.g. functional small airways disease (fSAD%). Structural variables were assessed at TLC images, e.g. emphysema and airway wall thickness and diameter. We employed an unsupervised method for clustering. RESULTS: Four clusters were identified. Cluster 1 had relatively normal airway structures; Cluster 2 had an increase of fSAD% and wall thickness; Cluster 3 exhibited a further increase of fSAD% but a decrease of wall thickness and airway diameter; Cluster 4 had a significant increase of fSAD% and emphysema. Clinically, Cluster 1 showed normal FEV1/FVC and low exacerbations. Cluster 4 showed relatively low FEV1/FVC and high exacerbations. While Cluster 2 and Cluster 3 showed similar exacerbations, Cluster 2 had the highest BMI among all clusters. CONCLUSIONS: Association of imaging-based clusters with existing clinical metrics suggests the sensitivity of MICA in differentiating subpopulations.

Human airway branch variation and chronic obstructive pulmonary disease.

Susceptibility to chronic obstructive pulmonary disease (COPD) beyond cigarette smoking is incompletely understood, although several genetic variants associated with COPD are known to regulate airway branch development. We demonstrate that in vivo central airway branch variants are present in 26.5% of the general population, are unchanged over 10 y, and exhibit strong familial aggregation. The most common airway branch variant is associated with COPD in two cohorts (n = 5,054), with greater central airway bifurcation density, and with emphysema throughout the lung. The second most common airway branch variant is associated with COPD among smokers, with narrower airway lumens in all lobes, and with genetic polymorphisms within the FGF10 gene. We conclude that central airway branch variation, readily detected by computed tomography, is a biomarker of widely altered lung structure with a genetic basis and represents a COPD susceptibility factor.

An integrated mathematical epithelial cell model for airway surface liquid regulation by mechanical forces.

A robust method based on reverse engineering was utilized to construct the ion-channel conductance functions for airway epithelial sodium channels (ENaC), the cystic fibrosis transmembrane conductance regulator (CFTR), and calcium-activated chloride channels (CaCC). The ion-channel conductance models for both normal (NL) and cystic fibrosis (CF) airway epithelia were developed and then coupled to an adenosine triphosphate (ATP) metabolism model and a fluid transport model (collectively called the integrated cell model) to investigate airway surface liquid (ASL) volume regulation and hence mucus concentration, by mechanical forces in NL and CF human airways. The epithelial cell models for NL and CF required differences in Cl- secretion (decreased in CF) and Na+ absorption (raised in CF) to reproduce behaviors similar to in vitro epithelial cells exposed to mechanical forces (cyclic shear stress, cyclic compressive pressure and cilial strain) and selected modulators of ion channels and ATP release. The epithelial cell models were then used to investigate the effects of mechanical forces and evaporative flux on ASL and mucus homeostasis in both NL and CF airway epithelia. Because of reduced CF ASL volumes, CF mucus concentrations increased and produced a greater dependence of ASL volume regulation on cilia-mucus-ATP release interactions in CF than NL epithelial nodules. Similarly, the CF model was less tolerant to evaporation induced ASL volume reduction at all ATP release rates than the NL model. Consequently, this reverse engineered model appears to provide a robust tool for investigating CF pathophysiology and novel therapies.

Quantitative computed tomography determined regional lung mechanics in normal nonsmokers, normal smokers and metastatic sarcoma subjects.

OBJECTIVES: Extra-thoracic tumors send out pilot cells that attach to the pulmonary endothelium. We hypothesized that this could alter regional lung mechanics (tissue stiffening or accumulation of fluid and inflammatory cells) through interactions with host cells. We explored this with serial inspiratory computed tomography (CT) and image matching to assess regional changes in lung expansion. MATERIALS AND METHODS: We retrospectively assessed 44 pairs of two serial CT scans on 21 sarcoma patients: 12 without lung metastases and 9 with lung metastases. For each subject, two or more serial inspiratory clinically-derived CT scans were retrospectively collected. Two research-derived control groups were included: 7 normal nonsmokers and 12 asymptomatic smokers with two inspiratory scans taken the same day or one year apart respectively. We performed image registration for local-to-local matching scans to baseline, and derived local expansion and density changes at an acinar scale. Welch two sample t test was used for comparison between groups. Statistical significance was determined with a p value < 0.05. RESULTS: Lung regions of metastatic sarcoma patients (but not the normal control group) demonstrated an increased proportion of normalized lung expansion between the first and second CT. These hyper-expanded regions were associated with, but not limited to, visible metastatic lung lesions. Compared with the normal control group, the percent of increased normalized hyper-expanded lung in sarcoma subjects was significantly increased (p < 0.05). There was also evidence of increased lung "tissue" volume (non-air components) in the hyper-expanded regions of the cancer subjects relative to non-hyper-expanded regions. "Tissue" volume increase was present in the hyper-expanded regions of metastatic and non-metastatic sarcoma subjects. This putatively could represent regional inflammation related to the presence of tumor pilot cell-host related interactions. CONCLUSIONS: This new quantitative CT (QCT) method for linking serial acquired inspiratory CT images may provide a diagnostic and prognostic means to objectively characterize regional responses in the lung following oncological treatment and monitoring for lung metastases.

Improved CT-based estimate of pulmonary gas trapping accounting for scanner and lung-volume variations in a multicenter asthmatic study.

Lung air trapping is estimated via quantitative computed tomography (CT) using density threshold-based measures on an expiration scan. However, the effects of scanner differences and imaging protocol adherence on quantitative assessment are known to be problematic. This study investigates the effects of protocol differences, such as using different CT scanners and breath-hold coaches in a multicenter asthmatic study, and proposes new methods that can adjust intersite and intersubject variations. CT images of 50 healthy subjects and 42 nonsevere and 52 severe asthmatics at total lung capacity (TLC) and functional residual capacity (FRC) were acquired using three different scanners and two different coaching methods at three institutions. A fraction threshold-based approach based on the corrected Hounsfield unit of air with tracheal density was applied to quantify air trapping at FRC. The new air-trapping method was enhanced by adding a lung-shaped metric at TLC and the lobar ratio of air-volume change between TLC and FRC. The fraction-based air-trapping method is able to collapse air-trapping data of respective populations into distinct regression lines. Relative to a constant value-based clustering scheme, the slope-based clustering scheme shows the improved performance and reduced misclassification rate of healthy subjects. Furthermore, both lung shape and air-volume change are found to be discriminant variables for differentiating among three populations of healthy subjects and nonsevere and severe asthmatics. In conjunction with the lung shape and air-volume change, the fraction-based measure of air trapping enables differentiation of severe asthmatics from nonsevere asthmatics and nonsevere asthmatics from healthy subjects, critical for the development and evaluation of new therapeutic interventions.

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

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

Multiscale image-based modeling and simulation of gas flow and particle transport in the human lungs.

Improved understanding of structure and function relationships in the human lungs in individuals and subpopulations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment, and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways-from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model-will be reviewed. The interaction of CFD models with local parenchymal tissue expansion-assessed by image registration-allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model 'entrance' to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed.

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

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

Airway gas flow.

Local characteristics of airflow and its global distribution in the lung are determined by interaction between resistance to flow through the airways and the compliance of the tissue, with tissue compliance dominating flow distribution in the healthy lung. Current understanding is that conceptualizing the airways of the lung as a system of smooth adjoined cylinders through which air traverses laminarly is insufficient for understanding flow and energy dissipation and is particularly poor for predicting physiologically realistic transport of particles by the airflow. With rapid advances in medical imaging, computer technologies, and computational techniques, computational fluid dynamics is now becoming a viable tool for providing detailed information on the mechanics of airflow in the human respiratory tract. Studies using such techniques have shown that the upper airway (specifically its development of a turbulent laryngeal jet in the trachea), airway geometry, branching and rotation angle, and the pattern of joining of successive bifurcations are important in determining airflow structures. It is now possible to compute airflow in physical domains that are anatomically accurate and subject specific, enabling comparisons among intersubjects, that among subjects of different ages, and that among different species.

Airway wall stiffening increases peak wall shear stress: a fluid-structure interaction study in rigid and compliant airways.

The airflow characteristics in a computed tomography (CT) based human airway bifurcation model with rigid and compliant walls are investigated numerically. An in-house three-dimensional (3D) fluid-structure interaction (FSI) method is applied to simulate the flow at different Reynolds numbers and airway wall stiffness. As the Reynolds number increases, the airway wall deformation increases and the secondary flow becomes more prominent. It is found that the peak wall shear stress on the rigid airway wall can be five times stronger than that on the compliant airway wall. When adding tethering forces to the model, we find that these forces, which produce larger airway deformation than without tethering, lead to more skewed velocity profiles in the lower branches and further reduced wall shear stresses via a larger airway lumen. This implies that pathologic changes in the lung such as fibrosis or remodeling of the airway wall-both of which can serve to restrain airway wall motion-have the potential to increase wall shear stress and thus can form a positive feed-back loop for the development of altered flow profiles and airway remodeling. These observations are particularly interesting as we try to understand flow and structural changes seen in, for instance, asthma, emphysema, cystic fibrosis, and interstitial lung disease.

Rarefaction and compressibility effects of the lattice-Boltzmann-equation method in a gas microchannel.

A wall equilibrium boundary condition for an implicit lattice-Boltzmann-equation method is proposed to simulate gas flows in a microchannel with rough surface on the characteristic length of gas molecules. The boundary condition is based on the assumption that impinging molecules reach equilibrium with the surface. The molecular mean free path used to define the Knudsen number is determined by the lattice speed and the relaxation time of the lattice-Boltzmann equation. With the wall equilibrium boundary condition and the appropriate relation defined for the Knudsen number and the relaxation time, the computed slip velocity and nonlinear pressure distribution along the microchannel are in excellent agreement with analytical solutions.