Computational models of structure-function relationships in the pulmonary circulation and their validation

The pulmonary airway, arterial, venous and capillary networks are vast complex branching and converging systems that are mechanically coupled to the surrounding lung tissue. Early studies that examined vascular or airway geometry relied on measurements from casts, but medical imaging now enables measurement of the lung in vivo, at controlled lung volumes. The high-quality data that imaging provides have prompted development of increasingly sophisticated models of the geometry of the airway and pulmonary vascular trees. The accurate spatial relationships between airway, vessel and tissue in these imaging-derived models are necessary for computational analysis that aims to elucidate regional airway-vessel-tissue interactions. Predictions of blood flow through multiscale imaging-derived models of the pulmonary arteries and capillary bed reveal geometry-dependent patterns of perfusion in response to gravity and lung orientation that cannot be predicted with simplified, summary representations of the pulmonary transport trees. Validation of such predictions against measures from functional imaging holds significant potential for explaining and differentiating normal and disease-related heterogeneity in regional blood flow calculated using perfusion imaging.     

Three-dimensional segmentation and skeletonization to build an airway tree data structure for small animals

Quantitative analysis of intrathoracic airway tree geometry is important for objective evaluation of bronchial tree structure and function. Currently, there is more human data than small animal data on airway morphometry. In this study, we implemented a semi-automatic approach to quantitatively describe airway tree geometry by using high-resolution computed tomography (CT) images to build a tree data structure for small animals such as rats and mice. Silicon lung casts of the excised lungs from a canine and a mouse were used for micro-CT imaging of the airway trees. The programming language IDL was used to implement a 3D region-growing threshold algorithm for segmenting out the airway lung volume from the CT data. Subsequently, a fully-parallel 3D thinning algorithm was implemented in order to complete the skeletonization of the segmented airways. A tree data structure was then created and saved by parsing through the skeletonized volume using the Python programming language. Pertinent information such as the length of all airway segments was stored in the data structure. This approach was shown to be accurate and efficient for up to six generations for the canine lung cast and ten generations for the mouse lung cast.     

Computational modeling of airway and pulmonary vascular structure and function: development of a "lung physiome"

Computational models of lung structure and function necessarily span multiple spatial and temporal scales, i.e., dynamic molecular interactions give rise to whole organ function, and the link between these scales cannot be fully understood if only molecular or organ-level function is considered. Here, we review progress in constructing multiscale finite element models of lung structure and function that are aimed at providing a computational framework for bridging the spatial scales from molecular to whole organ. These include structural models of the intact lung, embedded models of the pulmonary airways that couple to model lung tissue, and models of the pulmonary vasculature that account for distinct structural differences at the extra- and intra-acinar levels. Biophysically based functional models for tissue deformation, pulmonary blood flow, and airway bronchoconstriction are also described. The development of these advanced multiscale models has led to a better understanding of complex physiological mechanisms that govern regional lung perfusion and emergent heterogeneity during bronchoconstriction.     

Computational modeling of the obstructive lung diseases asthma and COPD

Asthma and chronic obstructive pulmonary disease (COPD) are characterized by airway obstruction and airflow limitation and pose a huge burden to society. These obstructive lung diseases impact the lung physiology across multiple biological scales. Environmental stimuli are introduced via inhalation at the organ scale, and consequently impact upon the tissue, cellular and sub-cellular scale by triggering signaling pathways. These changes are propagated upwards to the organ level again and vice versa. In order to understand the pathophysiology behind these diseases we need to integrate and understand changes occurring across these scales and this is the driving force for multiscale computational modeling.There is an urgent need for improved diagnosis and assessment of obstructive lung diseases. Standard clinical measures are based on global function tests which ignore the highly heterogeneous regional changes that are characteristic of obstructive lung disease pathophysiology. Advances in scanning technology such as hyperpolarized gas MRI has led to new regional measurements of ventilation, perfusion and gas diffusion in the lungs, while new image processing techniques allow these measures to be combined with information from structural imaging such as Computed Tomography (CT). However, it is not yet known how to derive clinical measures for obstructive diseases from this wealth of new data. Computational modeling offers a powerful approach for investigating this relationship between imaging measurements and disease severity, and understanding the effects of different disease subtypes, which is key to developing improved diagnostic methods.Gaining an understanding of a system as complex as the respiratory system is difficult if not impossible via experimental methods alone. Computational models offer a complementary method to unravel the structure-function relationships occurring within a multiscale, multiphysics system such as this. Here we review the current state-of-the-art in techniques developed for pulmonary image analysis, development of structural models of the respiratory system and predictions of function within these models. We discuss application of modeling techniques to obstructive lung diseases, namely asthma and emphysema and the use of models to predict response to therapy. Finally we introduce a large European project, AirPROM that is developing multiscale models to investigate structure-function relationships in asthma and COPD.     

Assessment of mechanical ventilation parameters on respiratory mechanics

Better understanding of airway mechanics is very important in order to avoid lung injuries for patients undergoing mechanical ventilation for treatment of respiratory problems in intensive-care medicine, as well as pulmonary medicine. Mechanical ventilation depends on several parameters, all of which affect the patient outcome. As there are no systematic numerical investigations of the role of mechanical ventilation parameters on airway mechanics, the objective of this study was to investigate the role of mechanical ventilation parameters on airway mechanics using coupled fluid-solid computational analysis. For the airway geometry of 3 to 5 generations considered, the simulation results showed that airflow velocity increased with increasing airflow rate. Airway pressure increased with increasing airflow rate, tidal volume and positive end-expiratory pressure (PEEP). Airway displacement and airway strains increased with increasing airflow rate, tidal volume and PEEP form mechanical ventilation. Among various waveforms considered, sine waveform provided the highest airflow velocity and airway pressure while descending waveform provided the lowest airway pressure, airway displacement and airway strains. These results combined with optimization suggest that it is possible to obtain a set of mechanical ventilation strategies to avoid lung injuries in patients.     

Generation of an Anatomically Based Geometric Coronary Model

A discrete anatomically accurate finite element model of the largest six generations of the coronary arterial network is developed. Using a previously developed anatomically accurate model of ventricular geometry the boundaries of the coronary mesh are defined from measured epicardial coronaries. Network topology is then generated stochastically from published anatomical data. Spatial information is added to this topological data using an avoidance algorithm accounting for global network geometry and optimal local branch angle properties. The generated vessel lengths, radii and connectivity are consistent with the published studies and a relativity even spatial distribution of vessels within the ventricular mesh is achieved. The local finite element coordinates of the coronary nodes within the ventricular mesh are calculated such that the coronary geometry can be recalculated within a deformed ventricular mesh. © 2000 Biomedical Engineering Society. PAC00: 8710+e, 8718Bb, 0270Dh     

Measurement of the internal diameter of plastic tubes from projection MR images using a model-based least-squares fit approach

Hyperpolarized (HP) 3He MRI is an emerging tool in the diagnosis and evaluation of pulmonary diseases involving bronchoconstriction, such as asthma. Previously, airway diameters from dynamic HP 3He MR images of the lung were assessed manually and subjectively, and were thus prone to uncertainties associated with human error and partial volume effects. A model-based algorithm capable of fully utilizing pixel intensity profile information and attaining subpixel resolution has been developed to measure surrogate airway diameters from HP 3He MR static projection images of plastic tubes. This goal was achieved by fitting ideal pixel intensity profiles for various diameter (6.4 to 19.1 mm) circular tubes to actual pixel intensity data. A phantom was constructed from plastic tubes of various diameters connected in series and filled with water mixed with contrast agent. Projection MR images were then taken of the phantom. The favorable performance of the model-based algorithm compared to manual assessment demonstrates the viability of our approach. The manual and algorithm approaches yielded diameter measurements that generally stayed within 1 x the pixel dimension. However, inconsistency of the manual approach can be observed from the larger standard deviations of its measured values. The method was then extended to HP 3He MRI, producing encouraging results at tube diameters characteristic of airways beyond the second generation, thereby justifying their application to lung airway imaging and measurement. Potential obstacles when measuring airway diameters using this method are discussed.     

Design,Development, and Analysis of a Surrogate for Pulmonary Injury Prediction

Current anthropomorphic test devices (ATDs) measure chest acceleration and deflection to assess risk of injury to the thorax. This study presents a lung surrogate prototype designed to expand the injury assessment capabilities of ATDs to include a risk measure for pulmonary contusion (PC). The surrogate augments these existing measures by providing pressure data specific to the lung and its lobes. The prototype was created from a rendering of a 50th percentile male lung inflated to normal inspiration, obtained from clinical CT data. Surrogate size, lobe volume, and airway cross sections were selected to match the morphology of the lung. Elastomeric urethane was molded via rapid prototyping to create a functional prototype. Pressure sensors in each of the five terminal airways independently monitored pressure traces in the lobes during impacts to the surrogate. Software was created to analyze the surrogate impact pressure data, determine the lobe with the greatest pressure rise for a particular impact, and estimate the initial speed of surface deformation. Calibration testing indicates an approximately linear relationship between peak lobe pressure and surface impact speed. No type I or II errors were demonstrated during lobe detection testing. During repeatability testing, the standard deviation was between 2 and 4% of the mean peak pressure. Ongoing research will focus on correlating surrogate data, pressure pulses, or surface deformation, to risk functions for PC.     

Statistical modelling of the whole human femur incorporating geometric and material properties

When analysing the performance of orthopaedic implants the vast majority of computational studies use either a single or limited number of bone models. The results are then extrapolated to the population as a whole, overlooking the inherent and large interpatient variability in bone quality and geometry. This paper describes the creation of a three dimensional, statistical, finite element analysis (FEA) ready model of the femur using principal component analysis. To achieve this a registration scheme based on elastic surface matching and a mesh morphing algorithm has been developed. This method is fully automated enabling registration and generation of high resolution models. The variation in both geometry and material properties was extracted from 46 computer tomography scans and captured by the statistical model. Analysis of mesh quality showed this was maintained throughout the model generation and sampling process. Reconstruction of the training femurs showed 35 eigenmodes were required for accurate reproduction. A set of unique, anatomically realistic femur models were generated using the statistical model, with a variation comparable to that seen in the population. This study illustrates a methodology with the potential to generate femur models incorporating material properties for large scale multi-femur finite element studies.     

Predicted Tracheobronchial and Pulmonary Deposition in a Murine Asthma Model

Particulate matter dosimetry provides the critical link between exposures and initial doses reaching various sites in the respiratory tract. To extrapolate findings from animal models to humans, quantitative respiratory‐tract anatomical data dosimetry in these animal models is required. The goal of this study was to provide anatomical information for the tracheobronchial and pulmonary region so predictions of particle deposition could be performed for a widely used model of asthma; the sensitized Balb/c mouse. Tracheobronchial airway morphometry of sensitized male Balb/c mice was generated from three in situ prepared lung casts. Distribution of the number of generations to terminal bronchiole for each lung lobe was determined by assigning a unique binary number to each airway. This strategy enabled the median path length to terminal bronchiole to be determined. A total of 25 median length paths to terminal bronchiole were measured (airway length, diameter, and branch angle) in each lung cast. These 25 paths were proportionately distributed among the six lobes based upon the number of median length pathways in each cast. Airway length, diameter, and branch angle were measured for each airway in the 25 median length pathways. Measurements of airway length, diameter, and branch angle for each generation were averaged to create a typical path tracheobronchial anatomy model. A pulmonary airway model was also developed so that particle deposition predictions could be performed for particle diameters of 0.2–10 micrometers. Particle deposition efficiency predictions were consistent with in vivo measured deposition. Anat Rec, 290:1309–1314, 2007. © 2007 Wiley‐Liss, Inc.     

A cubic B-spline-based hybrid registration of lung CT images for a dynamic airway geometric model with large deformation

The goal of this study is to develop a matching algorithm that can handle large geometric changes in x-ray computed tomography (CT)-derived lung geometry occurring during deep breath maneuvers. These geometric relationships are further utilized to build a dynamic lung airway model for computational fluid dynamics (CFD) studies of pulmonary air flow. The proposed algorithm is based on a cubic B-spline-based hybrid registration framework that incorporates anatomic landmark information with intensity patterns. A sequence of invertible B-splines is composed in a multiresolution framework to ensure local invertibility of the large deformation transformation and a physiologically meaningful similarity measure is adopted to compensate for changes in voxel intensity due to inflation. Registrations are performed using the proposed approach to match six pairs of 3D CT human lung datasets. Results show that the proposed approach has the ability to match the intensity pattern and the anatomical landmarks, and ensure local invertibility for large deformation transformations. Statistical results also show that the proposed hybrid approach yields significantly improved results as compared with approaches using either landmarks or intensity alone.     

Macro-optical color assessment of the pulmonary airways with subsequent three-dimensional multidetector-x-ray-computed-tomography assisted display

Bronchial diseases alter the color and structural characteristics of the pulmonary mucosa through changes in blood flow, epithelial thickening, and abnormal cell growth. Current analysis of these subtle changes includes visual interpretation of the airway color and topography through bronchoscopy procedures, and quantitative multidetector-x-ray-computed-tomography (MDCT)-based structural analysis, each affording valuable insights to the health of the lungs. The fusion of the bronchoscopy and MDCT image data promises to provide a synergistic data set exhibiting both mucosal color and topography crucial to fostering an understanding of airway structure and function. A real-time airway color analysis imaging system is developed and utilized to perform pulmonary mucosal color assessment in healthy volunteers with subsequent comparative studies performed in example disease states. Our results indicate that macro-optical digital bronchoscopes with appropriate image analysis may have a significant impact on understanding bronchial diseases. To ensure the correct interpretation of scene content, which is critical in the assessment of airway topography, we are developing methods of extracting 3-D structure from 2-D bronchoscope images utilizing MDCT imaging techniques. The resulting 3-D true-color images of the pulmonary mucosa facilitate the combination of mucosal color and topography analysis as well as region of interest localization within the airway tree.     

Impact of Ventilation Frequency and Parenchymal Stiffness on Flow and Pressure Distribution in a Canine Lung Model

To determine the impact of ventilation frequency, lung volume, and parenchymal stiffness on ventilation distribution, we developed an anatomically-based computational model of the canine lung. Each lobe of the model consists of an asymmetric branching airway network subtended by terminal, viscoelastic acinar units. The model allows for empiric dependencies of airway segment dimensions and parenchymal stiffness on transpulmonary pressure. We simulated the effects of lung volume and parenchymal recoil on global lung impedance and ventilation distribution from 0.1 to 100 Hz, with mean transpulmonary pressures from 5 to 25 cm H₂O. With increasing lung volume, the distribution of acinar flows narrowed and became more synchronous for frequencies below resonance. At higher frequencies, large variations in acinar flow were observed. Maximum acinar flow occurred at first antiresonance frequency, where lung impedance achieved a local maximum. The distribution of acinar pressures became very heterogeneous and amplified relative to tracheal pressure at the resonant frequency. These data demonstrate the important interaction between frequency and lung tissue stiffness on the distribution of acinar flows and pressures. These simulations provide useful information for the optimization of frequency, lung volume, and mean airway pressure during conventional ventilation or high frequency oscillation (HFOV). Moreover our model indicates that an optimal HFOV bandwidth exists between the resonant and antiresonant frequencies, for which interregional gas mixing is maximized.     

Identification system for airways in lung models: a note

A lobar notational system for the identification of airways in the mammalian lung is presented. This system was developed to identify uniquely the location of morphometric and deposition data within a lobe as well as within the lung, and to provide for easy and efficient data reduction. In addition, this notational system can be used to identify main stems like those found in the monopodial lung, and incorporates identification of terminal bronchioles in the airway identifier. The lobar notational system is composed of a two-character lobe code, followed by a third character identifying the branching structure as monopodial or symmetric. The fourth digit identifies the relative position of a branch within the lobe. Subsequent digits identify the airway's relative location within the branching.     

戒烟与肺康复对慢阻肺患者发病机制及疗效的研究

慢性阻塞性肺疾病是目前最常见的高发病率,高伤残率,高死亡的一种疾病,发病机制比较复杂,同时吸烟在慢阻肺的危险因素中是最重要的一项,可以通过破坏支气管,加重气道炎症和气道重塑,通过气道壁和肺实质产生炎症作用,从而导致结构和功能的改变。戒烟可以有效预防慢阻肺患者早期死亡,是需要长期坚持预防的措施。肺康复治疗能明显改善患者的肺功能,在慢阻肺预防控制中起到非常重要的作用。本文主要通过介绍戒烟,早期肺康复的干预,肺康复的传统以及现代模式等方面对肺康复的效果进行综述。     

CT肺功能指标判断评价石棉肺患者呼吸功能的研究

目的 采用多层螺旋CT肺功能成像技术评价石棉肺患者的呼吸功能障碍程度和肺功能指标的改变及特点.方法 61例石棉肺患者与30名健康者根据用力肺活量和第1秒用力肺活量分为肺呼吸功能正常组、轻度损伤组、中重度损伤组.对每个受检者分别在深吸气末和深呼气末屏住气行全肺扫描,对肺容积、肺密度、小气道指标进行测定.结果 肺呼吸功能正常组、轻度损伤组、中重度损伤组的各项肺容积指标(吸气与呼气末肺容积、容积差、容积比)差异具有统计学意义(均P＜0.05);各项平均肺密度指标(吸气与呼气末平均肺密度、肺密度差、肺密度比)差异具有统计学意义(均P＜0.05);各项小气道指标(吸气与呼气末壁厚直径比率、支气管壁面积率)差异具有统计学意义(均P＜0.05).结论 CT肺功能成像技术可以用来评价石棉肺患者的呼吸功能障碍程度.随着石棉肺患者肺呼吸功能障碍的发展,其肺总量降低,双肺的残气量逐渐增多,肺气肿逐渐加重,小气道壁和肺泡隔纤维性肥厚逐渐增厚.     

An Automated Self‐Similarity Analysis of the Pulmonary Tree of the Sprague–Dawley Rat

We present the results of an automated analysis of the morphometry of the pulmonary airway trees of the Sprague–Dawley rat. Our work is motivated by a need to inform lower‐dimensional mathematical models to prescribe realistic boundary conditions for multiscale hybrid models of rat lung mechanics. Silicone casts were made from three age‐matched, male Sprague–Dawley rats, immersed in a gel containing a contrast agent and subsequently imaged with magnetic resonance (MR). From a segmentation of this data, we extracted a connected graph, representing the airway centerline. Segment statistics (lengths and diameters) were derived from this graph. To validate this MR imaging/digital analysis method, airway segment measurements were compared with nearly 1,000 measurements collected by hand using an optical microscope from one of the rat lung casts. To evaluate the reproducibility of the MR imaging/digital analysis method, two lung casts were each imaged three times with randomized orientations in the MR bore. Diameters and lengths of randomly selected airways were compared among each of the repeated imaging datasets to estimate the variability. Finally, we analyzed the morphometry of the airway tree by assembling individual airway segments into structures that span multiple generations, which we call branches. We show that branches not segments are the fundamental repeating unit in the rat lung and develop simple mathematical relationships describing these structures for the entire lung. Our analysis shows that airway diameters and lengths have both a deterministic and stochastic character. Anat Rec, 2008. © 2008 Wiley‐Liss, Inc.     

Study of the three-dimensional geometry of the central conducting airways in man using computed tomographic (CT) images

Clinical research on the deposition of inhaled substances (e.g. inhaled medications, airborne contaminants, fumes) in the lungs necessitates anatomical models of the airways. Current conducting airway models lack three‐dimensional (3D) reality as little information is available in the literature on the distribution of the airways in space. This is a limitation to the assessment or predictions of the particle deposition in relation to the subject’s anatomy. Detailed information on the full topology and morphology of the airways is thus required to model the airway tree realistically. This paper presents the length, diameter, gravity, coronal and sagittal angles that together describe completely the airways in 3D space. The angle at which the airways branch out from their parent (branching angle) and the rotation angle between successive bifurcation planes are also included. These data are from the study of two sets of airways computed tomography (CT) images. One CT scan was performed on a human tracheobronchial tree cast and the other on a healthy male volunteer. The airways in the first nine generations of the cast and in the first six conducting generations of the volunteer were measured using a computer‐based algorithm. The data contribute to the knowledge of the lung anatomy. In particular, the spatial structure of the airways is shown to be strongly defined by the central airways with clear angular lobar patterns. Such patterns tend to disappear with a mean gravity, coronal and sagittal angles of 90° in each generation higher than 13–15. The mean branching angle per generation appears independent of the lobe to which the airways belong. Non‐planar geometry at bifurcation is observed with the mean (± SD) bifurcation plane rotation angle of 79 ± 41° (n = 229). This angle appears constant over the generations studied. The data are useful for improving the 3D realism of the conducting airway structure modelling as well as for studying aerosol deposition, flow and biological significance of non‐planar airway trees using analytical and computational flow dynamics modelling.     

A universal algorithm for an improved finite element mesh generation Mesh quality assessment in comparison to former automated mesh-generators and an analytic model

The FE-modeling of complex anatomical structures is not solved satisfyingly so far. Voxel-based as opposed to contour-based algorithms allow an automated mesh generation based on the image data. Nonetheless their geometric precision is limited. We developed an automated mesh-generator that combines the advantages of voxel-based generation with improved representation of the geometry by displacement of nodes on the object-surface. Models of an artificial 3D-pipe-section and a skullbase were generated with different mesh-densities using the newly developed geometric, unsmoothed and smoothed voxel generators. Compared to the analytic calculation of the 3D-pipe-section model the normalized RMS error of the surface stress was 0.173-0.647 for the unsmoothed voxel models, 0.111-0.616 for the smoothed voxel models with small volume error and 0.126-0.273 for the geometric models. The highest element-energy error as a criterion for the mesh quality was 2.61x10(-2) N mm, 2.46x10(-2) N mm and 1.81x10(-2) N mm for unsmoothed, smoothed and geometric voxel models, respectively. The geometric model of the 3D-skullbase resulted in the lowest element-energy error and volume error. This algorithm also allowed the best representation of anatomical details. The presented geometric mesh-generator is universally applicable and allows an automated and accurate modeling by combining the advantages of the voxel-technique and of improved surface-modeling.