Ventilation/Perfusion Matching: Of Myths, Mice, and Men.

Despite a huge range in lung size between species, there is little measured difference in the ability of the lung to provide a well-matched air flow (ventilation) to blood flow (perfusion) at the gas exchange tissue. Here, we consider the remarkable similarities in ventilation/perfusion matching between species through a biophysical lens and consider evidence that matching in large animals is dominated by gravity but in small animals by structure.

Evaluating Tissue Heterogeneity in the Radiologically Normal-Appearing Tissue in IPF Compared to Healthy Controls.

RATIONALE AND OBJECTIVES: Idiopathic Pulmonary Fibrosis (IPF) is a progressive interstitial lung disease characterised by heterogeneously distributed fibrotic lesions. The inter- and intra-patient heterogeneity of the disease has meant that useful biomarkers of severity and progression have been elusive. Previous quantitative computed tomography (CT) based studies have focussed on characterising the pathological tissue. However, we hypothesised that the remaining lung tissue, which appears radiologically normal, may show important differences from controls in tissue characteristics. MATERIALS AND METHODS: Quantitative metrics were derived from CT scans in IPF patients (N = 20) and healthy controls with a similar age (N = 59). An automated quantitative software (CALIPER, Computer-Aided Lung Informatics for Pathology Evaluation and Rating) was used to classify tissue as normal-appearing, fibrosis, or low attenuation area. Densitometry metrics were calculated for all lung tissue and for only the normal-appearing tissue. Heterogeneity of lung tissue density was quantified as coefficient of variation and by quadtree. Associations between measured lung function and quantitative metrics were assessed and compared between the two cohorts. RESULTS: All metrics were significantly different between controls and IPF (p < 0.05), including when only the normal tissue was evaluated (p < 0.04). Density in the normal tissue was 14% higher in the IPF participants than controls (p < 0.001). The normal-appearing tissue in IPF had heterogeneity metrics that exhibited significant positive relationships with the percent predicted diffusion capacity for carbon monoxide. CONCLUSION: We provide quantitative assessment of IPF lung tissue characteristics compared to a healthy control group of similar age. Tissue that appears visually normal in IPF exhibits subtle but quantifiable differences that are associated with lung function and gas exchange.

Quantitative Analysis of Lung Shape in Idiopathic Pulmonary Fibrosis: Insights Into Disease- and Age-Associated Patterns.

RATIONALE AND OBJECTIVES: Fibrotic scarring in idiopathic pulmonary fibrosis (IPF) typically develops first in the posterior-basal lung tissue before advancing to involve more of the lung. The complexity of lung shape in the costo-diaphragmatic region has been proposed as a potential factor in this regional development. Intrinsic and disease-related shape could therefore be important for understanding IPF risk and its staging. We hypothesized that lung and lobe shape in IPF would have important differences from controls. MATERIALS AND METHODS: A principal component (PC) analysis was used to derive a statistical shape model (SSM) of the lung for a control cohort aged > 50 years (N = 39), using segmented lung and fissure surface data from CT imaging. Individual patient shape models derived for baseline (N = 18) and follow-up (N = 16) CT scans in patients with IPF were projected to the SSM to describe shape as the sum of the SSM average and weighted PC modes. Associations between the first four PC shape modes, lung function, percentage of fibrosis (fibrosis%) and pulmonary vessel-related structures (PVRS%), and other tissue metrics were assessed and compared between the two cohorts. RESULTS: Shape was different between IPF and controls (P < 0.05 for all shape modes), with IPF shape forming a distinct shape cluster. Shape had a negative relationship with age in controls (P = 0.013), but a positive relationship with age in IPF (P = 0.026). Some features of shape changed on follow-up. Shape in IPF was associated with fibrosis% (P < 0.05) and PVRS% (P < 0.05). CONCLUSION: Quantitative comparison of lung and lobe shape in IPF with controls of a similar age reveals shape differences that are strongly associated with age and percent fibrosis. The clustering of IPF cohort shape suggests that it could be an important feature to describe disease.

Pulmonary vessel volume in idiopathic pulmonary fibrosis compared with healthy controls aged > 50 years.

Idiopathic pulmonary fibrosis (IPF) is characterised by progressive fibrosing interstitial pneumonia with an associated irreversible decline in lung function and quality of life. IPF prevalence increases with age, appearing most frequently in patients aged > 50 years. Pulmonary vessel-like volume (PVV) has been found to be an independent predictor of mortality in IPF and other interstitial lung diseases, however its estimation can be impacted by artefacts associated with image segmentation methods and can be confounded by adjacent fibrosis. This study compares PVV in IPF patients (N = 21) with PVV from a healthy cohort aged > 50 years (N = 59). The analysis includes a connected graph-based approach that aims to minimise artefacts contributing to calculation of PVV. We show that despite a relatively low extent of fibrosis in the IPF cohort (20% of the lung volume), PVV is 2-3 times higher than in controls. This suggests that a standardised method to calculate PVV that accounts for tree connectivity could provide a promising tool to provide early diagnostic or prognostic information in IPF patients and other interstitial lung disease.

An evaluation of a New Zealand "vape to quit smoking" programme.

AIM: To compare the use of smoking cessation aids across different ethnic groups and age groups within a large New Zealand cohort and to assess the uptake and effectiveness of e-cigarettes for smoking cessation via a "vape to quit" initiative. METHODS: Retrospective analysis of Te Ha - Waitaha smoking cessation service, including a telephone interview of a subgroup, who opted into the "vape to quit" programme. The uptake of different smoking cessation aids, including the use of medications and other products, was evaluated and the self-reported quit rate in a "vape to quit" cohort was evaluated. RESULTS: The final dataset analysed consisted of 1,118 participants: 66.6% NZ European; 28.1% Maori; 3.1% Pacific; and 2.2% Asian. Maori participants were younger on average and had increasing vaping use. Maori were less likely to receive varenicline to assist with smoking cessation. Vaping use increased over time in all groups. Nicotine containing e-cigarettes were the most common smoking cessation products used, with >65% of each ethnic cohort utilising these products. Of the 100 participants in the "vape to quit" cohort 16% were smokefree and vapefree, 31% were smokefree and vaping, 31% were smoking and not vaping, and 22% were smoking and vaping. CONCLUSIONS: The Te Ha - Waitaha service was successful in engaging Maori in their smoking cessation programme. Nicotine containing e-cigarette products were popular in all cohorts. Nicotine containing e-cigarettes are showing potential in smoking cessation programmes in support of the Smokefree Aotearoa 2025; however, 22% of those in the "vape to quit" programme became dual users.

Simulating Multi-Scale Pulmonary Vascular Function by Coupling Computational Fluid Dynamics With an Anatomic Network Model.

The function of the pulmonary circulation is truly multi-scale, with blood transported through vessels from centimeter to micron scale. There are scale-dependent mechanisms that govern the flow in the pulmonary vascular system. However, very few computational models of pulmonary hemodynamics capture the physics of pulmonary perfusion across the spatial scales of functional importance in the lung. Here we present a multi-scale model that incorporates the 3-dimensional (3D) complexities of pulmonary blood flow in the major vessels, coupled to an anatomically-based vascular network model incorporating the multiple contributing factors to capillary perfusion, including gravity. Using the model we demonstrate how we can predict the impact of vascular remodeling and occlusion on both macro-scale functional drivers (flow distribution between lungs, and wall shear stress) and micro-scale contributors to gas exchange. The model predicts interactions between 3D and 1D models that lead to a redistribution of blood between postures, both on a macro- and a micro-scale. This allows us to estimate the effect of posture on left and right pulmonary artery wall shear stress, with predictions varying by 0.75-1.35 dyne/cm2 between postures.

Integrative Computational Models of Lung Structure-Function Interactions.

Anatomically based integrative models of the lung and their interaction with other key components of the respiratory system provide unique capabilities for investigating both normal and abnormal lung function. There is substantial regional variability in both structure and function within the normal lung, yet it remains capable of relatively efficient gas exchange by providing close matching of air delivery (ventilation) and blood delivery (perfusion) to regions of gas exchange tissue from the scale of the whole organ to the smallest continuous gas exchange units. This is despite remarkably different mechanisms of air and blood delivery, different fluid properties, and unique scale-dependent anatomical structures through which the blood and air are transported. This inherent heterogeneity can be exacerbated in the presence of disease or when the body is under stress. Current computational power and data availability allow for the construction of sophisticated data-driven integrative models that can mimic respiratory system structure, function, and response to intervention. Computational models do not have the same technical and ethical issues that can limit experimental studies and biomedical imaging, and if they are solidly grounded in physiology and physics they facilitate investigation of the underlying interaction between mechanisms that determine respiratory function and dysfunction, and to estimate otherwise difficult-to-access measures. © 2021 American Physiological Society. Compr Physiol 11:1501-1530, 2021.

A computational model of contributors to pulmonary hypertensive disease: impacts of whole lung and focal disease distributions.

Pulmonary hypertension has multiple etiologies and so can be difficult to diagnose, prognose, and treat. Diagnosis is typically made via invasive hemodynamic measurements in the main pulmonary artery and is based on observed elevation of mean pulmonary artery pressure. This static mean pressure enables diagnosis, but does not easily allow assessment of the severity of pulmonary hypertension, nor the etiology of the disease, which may impact treatment. Assessment of the dynamic properties of pressure and flow data obtained from catheterization potentially allows more meaningful assessment of the strain on the right heart and may help to distinguish between disease phenotypes. However, mechanistic understanding of how the distribution of disease in the lung leading to pulmonary hypertension impacts the dynamics of blood flow in the main pulmonary artery and/or the pulmonary capillaries is lacking. We present a computational model of the pulmonary vasculature, parameterized to characteristic features of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension to help understand how the two conditions differ in terms of pulmonary vascular response to disease. Our model incorporates key features known to contribute to pulmonary vascular function in health and disease, including anatomical structure and multiple contributions from gravity. The model suggests that dynamic measurements obtained from catheterization potentially distinguish between distal and proximal vasculopathy typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension. However, the model suggests a non-linear relationship between these data and vascular structural changes typical of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension which may impede analysis of these metrics to distinguish between cohorts.

Human lungs are created to breathe clean air: the questionable quantification of vaping safety "95% less harmful".

The New Zealand government is aiming for Smokefree Aotorea, equivalent to a reduction in smoking prevalence to 5% or less by 2025. E-cigarettes may be one tool to meet this target, but how safe are they? Little is known about their long-term health implications in humans. In 2015, Public Health England commissioned a report summarising the available literature on e-cigarettes and coined the now well-known quantification that "e-cigarettes are 95% less harmful to your health than normal cigarettes". In this article, we argue that this is an unfounded quantification because the data required to make this quantification are not yet available. The value of '95% safer' was based on a study estimating the relative harms of nicotine-containing products that utilised scoring from a selected panel of experts. One of the key limitations of this quantification is that while the scores provided by the panellists were informed by knowledge, they are fundamentally value judgements and are not an exact science. E-cigarettes are probably safer than conventional cigarettes, however, there is mounting evidence that they are not without harm and the long-term health impacts are not yet known.

Integrated lung tissue mechanics one piece at a time: Computational modeling across the scales of biology.

The lung is a delicately balanced and highly integrated mechanical system. Lung tissue is continuously exposed to the environment via the air we breathe, making it susceptible to damage. As a consequence, respiratory diseases present a huge burden on society and their prevalence continues to rise. Emergent function is produced not only by the sum of the function of its individual components but also by the complex feedback and interactions occurring across the biological scales - from genes to proteins, cells, tissue and whole organ - and back again. Computational modeling provides the necessary framework for pulling apart and putting back together the pieces of the body and organ systems so that we can fully understand how they function in both health and disease. In this review, we discuss models of lung tissue mechanics spanning from the protein level (the extracellular matrix) through to the level of cells, tissue and whole organ, many of which have been developed in isolation. This is a vital step in the process but to understand the emergent behavior of the lung, we must work towards integrating these component parts and accounting for feedback across the scales, such as mechanotransduction. These interactions will be key to unlocking the mechanisms occurring in disease and in seeking new pharmacological targets and improving personalized healthcare.

Modelling pulmonary blood flow.

Computational model analysis has been used widely to understand and interpret complexity of interactions in the pulmonary system. Pulmonary blood transport is a multi-scale phenomenon that involves scale-dependent structure and function, therefore requiring different model assumptions for the microcirculation and the arterial or venous flows. The blood transport systems interact with the surrounding lung tissue, and are dependent on hydrostatic pressure gradients, control of vasoconstriction, and the topology and material composition of the vascular trees. This review focuses on computational models that have been developed to study the different mechanisms contributing to regional perfusion of the lung. Different models for the microcirculation and the pulmonary arteries are considered, including fractal approaches and anatomically-based methods. The studies that are reviewed illustrate the different complementary approaches that can be used to address the same physiological question of flow heterogeneity.

Multi-scale models of the lung airways and vascular system.

Medical imaging now enables measurement of the lung in vivo at controlled volumes, prompting the development of increasingly sophisticated models of the geometry of the lung, from the largest airways and vessels to the alveolar tissue and capillary bed. We have developed methods for deriving subject-specific models of the airway and pulmonary vascular trees and have developed methods to represent the structure of alveolated parenchymal tissue and the segmented alveolocapillary network. These multi-scale models have geometry that is consistent with published lung morphometry and have defined relationships with one another. The models can therefore be readily exploited to couple multiple processes at the same physical scale (e.g., tissue mechanics and blood flow), or to couple over multiple scales (e.g., Newtonian flow in the large elastic blood vessels, and two-phase fluid transit in the microcirculation). We have studied function in the peripheral pulmonary system (alveolated airways and accompanying arterial and venous vessels) using a multi-scale approach that integrates detailed structure at this level of interest with estimates of air, blood and tissue pressures from functional models in the larger airways and vessels and simulations of soft tissue deformation of the whole lung. This approach allows us to study how ventilation of the acinus, mixing of inert gases and perfusion of the capillary bed varies with gravity, location in the lung and posture. An extension of the multi-scale models is incorporation of respiratory gas exchange, which can also be considered at several scales of interest.

In silico modeling of oxygen-enhanced MRI of specific ventilation.

Specific ventilation imaging (SVI) proposes that using oxygen-enhanced 1H MRI to capture signal change as subjects alternatively breathe room air and 100% O2 provides an estimate of specific ventilation distribution in the lung. How well this technique measures SV and the effect of currently adopted approaches of the technique on resulting SV measurement is open for further exploration. We investigated (1) How well does imaging a single sagittal lung slice represent whole lung SV? (2) What is the influence of pulmonary venous blood on the measured MRI signal and resultant SVI measure? and (3) How does inclusion of misaligned images affect SVI measurement? In this study, we utilized two patient-based in silico models of ventilation, perfusion, and gas exchange to address these questions for normal healthy lungs. Simulation results from the two healthy young subjects show that imaging a single slice is generally representative of whole lung SV distribution, with a calculated SV gradient within 90% of that calculated for whole lung distributions. Contribution of O2 from the venous circulation results in overestimation of SV at a regional level where major pulmonary veins cross the imaging plane, resulting in a 10% increase in SV gradient for the imaging slice. A worst-case scenario simulation of image misalignment increased the SV gradient by 11.4% for the imaged slice.

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.

Computational predictions of pulmonary blood flow gradients: gravity versus structure.

A computational model of blood flow through the human pulmonary arterial tree has been developed to investigate the mechanisms contributing to regional pulmonary perfusion in the isolated network when the lung is in different orientations. The arterial geometric model was constructed using a combination of computed tomography and a volume-filling branching algorithm. Equations governing conservation of mass, momentum, and vessel distension, incorporating gravity, were solved to predict pressure, flow, and vessel radius. Analysis of results in the upright posture, with and without gravity, and in the inverted, prone, and supine postures reveals significant flow heterogeneity and a persistent decrease in flow in the cranial and caudal regions for all postures suggesting that vascular geometry makes a major contribution to regional flow with gravity having a lesser role. Results in the isolated arterial tree demonstrate that the vascular path lengths and therefore the positioning of the pulmonary trunk relative to the rest of the network play a significant role in the determination of flow.

Anatomically based finite element models of the human pulmonary arterial and venous trees including supernumerary vessels.

Studies of the origin of pulmonary blood flow heterogeneity have highlighted the significant role of vessel branching structure on flow distribution. To enable more detailed investigation of structure-function relationships in the pulmonary circulation, an anatomically based finite element model of the arterial and venous networks has been developed to more accurately reflect the geometry found in vivo. Geometric models of the arterial and venous tree structures are created using a combination of multidetector row X-ray computed tomography imaging to define around 2,500 vessels from each tree, a volume-filling branching algorithm to generate the remaining accompanying conducting vessels, and an empirically based algorithm to generate the supernumerary vessel geometry. The explicit generation of supernumerary vessels is a unique feature of the computational model. Analysis of branching properties and geometric parameters demonstrates close correlation between the model geometry and anatomical measures of human pulmonary blood vessels. A total of 12 Strahler orders for the arterial system and 10 Strahler orders for the venous system are generated, down to the equivalent level of the terminal bronchioles in the bronchial tree. A simple Poiseuille flow solution, assuming rigid vessels, is obtained within the arterial geometry of the left lung, demonstrating a large amount of heterogeneity in the flow distribution, especially with inclusion of supernumerary vessels. This model has been constructed to accurately represent available morphometric data derived from the complex asymmetric branching structure of the human pulmonary vasculature in a form that will be suitable for application in functional simulations.

Investigation of the relative effects of vascular branching structure and gravity on pulmonary arterial blood flow heterogeneity via an image-based computational model.

RATIONALE AND OBJECTIVES: A computational model of blood flow through the human pulmonary arterial tree has been developed to investigate the relative influence of branching structure and gravity on blood flow distribution in the human lung. MATERIALS AND METHODS: Geometric models of the largest arterial vessels and lobar boundaries were first derived using multidetector row x-ray computed tomography (MDCT) scans. Further accompanying arterial vessels were generated from the MDCT vessel endpoints into the lobar volumes using a volume-filling branching algorithm. Equations governing the conservation of mass and momentum were solved within the geometric model to calculate pressure, velocity, and vessel radius. Blood flow results in the anatomically based model, with and without gravity, and in a symmetric geometric model were compared to investigate their relative contributions to blood flow heterogeneity. RESULTS: Results showed a persistent blood flow gradient and flow heterogeneity in the absence of gravitational forces in the anatomically based model. Comparison with flow results in the symmetric model revealed that the asymmetric vascular branching structure was largely responsible for producing this heterogeneity. Analysis of average results in varying slice thicknesses illustrated a clear flow gradient because of gravity in "lower resolution" data (thicker slices), but on examination of higher resolution data, a trend was less obvious. CONCLUSIONS: Results suggest that although gravity does influence flow distribution, the influence of the tree branching structure is also a dominant factor. These results are consistent with high-resolution experimental studies that have demonstrated gravity to be only a minor determinant of blood flow distribution.

Development and Analysis of Patient-Based Complete Conducting Airways Models.

The analysis of high-resolution computed tomography (CT) images of the lung is dependent on inter-subject differences in airway geometry. The application of computational models in understanding the significance of these differences has previously been shown to be a useful tool in biomedical research. Studies using image-based geometries alone are limited to the analysis of the central airways, down to generation 6-10, as other airways are not visible on high-resolution CT. However, airways distal to this, often termed the small airways, are known to play a crucial role in common airway diseases such as asthma and chronic obstructive pulmonary disease (COPD). Other studies have incorporated an algorithmic approach to extrapolate CT segmented airways in order to obtain a complete conducting airway tree down to the level of the acinus. These models have typically been used for mechanistic studies, but also have the potential to be used in a patient-specific setting. In the current study, an image analysis and modelling pipeline was developed and applied to a number of healthy (n = 11) and asthmatic (n = 24) CT patient scans to produce complete patient-based airway models to the acinar level (mean terminal generation 15.8 ± 0.47). The resulting models are analysed in terms of morphometric properties and seen to be consistent with previous work. A number of global clinical lung function measures are compared to resistance predictions in the models to assess their suitability for use in a patient-specific setting. We show a significant difference (p < 0.01) in airways resistance at all tested flow rates in complete airway trees built using CT data from severe asthmatics (GINA 3-5) versus healthy subjects. Further, model predictions of airways resistance at all flow rates are shown to correlate with patient forced expiratory volume in one second (FEV1) (Spearman ρ = -0.65, p < 0.001) and, at low flow rates (0.00017 L/s), FEV1 over forced vital capacity (FEV1/FVC) (ρ = -0.58, p < 0.001). We conclude that the pipeline and anatomical models can be used directly in mechanistic modelling studies and can form the basis for future patient-based modelling studies.

Dynamic flow characteristics in normal and asthmatic lungs.

Complex flow patterns exist within the asymmetric branching airway network in the lungs. These flow patterns are known to become increasingly heterogeneous during disease as a result of various mechanisms such as bronchoconstriction or alterations in lung tissue compliance. Here, we present a coupled model of tissue deformation and network airflow enabling predictions of dynamic flow properties, including temporal flow rate, pressure distribution, and the occurrence of reverse flows. We created two patient-specific airway geometries, one for a healthy subject and one for a severe asthmatic subject, derived using a combination of high-resolution CT data and a volume-filling branching algorithm. In addition, we created virtually constricted airway geometry by reducing the airway radii of the healthy subject model. The flow model was applied to these three different geometries to solve the pressure and flow distribution over a breathing cycle. The differences in wave phase of the flows in parallel airways induced by asymmetric airway geometry and bidirectional interaction between intra-acinar and airway network pressures were small in central airways but were more evident in peripheral airways. The asthmatic model showed elevated ventilation heterogeneity and significant flow disturbance. The reverse flows in the asthmatic model not only altered the local flow characteristics but also affected total lung resistance. The clinical significance of temporal flow disturbance on lung ventilation in normal airway model is obscure. However, increased flow disturbance and ventilation heterogeneity observed in the asthmatic model suggests that reverse flow may be an important factor for asthmatic lung function.

Developing integrative computational models of pulmonary structure.

Integrative computational modeling of the pulmonary system aims to incorporate interactions between the lung's subsystems by means of a hierarchy of structural and functional models. This requires detailed imaging-based data, along with a wide range of functional information from experiments. Advances in computed tomography imaging technology ensure that high-resolution data are now readily available upon which the structure of these models can be based. We present methods for constructing anatomically realistic finite element models of interrelated pulmonary structures from such data. Segmented human lung lobe data are fit to high-order (cubic Hermite) volume elements. Meshes for the conducting airways and pulmonary arteries and veins are constructed within the lobe mesh, using a combination of fitting to imaging data and a bifurcating-distributive algorithm. The algorithm generates an airway-consistent mesh within a host volume, and this airway mesh is then used as a template for generating blood vessel models. The lung parenchyma is modeled as a space-filling three-dimensional (3D) Voronoi mesh, with generated geometry consistent with the alveolated airway structure. Pulmonary capillaries are generated over the alveolar model, as a 2D Voronoi mesh. These structural models have been compared extensively with morphometric data to verify that their geometry is representative of the pulmonary system. The models are designed to be integrative: they relate multiple structural systems within the same individual, and their use as computational meshes allows application of spatially distributed properties.