Mechanical Behavior and Collagen Structure of Degenerative Mitral Valve Leaflets and a Finite Element Model of Primary Mitral Regurgitation

Integration of cross-links, discrete fiber distributions and of a non-local theory in the Homogenized Constrained Mixture Model to Simulate Patient-Specific Thoracic Aortic Aneurysm Progression

Thoracic aortic aneurysms (TAA) represent a critical health issue for which computational models can significantly contribute to better understand the physiopathology. Among different computational frameworks, the Homogenized Constrained Mixture Theory has shown to be a computationally efficient option, allowing the inclusion of several mechanically significant constituents into a layer-specific mixture. Different patient-specific Growth and Remodeling (G&R) models correctly predicted TAA progression, although simplifications such as the inclusion of a limited number of collagen fibers and imposed boundary conditions might limit extensive analyses. The current study aims to enhance existing models by incorporating several discrete collagen fibers and to remove restrictive boundary conditions of the previous models. The implementation of discretized fiber dispersion presents a more realistic description of the vessel, while the removal of boundary conditions was addressed by including cross-links in the model to provide a supplemental stiffness against through-thickness shearing, a feature that was previously absent, and by the development of a non-local framework that ensures the stable deposition and degradation of collagen fibers. With these improvements, the current model represents a step forward towards more robust and comprehensive simulations of TAA growth.

Second harmonic generation microscopy, biaxial mechanical tests and fiber dispersion models in human skin biomechanics

Advanced numerical simulations of the mechanical behavior of human skin require thorough calibration of the material's constitutive models based on experimental ex vivo mechanical tests along with images of tissue microstructure for a variety of biomedical applications. In this work, a total of 14 human healthy skin samples and 4 additional scarred skin samples were experimentally analyzed to gain deep insights into the biomechanics of human skin. In particular, second harmonic generation (SHG) microscopy was used to extract detailed images of the distribution of collagen fibers, which were subsequently processed using a three-dimensional Fourier transform-based method recently proposed by the authors to quantify the distribution of fiber orientations. Mechanical tests under both biaxial and uniaxial loading were performed to calibrate the relevant mechanical parameters of two widely used constitutive models of soft fiber-reinforced biological tissues that account for non-symmetrical fiber dispersion. The calibration of the models allowed us to identify correlations between the mechanical parameters of the constitutive models considered. STATEMENT OF SIGNIFICANCE: Constitutive models for soft collagenous tissues can accurately reproduce the complex nonlinear and anisotropic mechanical behavior of skin. However, a comprehensive analysis of both microstructural and mechanical parameters is still missing for human skin. In this study, these parameters are determined by combining biaxial mechanical tests and SHG stacks of collagen fibers on ex vivo healthy human skin samples. The constitutive parameters are provided for two widely used hyperelastic models and enable accurate characterization of skin mechanical behavior for advanced numerical simulations.

Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics-Informed Neural Networks

The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional engineering approaches is fundamentally challenging due to difficulties in estimating local stress fields. Recently, there has been a growing interest in data-driven models for learning full-field mechanical responses, such as displacement and strain, from experimental or synthetic data. However, research studies on inferring full-field elastic properties of materials, a more challenging problem, are scarce, particularly for large deformation, hyperelastic materials. Here, a physics-informed machine learning approach is proposed to identify the elasticity map in nonlinear, large deformation hyperelastic materials. This study reports the prediction accuracies and computational efficiency of physics-informed neural networks (PINNs) in inferring the heterogeneous elasticity maps across materials with structural complexity that closely resemble real tissue microstructure, such as brain, tricuspid valve, and breast cancer tissues. Further, the improved architecture is applied to three hyperelastic constitutive models: Neo-Hookean, Mooney Rivlin, and Gent. The improved network architecture consistently produces accurate estimations of heterogeneous elasticity maps, even when there is up to 10% noise present in the training data.

Quantified planar collagen distribution in healthy and degenerative mitral valve: biomechanical and clinical implications

Degenerative mitral valve disease is a common valvular disease with two arguably distinct phenotypes: fibroelastic deficiency and Barlow's disease. These phenotypes significantly alter the microstructures of the leaflets, particularly the collagen fibers, which are the main mechanical load carriers. The predominant method of investigation is histological sections. However, the sections are cut transmurally and provide a lateral view of the microstructure of the leaflet, while the mechanics and function are determined by the planar arrangement of the collagen fibers. This study, for the first time, quantitatively examined planar collagen distribution quantitatively in health and disease using second harmonic generation microscopy throughout the thickness of the mitral valve leaflets. Twenty diseased samples from eighteen patients and six control samples were included in this study. Healthy tissue had highly aligned collagen fibers. In fibroelastic deficiency they are less aligned and in Barlow's disease they are completely dispersed. In both diseases, collagen fibers have two preferred orientations, which, in contrast to the almost constant one orientation in healthy tissues, also vary across the thickness. The results indicate altered in vivo mechanical stresses and strains on the mitral valve leaflets as a result of disease-related collagen remodeling, which in turn triggers further remodeling.

Uniaxial mechanical stretch properties correlated with three-dimensional microstructure of human dermal skin

The intact and healthy skin forms a barrier to the outside world and protects the body from mechanical impact. The skin is a complex structure with unique mechano-elastic properties. To better direct the design of biomimetic materials and induce skin regeneration in wounds with optimal outcome, more insight is required in how the mechano-elastic properties emerge from the skin's main constituents, collagen and elastin fibers. Here, we employed two-photon excited autofluorescence and second harmonic generation microscopy to characterize collagen and elastin fibers in 3D in 24 human dermis skin samples. Through uniaxial stretching experiments, we derive uni-directional mechanical properties from resultant stress-strain curves, including the initial Young's modulus, elastic Young's modulus, maximal stress, and maximal and mid-strain values. The stress-strain curves show a large variation, with an average Young's modules in the toe and linear regions of 0.1 MPa and 21 MPa. We performed a comprehensive analysis of the correlation between the key mechanical properties with age and with microstructural parameters, e.g., fiber density, thickness, and orientation. Age was found to correlate negatively with Young's modulus and collagen density. Moreover, real-time monitoring during uniaxial stretching allowed us to observe changes in collagen and elastin alignment. Elastin fibers aligned significantly in both the heel and linear regions, and the collagen bundles engaged and oriented mainly in the linear region. This research advances our understanding of skin biomechanics and yields input for future first principles full modeling of skin tissue.

Leaflet remodeling reduces tricuspid valve function in a computational model

Tricuspid valve leaflets have historically been considered "passive flaps". However, we have recently shown that tricuspid leaflets actively remodel in sheep with functional tricuspid regurgitation. We hypothesize that these remodeling-induced changes reduce leaflet coaptation and, therefore, contribute to valvular dysfunction. To test this, we simulated the impact of remodeling-induced changes on valve mechanics in a reverse-engineered computer model of the human tricuspid valve. To this end, we combined right-heart pressures and tricuspid annular dynamics recorded in an ex vivo beating heart, with subject-matched in vitro measurements of valve geometry and material properties, to build a subject-specific finite element model. Next, we modified the annular geometry and boundary conditions to mimic changes seen in patients with pulmonary hypertension. In this model, we then increased leaflet thickness and stiffness and reduced the stretch at which leaflets stiffen, which we call "transition-λ." Subsequently, we quantified mean leaflet stresses, leaflet systolic angles, and coaptation area as measures of valve function. We found that leaflet stresses, leaflet systolic angle, and coaptation area are sensitive to independent changes in stiffness, thickness, and transition-λ. When combining thickening, stiffening, and changes in transition-λ, we found that anterior and posterior leaflet stresses decreased by 26% and 28%, respectively. Furthermore, systolic angles increased by 43%, and coaptation area decreased by 66%; thereby impeding valve function. While only a computational study, we provide the first evidence that remodeling-induced leaflet thickening and stiffening may contribute to valvular dysfunction. Targeted suppression of such changes in diseased valves could restore normal valve mechanics and promote leaflet coaptation.

Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units

Several materials and tissues are characterized by a microstructure composed of fibrous units embedded in a ground matrix. In this paper, a novel three-dimensional (3D) Fourier transform-based method for quantifying the distribution of fiber orientations is presented. The method allows for an accurate identification of individual fiber families, their in-plane and out-of-plane dispersion, and showed fast computation times. We validated the method using artificially generated 3D images, in terms of fiber dispersion by considering the error between the standard deviation of the reconstructed and the prescribed distributions of the artificial fibers. In addition, we considered the measured mean orientation angles of the fibers and validated the robustness using a measure of fiber density. Finally, the method is employed to reconstruct a full 3D view of the distribution of collagen fiber orientations based on in vitro second harmonic generation microscopy of collagen fibers in human and mouse skin. The dispersion parameters of the reconstructed fiber network can be used to inform mechanical models of soft fiber-reinforced materials and biological tissues that account for non-symmetrical fiber dispersion.

A Comparative Analysis of Orthotopic and Subcutaneous Pancreatic Tumour Models: Tumour Microenvironment and Drug Delivery

Pancreatic ductal adenocarcinoma (PDAC) remains a challenging malignancy, mainly due to its resistance to chemotherapy and its complex tumour microenvironment characterised by stromal desmoplasia. There is a need for new strategies to improve the delivery of drugs and therapeutic response. Relevant preclinical tumour models are needed to test potential treatments. This paper compared orthotopic and subcutaneous PDAC tumour models and their suitability for drug delivery studies. A novel aspect was the broad range of tumour properties that were studied, including tumour growth, histopathology, functional vasculature, perfusion, immune cell infiltration, biomechanical characteristics, and especially the extensive analysis of the structure and the orientation of the collagen fibres in the two tumour models. The study unveiled new insights into how these factors impact the uptake of a fluorescent model drug, the macromolecule called 800CW. While the orthotopic model offered a more clinically relevant microenvironment, the subcutaneous model offered advantages for drug delivery studies, primarily due to its reproducibility, and it was characterised by a more efficient drug uptake facilitated by its collagen organisation and well-perfused vasculature. The tumour uptake seemed to be influenced mainly by the structural organisation and the alignment of the collagen fibres and perfusion. Recognising the diverse characteristics of these models and their multifaceted impacts on drug delivery is crucial for designing clinically relevant experiments and improving our understanding of pancreatic cancer biology.

Mitral valve geometrical echocardiographic analysis and 3D computational modeling of a normal mitral valve

Aim: This research aims to develop a consistent computational model of a normal mitral valve (MV) and describe mitral regurgitation (MR) geometry based on Carpentier's classification. Materials & methods: MV geometry was assessed by 2D transthoracic echocardiogram in 100 individuals. A 3D parametric geometric model of the MV was developed. A computational model of a normal MV was performed. Results: The simulation of the valve function was successfully accomplished and its kinematics was analyzed. Differences in geometry were revealed between normal and type III MR. Conclusion: 3D computational models of the normal MV can be constructed relying on standard measurements performed by 2D echocardiography. Certain geometrical differences exist among the normal and the most severe type of MR.