Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface

Human-airway surface mesh smoothing based on graph convolutional neural networks

BACKGROUND AND OBJECTIVE

A detailed representation of the airway geometry in the respiratory system is critical for predicting precise airflow and pressure behaviors in computed tomography (CT)-image-based computational fluid dynamics (CFD). The CT-image-based geometry often contains artifacts, noise, and discontinuities due to the so-called stair step effect. Hence, an advanced surface smoothing is necessary. The existing smoothing methods based on the Laplacian operator drastically shrink airway geometries, resulting in the loss of information related to smaller branches. This study aims to introduce an unsupervised airway-mesh-smoothing learning (AMSL) method that preserves the original geometry of the three-dimensional (3D) airway for accurate CT-image-based CFD simulations.

METHOD

The AMSL method jointly trains two graph convolutional neural networks (GCNNs) defined on airway meshes to filter vertex positions and face normal vectors. In addition, it regularizes a combination of loss functions such as reproducibility, smoothness and consistency of vertex positions, and normal vectors. The AMSL adopts the concept of a deep mesh prior model, and it determines the self-similarity for mesh restoration without using a large dataset for training. Images of the airways of 20 subjects were smoothed by the AMSL method, and among them, the data of two subjects were used for the CFD simulations to assess the effect of airway smoothing on flow properties.

RESULTS

In 18 of 20 benchmark problems, the proposed smoothing method delivered better results compared with the conventional or state-of-the-art deep learning methods. Unlike the traditional smoothing, the AMSL successfully constructed 20 smoothed airways with airway diameters that were consistent with the original CT images. Besides, CFD simulations with the airways obtained by the AMSL method showed much smaller pressure drop and wall shear stress than the results obtained by the traditional method.

CONCLUSIONS

The airway model constructed by the AMSL method reproduces branch diameters accurately without any shrinkage, especially in the case of smaller airways. The accurate estimation of airway geometry using a smoothing method is critical for estimating flow properties in CFD simulations.

Morphometric analysis of airways in pre-COPD and mild COPD lungs using continuous surface representations of the bronchial lumen

Introduction: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory disease that presents a high rate of underdiagnosis during onset and early stages. Studies have shown that in mild COPD patients, remodeling of the small airways occurs concurrently with morphological changes in the proximal airways. Despite this evidence, the geometrical study of the airway tree from computed tomography (CT) lung images remains underexplored due to poor representations and limited tools to characterize the airway structure. Methods: We perform a comprehensive morphometric study of the proximal airways based on geometrical measures associated with the different airway generations. To this end, we leverage the geometric flexibility of the Snakes IsoGeometric Analysis method to accurately represent and characterize the airway luminal surface and volume informed by CT images of the respiratory tree. Based on this framework, we study the airway geometry of smoking pre-COPD and mild COPD individuals. Results: Our results show a significant difference between groups in airway volume, length, luminal eccentricity, minimum radius, and surface-area-to-volume ratio in the most distal airways. Discussion: Our findings suggest a higher degree of airway narrowing and collapse in COPD patients when compared to pre-COPD patients. We envision that our work has the potential to deliver a comprehensive tool for assessing morphological changes in airway geometry that take place in the early stages of COPD.

Transport and deposition of beclomethasone dipropionate drug aerosols with varying ethanol concentration in severe asthmatic subjects

This study aims to assess the effects of varying an ethanol co-solvent on the deposition of drug particles in severe asthmatic subjects with distinct airway structures and lung functions using computational fluid dynamics. The subjects were selected from two quantitative computed tomography imaging-based severe asthmatic clusters, differentiated by airway constriction in the left lower lobe. Drug aerosols were assumed to be generated from a pressurized metered-dose inhaler (MDI). The aerosolized droplet sizes were varied by increasing the ethanol co-solvent concentration in the MDI solution. The MDI formulation consists of 1,1,2,2-tetrafluoroethane (HFA-134a), ethanol, and beclomethasone dipropionate (BDP) as the active pharmaceutical ingredient. Since HFA-134a and ethanol are volatile, both substances evaporate rapidly under ambient conditions and trigger condensation of water vapor, increasing the size of aerosols that are predominantly composed of water and BDP. The average deposition fraction in intra-thoracic airways for severe asthmatic subjects with (or without) airway constriction increased from 37%±12 to 53.2%±9.4 (or from 20.7%± 4.6 to 34.7%±6.6) when the ethanol concentration was increased from 1 to 10%wt/wt. However, when the ethanol concentration was further increased from 10 to 20%wt/wt, the deposition fraction decreased. This indicates the importance of selecting appropriate co-solvent amounts during drug formulation development for the treatment of patients with narrowed airway disease. For severe asthmatic subjects with airway narrowing, the inhaled aerosol may benefit from a low hygroscopic effect by reducing ethanol concentration to penetrate the peripheral region effectively. These results could potentially inform the selection of co-solvent amounts for inhalation therapies in a cluster-specific manner.

A computed tomography imaging-based subject-specific whole-lung deposition model

The respiratory tract is an important route for beneficial drug aerosol or harmful particulate matter to enter the body. To assess the therapeutic response or disease risk, whole-lung deposition models have been developed, but were limited by compartment, symmetry or stochastic approaches. In this work, we proposed an imaging-based subject-specific whole-lung deposition model. The geometries of airways and lobes were segmented from computed tomography (CT) lung images at total lung capacity (TLC), and the regional air-volume changes were calculated by registering CT images at TLC and functional residual capacity (FRC). The geometries were used to create the structure of entire subject-specific conducting airways and acinar units. The air-volume changes were used to estimate the function of subject-specific ventilation distributions among acinar units and regulate flow rates in respiratory airway models. With the airway dimensions rescaled to a desired lung volume and the airflow field simulated by a computational fluid dynamics model, particle deposition fractions were calculated using deposition probability formulae adjusted with an enhancement factor to account for the effects of secondary flow and airway geometry in proximal airways. The proposed model was validated in silico against existing whole-lung deposition models, three-dimensional (3D) computational fluid and particle dynamics (CFPD) for an acinar unit, and 3D CFPD deep lung model comprising conducting and respiratory regions. The model was further validated in vivo against the lobar particle distribution and the coefficient of variation of particle distribution obtained from CT and single-photon emission computed tomography (SPECT) images, showing good agreement. Subject-specific airway structure increased the deposition fraction of 10.0-μm particles and 0.01-μm particles by approximately 10%. An enhancement factor increased the overall deposition fractions, especially for particle sizes between 0.1 and 1.0 μm.

Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics

PURPOSE

Computational fluid dynamics (CFD) of lung airflow during normal and pathophysiological breathing provides insight into regional pulmonary ventilation. By integrating CFD methods with 4D lung imaging workflows, regions of normal pulmonary function can be spared during treatment planning. To facilitate the use of CFD simulations in a clinical setup, a robust, automated, and CFD-compliant airway mesh generation technique is necessary.

METHODS

We define a CFD-compliant airway mesh to be devoid of blockages of airflow and leaks in the airway path, both of which are caused by airway meshing errors that occur when using conventional meshing techniques. We present an algorithm to create a CFD-compliant airway mesh in an automated manner. Beginning with a medial skeleton of the airway segmentation, the branches were tracked, and 3D points at which bifurcations occur were identified. Airway branches and bifurcation features were isolated to allow for automated and careful meshing that considered their anatomical nature.

RESULTS

We present the meshing results from three state-of-the-art tools and compare them with the meshes generated by our algorithm. The results show that fully CFD-compliant meshes were automatically generated for an ideal geometry and patient-specific CT scans. Using an open-source smoothed-particle hydrodynamics CFD implementation, we compared the airflow using our approach and conventionally generated airway meshes.

CONCLUSION

Our meshing algorithm was able to successfully generate a CFD-compliant mesh from pre-segmented lung CT scans, providing an automatic meshing approach that enables interventional CFD simulations to guide lung procedures such as radiotherapy or lung volume reduction surgery.

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.

Transport and deposition of hygroscopic particles in asthmatic subjects with and without airway narrowing

This study numerically investigates the effect of hygroscopicity on transport and deposition of particles in severe asthmatic lungs with distinct airway structures. The study human subjects were selected from two imaging-based severe asthmatic clusters with one characterized by non-constricted airways and the other by constricted airways in the lower left lobe (LLL). We compared the deposition fractions of sodium chloride (NaCl) particles with a range of aerodynamic diameters (1-8 μm) in cluster archetypes under conditions with and without hygroscopic growth. The temperature and water vapor distributions in the airways were simulated with an airway wall boundary condition that accounts for variable temperature and water vapor evaporation at the interface between the lumen and the airway surface liquid layer. On average, the deposition fraction increased by about 6% due to hygroscopic particle growth in the cluster subjects with constricted airways, while it increased by only about 0.5% in those with non-constricted airways. The effect of particle growth was most significant for particles with an initial diameter of 2 μm in the cluster subjects with constricted airways. The effect diminished with increasing particle size, especially for particles with an initial diameter larger than 4 μm. This suggests the necessity to differentiate asthmatic subjects by cluster in engineering the aerosol size for tailored treatment. Specifically, the treatment of severe asthmatic subjects who have constricted airways with inhalation aerosols may need submicron-sized hygroscopic particles to compensate for particle growth, if one targets for delivering to the peripheral region. These results could potentially inform the choice of particle size for inhalational drug delivery in a cluster-specific manner.

Structural and hemodynamic properties of murine pulmonary arterial networks under hypoxia-induced pulmonary hypertension

Detection and monitoring of patients with pulmonary hypertension, defined as a mean blood pressure in the main pulmonary artery above 25 mmHg, requires a combination of imaging and hemodynamic measurements. This study demonstrates how to combine imaging data from microcomputed tomography images with hemodynamic pressure and flow waveforms from control and hypertensive mice. Specific attention is devoted to developing a tool that processes computed tomography images, generating subject-specific arterial networks in which one-dimensional fluid dynamics modeling is used to predict blood pressure and flow. Each arterial network is modeled as a directed graph representing vessels along the principal pathway to ensure perfusion of all lobes. The one-dimensional model couples these networks with structured tree boundary conditions representing the small arteries and arterioles. Fluid dynamics equations are solved in this network and compared to measurements of pressure in the main pulmonary artery. Analysis of microcomputed tomography images reveals that the branching ratio is the same in the control and hypertensive animals, but that the vessel length-to-radius ratio is significantly lower in the hypertensive animals. Fluid dynamics predictions show that in addition to changed network geometry, vessel stiffness is higher in the hypertensive animal models than in the control models.

Simulation of bronchial airway acoustics in healthy and asthmatic subjects

The onset and development of many airway pathologies affect sound propagation throughout the respiratory system; changes in respiratory sounds are detected primarily by auscultation, which is highly skill dependent. The aim of the present study was to compare healthy and asthmatic pulmonary acoustics by applying a 1D model of wave propagation on CT-based patient-specific geometries. High-resolution CT lung images were acquired in five healthy volunteers and five asthmatic patients at total lung capacity (TLC) and functional residual capacity (FRC). Tracheobronchial trees were reconstructed from CT images. Acoustic pressure, impedance and wall radial velocity were measured by simulating acoustic wave propagation of two external, acoustic pressure waves (1 Pa, 200 and 600 Hz) from the trachea level to the 4th generation. In asthmatic patients, acoustic pressure averaged across the last three generations showed a reduction equal to 29.7% (p<0.01) at FRC, at 200 Hz; input and terminal impedance were 34.5% (p<0.05) higher both at FRC and TLC; wall radial velocity was more than 80% (p<0.05) lower in higher generations both at FRC and TLC. Airway differences in asthma alter acoustic parameters at FRC and TLC, with the greatest difference at FRC and 200 Hz. Acoustic wave propagation analysis represents a quantitative approach that has potential to objectively characterize airway differences in individuals with diseases such as asthma.

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.

Differences in Particle Deposition Between Members of Imaging-Based Asthma Clusters

Background: Four computed tomography (CT) imaging-based clusters have been identified in a study of the Severe Asthma Research Program (SARP) cohort and have been significantly correlated with clinical and demographic metrics (J Allergy Clin Immunol 2017; 140:690-700.e8). We used a computational fluid dynamics (CFD) model to investigate air flow and aerosol deposition within imaging archetypes representative of the four clusters. Methods: CFD simulations for air flow and 1-8 μm particle transport were performed using CT-based airway models from two healthy subjects and eight asthma subjects. The subject selection criterion was based on the discriminant imaging-based flow-related variables of J(Total) (average local volume expansion in the total lung) and Dh*(sLLL) (normalized airway hydraulic diameter in the left lower lobe), where reduced J(Total) and Dh*(sLLL) indicate reduced regional ventilation and airway constriction, respectively. The analysis focused on the comparisons between all clusters with respect to healthy subjects, between cluster 2 and cluster 4 (nonsevere and severe asthma clusters with airway constriction) and between cluster 3 and cluster 4 (two severe asthma clusters characterized by normal and constricted airways, respectively). Results: Nonsevere asthma cluster 2 and severe asthma cluster 4 subjects characterized by airway constriction had an increase in the deposition fraction (DF) in the left lower lobe. Constricted flows impinged on distal bifurcations resulting in large depositions. Although both cluster 3 (without constriction) and cluster 4 (with constriction) were severe asthma, they exhibited different particle deposition patterns with increasing particle size. The statistical analysis showed that Dh*(sLLL) plays a more important role in particle deposition than J(Total), and regional flow fraction is correlated with DF among lobes for smaller particles. Conclusions: We demonstrated particle deposition characteristics associated with cluster-specific imaging-based metrics such as airway constriction, which could pertain to the design of future drug delivery improvements.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

Aerosol deposition predictions in computed tomography-derived skeletons from severe asthmatics: A feasibility study

BACKGROUND

The authors numerically investigated the correlation between airway skeletons of severe asthmatic human subjects and predicted aerosol deposition to shed light on the effect of environmental factors on asthma risk. We hypothesized that there are asthmatic subjects whose airway skeletal structure can expose the subject to a risk of higher local aerosol deposition compared to subjects with a more common/normal branching pattern.

METHODS

From a population of severe asthmatics studied at total lung capacity via computed tomography we randomly selected 8 subjects whose Forced Expiratory Volume in 1s, percent predicted fell below 45% predicted. To simulate aerosol motion in the human lungs, we employed in-house three-dimensional eddy-resolving computational fluid dynamics and particle tracking models utilizing 3 of the 8 severe asthmatic subjects. One of the 3 subjects was found to have a distinct, localized airway narrowing chosen for further investigation. In the simulation, we controlled flow rate and luminal area, i.e., Reynolds and Stokes numbers, in each branch of the computed tomography-derived airway skeletons.

FINDINGS

We found a distinct enhancement of aerosol deposition associated with the narrowed branches of one subject even when the luminal area was numerically adjusted from its narrowed state to that of a non-asthmatic subject. The branching angle, freed of luminal narrowing persisted in demonstrating a marginally significant increase in local particle deposition compared with the subjects without the initial constriction.

INTERPRETATION

These results demonstrate the possibility that inherent airway structure may influence localized constriction found in severe asthmatics.

Effects of homogeneous and heterogeneous changes in the lung periphery on spirometry results

BACKGROUND AND OBJECTIVES

The most widespread chronic pulmonary disorders are associated with heterogeneous changes in the lung periphery and spirometry is the most commonly used test to monitor these diseases. So far only a few attempts have been undertaken to investigate the effects of lung inhomogeneity on spirometry results. The aim of this work was to evaluate whether the spirometric curve and indexes are sensitive to parallel peripheral inhomogeneities, and if the level of heterogeneity can be deduced from this test.

METHODS

To this end, an enhanced computational model for forced expiration, taking into account a heterogeneous structure and properties of the respiratory system, was used. Two main phenomena were mimicked: small airways narrowing and the loss of tissue elastic recoil. Numerical simulations were performed with the model having 76 separate peripheral compartments. For a given degree of mean change, three heterogeneity levels were investigated and compared to the effects of homogeneous alterations.

RESULTS

All spirometric curves representing different patterns of inhomogeneous constriction, computed for each of the investigated cases, almost coincided with the curve originating from homogeneous changes, regardless of the heterogeneity level. Also the differences between the spirometric indexes obtained for heterogeneous and homogeneous alterations were negligible in comparison to their values.

CONCLUSION

The main finding is that the spirometry results are insensitive to the level of heterogeneity in the lung periphery and that it is practically impossible to distinguish between the homogeneous or heterogeneous nature of pathological processes occurring in this lung region.

Iterative multi-path tracking for video and volume segmentation with sparse point supervision

Recent machine learning strategies for segmentation tasks have shown great ability when trained on large pixel-wise annotated image datasets. It remains a major challenge however to aggregate such datasets, as the time and monetary cost associated with collecting extensive annotations is extremely high. This is particularly the case for generating precise pixel-wise annotations in video and volumetric image data. To this end, this work presents a novel framework to produce pixel-wise segmentations using minimal supervision. Our method relies on 2D point supervision, whereby a single 2D location within an object of interest is provided on each image of the data. Our method then estimates the object appearance in a semi-supervised fashion by learning object-image-specific features and by using these in a semi-supervised learning framework. Our object model is then used in a graph-based optimization problem that takes into account all provided locations and the image data in order to infer the complete pixel-wise segmentation. In practice, we solve this optimally as a tracking problem using a K-shortest path approach. Both the object model and segmentation are then refined iteratively to further improve the final segmentation. We show that by collecting 2D locations using a gaze tracker, our approach can provide state-of-the-art segmentations on a range of objects and image modalities (video and 3D volumes), and that these can then be used to train supervised machine learning classifiers.

A Feasible Computational Fluid Dynamics Study for Relationships of Structural and Functional Alterations with Particle Depositions in Severe Asthmatic Lungs

This study aims to investigate the effect of altered structures and functions in severe asthma on particle deposition by using computational fluid dynamics (CFD) models. Airway geometrical models of two healthy subjects and two severe asthmatics were reconstructed from computed tomography (CT) images. Subject-specific flow boundary conditions were obtained by image registration to account for regional functional alterations of severe asthmatics. A large eddy simulation (LES) model for transitional and turbulent flows was applied to simulate airflows, and particle transport simulations were then performed for 2.5, 5, and 10 μm particles using CFD-predicted flow fields. Compared to the healthy subjects, the severe asthmatics had a smaller air-volume change in the lower lobes and a larger air-volume change in the upper lobes. Both severe asthmatics had smaller airway circularity (Cr), but one of them had a significant reduction of hydraulic diameter (D_h). In severe asthmatics, the larger air-volume change in the upper lobes resulted in more particles in the upper lobes, especially for the small 2.5 μm particles. The structural alterations measured by Cr and D_h were associated with a higher particle deposition. D_h was found to be the most important metric which affects the specific location of particle deposition. This study demonstrates the relationship of CT-based structural and functional alterations in severe asthma with flow and particle dynamics.

Localization of adventitious respiratory sounds

In a recent publication by Henry and Royston [J. Acoust. Soc. Am. 142, 1774-1783 (2017)], an algorithm was introduced to calculate the acoustic response to externally introduced and endogenous respiratory sounds within a realistic, patient-specific subglottal airway tree. This work is extended using an efficient numerical boundary element (BE) approach to calculate the resulting radiated sound field from the airway tree into the lung parenchyma taking into account the surrounding chest wall. Within the BE model of the left lung parenchyma, comprised of more than 6000 triangular surface elements, more than 30 000 monopoles are used to approximate complex airway-originated acoustic sources. The chest wall is modeled as a boundary condition on the parenchymal surface. Several cases were simulated, including a bronchoconstricted lung that had an internal acoustic source introduced in a bronchiole, approximating a wheeze. An acoustic source localization algorithm coupled to the BE model estimated the wheeze source location to within a few millimeters based solely on the acoustic field at the surface. Improved noninvasive means of locating adventitious respiratory sounds may enhance an understanding of acoustic changes correlated to pathology, and potentially provide improved noninvasive tools for the diagnosis of pulmonary diseases that uniquely alter acoustics.

Simulation of the human airways using virtual topology tools and meshing optimization

A method is proposed to improve the quality of the three-dimensional airway geometric models using a commercial software, checking the number of elements, meshing time, and aspect ratio and skewness parameters. The use of real and virtual topologies combined with patch-conforming and patch-independent meshing algorithms results in four different models being the best solution the combination of virtual topology and patch-independent algorithm, due to an excellent aspect ratio and skewness of the elements, and minimum meshing time. The result is a reduction in the computational time required for both meshing and simulation due to a smaller number of cells. The use of virtual topologies combined with patch-independent meshing algorithms could be extended in bioengineering because the geometries handling is similar to this case. The method is applied to a healthy person using their computed tomography images. The resulting numerical models are able to simulate correctly a forced spirometry.

A multiscale analytical model of bronchial airway acoustics

Sound transmission and resulting airway wall vibration in a complex multiscale viscoelastic model of the subglottal bronchial tree was calculated using a modified one-dimensional (1D) branching acoustic waveguide approach. This is an extension of previous work to enable use of complex airway trees that are partially derived from subject-specific medical images, without the need for self-similarity in the geometric structure. The approach was validated numerically for simplified airway geometries, as well as experimentally by comparison to previous studies. A comprehensive conducting airway tree with about 60 000 branches was then modified to create fibrotic, bronchoconstrictive, and pulmonary infiltrate conditions. The fibrotic case-systemic increase in soft tissue stiffness-increased the Helmholtz resonance frequency due to the increased acoustic impedance. Bronchoconstriction, with geometric changes in small conducting airways, decreased acoustic energy transmission to the peripheral airways due in part to the increased impedance mismatch between airway orders. Pulmonary infiltrate significantly altered the local acoustic field in the affected lobe. Calculation of acoustic differences between healthy versus pathologic cases can be used to enhance the understanding of vibro-acoustic changes correlated to pathology, and potentially provide improved tools for the diagnosis of pulmonary diseases that uniquely alter the acoustics of the airways.

Image-based computational fluid dynamics in the lung: virtual reality or new clinical practice?

The development and implementation of personalized medicine is paramount to improving the efficiency and efficacy of patient care. In the respiratory system, function is largely dictated by the choreographed movement of air and blood to the gas exchange surface. The passage of air begins in the upper airways, either via the mouth or nose, and terminates at the alveolar interface, while blood flows from the heart to the alveoli and back again. Computational fluid dynamics (CFD) is a well-established tool for predicting fluid flows and pressure distributions within complex systems. Traditionally CFD has been used to aid in the effective or improved design of a system or device; however, it has become increasingly exploited in biological and medical-based applications further broadening the scope of this computational technique. In this review, we discuss the advancement in application of CFD to the respiratory system and the contributions CFD is currently making toward improving precision medicine. The key areas CFD has been applied to in the pulmonary system are in predicting fluid transport and aerosol distribution within the airways. Here we focus our discussion on fluid flows and in particular on image-based clinically focused CFD in the ventilatory system. We discuss studies spanning from the paranasal sinuses through the conducting airways down to the level of the alveolar airways. The combination of imaging and CFD is enabling improved device design in aerosol transport, improved biomarkers of lung function in clinical trials, and improved predictions and assessment of surgical interventions in the nasal sinuses. WIREs Syst Biol Med 2017, 9:e1392. doi: 10.1002/wsbm.1392 For further resources related to this article, please visit the WIREs website.

Numerical simulations of aerosol delivery to the human lung with an idealized laryngeal model, image-based airway model, and automatic meshing algorithm

The authors proposed a new method to automatically mesh computed tomography (CT)-based three-dimensional human airway geometry for computational fluid dynamics (CFD)-based simulations of pulmonary gas-flow and aerosol delivery. Traditional methods to construct and mesh realistic geometry were time-consuming, because they were done manually using image-processing and mesh-generating programs. Furthermore, most of CT thoracic image data sets do not include the upper airway structures. To overcome these issues, the proposed method consists of CFD grid-size distribution, an automatic meshing algorithm, and the addition of a laryngeal model along with turbulent velocity inflow boundary condition attached to the proximal end of the trachea. The method is based on our previously developed geometric model with irregular centerlines and cross-sections fitted to CT segmented airway surfaces, dubbed the "fitted-surface model." The new method utilizes anatomical information obtained from the one-dimensional tree, e.g., skeleton connectivity and branch diameters, to efficiently generate optimal CFD mesh, automatically impose boundary conditions, and systematically reduce simulation results. The aerosol deposition predicted by the proposed method agreed well with the prediction by a traditional CT-based model, and the laryngeal model generated a realistic level of turbulence in the trachea. Furthermore, the computational time was reduced by factor of two without losing accuracy by using the proposed grid-size distribution. The new method is well suited for branch-by-branch analyses of gas-flow and aerosol distribution in multiple subjects due to embedded anatomical information.