Image-based modeling of lung structure and function

Towards a multi-scale computer modeling workflow for simulation of pulmonary ventilation in advanced COVID-19

Physics-based multi-scale in silico models offer an excellent opportunity to study the effects of heterogeneous tissue damage on airflow and pressure distributions in COVID-19-afflicted lungs. The main objective of this study is to develop a computational modeling workflow, coupling airflow and tissue mechanics as the first step towards a virtual hypothesis-testing platform for studying injury mechanics of COVID-19-afflicted lungs. We developed a CT-based modeling approach to simulate the regional changes in lung dynamics associated with heterogeneous subject-specific COVID-19-induced damage patterns in the parenchyma. Furthermore, we investigated the effect of various levels of inflammation in a meso-scale acinar mechanics model on global lung dynamics. Our simulation results showed that as the severity of damage in the patient's right lower, left lower, and to some extent in the right upper lobe increased, ventilation was redistributed to the least injured right middle and left upper lobes. Furthermore, our multi-scale model reasonably simulated a decrease in overall tidal volume as the level of tissue injury and surfactant loss in the meso-scale acinar mechanics model was increased. This study presents a major step towards multi-scale computational modeling workflows capable of simulating the effect of subject-specific heterogenous COVID-19-induced lung damage on ventilation dynamics.

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

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

Correlating Local Volumetric Tissue Strains with Global Lung Mechanics Measurements

The mechanics of breathing is a fascinating and vital process. The lung has complexities and subtle heterogeneities in structure across length scales that influence mechanics and function. This study establishes an experimental pipeline for capturing alveolar deformations during a respiratory cycle using synchrotron radiation micro-computed tomography (SR-micro-CT). Rodent lungs were mechanically ventilated and imaged at various time points during the respiratory cycle. Pressure-Volume (P-V) characteristics were recorded to capture any changes in overall lung mechanical behaviour during the experiment. A sequence of tomograms was collected from the lungs within the intact thoracic cavity. Digital volume correlation (DVC) was used to compute the three-dimensional strain field at the alveolar level from the time sequence of reconstructed tomograms. Regional differences in ventilation were highlighted during the respiratory cycle, relating the local strains within the lung tissue to the global ventilation measurements. Strains locally reached approximately 150% compared to the averaged regional deformations of approximately 80-100%. Redistribution of air within the lungs was observed during cycling. Regions which were relatively poorly ventilated (low deformations compared to its neighbouring region) were deforming more uniformly at later stages of the experiment (consistent with its neighbouring region). Such heterogenous phenomena are common in everyday breathing. In pathological lungs, some of these non-uniformities in deformation behaviour can become exaggerated, leading to poor function or further damage. The technique presented can help characterize the multiscale biomechanical nature of a given pathology to improve patient management strategies, considering both the local and global lung mechanics.

Investigation of airflow at different activity conditions in a realistic model of human upper respiratory tract

In the present study, the turbulent flows inside a realistic model of the upper respiratory tract were investigated numerically and experimentally. The airway model included the geometrical details of the oral cavity to the end of the trachea that was based on a series of CT-scan images. The topological data of the respiratory tract were used for generating the computational model as well as the 3D-printed model that was used in the experimental pressure drop measurement. Different airflow rates of 30, 45, and 60 L/min, which correspond to the light, semi-light, and heavy activity breathing conditions, were investigated numerically using turbulence and transition models, as well as experimentally. Simulation results for airflow properties, including velocity vectors, pressure drops, streamlines, eddy viscosity, and turbulent kinetic energy contours in the oral-trachea airway model, were presented. The simulated pressure drop was compared with the experimental data, and reasonable agreement was found. The obtained results showed that the maximum pressure drop occurs in the narrowest part of the larynx region. A comparison between the numerical results and experimental data showed that the transition (γ-Reθ) SST model predicts higher pressure losses, especially at higher breathing rates. Formations of the secondary flows in the oropharynx and trachea regions were also observed. In addition, the simulation results showed that in the trachea region, the secondary flow structures dissipated faster for the flow rate of 60 L/min compared to the lower breathing rates of 30 and 45 L/min.

A Review of Respiratory Anatomical Development, Air Flow Characterization and Particle Deposition

The understanding of complex inhalation and transport processes of pollutant particles through the human respiratory system is important for investigations into dosimetry and respiratory health effects in various settings, such as environmental or occupational health. The studies over the last few decades for micro- and nanoparticle transport and deposition have advanced the understanding of drug-aerosol impacts in the mouth-throat and the upper airways. However, most of the Lagrangian and Eulerian studies have utilized the non-realistic symmetric anatomical model for airflow and particle deposition predictions. Recent improvements to visualization techniques using high-resolution computed tomography (CT) data and the resultant development of three dimensional (3-D) anatomical models support the realistic representation of lung geometry. Yet, the selection of different modelling approaches to analyze the transitional flow behavior and the use of different inlet and outlet conditions provide a dissimilar prediction of particle deposition in the human lung. Moreover, incorporation of relevant physical and appropriate boundary conditions are important factors to consider for the more accurate prediction of transitional flow and particle transport in human lung. This review critically appraises currently available literature on airflow and particle transport mechanism in the lungs, as well as numerical simulations with the aim to explore processes involved. Numerical studies found that both the Euler–Lagrange (E-L) and Euler–Euler methods do not influence nanoparticle (particle diameter ≤50 nm) deposition patterns at a flow rate ≤25 L/min. Furthermore, numerical studies demonstrated that turbulence dispersion does not significantly affect nanoparticle deposition patterns. This critical review aims to develop the field and increase the state-of-the-art in human lung modelling.

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

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

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

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.

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.

Computational fluid dynamics evaluation of excessive dynamic airway collapse

BACKGROUND

Excessive dynamic airway collapse, which is often caused by the collapse of the posterior membrane wall during exhalation, is often misdiagnosed with other diseases; stents can provide support for the collapsing airways. The standard pulmonary function tests do not necessarily show change in functional breathing condition for evaluation of these type of diseases.

METHODS

Flow characteristics through a patient's airways with excessive dynamic airway collapse have been numerically investigated. A stent was placed to support the collapsing airway and to improve breathing conditions. Computed tomography images of the patient's pre- and post-stenting were used for generating 3-Dimensional models of the airways, and were imported into a computational fluid dynamics software for simulation of realistic air flow behavior. Unsteady simulations of the inspiratory phase and expiratory phase were performed with patient-specific boundary conditions for pre- and post-intervention cases to investigate the effect of stent placement on flow characteristic and possible improvements.

FINDINGS

Results of post-stent condition show reduced pressure, velocity magnitude and wall shear stress during expiration. The variation in wall shear stress, velocity magnitude and pressure drop is negligible during inspiration.

INTERPRETATION

Although Spirometry tests do not show significant improvements, computational fluid dynamics results show significant improvements in pre- and post-treatment results, suggesting improvement in breathing condition.

Particulate Deposition in a Patient With Tracheal Stenosis

The presence of obstructions such as tracheal stenosis has important effects on respiratory functions. Tracheal stenosis impacts the therapeutic efficacy of inhaled medications as a result of alterations in particle transport and deposition pattern. This study explores the effects of the presence and absence of stenosis/obstruction in the trachea on air flow characteristics and particle depositions. Computational fluid dynamics (CFD) simulations were performed on three-dimensional (3D) patient-specific models created from computed tomography (CT) images. The analyzed model was generated from a subject with tracheal stenosis and includes the airway tree up to eight generations. CT scans of expiratory and inspiratory phases were used for patient-specific boundary conditions. Pre- and post-intervention CFD simulations' comparison reveals the effect of the stenosis on the characteristics of air flow, transport, and depositions of particles with diameters of 1, 2.5, 4, 6, 8, and 10 μm. Results indicate that the existence of the stenosis inflicts a major pressure force on the flow of inhaled air, leading to an increased deposition of particles both above and below the stenosis. Comparisons of the decrease in pressure in each generation between pre- and post-tracheal stenosis intervention demonstrated a significant reduction in pressure following the stenosis, which was maintained in all downstream generations. Good agreements were found using experimental validation of CFD findings with a model of the control subject up to the third generation, constructed via additive layer manufacturing from CT images.

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.

A poroelastic model coupled to a fluid network with applications in lung modelling

We develop a lung ventilation model based on a continuum poroelastic representation of lung parenchyma that is strongly coupled to a pipe network representation of the airway tree. The continuous system of equations is discretized using a low-order stabilised finite element method. The framework is applied to a realistic lung anatomical model derived from computed tomography data and an artificially generated airway tree to model the conducting airway region. Numerical simulations produce physiologically realistic solutions and demonstrate the effect of airway constriction and reduced tissue elasticity on ventilation, tissue stress and alveolar pressure distribution. The key advantage of the model is the ability to provide insight into the mutual dependence between ventilation and deformation. This is essential when studying lung diseases, such as chronic obstructive pulmonary disease and pulmonary fibrosis. Thus the model can be used to form a better understanding of integrated lung mechanics in both the healthy and diseased states. Copyright © 2015 John Wiley & Sons, Ltd.

A Conjugate Fluid-Porous Approach for Simulating Airflow in Realistic Geometric Representations of the Human Respiratory System

Simulation of flow in the human lung is of great practical interest as a means to study the detailed flow patterns within the airways for many physiological applications. While computational simulation techniques are quite mature, lung simulations are particularly complicated due to the vast separation of length scales between upper airways and alveoli. Many past studies have presented numerical results for truncated airway trees, however, there are significant difficulties in connecting such results with respiratory airway models. This article presents a new modeling paradigm for flow in the full lung, based on a conjugate fluid-porous formulation where the upper airway is considered as a fluid region with the remainder of the lung being considered as a coupled porous region. Results are presented for a realistic lung geometry obtained from computed tomography (CT) images, which show the method's potential as being more efficient and practical than attempting to directly simulate flow in the full lung.

Coupled and reduced dimensional modeling of respiratory mechanics during spontaneous breathing

In this paper, we develop a total lung model based on a tree of 0D airway and acinar models for studying respiratory mechanics during spontaneous breathing. This model utilizes both computer tomography-based geometries and artificially generated lobe-filling airway trees to model the entire conducting region of the lung. Beyond the conducting airways, we develop an acinar model, which takes into account the alveolar tissue resistance, compliance, and the intrapleural pressure. With this methodology, we compare four different 0D models of airway mechanics and determine the best model based on a comparison with a 3D-0D coupled model of the conducting airways; this methodology is possible because the majority of airway resistance is confined to the lower generations, that is, the trachea and the first few bronchial generations. As an example application of the model, we simulate the flow and pressure dynamics under spontaneous breathing conditions, that is, at flow conditions driven purely by pleural space pressure. The results show good agreement, both qualitatively and quantitatively, with reported physiological values. One of the key advantages of this model is the ability to provide insight into lung ventilation in the peripheral regions. This is often crucial because this is where information, specifically for studying diseases and gas exchange, is needed. Thus, the model can be used as a tool for better understanding local peripheral lung mechanics without excluding the upper portions of the lung. This tool will be also useful for in vitro investigations of lung mechanics in both health and disease.

Multiscale image-based modeling and simulation of gas flow and particle transport in the human lungs

Improved understanding of structure and function relationships in the human lungs in individuals and subpopulations is fundamentally important to the future of pulmonary medicine. Image-based measures of the lungs can provide sensitive indicators of localized features, however to provide a better prediction of lung response to disease, treatment, and environment, it is desirable to integrate quantifiable regional features from imaging with associated value-added high-level modeling. With this objective in mind, recent advances in computational fluid dynamics (CFD) of the bronchial airways-from a single bifurcation symmetric model to a multiscale image-based subject-specific lung model-will be reviewed. The interaction of CFD models with local parenchymal tissue expansion-assessed by image registration-allows new understanding of the interplay between environment, hot spots where inhaled aerosols could accumulate, and inflammation. To bridge ventilation function with image-derived central airway structure in CFD, an airway geometrical modeling method that spans from the model 'entrance' to the terminal bronchioles will be introduced. Finally, the effects of turbulent flows and CFD turbulence models on aerosol transport and deposition will be discussed.

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

A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C₁ continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

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.

Steady streaming: A key mixing mechanism in low-Reynolds-number acinar flows

Study of mixing is important in understanding transport of submicron sized particles in the acinar region of the lung. In this article, we investigate transport in view of advective mixing utilizing Lagrangian particle tracking techniques: tracer advection, stretch rate and dispersion analysis. The phenomenon of steady streaming in an oscillatory flow is found to hold the key to the origin of kinematic mixing in the alveolus, the alveolar mouth and the alveolated duct. This mechanism provides the common route to folding of material lines and surfaces in any region of the acinar flow, and has no bearing on whether the geometry is expanding or if flow separates within the cavity or not. All analyses consistently indicate a significant decrease in mixing with decreasing Reynolds number (Re). For a given Re, dispersion is found to increase with degree of alveolation, indicating that geometry effects are important. These effects of Re and geometry can also be explained by the streaming mechanism. Based on flow conditions and resultant convective mixing measures, we conclude that significant convective mixing in the duct and within an alveolus could originate only in the first few generations of the acinar tree as a result of nonzero inertia, flow asymmetry, and large Keulegan-Carpenter (K(C)) number.

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.