Experimental characterization and model identification of the nonlinear compressible material behavior of lung parenchyma

Design and comparison of computationally efficient uniaxial stress-strain models of the lung parenchyma for real-time applications

Real-time clinical applications such as robotic lung surgery, tumor localization, atelectasis diagnosis, tumor motion prediction for radiation therapy of lung cancer, or surgery training are in need of biomechanical models of lungs, not necessarily highly accurate, but with good computational properties. These properties can include one or several of the following: low computation time, low memory resource requirement, a low number of parameters, and ease of parameter identification in real-time. Among the numerous existing models of lung parenchyma, some may be well suited for real-time applications; however, they should be extensively assessed against both accuracy and computational efficiency criteria to make an informed choice depending on the requirements of the application. After demonstrating how to derive a real-time compliant force-indentation model from a unixial stress-strain model with rational expression, the core purpose of this paper is to propose such an evaluation of selected models in fitting human lung parenchyma experimental and synthetic data of uniaxial tension. Furthermore, new uniaxial stress-strain models are developed based on an empirical observation of the volumetric behavior of the lungs along with an emphasis on computational performance. These new proposed models are competitive with existing one in terms of computational efficiency and compliance with experimental and synthetic data. One of them reduces the prediction error by 2 compared to other investigated models while maintaining an excellent adjusted coefficient of determination between 0.999 and 1 across various datasets. It exhibits excellent real-time capabilities with an explicit rational expression, only 3 parameters and linear numerator and denominator in the parameters. It is computed with only 20 floating point operations (flops) while another proposed model even requires as few as 2 flops.

Mechanical and morphological characterization of the emphysematous lung tissue

Irreversible alveolar airspace enlargement is the main characteristic of pulmonary emphysema, which has been extensively studied using animal models. While the alterations in lung mechanics associated with these morphological changes have been documented in the literature, the study of the mechanical behavior of parenchymal tissue from emphysematous lungs has been poorly investigated. In this work, we characterize the mechanical and morphological properties of lung tissue in elastase-induced emphysema rat models under varying severity conditions. We analyze the non-linear tissue behavior using suitable hyperelastic constitutive models that enable to compare different non-linear responses in terms of hyperelastic material parameters. We further analyze the effect of the elastase dose on alveolar morphology and tissue material parameters and study their connection with respiratory-system mechanical parameters. Our results show that while the lung mechanical function is not significantly influenced by the elastase treatment, the tissue mechanical behavior and alveolar morphology are markedly affected by it. We further show a strong association between alveolar enlargement and tissue softening, not evidenced by respiratory-system compliance. Our findings highlight the importance of understanding tissue mechanics in emphysematous lungs, as changes in tissue properties could detect the early stages of emphysema remodeling. STATEMENT OF SIGNIFICANCE: Gas exchange is vital for life and strongly relies on the mechanical function of the lungs. Pulmonary emphysema is a prevalent respiratory disease where alveolar walls are damaged, causing alveolar enlargement that induces harmful changes in the mechanical response of the lungs. In this work, we study how the mechanical properties of lung tissue change during emphysema. Our results from animal models show that tissue properties are more sensitive to alveolar enlargement due to emphysema than other mechanical properties that describe the function of the whole respiratory system.

Role of lung lobar sliding on parenchymal distortion during breathing

Sliding between lung lobes along lobar fissures is a poorly understood aspect of lung mechanics. The objective of this study was to test the hypothesis that lobar sliding helps reduce distortion in the lung parenchyma during breathing. Finite element models of left lungs with geometries and boundary conditions derived from medical images of human subjects were developed. Effect of lobar sliding was studied by comparing nonlinear finite elastic contact mechanics simulations that allowed and disallowed lobar sliding. Lung parenchymal distortion during simulated breath-holds and tidal breathing was quantified with the model's spatial mean anisotropic deformation index (ADI), a measure of directional preference in volume change that varies spatially in the lung. Models that allowed lobar sliding had significantly lower mean ADI (i.e., lesser parenchymal distortion) than models that disallowed lobar sliding under simulations of both tidal breathing (5.3% median difference, P = 0.008, n = 8) and lung deformation between breath-holds at total lung capacity and functional residual capacity (3.2% median difference, P = 0.03, n = 6). This effect was most pronounced in the lower lobe where lobar sliding reduced parenchymal distortion with statistical significance, but not in the upper lobe. In addition, more lobar sliding was correlated with greater reduction in distortion between sliding and nonsliding models in our study cohorts (Pearson's correlation coefficient of 0.95 for tidal breathing, 0.87 for breath-holds, and 0.91 for the combined dataset). These findings are consistent with the hypothesis that lung lobar sliding reduces parenchymal distortion during breathing.NEW & NOTEWORTHY The role of lobar sliding in lung mechanics is poorly understood. Delineating this role could help explain how breathing is affected by anatomical differences between subjects such as incomplete and missing lobar fissures. We used computational contact mechanics models of lungs from human subjects to delineate the effect of lobar sliding by comparing simulations that allowed and disallowed sliding. We found evidence consistent with the hypothesis that lung lobar sliding reduces parenchymal distortion during breathing.

Quasi-dynamic breathing model of the lung incorporating viscoelasticity of the lung tissue

We advanced a novel model to calculate viscoelastic lung compliance and airflow resistance in presence of mucus, accounting for the quasi-linear viscoelastic stress-strain response of the parenchyma (alveoli) tissue. We adapted a continuum-based numerical modeling approach for the lung, integrating the fluid mechanics of the airflow within individual generations of the bronchi and alveoli. The model accounts for elasticity of the deformable bronchioles, resistance to airflow due to the presence of mucus within the bronchioles, and subsequent mucus flow. Simulated quasi-dynamic inhalation and expiration cycles were used to characterize the net compliance and resistance of the lung, considering the rheology of the mucus and viscoelastic properties of the parenchyma tissue. The structure and material properties of the lung were identified to have an important contribution to the lung compliance and airflow resistance. The secondary objective of this work was to assess whether a higher frequency and smaller volume of harmonic air flow rate compared to a normal ventilator breathing cycle enhanced mucus outflow. Results predict, lower mucus viscosity and higher excitation frequency of breathing are favorable for the flow of mucus up the bronchi tree, towards the trachea.

Lung Mechanics: A Review of Solid Mechanical Elasticity in Lung Parenchyma

The lung is the main organ of the respiratory system. Its purpose is to facilitate gas exchange (breathing). Mechanically, breathing may be described as the cyclic application of stresses acting upon the lung surface. These forces are offset by prominent stress-bearing components of lung tissue. These components result from the mechanical elastic properties of lung parenchyma. Various studies have been dedicated to understanding the macroscopic behaviour of parenchyma. This has been achieved through pressure-volume analysis, numerical methods, the development of constitutive equations or strain-energy functions, finite element methods, image processing and elastography. Constitutive equations can describe the elastic behaviour exhibited by lung parenchyma through the relationship between the macroscopic stress and strain. The research conducted within lung mechanics around the elastic and resistive properties of the lung has allowed scientists to develop new methods and equipment for evaluating and treating pulmonary pathogens. This paper establishes a review of mathematical studies conducted within lung mechanics, centering on the development and implementation of solid mechanics to the understanding of the mechanical properties of the lung. Under the classical theory of elasticity, the lung is said to behave as an isotropic elastic continuum undergoing small deformations. However, the lung has also been known to display heterogeneous anisotropic behaviour associated with large deformations. Therefore, focus is placed on the assumptions and development of the various models, their mechanical influence on lung physiology, and the development of constitutive equations through the classical and non-classical theory of elasticity. Lastly, we also look at lung blast mechanics. No explicit emphasis is placed on lung pathology.

Whole-lung finite-element models for mechanical ventilation and respiratory research applications

Mechanical ventilation has been a vital treatment for Covid-19 patients with respiratory failure. Lungs assisted with mechanical ventilators present a wide variability in their response that strongly depends on air-tissue interactions, which motivates the creation of simulation tools to enhance the design of ventilatory protocols. In this work, we aim to create anatomical computational models of the lungs that predict clinically-relevant respiratory variables. To this end, we formulate a continuum poromechanical framework that seamlessly accounts for the air-tissue interaction in the lung parenchyma. Based on this formulation, we construct anatomical finite-element models of the human lungs from computed-tomography images. We simulate the 3D response of lungs connected to mechanical ventilation, from which we recover physiological parameters of high clinical relevance. In particular, we provide a framework to estimate respiratory-system compliance and resistance from continuum lung dynamic simulations. We further study our computational framework in the simulation of the supersyringe method to construct pressure-volume curves. In addition, we run these simulations using several state-of-the-art lung tissue models to understand how the choice of constitutive models impacts the whole-organ mechanical response. We show that the proposed lung model predicts physiological variables, such as airway pressure, flow and volume, that capture many distinctive features observed in mechanical ventilation and the supersyringe method. We further conclude that some constitutive lung tissue models may not adequately capture the physiological behavior of lungs, as measured in terms of lung respiratory-system compliance. Our findings constitute a proof of concept that finite-element poromechanical models of the lungs can be predictive of clinically-relevant variables in respiratory medicine.

Computational lung modelling in respiratory medicine

Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure-function relationship in the lung.

Integrative Computational Models of Lung Structure-Function Interactions

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

Constituent-specific material behavior of soft biological tissue: experimental quantification and numerical identification for lung parenchyma

In this study, we present a method to experimentally quantify and numerically identify the constituent-specific material behavior of soft biological tissues. This allows the clear identification of the individual contributions of major load-bearing constituents and their interactions in the constitutive law. While the overall approach is applicable for many tissues, here it will be presented for the identification of a sophisticated constituent-specific material model of viable lung parenchyma. This material model will help to better model the effects of various lung diseases that feature altered fiber content in the lungs, such as emphysema or fibrosis. To experimentally quantify the mechanical properties of collagen, elastin, collagen-elastin-fiber interactions, and ground substance, we examined 18 collagenase and elastase treated rat lung parenchymal slices. The mechanical contributions of the collagen and elastin fibers in the living tissue were inferred from uniaxial tension tests comparing the behavior before and after the selective digestion of the respective fibers. In order to also obtain the mechanical influence of the ground substance, we consecutively treated the samples with both proteases. Collagen and elastin fibers are morphologically interconnected. Thus, a mechanical interaction between these fibers appears likely, but has not yet been experimentally verified. In this paper, we propose an experimental method to quantitatively assess the mechanical behavior of these collagen-elastin-fiber interactions. Based on our experiments, we have identified individual material models within a nonlinear continuum mechanics framework for each load-bearing component via an inverse analysis. The proposed constituent-specific material law can be incorporated into computational models of the respiratory system to simulate and even predict the behavior and alteration of the individual constituents and their effect on the whole respiratory system during normal and artificial breathing, in particular in the case of diseases that alter the fibers in the tissue.

A viscoelastic nonlinear compressible material model of lung parenchyma - Experiments and numerical identification

Characterizing material properties of lung parenchyma is essential in order to describe and predict the mechanical behavior of the lung in health and disease. Hence, we aim to identify the viscoelastic constitutive behavior of viable lung parenchyma with a particular focus on the nonlinear, compressible, and frequency-dependent material properties. To quantify the viscoelastic material behavior of rat lung parenchyma experimentally, we performed uniaxial tension tests with different frequencies, including the whole range of physiological frequencies, in combination with full-field displacement measurements (a total of 120 tests on 30 samples of 5 rats). By means of these experimental measurements, we identified the material parameters of two viscoelastic material models applicable to large three-dimensional deformations, i.e., the standard linear solid model and the model of fractional viscoelasticity. Our aim is to identify one set of material parameters that describes the whole range of physiological frequencies; therefore, we utilized a coupled inverse analysis, which equally incorporates all different tensile tests performed on one sample. The model most suitable for the description of the viscoelastic, nonlinear, and compressible material behavior of viable rat lung parenchyma is the strain energy function [Formula: see text] in combination with the model of fractional viscoelasticity (τ=0.06454s,α=0.5378, and β=1.856). This material model was validated to describe the complex nonlinear and compressible viscoelastic material behavior of lung parenchyma and can be utilized in finite element simulations of the whole range of physiological frequencies. Based on this model, it will be possible to quantify the stresses and strains of lung tissue during spontaneous and artificial breathing more reliable in the future.

A coupled approach for identification of nonlinear and compressible material models for soft tissue based on different experimental setups - Exemplified and detailed for lung parenchyma

In this paper, a coupled inverse analysis is proposed to identify nonlinear compressible hyperelastic material models described by two sets of experiments. While the overall approach is applicable for different materials, here it will be presented for viable lung parenchyma. Characterizing the material properties of lung parenchyma is essential to describe and predict the mechanical behavior of the respiratory system in health and disease. During breathing and mechanical ventilation, lung parenchyma is mainly subjected to volumetric deformations along with isochoric and asymmetric deformations that occur especially in diseased heterogeneous lungs. Notwithstanding, most studies examine lung tissue in predominantly isochoric tension tests. In this paper, we investigate the volumetric material behavior as well as the isochoric deformations in two sets of experiments: namely, volume-pressure-change experiments (performed with 287 samples of 26 rats) and uniaxial tension tests (performed with 30 samples of 5 rats). Based on these sets of experiments, we propose a coupled inverse analysis, which simultaneously incorporates both measurement sets to optimize the material parameters. Accordingly, we determine a suitable material model using the experimental results of both sets of experiments in one coupled identification process. The identified strain energy function with the corresponding material parameters [Formula: see text] is validated to model both sets of experiments precisely. Hence, this constitutive model describes the complex volumetric and isochoric nonlinear material behavior of lung parenchyma. This derived material model can be used for nonlinear finite element simulations of lung parenchyma and will help to quantify the stresses and strains of lung tissue during spontaneous and artificial breathing; thus, allowing new insights into lung function and biology.

Coupled Immunological and Biomechanical Model of Emphysema Progression

Chronic Obstructive Pulmonary Disease (COPD) is a disabling respiratory pathology, with a high prevalence and a significant economic and social cost. It is characterized by different clinical phenotypes with different risk profiles. Detecting the correct phenotype, especially for the emphysema subtype, and predicting the risk of major exacerbations are key elements in order to deliver more effective treatments. However, emphysema onset and progression are influenced by a complex interaction between the immune system and the mechanical properties of biological tissue. The former causes chronic inflammation and tissue remodeling. The latter influences the effective resistance or appropriate mechanical response of the lung tissue to repeated breathing cycles. In this work we present a multi-scale model of both aspects, coupling Finite Element (FE) and Agent Based (AB) techniques that we would like to use to predict the onset and progression of emphysema in patients. The AB part is based on existing biological models of inflammation and immunological response as a set of coupled non-linear differential equations. The FE part simulates the biomechanical effects of repeated strain on the biological tissue. We devise a strategy to couple the discrete biological model at the molecular /cellular level and the biomechanical finite element simulations at the tissue level. We tested our implementation on a public emphysema image database and found that it can indeed simulate the evolution of clinical image biomarkers during disease progression.