The lung physiome: merging imaging-based measures with predictive computational models

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

BACKGROUND AND OBJECTIVE

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

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

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

Origins of and lessons from quantitative functional X-ray computed tomography of the lung

Functional CT of the lung has emerged from quantitative CT (qCT). Structural details extracted at multiple lung volumes offer indices of function. Additionally, single volumetric images, if acquired at standardized lung volumes and body posture, can be used to model function by employing such engineering techniques as computational fluid dynamics. With the emergence of multispectral CT imaging including dual energy from energy integrating CT scanners and multienergy binning using the newly released photon counting CT technology, function is tagged via use of contrast agents. Lung disease phenotypes have previously been lumped together by the limitations of spirometry and plethysmography. QCT and its functional embodiment have been imbedded into studies seeking to characterize chronic obstructive pulmonary disease, severe asthma, interstitial lung disease and more. Reductions in radiation dose by an order of magnitude or more have been achieved. At the same time, we have seen significant increases in spatial and density resolution along with methodologic validations of extracted metrics. Together, these have allowed attention to turn towards more mild forms of disease and younger populations. In early applications, clinical CT offered anatomic details of the lung. Functional CT offers regional measures of lung mechanics, the assessment of functional small airways disease, as well as regional ventilation-perfusion matching (V/Q) and more. This paper will focus on the use of quantitative/functional CT for the non-invasive exploration of dynamic three-dimensional functioning of the breathing lung and beating heart within the unique negative pressure intrathoracic environment of the closed chest.

The Mechanobiology of Vascular Remodeling in the Aging Lung

Aging is accompanied by declining lung function and increasing susceptibility to lung diseases. The role of endothelial dysfunction and vascular remodeling in these changes is supported by growing evidence, but underlying mechanisms remain elusive. In this review we summarize functional, structural, and molecular changes in the aging pulmonary vasculature and explore how interacting aging and mechanobiological cues may drive progressive vascular remodeling in the lungs.

A dynamical overview of droplets in the transmission of respiratory infectious diseases

The outbreak of the coronavirus disease has drawn public attention to the transmission of infectious pathogens, and as major carriers of those pathogens, respiratory droplets play an important role in the process of transmission. This Review describes respiratory droplets from a physical and mechanical perspective, especially their correlation with the transmission of infectious pathogens. It covers the important aspects of (i) the generation and expulsion of droplets during respiratory activities, (ii) the transport and evolution of respiratory droplets in the ambient environment, and (iii) the inhalation and deposition of droplets in the human respiratory tract. State-of-the-art experimental, computational, and theoretical models and results are presented, and the corresponding knowledge gaps are identified. This Review stresses the multidisciplinary nature of its subject and appeals for collaboration among different fields to fight the present pandemic.

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

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.

Optimising mechanical ventilation through model-based methods and automation

Mechanical ventilation (MV) is a core life-support therapy for patients suffering from respiratory failure or acute respiratory distress syndrome (ARDS). Respiratory failure is a secondary outcome of a range of injuries and diseases, and results in almost half of all intensive care unit (ICU) patients receiving some form of MV. Funding the increasing demand for ICU is a major issue and MV, in particular, can double the cost per day due to significant patient variability, over-sedation, and the large amount of clinician time required for patient management. Reducing cost in this area requires both a decrease in the average duration of MV by improving care, and a reduction in clinical workload. Both could be achieved by safely automating all or part of MV care via model-based dynamic systems modelling and control methods are ideally suited to address these problems. This paper presents common lung models, and provides a vision for a more automated future and explores predictive capacity of some current models. This vision includes the use of model-based methods to gain real-time insight to patient condition, improve safety through the forward prediction of outcomes to changes in MV, and develop virtual patients for in-silico design and testing of clinical protocols. Finally, the use of dynamic systems models and system identification to guide therapy for improved personalised control of oxygenation and MV therapy in the ICU will be considered. Such methods are a major part of the future of medicine, which includes greater personalisation and predictive capacity to both optimise care and reduce costs. This review thus presents the state of the art in how dynamic systems and control methods can be applied to transform this core area of ICU medicine.

A virtual patient model for mechanical ventilation

BACKGROUND AND OBJECTIVES

Mechanical ventilation (MV) is a primary therapy for patients with acute respiratory failure. However, poorly selected ventilator settings can cause further lung damage due to heterogeneity of healthy and damaged alveoli. Varying positive-end-expiratory-pressure (PEEP) to a point of minimum elastance is a lung protective ventilator strategy. However, even low levels of PEEP can lead to ventilator induced lung injury for individuals with highly inflamed pulmonary tissue. Hence, models that could accurately predict peak inspiratory pressures after changes to PEEP could improve clinician confidence in attempting potentially beneficial treatment strategies.

METHODS

This study develops and validates a physiologically relevant respiratory model that captures elastance and resistance via basis functions within a well-validated single compartment lung model. The model can be personalised using information available at a low PEEP to predict lung mechanics at a higher PEEP. Proof of concept validation is undertaken with data from four patients and eight recruitment manoeuvre arms.

RESULTS

Results show low error when predicting upwards over the clinically relevant pressure range, with the model able to predict peak inspiratory pressure with less than 10% error over 90% of the range of PEEP changes up to 12 cmH₂O.

CONCLUSIONS

The results provide an in-silico model-based means of predicting clinically relevant responses to changes in MV therapy, which is the foundation of a first virtual patient for MV.

Quantification of tissue-engineered trachea performance with computational fluid dynamics

OBJECTIVES/HYPOTHESIS

Current techniques for airway characterization include endoscopic or radiographic measurements that produce static, two-dimensional descriptions. As pathology can be multilevel, irregularly shaped, and dynamic, minimal luminal area (MLA) may not provide the most comprehensive description or diagnostic metric. Our aim was to examine the utilization of computational fluid dynamics (CFD) for the purpose of defining airway stenosis using an ovine model of tissue-engineered tracheal graft (TETG) implantation.

STUDY DESIGN

Animal research model.

METHODS

TETGs were implanted into sheep, and MLA was quantified with imaging and endoscopic measurements. Graft stenosis was managed with endoscopic dilation and stenting when indicated. Geometries of the TETG were reconstructed from three-dimensional fluoroscopic images. CFD simulations were used to calculate peak flow velocity (PFV) and peak wall shear stress (PWSS). These metrics were compared to values derived from a quantitative respiratory symptom score.

RESULTS

Elevated PFV and PWSS derived from CFD modeling correlated with increased respiratory symptoms. Immediate pre- and postimplantation CFD metrics were similar, and implanted sheep were asymptomatic. Respiratory symptoms improved with stenting, which maintained graft architecture similar to dilation procedures. With stenting, baseline PFV (0.33 m/s) and PWSS (0.006 Pa) were sustained for the remainder of the study. MLA measurements collected via bronchoscopy were also correlated with respiratory symptoms. PFV and PWSS found via CFD were correlated (R²  = 0.92 and 0.99, respectively) with respiratory symptoms compared to MLA (R²  = 0.61).

CONCLUSIONS

CFD is valid for informed interventions based on multilevel, complex airflow and airway characteristics. Furthermore, CFD may be used to evaluate TETG functionality.

LEVEL OF EVIDENCE

NA. Laryngoscope, E272-E279, 2018.

Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies.

Metrics of lung tissue heterogeneity depend on BMI but not age

Altered parenchymal microstructure and complexity have been observed in older age. How to distinguish between healthy, expected changes and early signs of pathology remains poorly understood. An objective quantitative analysis of computed tomography imaging was conducted to compare mean lung density, tissue density distributions, and tissue heterogeneity in 16 subjects, 8 aged >60 yr who were gender and body mass index matched with 8 subjects aged <30 yr. Subjects had never been smokers, with no prior respiratory disease, and no radiologically identified abnormalities on computed tomography. Volume-controlled breath hold imaging acquired at 80% vital capacity (end inspiration) and 55% vital capacity (end expiration) were used for analysis. Mean lung density was not different between the age groups at end inspiration ( P = 0.806) but was larger in the younger group at end expiration (0.26 ± 0.033 vs. 0.22 ± 0.026, P = 0.008), as is expected due to increased air trapping in the older population. However, gravitational gradients of tissue density did not differ with age; the only difference in distribution of tissue density between the two age groups was a lower density in the apices of the older group at end expiration. The heterogeneity of the lung tissue assessed using two metrics showed significant differences between end inspiration and end expiration, no dependence on age, and a significant relationship with body mass index at both lung volumes when heterogeneity was calculated using quadtree decomposition but only at end expiration when using a fractal dimension. NEW & NOTEWORTHY Changes to lung tissue heterogeneity can be a normal part of aging but can also be an early indicator of disease. We use novel techniques, which have previously not been used on thoracic computed tomography imaging, to quantify lung tissue heterogeneity in young and old healthy subjects. Our results show no dependence on age but a significant correlation with body mass index.

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.

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.

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

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11 % of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches.

Intratidal Overdistention and Derecruitment in the Injured Lung: A Simulation Study

GOAL

Ventilated patients with the acute respiratory distress syndrome (ARDS) are predisposed to cyclic parenchymal overdistention and derecruitment, which may worsen existing injury. We hypothesized that intratidal variations in global mechanics, as assessed at the airway opening, would reflect such distributed processes.

METHODS

We developed a computational lung model for determining local instantaneous pressure distributions and mechanical impedances continuously during a breath. Based on these distributions and previous literature, we simulated the within-breath variability of airway segment dimensions, parenchymal viscoelasticity, and acinar recruitment in an injured canine lung for tidal volumes( V_T ) of 10, 15, and 20 mL·kg^-1 and positive end-expiratory pressures (PEEP) of 5, 10, and 15 cm H₂O. Acini were allowed to transition between recruited and derecruited states when exposed to stochastically determined critical opening and closing pressures, respectively.

RESULTS

For conditions of low V_T and low PEEP, we observed small intratidal variations in global resistance and elastance, with a small number of cyclically recruited acini. However, with higher V_T and PEEP, larger variations in resistance and elastance were observed, and the majority of acini remained open throughout the breath. Changes in intratidal resistance, elastance, and impedance followed well-defined parabolic trajectories with tracheal pressure, achieving minima near 12 to 16 cm H₂O.

CONCLUSION

Intratidal variations in lung mechanics may allow for optimization of ventilator settings in patients with ARDS, by balancing lung recruitment against parenchymal overdistention.

SIGNIFICANCE

Titration of airway pressures based on variations in intratidal mechanics may mitigate processes associated with injurious ventilation.

Lung Structure and the Intrinsic Challenges of Gas Exchange

Structural and functional complexities of the mammalian lung evolved to meet a unique set of challenges, namely, the provision of efficient delivery of inspired air to all lung units within a confined thoracic space, to build a large gas exchange surface associated with minimal barrier thickness and a microvascular network to accommodate the entire right ventricular cardiac output while withstanding cyclic mechanical stresses that increase several folds from rest to exercise. Intricate regulatory mechanisms at every level ensure that the dynamic capacities of ventilation, perfusion, diffusion, and chemical binding to hemoglobin are commensurate with usual metabolic demands and periodic extreme needs for activity and survival. This article reviews the structural design of mammalian and human lung, its functional challenges, limitations, and potential for adaptation. We discuss (i) the evolutionary origin of alveolar lungs and its advantages and compromises, (ii) structural determinants of alveolar gas exchange, including architecture of conducting bronchovascular trees that converge in gas exchange units, (iii) the challenges of matching ventilation, perfusion, and diffusion and tissue-erythrocyte and thoracopulmonary interactions. The notion of erythrocytes as an integral component of the gas exchanger is emphasized. We further discuss the signals, sources, and limits of structural plasticity of the lung in alveolar hypoxia and following a loss of lung units, and the promise and caveats of interventions aimed at augmenting endogenous adaptive responses. Our objective is to understand how individual components are matched at multiple levels to optimize organ function in the face of physiological demands or pathological constraints.

Computational fluid dynamics simulation of airflow in the trachea and main bronchi for the subjects with left pulmonary artery sling

Background

Left pulmonary artery sling (LPAS) is a rare but severe congenital anomaly, in which the stenoses are formed in the trachea and/or main bronchi. Multi-detector computed tomography (MDCT) provides useful anatomical images, but does not offer functional information. The objective of the present study is to quantitatively analyze the airflow in the trachea and main bronchi of LPAS subjects through computational fluid dynamics (CFD) simulation.

Methods

Five subjects (four LPAS patients, one normal control) aging 6-19 months are analyzed. The geometric model of the trachea and the two main bronchi is extracted from the MDCT images. The inlet velocity is determined based on the body weight and the inlet area. Both the geometric model and personalized inflow conditions are imported into CFD software, ANSYS. The pressure drop, mass flow ratio through two bronchi, wall pressure, flow velocity and wall shear stress (WSS) are obtained, and compared to the normal control.

Results

Due to the tracheal and/or bronchial stenosis, the pressure drop for the LPAS patients ranges 78.9 - 914.5 Pa, much higher than for the normal control (0.7 Pa). The mass flow ratio through the two bronchi does not correlate with the sectional area ratio if the anomalous left pulmonary artery compresses the trachea or bronchi. It is suggested that the C-shaped trachea plays an important role on facilitating the air flow into the left bronchus with the inertia force. For LPAS subjects, the distributions of velocities, wall pressure and WSS are less regular than for the normal control. At the stenotic site, high velocity, low wall pressure and high WSS are observed.

Conclusions

Using geometric models extracted from CT images and the patient-specified inlet boundary conditions, CFD simulation can provide vital quantitative flow information for LPAS. Due to the stenosis, high pressure drops, inconsistent distributions of velocities, wall pressure and WSS are observed. The C-shaped trachea may facilitate a larger flow of air into the left bronchus under the inertial force, and decrease the ventilation of the right lung. Quantitative and personalized information may help understand the mechanism of LPAS and the correlations between stenosis and dyspnea, and facilitate the structural and functional assessment of LPAS.

Computational medicine: translating models to clinical care

Because of the inherent complexity of coupled nonlinear biological systems, the development of computational models is necessary for achieving a quantitative understanding of their structure and function in health and disease. Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks. Multiscale modeling links networks to cells, organs, and organ systems. Computational approaches are used to characterize anatomic shape and its variations in health and disease. In each case, the purposes of modeling are to capture all that we know about disease and to develop improved therapies tailored to the needs of individuals. We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health.

Space physiology IV: mathematical modeling of the cardiovascular system in space exploration

Mathematical modeling represents an important tool for analyzing cardiovascular function during spaceflight. This review describes how modeling of the cardiovascular system can contribute to space life science research and illustrates this process via modeling efforts to study postflight orthostatic intolerance (POI), a key issue for spaceflight. Examining this application also provides a context for considering broader applications of modeling techniques to the challenges of bioastronautics. POI, which affects a large fraction of astronauts in stand tests upon return to Earth, presents as dizziness, fainting and other symptoms, which can diminish crew performance and cause safety hazards. POI on the Moon or Mars could be more critical. In the field of bioastronautics, POI has been the dominant application of cardiovascular modeling for more than a decade, and a number of mechanisms for POI have been investigated. Modeling approaches include computational models with a range of incorporated factors and hemodynamic sophistication, and also physical models tested in parabolic and orbital flight. Mathematical methods such as parameter sensitivity analysis can help identify key system mechanisms. In the case of POI, this could lead to more effective countermeasures. Validation is a persistent issue in modeling efforts, and key considerations and needs for experimental data to synergistically improve understanding of cardiovascular responses are outlined. Future directions in cardiovascular modeling include subject-specific assessment of system status, as well as research on integrated physiological responses, leading, for instance, to assessment of subject-specific susceptibility to POI or effects of cardiovascular alterations on muscular, vision and cognitive function.

Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers

The analysis of anatomical tree-shape structures visualized in medical images provides insight into the relationship between tree topology and pathology of the corresponding organs. In this paper, we propose three methods to extract descriptive features of the branching topology; the asymmetry index, the encoding of branching patterns using a node labeling scheme and an extension of the Sholl analysis. Based on these descriptors, we present classification schemes for tree topologies with respect to the underlying pathology. Moreover, we present a classifier ensemble approach which combines the predictions of the individual classifiers to optimize the classification accuracy. We applied the proposed methodology to a dataset of x-ray galactograms, medical images which visualize the breast ductal tree, in order to recognize images with radiological findings regarding breast cancer. The experimental results demonstrate the effectiveness of the proposed framework compared to state-of-the-art techniques suggesting that the proposed descriptors provide more valuable information regarding the topological patterns of ductal trees and indicating the potential of facilitating early breast cancer diagnosis.

Phase-contrast MRI and CFD modeling of apparent ³He gas flow in rat pulmonary airways

Phase-contrast (PC) magnetic resonance imaging (MRI) with hyperpolarized ³He is potentially useful for developing and testing patient-specific models of pulmonary airflow. One challenge, however, is that PC-MRI provides apparent values of local ³He velocity that not only depend on actual airflow but also on gas diffusion. This not only blurs laminar flow patterns in narrow airways but also introduces anomalous airflow structure that reflects gas-wall interactions. Here, both effects are predicted in a live rat using computational fluid dynamics (CFD), and for the first time, simulated patterns of apparent ³He gas velocity are compared with in vivo PC-MRI. Results show (1) that correlations (R²) between measured and simulated airflow patterns increase from 0.23 to 0.79 simply by accounting for apparent ³He transport, and (2) that remaining differences are mainly due to uncertain airway segmentation and partial volume effects stemming from relatively coarse MRI resolution. Higher-fidelity testing of pulmonary airflow predictions should therefore be possible with future imaging improvements.

Biological constraints that limit compensation of a common skeletal trait variant lead to inequivalence of tibial function among healthy young adults

Having a better understanding of how complex systems like bone compensate for the natural variation in bone width to establish mechanical function will benefit efforts to identify traits contributing to fracture risk. Using a collection of pQCT images of the tibial diaphysis from 696 young adult women and men, we tested the hypothesis that bone cells cannot surmount the nonlinear relationship between bone width and whole bone stiffness to establish functional equivalence across a healthy population. Intrinsic cellular constraints limited the degree of compensation, leading to functional inequivalence relative to robustness, with slender tibias being as much as two to three times less stiff relative to body size compared with robust tibias. Using Path Analysis, we identified a network of compensatory trait interactions that explained 79% of the variation in whole-bone bending stiffness. Although slender tibias had significantly less cortical area relative to body size compared with robust tibias, it was the limited range in tissue modulus that was largely responsible for the functional inequivalence. Bone cells coordinately modulated mineralization as well as the cortical porosity associated with internal bone multicellular units (BMU)-based remodeling to adjust tissue modulus to compensate for robustness. Although anecdotal evidence suggests that functional inequivalence is tolerated under normal loading conditions, our concern is that the functional deficit of slender tibias may contribute to fracture susceptibility under extreme loading conditions, such as intense exercise during military training or falls in the elderly. Thus, we show the natural variation in bone robustness was associated with predictable functional deficits that were attributable to cellular constraints limiting the amount of compensation permissible in human long bone. Whether these cellular constraints can be circumvented prophylactically to better equilibrate function among individuals remains to be determined.

Pulmonary embolism: predicting disease severity

Pulmonary embolism (PE) is the most common cause of acute pulmonary hypertension, yet it is commonly undiagnosed, with risk of death if not recognized promptly and managed accordingly. Patients typically present with hypoxemia and hypomania, although the presentation varies greatly, being confounded by co-morbidities such as pre-existing cardio-respiratory disease. Previous studies have demonstrated variable patient outcomes in spite of similar extent and distribution of pulmonary vascular occlusion, but the path physiological determinants of outcome remain unclear. Computational models enable exact control over many of the compounding factors leading to functional outcomes and therefore provide a useful tool to understand and assess these mechanisms. We review the current state of pulmonary blood flow models. We present a pilot study within 10 patients presenting with acute PE, where patient-derived vascular occlusions are imposed onto an existing model of the pulmonary circulation enabling predictions of resultant haemodynamic after embolus occlusion. Results show that mechanical obstruction alone is not sufficient to cause pulmonary arterial hypertension, even when up to 65 per cent of lung tissue is occluded. Blood flow is found to preferentially redistribute to the gravitationally non-dependent regions. The presence of an additional downstream occlusion is found to significantly increase pressures.

Image-based modeling of lung structure and function

The current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of airflow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate airflow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft-tissue mechanics models.

Regional deposition of particles in an image-based airway model: large-eddy simulation and left-right lung ventilation asymmetry

Regional deposition and ventilation of particles by generation, lobe and lung during steady inhalation in a computed tomography (CT) based human airway model are investigated numerically. The airway model consists of a seven-generation human airway tree, with oral cavity, pharynx and larynx. The turbulent flow in the upper respiratory tract is simulated by large-eddy simulation. The flow boundary conditions at the peripheral airways are derived from CT images at two lung volumes to produce physiologically-realistic regional ventilation. Particles with diameter equal to or greater than 2.5 microns are selected for study because smaller particles tend to penetrate to the more distal parts of the lung. The current generational particle deposition efficiencies agree well with existing measurement data. Generational deposition efficiencies exhibit similar dependence on particle Stokes number regardless of generation, whereas deposition and ventilation efficiencies vary by lobe and lung, depending on airway morphology and airflow ventilation. In particular, regardless of particle size, the left lung receives a greater proportion of the particle bolus as compared to the right lung in spite of greater flow ventilation to the right lung. This observation is supported by the left-right lung asymmetry of particle ventilation observed in medical imaging. It is found that the particle-laden turbulent laryngeal jet flow, coupled with the unique geometrical features of the airway, causes a disproportionate amount of particles to enter the left lung.

A multifaceted approach to modeling the immune response in tuberculosis

Tuberculosis (TB) is a deadly infectious disease caused by Mycobacterium tuberculosis (Mtb). No available vaccine is reliable and, although treatment exists, approximately 2 million people still die each year. The hallmark of TB infection is the granuloma, a self-organizing structure of immune cells forming in the lung and lymph nodes in response to bacterial invasion. Protective immune mechanisms play a role in granuloma formation and maintenance; these act over different time/length scales (e.g., molecular, cellular, and tissue scales). The significance of specific immune factors in determining disease outcome is still poorly understood, despite incredible efforts to establish several animal systems to track infection progression and granuloma formation. Mathematical and computational modeling approaches have recently been applied to address open questions regarding host-pathogen interaction dynamics, including the immune response to Mtb infection and TB granuloma formation. This provides a unique opportunity to identify factors that are crucial to a successful outcome of infection in humans. These modeling tools not only offer an additional avenue for exploring immune dynamics at multiple biological scales but also complement and extend knowledge gained via experimental tools. We review recent modeling efforts in capturing the immune response to Mtb, emphasizing the importance of a multiorgan and multiscale approach that has tuneable resolution. Together with experimentation, systems biology has begun to unravel key factors driving granuloma formation and protective immune response in TB. WIREs Syst Biol Med 2011 3 479-489 DOI: 10.1002/wsbm.131