A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

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.

A critical analysis of the CFD-DEM simulation of pharmaceutical aerosols deposition in upper intra-thoracic airways: Considerations on air flow

A well-corroborated numerical methodology ensuring reproducibility in the modeling of pharmaceutical aerosols deposition in the respiratory system via CFD-DEM simulations within the RANS framework is currently missing. Often, inadequately clarified assumptions and approximations and the lack of evidences on their quantitative impact on the simulated deposition phenomenology, make a direct comparison among the different theoretical studies and the limited number of experiments a very challenging task. Here, with the ultimate goal of providing a critical analysis of some crucial computational aspects of aerosols deposition, we address the issues of velocity fluctuations propagation in the upper intra-thoracic airways and of the persistence of secondary flows using the SimInhale reference benchmark. We complement the investigation by describing how methodologies used to drive the flow through a truncated lung model may affect numerical results and how small discrepancies are observed in velocity profiles when comparing simulations based on different meshing strategies.

Automated bidirectional coupling of multiscale models of aerosol dosimetry: validation with subject-specific deposition data

Assessing the toxicity of airborne particulate matter or the efficacy of inhaled drug depends upon accurate estimates of deposited fraction of inhaled materials. In silico approaches can provide important insights into site- or airway-specific deposition of inhaled aerosols in the respiratory system. In this study, we improved on our recently developed 3D/1D model that simulate aerosol transport and deposition in the whole lung over multiple breath cycles (J. Aerosol Sci 151:105647). A subject-specific multiscale lung model of a healthy male subject using computational fluid-particle dynamics (CFPD) in a 3D model of the oral cavity through the large bronchial airways entering each lobe was bidirectionally coupled with a recently improved Multiple Path Particle Dosimetry (MPPD) model to predict aerosol deposition over the entire respiratory tract over multiple breaths for four conditions matching experimental aerosol exposures in the same subject from which the model was developed. These include two particle sizes (1 and 2.9 μm) and two subject-specific breathing rates of ~300 ml/s (slow breathing) and ~750 ml/s (fast breathing) at a target tidal volume of 1 L. In silico predictions of retained fraction were 0.31 and 0.29 for 1 μm and 0.66 and 0.62 for 2.9 μm during slow and fast breathing, respectively, and compared well with experimental data (1 μm: 0.31±0.01 (slow) and 0.27±0.01 (fast), 2.9 μm: 0.63±0.03 (slow) and 0.68±0.02 (fast)). These results provide a great deal of confidence in the validity and reliability of our approach.

CT-based lung motion differences in patients with usual interstitial pneumonia and nonspecific interstitial pneumonia

We applied quantitative CT image matching to assess the degree of motion in the idiopathic ILD such as usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). Twenty-one normal subjects and 42 idiopathic ILD (31 UIP and 11 NSIP) patients were retrospectively included. Inspiratory and expiratory CT images, reviewed by two experienced radiologists, were used to compute displacement vectors at local lung regions matched by image registration. Normalized three-dimensional and two-dimensional (dorsal-basal) displacements were computed at a sub-acinar scale. Displacements, volume changes, and tissue fractions in the whole lung and the lobes were compared between normal, UIP, and NSIP subjects. The dorsal-basal displacement in lower lobes was smaller in UIP patients than in NSIP or normal subjects (p = 0.03, p = 0.04). UIP and NSIP were not differentiated by volume changes in the whole lung or upper and lower lobes (p = 0.53, p = 0.12, p = 0.97), whereas the lower lobe air volume change was smaller in both UIP and NSIP than normal subjects (p = 0.02, p = 0.001). Regional expiratory tissue fractions and displacements showed positive correlations in normal and UIP subjects but not in NSIP subjects. In summary, lung motionography quantified by image registration-based lower lobe dorsal-basal displacement may be used to assess the degree of motion, reflecting limited motion due to fibrosis in the ILD such as UIP and NSIP.

Functional analysis of the airways after pulmonary lobectomy through computational fluid dynamics

Pulmonary lobectomy, which consists of the partial or complete resection of a lung lobe, is the gold standard intervention for lung cancer removal. The removal of functional tissue during the surgery and the re-adaptation of the remaining thoracic structures decrease the patient's post-operative pulmonary function. Residual functionality is evaluated through pulmonary function tests, which account for the number of resected segments without considering local structural alterations and provide an average at-the-mouth estimation. Computational Fluid Dynamics (CFD) has been demonstrated to provide patient-specific, quantitative, and local information about airways airflow dynamics. A CFD investigation was performed on image-based airway trees reconstructed before and after the surgery for twelve patients who underwent lobectomy at different lobes. The geometrical alterations and the variations in fluid dynamics parameters and in lobar ventilation between the pre and post-operative conditions were evaluated. The post-operative function was estimated and compared with current clinical algorithms and with actual clinical data. The post-operative configuration revealed a high intersubject variability: regardless of the lobectomy site, an increment of global velocity, wall pressure, and wall shear stress was observed. Local flow disturbances also emerged at, and downstream of, the resection site. The analysis of lobar ventilation showed severe variations in the volume flow rate distribution, highlighting the compensatory effects in the contralateral lung with an increment of inflow. The estimation of post-operative function through CFD was comparable with the current clinical algorithm and the actual spirometric measurements. The results confirmed that CFD could provide additional information to support the current clinical approaches both in the operability assessment and in the prescription of personalized respiratory rehabilitation.

Imaging in Asthma Management

Asthma is a heterogeneous disease characterized by chronic airway inflammation that affects more than 300 million people worldwide. Clinically, asthma has a widely variable presentation and is defined based on a history of respiratory symptoms alongside airflow limitation. Imaging is not needed to confirm a diagnosis of asthma, and thus the use of imaging in asthma has historically been limited to excluding alternative diagnoses. However, significant advances continue to be made in novel imaging methodologies, which have been increasingly used to better understand respiratory impairment in asthma. As a disease primarily impacting the airways, asthma is best understood by imaging methods with the ability to elucidate airway impairment. Techniques such as computed tomography, magnetic resonance imaging with gaseous contrast agents, and positron emission tomography enable assessment of the small airways. Others, such as optical coherence tomography and endobronchial ultrasound enable high-resolution imaging of the large airways accessible to bronchoscopy. These imaging techniques are providing new insights in the pathophysiology and treatments of asthma and are poised to impact the clinical management of asthma.

A computational model of upper airway respiratory function with muscular coupling

A two dimensional finite element model of upper airway respiratory function was developed emphasizing the effects of dilator muscular activation on the human retro-lingual airway. The model utilized an upright mid-sagittal computed tomography of the human head and neck to reconstruct relevant structures of the tongue, mandible, and the hyoid-related soft tissues, along with the retro-lingual airway. The reconstructed geometry was divided into fluid and solid domains and discretized into finite element (FE) meshes used for the computational model. Three cases were investigated: standing position; supine position; and supine position coupled with dilator muscle activation. Computations were performed for the inspiration stage of the breathing cycle, utilizing a fluid-structure interaction (FSI) method to couple structural deformation with airflow dynamics. The spatio-temporal deformation of the structures surrounding the airway wall were predicted to be in general agreement with known changes from upright to supine posture on luminal opening, as well as the distribution of airflow. The model effectively captured the effects of muscular stimulation on the upper airway anatomical changes, the flow characteristics relevant to airway reduction in the supine position and airway enlargement with muscle activation. The smallest airway opening in the retro-lingual section is predicted to occur at the epiglottic region in all the three cases considered, an unexpected vulnerable location of airway obstruction. The model also predicted that hyoid displacement would be associated with recovery from airway collapse. This information may be useful for building more complex models relevant to mechanisms and clinical interventions for obstructive sleep apnea.

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

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

Computational fluid dynamics of the airways after left-upper pulmonary lobectomy: A case study

Pulmonary lobectomy is the gold standard intervention for lung cancer removal and consists of the complete resection of the affected lung lobe, which, coupled with the re-adaptation of the remaining thoracic structures, decreases the postoperative pulmonary function of the patient. Current clinical practice, based on spirometry and cardiopulmonary exercise tests, does not consider local changes, providing an average at-the-mouth estimation of residual functionality. Computational Fluid Dynamics (CFD) has proved a valuable solution to obtain quantitative and local information about airways airflow dynamics. A CFD investigation was performed on the airway tree of a left-upper pulmonary lobectomy patient, to quantify the effects of the postoperative alterations. The patient-specific bronchial models were reconstructed from pre- and postoperative CT scans. A parametric laryngeal model was merged to the geometries to account for physiological-like inlet conditions. Numerical simulations were performed in Fluent. The postoperative configuration revealed fluid dynamic variations in terms of global velocity (+23%), wall pressure (+48%), and wall shear stress (+39%). Local flow disturbances emerged at the resection site: a high-velocity peak of 4.92 m/s was found at the left-lower lobe entrance, with a local increase of pressure at the suture zone (18 Pa). The magnitude of pressure and secondary flows increased in the trachea and flow dynamics variations were observed also in the contralateral lung, causing altered lobar ventilation. The results confirmed that CFD is a patient-specific approach for a quantitative evaluation of fluid dynamics parameters and local ventilation providing additional information with respect to current clinical approaches.

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.

A quasi-3D model of the whole lung: airway extension to the tracheobronchial limit using the constrained constructive optimization and alveolar modeling, using a sac-trumpet model

Existing computational models used for simulating the flow and species transport in the human airways are zero-dimensional (0D) compartmental, three-dimensional (3D) computational fluid dynamics (CFD), or the recently developed quasi-3D (Q3D) models. Unlike compartmental models, the full CFD and Q3D models are physiologically and anatomically consistent in the mouth and the upper airways, since the starting point of these models is the mouth-lung surface geometry, typically created from computed tomography (CT) scans. However, the current resolution of CT scans limits the airway detection between the 3rd-4th and 7th-9th generations. Consequently, CFD and the Q3D models developed using these scans are generally limited to these generations. In this study, we developed a method to extend the conducting airways from the end of the truncated Q3D lung to the tracheobronchial (TB) limit. We grew the lung generations within the closed lung lobes using the modified constrained constructive optimization, creating an aerodynamically optimized network aiming to produce equal pressure at the distal ends of the terminal segments. This resulted in a TB volume and lateral area of ∼165 cc and ∼2000 cm², respectively. We created a "sac-trumpet" model at each of the TB outlets to represent the alveoli. The volumes of the airways and the individual alveolar generations match the anatomical values by design: with the functional residual capacity at 2611 cc. Lateral surface areas were scaled to match the physiological values. These generated Q3D whole lung models can be efficiently used for conducting multiple breathing cycles of drug transport and deposition simulations.

Efficient bi-directional coupling of 3D Computational Fluid-Particle Dynamics and 1D Multiple Path Particle Dosimetry lung models for multiscale modeling of aerosol dosimetry

The development of predictive aerosol dosimetry models has been a major focus of environmental toxicology and pharmaceutical health research for decades. One-dimensional (1D) models successfully predict overall deposition averages but fail to accurately predict local deposition. Computational fluid-particle dynamics (CFPD) models provide site-specific predictions but at a computational cost that prohibits whole lung predictions. Thus, there is a need for developing multiscale strategies to provide a realistic subject-specific picture of the fate of inhaled aerosol in the lungs. CT-based 3D/CFPD models of the large airways were bidirectionally coupled with individualized 1D Navier-Stokes airflow and particle transport based upon the widely used Multiple Path Particle Dosimetry Model (MPPD). Distribution of airflows among lobes was adjusted by measured lobar volume changes observed in CT images between FRC and FRC + 1.5 L. As a test of the effectiveness of the coupling procedures, deposition modeling of previous 1 μm aerosol exposure studies was performed. The complete coupled model was run for 3 breaths, with the computation-intense portion being the 3D CFPD Lagrangian particle tracking calculation. The average deposition per breath was 11% in the combined multiscale model with site-specific doses available in the CFPD portion of the model and airway- or region-specific deposition available for the MPPD portion. In conclusion, the key methods developed in this study enable predictions of ventilation heterogeneities and aerosol deposition across the lungs that are not captured by 3D or 1D models alone. These methods can be used as the foundation for multi-scale modeling of the full respiratory system.

Relative Regional Air Volume Change Maps at the Acinar Scale Reflect Variable Ventilation in Low Lung Attenuation of COPD patients

OBJECTIVES

The purpose of this study was to investigate regional air volume changes at the acinar scale of the lung in chronic obstructive pulmonary disease (COPD) patients using an image registration technique.

MATERIALS AND METHODS

Thirty-four emphysema patients and 24 subjects with normal chest CT and pulmonary function test (PFT) results were included in this retrospective study for which informed consent was waived by the institutional review board. After lung segmentation, a mass-preserving image registration technique was used to compute relative regional air volume changes (RRAVCs) between inspiration and expiration CT scans. After determining the appropriate thresholds of RRAVCs for low ventilation areas (LVAs), they were displayed and analyzed using color maps on the background inspiration CT image, and compared with the low attenuation area (LAA) map. Correlations between quantitative CT parameters and PFTs were assessed using Pearson's correlation test, and parameters were compared between emphysema and normal-CT patients using the Student's t-test.

RESULTS

LVA percentage with an RRAVC threshold of 0.5 (%LVA_0.5) showed the strongest correlations with FEV₁/FVC (r = -0.566), FEV₁ (r = -0.534), %LAA_-950insp (r = 0.712), and %LAA_-856exp (r = 0.775). %LVA_0.5 was significantly higher (P < 0.001) in COPD patients than normal subjects. Despite the identical appearance of emphysematous lesions on the LAA_-950insp map, the RRAVC map depicted a wide range of ventilation differences between these LAA clusters.

CONCLUSION

RRAVC-based %LVA_0.5 correlated well with FEV₁/FVC, FEV₁, %LAA_-950insp and %LAA_-856exp. RRAVC holds the potential for providing additional acinar scale functional information for emphysematous LAAs in inspiratory CT images, providing the basis for a novel set for emphysematous phenotypes.

Can indoor sports centers be allowed to re-open during the COVID-19 pandemic based on a certificate of equivalence?

Within a time span of only a few months, the SARS-CoV-2 virus has managed to spread across the world. This virus can spread by close contact, which includes large droplet spray and inhalation of microscopic droplets, and by indirect contact via contaminated objects. While in most countries, supermarkets have remained open, due to the COVID-19 pandemic, authorities have ordered many other shops, restaurants, bars, music theaters and indoor sports centers to be closed. As part of COVID-19 (semi)lock-down exit strategies, many government authorities are now (May-June 2020) allowing a gradual re-opening, where sometimes indoor sport centers are last in line to be permitted to re-open. This technical note discusses the challenges in safely re-opening these facilities and the measures already suggested by others to partly tackle these challenges. It also elaborates three potential additional measures and based on these additional measures, it suggests the concept of a certificate of equivalence that could allow indoor sports centers with such a certificate to re-open safely and more rapidly. It also attempts to stimulate increased preparedness of indoor sports centers that should allow them to remain open safely during potential next waves of SARS-CoV-2 as well as future pandemics. It is concluded that fighting situations such as the COVID-19 pandemic and limiting economic damage requires increased collaboration and research by virologists, epidemiologists, microbiologists, aerosol scientists, building physicists, building services engineers and sports scientists.

Numerical Simulation of Tidal Breathing Through the Human Respiratory Tract

The objective of this study is to explore the complexity of airflow through the human respiratory tract by carrying out computational fluid dynamics simulation. In order to capture the detailed physics of the flow in this complex system, large eddy simulation (LES) is performed. The crucial step in this analysis is to investigate the impact of breathing transience on the flow field. In this connection, simulations are carried out for transient breathing in addition to peak inspiration and expiration. To enable a fair comparison, the flowrates for constant inspiration/expiration are selected to be identical to the peak flowrates during the transient breathing. Physiologically appropriate regional ventilation for two different flowrates is induced. The velocity field and turbulent flow features are discussed for both flowrates. The airflow through the larynx is observed to be significantly complex with high turbulence level, recirculation, and secondary flow while the level of turbulence decreases through the higher bifurcations.

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.

A multi-scale model of gas transport in the lung to study heterogeneous lung ventilation during the multiple-breath washout test

The multiple-breath washout (MBW) is a lung function test that measures the degree of ventilation inhomogeneity (VI). The test is used to identify small airway impairment in patients with lung diseases like cystic fibrosis. However, the physical and physiological factors that influence the test outcomes and differentiate health from disease are not well understood. Computational models have been used to better understand the interaction between anatomical structure and physiological properties of the lung, but none of them has dealt in depth with the tracer gas washout test in a whole. Thus, our aim was to create a lung model that simulates the entire MBW and investigate the role of lung morphology and tissue mechanics on the tracer gas washout procedure. To this end, we developed a multi-scale lung model to simulate the inert gas transport in airways of all size. We then applied systematically different modifications to geometrical and mechanical properties of the lung model (compliance, residual airway volume and flow resistance) which have been associated with VI. The modifications were applied to distinct parts of the model, and their effects on the gas distribution within the lung and on the gas concentration profile were assessed. We found that variability in compliance and residual volume of the airways, as well as the spatial distribution of this variability in the lung had a direct influence on gas distribution among airways and on the MBW pattern (washout duration, characteristic concentration profile during each expiration), while the effects of variable flow resistance were negligible. Based on these findings, it is possible to classify different types of inhomogeneities in the lung and relate them to specific features of the MBW pattern, which builds the basis for a more detailed association of lung function and structure.

Obstructive lung diseases, like cystic fibrosis or primary ciliary dyskinesia, lead to inhomogeneous ventilation. The degree of observed inhomogeneity represents a clinical measure for the progression of the disease. The multiple-breath washout (MBW) is a lung function test that measures this inhomogeneity in the lung. However, the factors that influence the results of the test and differentiate between health and disease are not well understood. Computational models help us to understand better the relation between anatomical structure and physiological properties of the lung, but none of them has dealt in depth with the MBW test in whole. Our aim was to create a lung model that simulates the entire MBW test and study the role of lung structure and tissue mechanics on the washout procedure. We developed a multi-scale lung model to simulate the inert gas transport in all airways including the gas exchange area. Our model offers the opportunity to understand the ventilation distribution in the healthy lung. It can also mimic certain patterns of lung disease by applying modifications in mechanical properties out of the physiological limits. Thus, it can be used to study MBW characteristics in health and disease.

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.

Assessing the relationship between movement and airflow in the upper airway using computational fluid dynamics with motion determined from magnetic resonance imaging

BACKGROUND

Computational fluid dynamics simulations of respiratory airflow in the upper airway reveal clinically relevant information, including sites of local resistance, inhaled particle deposition, and the effect of pathological constrictions. Unlike previous simulations, which have been performed on rigid anatomical models from static medical imaging, this work utilises ciné imaging during respiration to create dynamic models and more closely represent airway physiology.

METHODS

Airway movement maps were obtained from non-rigid image registration of fast-cine MRI and applied to high-spatial-resolution airway surface models. Breathing flowrates were recorded simultaneously with imaging. These data formed the boundary conditions for large eddy simulation computations of the airflow from exterior mask to bronchi. Simulations with rigid geometries were performed to demonstrate the resulting airflow differences between airflow simulations in rigid and dynamic airways.

FINDINGS

In the analysed rapid breathing manoeuvre, incorporating airway movement significantly changed the findings of the CFD simulations. Peak resistance increased by 19.8% and occurred earlier in the breath. Overall pressure loss decreased by 19.2%, and the proportion of flow in the mouth increased by 13.0%. Airway wall motion was out-of-phase with the air pressure force, demonstrating the presence of neuromuscular motion. In total, the anatomy did 25.2% more work on the air than vice versa.

INTERPRETATIONS

Realistic movement of the airway is incorporated into CFD simulations of airflow in the upper airway for the first time. This motion is vital to producing clinically relevant computational models of respiratory airflow and will allow novel analysis of dynamic conditions, such as sleep apnoea.

1D network simulations for evaluating regional flow and pressure distributions in healthy and asthmatic human lungs

This study aimed to introduce a one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance to examine the relationship between airway resistance, pressure, and regional flow distribution. We employed five healthy and five asthmatic subjects who had dynamic computed tomography (CT) scans (4D CT) along with two static scans at total lung capacity and functional residual capacity. Fractional air-volume change ( ΔVairf ) from 4D CT was used for a validation of the 1D CFD model. We extracted the diameter ratio from existing data sets of 61 healthy subjects for computing mean and standard deviation (SD) of airway constriction/dilation in CT-resolved airways. The lobar mean (SD) of airway constriction/dilation was used to determine diameters of CT-unresolved airways. A 1D isothermal energy balance equation was solved, and pressure boundary conditions were imposed at the acinar region (model A) or at the pleural region (model B). A static compliance model was only applied for model B to link acinar and pleural regions. The values of 1D CFD-derived ΔVairf for model B demonstrated better correlation with 4D CT-derived ΔVairf than model A. In both inspiration and expiration, asthmatic subjects with airway constriction show much greater pressure drop than healthy subjects without airway constriction. This increased transpulmonary pressures in the asthmatic subjects, leading to an increased workload (hysteresis). The 1D CFD model was found to be useful in investigating flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of 3D CFD. NEW & NOTEWORTHY A one-dimensional (1D) computational fluid dynamics (CFD) model for airway resistance and lung compliance was introduced to examine the relationship between airway resistance, pressure, and regional flow distribution. The 1D CFD model investigated differences of flow structure, lung hysteresis, and pressure distribution for healthy and asthmatic subjects. The derived flow distribution could be used for imposing boundary conditions of three-dimensional CFD.

In vivo dynamics of the tracheal airway and its influences on respiratory airflows

Respiration is a dynamic process accompanied by morphological changes in the airways. Although deformation of large airways is expected to exacerbate pulmonary disease symptoms by obstructing airflow during increased minute ventilation, its quantitative effects on airflow characteristics remain unclear. Here, we used an exemplar case derived from in vivo dynamic imaging and examined the effects of tracheal deformation on airflow characteristics under different conditions. First, we measured tracheal deformation profiles of a healthy lung using magnetic resonance imaging during forced exhalation, which we simulated to characterize subject-specific airflow patterns. Subsequently, for both inhalation and exhalation, we compared the airflows when the maximal deformation in tracheal cross-sectional area was 0% (rigid), 33% (mild), 50% (moderate), or 75% (severe). We quantified differences in airflow patterns between deformable and rigid airways by computing the correlation coefficients (R) and the root-mean-square of differences (Drms) between their velocity contours. For both inhalation and exhalation, airflow patterns were similar in all branches between the rigid and mild conditions (R > 0.9; Drms < 32%). However, airflow characteristics in the moderate and severe conditions differed markedly from those in the rigid and mild conditions in all lung branches, particularly for inhalation (moderate: R > 0.1, Drms < 76%; severe: R > 0.2, Drms < 96%). Our exemplar case supports the use of a rigid airway assumption to compute flows for mild deformation. For moderate or severe deformation, however, dynamic contraction should be considered, especially during inhalation, to accurately predict airflow and elucidate the underlying pulmonary pathology.

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 novel method to generate dynamic boundary conditions for airway CFD by mapping upper airway movement with non-rigid registration of dynamic and static MRI

Computational fluid dynamics (CFD) simulations of airflow in the human airways have the potential to provide a great deal of information that can aid clinicians in case management and surgical decision making, such as airway resistance, energy expenditure, airflow distribution, heat and moisture transfer, and particle deposition, as well as the change in each of these due to surgical interventions. However, the clinical relevance of CFD simulations has been limited to date, as previous models either did not incorporate neuromuscular motion or any motion at all. Many common airway pathologies, such as obstructive sleep apnea (OSA) and tracheomalacia, involve large movements of the structures surrounding the airway, such as the tongue and soft palate. Airway wall motion may be due to many factors including neuromuscular motion, internal aerodynamic forces, and external forces such as gravity. Therefore, to realistically model these airway diseases, a method is required to derive the airway wall motion, whatever the cause, and apply it as a boundary condition to CFD simulations. This paper presents and validates a novel method of capturing in vivo motion of airway walls from magnetic resonance images with high spatiotemporal resolution, through a novel combination of non-rigid image, surface, and surface-normal-vector registration. Coupled with image-synchronous pneumotachography, this technique provides the necessary boundary conditions for dynamic CFD simulations of breathing, allowing the effect of the airway's complex motion to be calculated for the first time, in both normal subjects and those with conditions such as OSA.

A review of inflammatory mechanism in airway diseases

BACKGROUND

Inflammation in the lung is the body's natural response to injury. It acts to remove harmful stimuli such as pathogens, irritants, and damaged cells and initiate the healing process. Acute and chronic pulmonary inflammation are seen in different respiratory diseases such as; acute respiratory distress syndrome, chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF).

FINDINGS

In this review, we found that inflammatory response in COPD is determined by the activation of epithelial cells and macrophages in the respiratory tract. Epithelial cells and macrophages discharge transforming growth factor-β (TGF-β), which trigger fibroblast proliferation and tissue remodeling. Asthma leads to airway hyper-responsiveness, obstruction, mucus hyper-production, and airway-wall remodeling. Cytokines, allergens, chemokines, and infectious agents are the main stimuli that activate signaling pathways in epithelial cells in asthma. Mutation of the CF transmembrane conductance regulator (CFTR) gene results in CF. Mutations in CFTR influence the lung epithelial innate immune function that leads to exaggerated and ineffective airway inflammation that fails to abolish pulmonary pathogens. We present mechanistic computational models (based on ordinary differential equations, partial differential equations and agent-based models) that have been applied in studying the complex physiological and pathological mechanisms of chronic inflammation in different airway diseases.

CONCLUSION

The scope of the present review is to explore the inflammatory mechanism in airway diseases and highlight the influence of aging on airways' inflammation mechanism. The main goal of this review is to encourage research collaborations between experimentalist and modelers to promote our understanding of the physiological and pathological mechanisms that control inflammation in different airway diseases.

Contributions of Kinetic Energy and Viscous Dissipation to Airway Resistance in Pulmonary Inspiratory and Expiratory Airflows in Successive Symmetric Airway Models With Various Bifurcation Angles

The aim of this study was to investigate and quantify contributions of kinetic energy and viscous dissipation to airway resistance during inspiration and expiration at various flow rates in airway models of different bifurcation angles. We employed symmetric airway models up to the 20th generation with the following five different bifurcation angles at a tracheal flow rate of 20 L/min: 15 deg, 25 deg, 35 deg, 45 deg, and 55 deg. Thus, a total of ten computational fluid dynamics (CFD) simulations for both inspiration and expiration were conducted. Furthermore, we performed additional four simulations with tracheal flow rate values of 10 and 40 L/min for a bifurcation angle of 35 deg to study the effect of flow rate on inspiration and expiration. Using an energy balance equation, we quantified contributions of the pressure drop associated with kinetic energy and viscous dissipation. Kinetic energy was found to be a key variable that explained the differences in airway resistance on inspiration and expiration. The total pressure drop and airway resistance were larger during expiration than inspiration, whereas wall shear stress and viscous dissipation were larger during inspiration than expiration. The dimensional analysis demonstrated that the coefficients of kinetic energy and viscous dissipation were strongly correlated with generation number. In addition, the viscous dissipation coefficient was significantly correlated with bifurcation angle and tracheal flow rate. We performed multiple linear regressions to determine the coefficients of kinetic energy and viscous dissipation, which could be utilized to better estimate the pressure drop in broader ranges of successive bifurcation structures.

640-slice DVCT multi-dimensionally and dynamically presents changes in bladder volume and urine flow rate

The present study aimed to explore the application of 640-slice dynamic volume computed tomography (DVCT) to excretory cystography and urethrography. A total of 70 healthy subjects were included in the study. Excretory cystography and urethrography using 640-slice DVCT was conducted to continuously record the motions of the bladder and the proximal female and male urethra. The patients' voiding process was divided into early, early to middle, middle, middle to late, and late voiding phases. The subjects were analyzed using DVCT and conventional CT. The cross-sectional areas of various sections of the male and female urethra were evaluated, and the average urine flow rate was calculated. The 640-slice DVCT technique was used to dynamically observe the urine flow rate and changes in bladder volume at all voiding phases. The urine volume detected by 640-slice DVCT exhibited no significant difference compared with the actual volume, and no significant difference compared with that determined using conventional CT. Furthermore, no significant difference in the volume of the bladder at each phase of the voiding process was detected between 640-slice DVCT and conventional CT. The results indicate that 640-slice DVCT can accurately evaluate the status of the male posterior urethra and female urethra. In conclusion, 640-slice DVCT is able to multi-dimensionally and dynamically present changes in bladder volume and urine flow rate, and could obtain similar results to conventional CT in detecting urine volume, as well as the status of the male posterior urethra and female urethra.

Substance deposition assessment in obstructed pulmonary system through numerical characterization of airflow and inhaled particles attributes

BACKGROUND

Chronic obstructive pulmonary disease (COPD) and asthma are considered as the two most widespread obstructive lung diseases, whereas they affect more than 500 million people worldwide. Unfortunately, the requirement for detailed geometric models of the lungs in combination with the increased computational resources needed for the simulation of the breathing did not allow great progress to be made in the past for the better understanding of inflammatory diseases of the airways through detailed modelling approaches. In this context, computational fluid dynamics (CFD) simulations accompanied by fluid particle tracing (FPT) analysis of the inhaled ambient particles are deemed critical for lung function assessment. Also they enable the understanding of particle depositions on the airways of patients, since these accumulations may affect or lead to inflammations. In this direction, the current study conducts an initial investigation for the better comprehension of particle deposition within the lungs. More specifically, accurate models of the airways obstructions that relate to pulmonary disease are developed and a thorough assessment of the airflow behavior together with identification of the effects of inhaled particle properties, such as size and density, is conducted. Our approach presents a first step towards an effective personalization of pulmonary treatment in regards to the geometric characteristics of the lungs and the in depth understanding of airflows within the airways.

METHODS

A geometry processing technique involving contraction algorithms is established and used to employ the different respiratory arrangements associated with lung related diseases that exhibit airways obstructions. Apart from the normal lung case, two categories of obstructed cases are examined, i.e. models with obstructions in both lungs and models with narrowings in the right lung only. Precise assumptions regarding airflow and deposition fraction (DF) over various sections of the lungs are drawn by simulating these distinct incidents through the finite volume method (FVM) and particularly the CFD and FPT algorithms. Moreover, a detailed parametric analysis clarifies the effects of the particles size and density in terms of regional deposition upon several parts of the pulmonary system. In this manner, the deposition pattern of various substances can be assessed.

RESULTS

For the specific case of the unobstructed lung model most particles are detected on the right lung (48.56% of total, when the air flowrate is 12.6 L/min), a fact that is also true when obstructions arise symmetrically in both lungs (51.45% of total, when the air flowrate is 6.06 L/min and obstructions occur after the second generation). In contrast, when narrowings are developed on the right lung only, most particles are pushed on the left section (68.22% of total, when the air flowrate is 11.2 L/min) indicating that inhaled medication is generally deposited away from the areas of inflammation. This observation is useful when designing medical treatment of lung diseases. Furthermore, particles with diameters from 1 μm to 10 μm are shown to be mainly deposited on the lower airways, whereas particles with diameters of 20 μm and 30 μm are mostly accumulated in the upper airways. As a result, the current analysis indicates increased DF levels in the upper airways when the particle diameter is enlarged. Additionally, when the particles density increases from 1000 Kg/m³ to 2000 Kg/m³, the DF is enhanced on every generation and for all cases investigated herein. The results obtained by our simulations provide an accurate and quantitative estimation of all important parameters involved in lung modeling.

CONCLUSIONS

The treatment of respiratory diseases with inhaled medical substances can be advanced by the clinical use of accurate CFD and FPT simulations and specifically by evaluating the deposition of inhaled particles in a regional oriented perspective in regards to different particle sizes and particle densities. Since a drug with specific characteristics (i.e. particle size and density) exhibits maximum deposition on particular lung areas, the current study provides initial indications to a qualified physician for proper selection of medication.

Capturing complexity in pulmonary system modelling

Respiratory disease is a significant problem worldwide, and it is a problem with increasing prevalence. Pathology in the upper airways and lung is very difficult to diagnose and treat, as response to disease is often heterogeneous across patients. Computational models have long been used to help understand respiratory function, and these models have evolved alongside increases in the resolution of medical imaging and increased capability of functional imaging, advances in biological knowledge, mathematical techniques and computational power. The benefits of increasingly complex and realistic geometric and biophysical models of the respiratory system are that they are able to capture heterogeneity in patient response to disease and predict emergent function across spatial scales from the delicate alveolar structures to the whole organ level. However, with increasing complexity, models become harder to solve and in some cases harder to validate, which can reduce their impact clinically. Here, we review the evolution of complexity in computational models of the respiratory system, including successes in translation of models into the clinical arena. We also highlight major challenges in modelling the respiratory system, while making use of the evolving functional data that are available for model parameterisation and testing.

Morphological and functional properties of the conducting human airways investigated by in vivo computed tomography and in vitro MRI

The accurate representation of the human airway anatomy is crucial for understanding and modeling the structure-function relationship in both healthy and diseased lungs. The present knowledge in this area is based on morphometric studies of excised lung casts, partially complemented by in vivo studies in which computed tomography (CT) was used on a small number of subjects. In the present study, we analyzed CT scans of a cohort of healthy subjects and obtained comprehensive morphometric information down to the seventh generation of bronchial branching, including airway diameter, length, branching angle, and rotation angle. Although some of the geometric parameters (such as the child-to-parent branch diameter ratio) are found to be in line with accepted values, for others (such as the branch length-to-diameter ratio) our findings challenge the common assumptions. We also evaluated several metrics of self-similarity, including the fractal dimension of the airway tree. Additionally, we used phase-contrast magnetic resonance imaging (MRI) to obtain the volumetric flow field in the three-dimensional-printed airway model of one of the subjects during steady inhalation. This is used to relate structural and functional parameters and, in particular, to close the power-law relationship between branch flow rate and diameter. The diameter exponent is found to be significantly lower than in the usually assumed Poiseuille regime, which we attribute to the strong secondary (i.e., transverse) velocity component. The strength of the secondary velocity with respect to the axial component exceeds the levels found in idealized airway models and persists within the first seven generations. NEW & NOTEWORTHY We performed a comprehensive computed tomography-based study of the conductive airway morphology in normal human subjects, including branch diameter, length, and mutual angles. We found significant departure from classic homothetic relationships. We also carried out MRI measurements of the three-dimensional inspiratory flow in an anatomy-based model and directly assessed structure-function relationships that have so far been assumed. We found that strong secondary flows (i.e., transverse velocity components) persist through the first seven generations of bronchial branching.

A tree-parenchyma coupled model for lung ventilation simulation

In this article, we develop a lung ventilation model. The parenchyma is described as an elastic homogenized media. It is irrigated by a space-filling dyadic resistive pipe network, which represents the tracheobronchial tree. In this model, the tree and the parenchyma are strongly coupled. The tree induces an extra viscous term in the system constitutive relation, which leads, in the finite element framework, to a full matrix. We consider an efficient algorithm that takes advantage of the tree structure to enable a fast matrix-vector product computation. This framework can be used to model both free and mechanically induced respiration, in health and disease. Patient-specific lung geometries acquired from computed tomography scans are considered. Realistic Dirichlet boundary conditions can be deduced from surface registration on computed tomography images. The model is compared to a more classical exit compartment approach. Results illustrate the coupling between the tree and the parenchyma, at global and regional levels, and how conditions for the purely 0D model can be inferred. Different types of boundary conditions are tested, including a nonlinear Robin model of the surrounding lung structures.

The effect of disease and respiration on airway shape in patients with moderate persistent asthma

Computational models of gas transport and aerosol deposition frequently utilize idealized models of bronchial tree structure, where airways are considered a network of bifurcating cylinders. However, changes in the shape of the lung during respiration affect the geometry of the airways, especially in disease conditions. In this study, the internal airway geometry was examined, concentrating on comparisons between mean lung volume (MLV) and total lung capacity (TLC). A set of High Resolution CT images were acquired during breath hold on a group of moderate persistent asthmatics at MLV and TLC after challenge with a broncho-constrictor (methacholine) and the airway trees were segmented and measured. The airway hydraulic diameter (Dh) was calculated through the use of average lumen area (Ai) and average internal perimeter (Pi) at both lung volumes and was found to be systematically higher at TLC by 13.5±9% on average, with the lower lobes displaying higher percent change in comparison to the lower lobes. The average internal diameter (Din) was evaluated to be 12.4±6.8% (MLV) and 10.8±6.3% (TLC) lower than the Dh, for all the examined bronchi, a result displaying statistical significance. Finally, the airway distensibility per bronchial segment and per generation was calculated to have an average value of 0.45±0.28, exhibiting high variability both between and within lung regions and generations. Mixed constriction/dilation patterns were recorded between the lung volumes, where a number of airways either failed to dilate or even constricted when observed at TLC. We conclude that the Dh is higher than Din, a fact that may have considerable effects on bronchial resistance or airway loss at proximal regions. Differences in caliber changes between lung regions are indicative of asthma-expression variability in the lung. However, airway distensibility at generation 3 seems to predict distensibility more distally.

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.

A quasi-3D wire approach to model pulmonary airflow in human airways

The models used for modeling the airflow in the human airways are either 0-dimensional compartmental or full 3-dimensional (3D) computational fluid dynamics (CFD) models. In the former, airways are treated as compartments, and the computations are performed with several assumptions, thereby generating a low-fidelity solution. The CFD method displays extremely high fidelity since the solution is obtained by solving the conservation equations in a physiologically consistent geometry. However, CFD models (1) require millions of degrees of freedom to accurately describe the geometry and to reduce the discretization errors, (2) have convergence problems, and (3) require several days to simulate a few breathing cycles. In this paper, we present a novel, fast-running, and robust quasi-3D wire model for modeling the airflow in the human lung airway. The wire mesh is obtained by contracting the high-fidelity lung airway surface mesh to a system of connected wires, with well-defined radii. The conservation equations are then solved in each wire. These wire meshes have around O(1000) degrees of freedom and hence are 3000 to 25 000 times faster than their CFD counterparts. The 3D spatial nature is also preserved since these wires are contracted out of the actual lung STL surface. The pressure readings between the 2 approaches showed minor difference (maximum error = 15%). In general, this formulation is fast and robust, allows geometric changes, and delivers high-fidelity solutions. Hence, this approach has great potential for more complicated problems including modeling of constricted/diseased lung sections and for calibrating the lung flow resistances through parameter inversion.

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.

A four-dimensional computed tomography comparison of healthy and asthmatic human lungs

The purpose of this study was to explore new insights in non-linearity, hysteresis and ventilation heterogeneity of asthmatic human lungs using four-dimensional computed tomography (4D-CT) image data acquired during tidal breathing. Volumetric image data were acquired for 5 non-severe and one severe asthmatic volunteers. Besides 4D-CT image data, function residual capacity and total lung capacity image data during breath-hold were acquired for comparison with dynamic scans. Quantitative results were compared with the previously reported analysis of five healthy human lungs. Using an image registration technique, local variables such as regional ventilation and anisotropic deformation index (ADI) were estimated. Regional ventilation characteristics of non-severe asthmatic subjects were similar to those of healthy subjects, but different from the severe asthmatic subject. Lobar airflow fractions were also well correlated between static and dynamic scans (R²>0.84). However, local ventilation heterogeneity significantly increased during tidal breathing in both healthy and asthmatic subjects relative to that of breath-hold perhaps because of airway resistance present only in dynamic breathing. ADI was used to quantify non-linearity and hysteresis of lung motion during tidal breathing. Non-linearity was greater on inhalation than exhalation among all subjects. However, exhalation non-linearity among asthmatic subjects was greater than healthy subjects and the difference diminished during inhalation. An increase of non-linearity during exhalation in asthmatic subjects accounted for lower hysteresis relative to that of healthy ones. Thus, assessment of non-linearity differences between healthy and asthmatic lungs during exhalation may provide quantitative metrics for subject identification and outcome assessment of new interventions.

The Creation and Statistical Evaluation of a Deterministic Model of the Human Bronchial Tree from HRCT Images

A quantitative description of the morphology of lung structure is essential prior to any form of predictive modeling of ventilation or aerosol deposition implemented within the lung. The human lung is a very complex organ, with airway structures that span two orders of magnitude and having a multitude of interfaces between air, tissue and blood. As such, current medical imaging protocols cannot provide medical practitioners and researchers with in-vivo knowledge of deeper lung structures. In this work a detailed algorithm for the generation of an individualized 3D deterministic model of the conducting part of the human tracheo-bronchial tree is described. Distinct initial conditions were obtained from the high-resolution computed tomography (HRCT) images of seven healthy volunteers. The algorithm developed is fractal in nature and is implemented as a self-similar space sub-division procedure. The expansion process utilizes physiologically realistic relationships and thresholds to produce an anatomically consistent human airway tree. The model was validated through extensive statistical analysis of the results and comparison of the most common morphological features with previously published morphometric studies and other equivalent models. The resulting trees were shown to be in good agreement with published human lung geometric characteristics and can be used to study, among other things, structure-function relationships in simulation studies.

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

CONTEXT

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry.

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry.

Effect of static vs. dynamic imaging on particle transport in CT-based numerical models of human central airways

Advances in quantitative computed tomography (CT) has provided methods to assess the detailed structure of the pulmonary airways and parenchyma, providing the means of applying computational fluid dynamics-based modeling to better understand subject-specific differences in structure-to-function relationships. Most of the previous numerical studies, seeking to predict patterns of inhaled particle deposition, have considered airway geometry and regional ventilation derived from static images. Because geometric alterations of the airway and parenchyma associated with regional ventilation may greatly affect particle transport, we have sought to investigate the effect of rigid vs. deforming airways, linear vs. nonlinear airway deformations, and step-wise static vs. dynamic imaging on particle deposition with varying numbers of intermediate lung volume increments. Airway geometry and regional ventilation at different time points were defined by four-dimensional (space and time) dynamic or static CT images. Laminar, transitional, and turbulent air flows were reproduced with a three-dimensional eddy-resolving computational fluid dynamics model. Finally, trajectories of particles were computed with the Lagrangian tracking algorithm. The results demonstrated that static-imaging-based models can contribute 7% uncertainty to overall particle distribution and deposition primarily due to regional flow rate (ventilation) differences as opposed to geometric alterations. The effect of rigid vs. deforming airways on serial distribution of particles over generations was significantly smaller than reported in a previous study that used the symmetric Weibel geometric model with smaller flow rate. Rigid vs. deforming airways were also shown to affect parallel particle distribution over lobes by 8% and the differences associated with use of static vs. dynamic imaging was 18%. These differences demonstrate that estimates derived from static vs. dynamic imaging can significantly affect the assessment of particle distribution heterogeneity. The effect of linear vs. nonlinear airway deformations was within the uncertainty due to mesh size.

Modeling the Nonlinear Motion of the Rat Central Airways

Advances in volumetric medical imaging techniques allowed the subject-specific modeling of the bronchial flow through the first few generations of the central airways using computational fluid dynamics (CFD). However, a reliable CFD prediction of the bronchial flow requires modeling of the inhomogeneous deformation of the central airways during breathing. This paper addresses this issue by introducing two models of the central airways motion. The first model utilizes a node-to-node mapping between the discretized geometries of the central airways generated from a number of successive computed tomography (CT) images acquired dynamically (without breath hold) over the breathing cycle of two Sprague-Dawley rats. The second model uses a node-to-node mapping between only two discretized airway geometries generated from the CT images acquired at end-exhale and at end-inhale along with the ventilator measurement of the lung volume change. The advantage of this second model is that it uses just one pair of CT images, which more readily complies with the radiation dosage restrictions for humans. Three-dimensional computer aided design geometries of the central airways generated from the dynamic-CT images were used as benchmarks to validate the output from the two models at sampled time-points over the breathing cycle. The central airway geometries deformed by the first model showed good agreement to the benchmark geometries within a tolerance of 4%. The central airway geometry deformed by the second model better approximated the benchmark geometries than previous approaches that used a linear or harmonic motion model.

Developmental model of an automatic production of the human bronchial tree based on L-system

BACKGROUND AND OBJECTIVE

The human lungs exchange air with the external environment via the conducting airways. The application of an anatomically accurate model of the conducting airways can be helpful for simulating gas exchange and fluid distribution throughout the bronchial tree in the lung.

METHODS

In the current study, Lindenmayer system (L-system) has been formulated to generate the bronchial tree structure in a human lung. It has been considered that the structure of the bronchial tree is divided into two main segments: 1) The central airways (from the trachea to segmental bronchi) and 2) the dichotomous structure (from segmental bronchi to terminal bronchioles). Two sets of parametric rewriting rules which can be used to develop central and peripheral airways have been proposed; the first set used to develop central airways consists of seven rules, while the second rule set contains four rules.

RESULTS

The proposed model is capable of generating bronchial tree inside the volume of the host lung; and comparison of the resulting model with those reported in the literature shows that the morphometric characteristics of L-system structure are in good agreement with their corresponding experimental data.

CONCLUSION

The resulting model can be used to obtain a mathematical model required for the study of transport phenomena occurring in the lung during respiration.

Quantitative Dual-Energy Computed Tomography Supports a Vascular Etiology of Smoking-induced Inflammatory Lung Disease

RATIONALE

Endothelial dysfunction is of interest in relation to smoking-associated emphysema, a component of chronic obstructive pulmonary disease (COPD). We previously demonstrated that computed tomography (CT)-derived pulmonary blood flow (PBF) heterogeneity is greater in smokers with normal pulmonary function tests (PFTs) but who have visual evidence of centriacinar emphysema (CAE) on CT.

OBJECTIVES

We introduced dual-energy CT (DECT) perfused blood volume (PBV) as a PBF surrogate to evaluate whether the CAE-associated increased PBF heterogeneity is reversible with sildenafil.

METHODS

Seventeen PFT-normal current smokers were divided into CAE-susceptible (SS; n = 10) and nonsusceptible (NS; n = 7) smokers, based on the presence or absence of CT-detected CAE. DECT-PBV images were acquired before and 1 hour after administration of 20 mg oral sildenafil. Regional PBV and PBV coefficients of variation (CV), a measure of spatial blood flow heterogeneity, were determined, followed by quantitative assessment of the central arterial tree.

MEASUREMENTS AND MAIN RESULTS

After sildenafil administration, regional PBV-CV decreased in SS subjects but did not decrease in NS subjects (P < 0.05), after adjusting for age and pack-years. Quantitative evaluation of the central pulmonary arteries revealed higher arterial volume and greater cross-sectional area (CSA) in the lower lobes of SS smokers, which suggested arterial enlargement in response to increased peripheral resistance. After sildenafil, arterial CSA decreased in SS smokers but did not decrease in NS smokers (P < 0.01).

CONCLUSIONS

These results demonstrate that sildenafil restores peripheral perfusion and reduces central arterial enlargement in normal SS subjects with little effect in NS subjects, highlighting DECT-PBV as a biomarker of reversible endothelial dysfunction in smokers with CAE.

Efficient methods for implementation of multi-level nonrigid mass-preserving image registration on GPUs and multi-threaded CPUs

BACKGROUND AND OBJECTIVE

Faster and more accurate methods for registration of images are important for research involved in conducting population-based studies that utilize medical imaging, as well as improvements for use in clinical applications. We present a novel computation- and memory-efficient multi-level method on graphics processing units (GPU) for performing registration of two computed tomography (CT) volumetric lung images.

METHODS

We developed a computation- and memory-efficient Diffeomorphic Multi-level B-Spline Transform Composite (DMTC) method to implement nonrigid mass-preserving registration of two CT lung images on GPU. The framework consists of a hierarchy of B-Spline control grids of increasing resolution. A similarity criterion known as the sum of squared tissue volume difference (SSTVD) was adopted to preserve lung tissue mass. The use of SSTVD consists of the calculation of the tissue volume, the Jacobian, and their derivatives, which makes its implementation on GPU challenging due to memory constraints. The use of the DMTC method enabled reduced computation and memory storage of variables with minimal communication between GPU and Central Processing Unit (CPU) due to ability to pre-compute values. The method was assessed on six healthy human subjects.

RESULTS

Resultant GPU-generated displacement fields were compared against the previously validated CPU counterpart fields, showing good agreement with an average normalized root mean square error (nRMS) of 0.044±0.015. Runtime and performance speedup are compared between single-threaded CPU, multi-threaded CPU, and GPU algorithms. Best performance speedup occurs at the highest resolution in the GPU implementation for the SSTVD cost and cost gradient computations, with a speedup of 112 times that of the single-threaded CPU version and 11 times over the twelve-threaded version when considering average time per iteration using a Nvidia Tesla K20X GPU.

CONCLUSIONS

The proposed GPU-based DMTC method outperforms its multi-threaded CPU version in terms of runtime. Total registration time reduced runtime to 2.9min on the GPU version, compared to 12.8min on twelve-threaded CPU version and 112.5min on a single-threaded CPU. Furthermore, the GPU implementation discussed in this work can be adapted for use of other cost functions that require calculation of the first derivatives.

Pulmonary CT and MRI phenotypes that help explain chronic pulmonary obstruction disease pathophysiology and outcomes

Pulmonary x-ray computed tomographic (CT) and magnetic resonance imaging (MRI) research and development has been motivated, in part, by the quest to subphenotype common chronic lung diseases such as chronic obstructive pulmonary disease (COPD). For thoracic CT and MRI, the main COPD research tools, disease biomarkers are being validated that go beyond anatomy and structure to include pulmonary functional measurements such as regional ventilation, perfusion, and inflammation. In addition, there has also been a drive to improve spatial and contrast resolution while at the same time reducing or eliminating radiation exposure. Therefore, this review focuses on our evolving understanding of patient-relevant and clinically important COPD endpoints and how current and emerging MRI and CT tools and measurements may be exploited for their identification, quantification, and utilization. Since reviews of the imaging physics of pulmonary CT and MRI and reviews of other COPD imaging methods were previously published and well-summarized, we focus on the current clinical challenges in COPD and the potential of newly emerging MR and CT imaging measurements to address them. Here we summarize MRI and CT imaging methods and their clinical translation for generating reproducible and sensitive measurements of COPD related to pulmonary ventilation and perfusion as well as parenchyma morphology. The key clinical problems in COPD provide an important framework in which pulmonary imaging needs to rapidly move in order to address the staggering burden, costs, as well as the mortality and morbidity associated with COPD.