On the in vivo function of the mitral heart valve leaflet: insights into tissue-interstitial cell biomechanical coupling

Simulated Effects of Acute Left Ventricular Myocardial Infarction on Mitral Regurgitation in an Ovine Model

Ischemic mitral regurgitation (IMR) occurs from incomplete coaptation of the mitral valve (MV) after myocardial infarction (MI), typically worsened by continued remodeling of the left ventricular (LV). The importance of LV remodeling is clear as IMR is induced by the post-MI dual mechanisms of mitral annular dilation and leaflet tethering from papillary muscle (PM) distension via the MV chordae tendineae (MVCT). However, the detailed etiology of IMR remains poorly understood, in large part due to the complex interactions of the MV and the post-MI LV remodeling processes. Given the patient-specific anatomical complexities of the IMR disease processes, simulation-based approaches represent an ideal approach to improve our understanding of this deadly disease. However, development of patient-specific models of left ventricle-mitral valve (LV-MV) interactions in IMR are complicated by the substantial variability and complexity of the MR etiology itself, making it difficult to extract underlying mechanisms from clinical data alone. To address these shortcomings, we developed a detailed ovine LV-MV finite element (FE) model based on extant comprehensive ovine experimental data. First, an extant ovine LV FE model (Sci. Rep. 2021 Jun 29;11(1):13466) was extended to incorporate the MV using a high fidelity ovine in vivo derived MV leaflet geometry. As it is not currently possible to image the MVCT in vivo, a functionally equivalent MVCT network was developed to create the final LV-MV model. Interestingly, in pilot studies, the MV leaflet strains did not agree well with known in vivo MV leaflet strain fields. We then incorporated previously reported MV leaflet prestrains (J. Biomech. Eng. 2023 Nov 1;145(11):111002) in the simulations. The resulting LV-MV model produced excellent agreement with the known in vivo ovine MV leaflet strains and deformed shapes in the normal state. We then simulated the effects of regional acute infarctions of varying sizes and anatomical locations by shutting down the local myocardial contractility. The remaining healthy (noninfarcted) myocardium mechanical behaviors were maintained, but allowed to adjust their active contractile patterns to maintain the prescribed pressure-volume loop behaviors in the acute post-MI state. For all cases studied, the LV-MV simulation demonstrated excellent agreement with known LV and MV in vivo strains and MV regurgitation orifice areas. Infarct location was shown to play a critical role in resultant MV leaflet strain fields. Specifically, extensional deformations of the posterior leaflets occurred in the posterobasal and laterobasal infarcts, while compressive deformations of the anterior leaflet were observed in the anterobasal infarct. Moreover, the simulated posterobasal infarct induced the largest MV regurgitation orifice area, consistent with experimental observations. The present study is the first detailed LV-MV simulation that reveals the important role of MV leaflet prestrain and functionally equivalent MVCT for accurate predictions of LV-MV interactions. Importantly, the current study further underscored simulation-based methods in understanding MV function as an integral part of the LV.

Bayesian Optimization-Based Inverse Finite Element Analysis for Atrioventricular Heart Valves

Inverse finite element analysis (iFEA) of the atrioventricular heart valves (AHVs) can provide insights into the in-vivo valvular function, such as in-vivo tissue strains; however, there are several limitations in the current state-of-the-art that iFEA has not been widely employed to predict the in-vivo, patient-specific AHV leaflet mechanical responses. In this exploratory study, we propose the use of Bayesian optimization (BO) to study the AHV functional behaviors in-vivo. We analyzed the efficacy of Bayesian optimization to estimate the isotropic Lee-Sacks material coefficients in three benchmark problems: (i) an inflation test, (ii) a simplified leaflet contact model, and (iii) an idealized AHV model. Then, we applied the developed BO-iFEA framework to predict the leaflet properties for a patient-specific tricuspid valve under a congenital heart defect condition. We found that the BO could accurately construct the objective function surface compared to the one from a [Formula: see text] grid search analysis. Additionally, in all cases the proposed BO-iFEA framework yielded material parameter predictions with average element errors less than 0.02 mm/mm (normalized by the simulation-specific characteristic length). Nonetheless, the solutions were not unique due to the presence of a long-valley minima region in the objective function surfaces. Parameter sets along this valley can yield functionally equivalent outcomes (i.e., closing behavior) and are typically observed in the inverse analysis or parameter estimation for the nonlinear mechanical responses of the AHV. In this study, our key contributions include: (i) a first-of-its-kind demonstration of the BO method used for the AHV iFEA; and (ii) the evaluation of a candidate AHV in-silico modeling approach wherein the chordae could be substituted with equivalent displacement boundary conditions, rendering the better iFEA convergence and a smoother objective surface.

Functional mechanical behavior of the murine pulmonary heart valve

Genetically modified mouse models provide a versatile and efficient platform to extend our understanding of the underlying disease processes and evaluate potential treatments for congenital heart valve diseases. However, applications have been limited to the gene and molecular levels due to the small size of murine heart valves, which prohibits the use of standard mechanical evaluation and in vivo imaging methods. We have developed an integrated imaging/computational mechanics approach to evaluate, for the first time, the functional mechanical behavior of the murine pulmonary heart valve (mPV). We utilized extant mPV high resolution µCT images of 1-year-old healthy C57BL/6J mice, with mPVs loaded to 0, 10, 20 or 30 mmHg then chemically fixed to preserve their shape. Individual mPV leaflets and annular boundaries were segmented and key geometric quantities of interest defined and quantified. The resulting observed inter-valve variations were small and consistent at each TVP level. This allowed us to develop a high fidelity NURBS-based geometric model. From the resultant individual mPV geometries, we developed a mPV shape-evolving geometric model (SEGM) that accurately represented mPV shape changes as a continuous function of transvalvular pressure. The SEGM was then integrated into an isogeometric finite element based inverse model that estimated the individual leaflet and regional mPV mechanical behaviors. We demonstrated that the mPV leaflet mechanical behaviors were highly anisotropic and nonlinear, with substantial leaflet and regional variations. We also observed the presence of strong axial mechanical coupling, suggesting the important role of the underlying collagen fiber architecture in the mPV. When compared to larger mammalian species, the mPV exhibited substantially different mechanical behaviors. Thus, while qualitatively similar, the mPV exhibited important functional differences that will need to accounted for in murine heart valve studies. The results of this novel study will allow detailed murine tissue and organ level investigations of semi-lunar heart valve diseases.

Three-dimensional analysis of hydrogel-imbedded aortic valve interstitial cell shape and its relation to contractile behavior

Cell-shape is a conglomerate of mechanical, chemical, and biological mechanisms that reflects the cell biophysical state. In a specific application, we consider aortic valve interstitial cells (AVICs), which maintain the structure and function of aortic heart valve leaflets. Actomyosin stress fibers help determine AVIC shape and facilitate processes such as adhesion, contraction, and mechanosensing. However, detailed 3D assessment of stress fiber architecture and function is currently impractical. Herein, we assessed AVIC shape and contractile behaviors using hydrogel-based 3D traction force microscopy to intuit the orientation and behavior of AVIC stress fibers. We utilized spherical harmonics (SPHARM) to quantify AVIC geometries through three days of incubation, which demonstrated a shift from a spherical shape to forming substantial protrusions. Furthermore, we assessed changes in post-three day AVIC shape and contractile function within two testing regimes: (1) normal contractile level to relaxation (cytochalasin D), and (2) normal contractile level to hyper-contraction (endothelin-1). In both scenarios, AVICs underwent isovolumic shape changes and produced complex displacement fields within the hydrogel. AVICs were more elongated when relaxed and more spherical in hyper-contraction. Locally, AVIC protrusions contracted along their long axis and expanded in their circumferential direction, indicating predominately axially aligned stress fibers. Furthermore, the magnitude of protrusion displacements was correlated with protrusion length and approached a consistent displacement plateau at a similar critical length across all AVICs. This implied that stress fiber behavior is conserved, despite great variations in AVIC shapes. We anticipate our findings will bolster future investigations into AVIC stress fiber architecture and function. STATEMENT OF SIGNIFICANCE: Within the aortic valve there exists a population of aortic valve interstitial cells, which orchestrate the turnover, secretion, and remodeling of its extracellular matrix, maintaining tissue integrity and ultimately sustaining the proper mechanical function. Alterations in these processes are thought to underlie diseases of the aortic valve, which affect hundreds of thousands domestically and world-wide. Yet, to date, there are no non-surgical treatments for aortic heart valve disease, in part due to our limited understanding of the underlying disease processes. In the present study, we built upon our previous study to include a full 3D analysis of aortic valve interstitial cell shapes at differing contractile levels. The resulting detailed shape and deformation analysis provided insight into the underlying stress-fiber structures and mechanical behaviors.

A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues From Digital Image Correlation Measurements

We present a data-driven workflow to biological tissue modeling, which aims to predict the displacement field based on digital image correlation (DIC) measurements under unseen loading scenarios, without postulating a specific constitutive model form nor possessing knowledge of the material microstructure. To this end, a material database is constructed from the DIC displacement tracking measurements of multiple biaxial stretching protocols on a porcine tricuspid valve anterior leaflet, with which we build a neural operator learning model. The material response is modeled as a solution operator from the loading to the resultant displacement field, with the material microstructure properties learned implicitly from the data and naturally embedded in the network parameters. Using various combinations of loading protocols, we compare the predictivity of this framework with finite element analysis based on three conventional constitutive models. From in-distribution tests, the predictivity of our approach presents good generalizability to different loading conditions and outperforms the conventional constitutive modeling at approximately one order of magnitude. When tested on out-of-distribution loading ratios, the neural operator learning approach becomes less effective. To improve the generalizability of our framework, we propose a physics-guided neural operator learning model via imposing partial physics knowledge. This method is shown to improve the model's extrapolative performance in the small-deformation regime. Our results demonstrate that with sufficient data coverage and/or guidance from partial physics constraints, the data-driven approach can be a more effective method for modeling biological materials than the traditional constitutive modeling.

Benchtop characterization of the tricuspid valve leaflet pre-strains

The pre-strains of biological soft tissues are important when relating their in vitro and in vivo mechanical behaviors. In this study, we present the first-of-its-kind experimental characterization of the tricuspid valve leaflet pre-strains. We use 3D photogrammetry and the reproducing kernel method to calculate the pre-strains within the central 10×10 mm region of the tricuspid valve leaflets from n=8 porcine hearts. In agreement with previous pre-strain studies for heart valve leaflets, our results show that all the three tricuspid valve leaflets shrink after explant from the ex vivo heart. These calculated strains are leaflet-specific and the septal leaflet experiences the most compressive changes. Furthermore, the strains observed after dissection of the central 10×10 mm region of the leaflet are smaller than when the valve is explanted, suggesting that our computed pre-strains are mainly due to the release of in situ annulus and chordae connections. The leaflets are then mounted on a biaxial testing device and preconditioned using force-controlled equibiaxial loading. We show that the employed preconditioning protocol does not 100% restore the leaflet pre-strains as removed during tissue dissection, and future studies are warranted to explore alternative preconditioning methods. Finally, we compare the calculated biomechanically oriented metrics considering five stress-free reference configurations. Interestingly, the radial tissue stretches and material anisotropies are significantly smaller compared to the post-preconditioning configuration. Extensions of this work can further explore the role of this unique leaflet-specific leaflet pre-strains on in vivo valve behavior via high-fidelity in-silico models.

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

Pre-surgical Prediction of Ischemic Mitral Regurgitation Recurrence Using In Vivo Mitral Valve Leaflet Strains

Ischemic mitral regurgitation (IMR) is a prevalent cardiac disease associated with substantial morbidity and mortality. Contemporary surgical treatments continue to have limited long-term success, in part due to the complex and multi-factorial nature of IMR. There is thus a need to better understand IMR etiology to guide optimal patient specific treatments. Herein, we applied our finite element-based shape-matching technique to non-invasively estimate peak systolic leaflet strains in human mitral valves (MVs) from in-vivo 3D echocardiographic images taken immediately prior to and post-annuloplasty repair. From a total of 21 MVs, we found statistically significant differences in pre-surgical MV size, shape, and deformation patterns between the with and without IMR recurrence patient groups at 6 months post-surgery. Recurrent MVs had significantly less compressive circumferential strains in the anterior commissure region compared to the recurrent MVs (p = 0.0223) and were significantly larger. A logistic regression analysis revealed that average pre-surgical circumferential leaflet strain in the Carpentier A1 region independently predicted 6-month recurrence of IMR (optimal cutoff value - 18%, p = 0.0362). Collectively, these results suggest greater disease progression in the recurrent group and underscore the highly patient-specific nature of IMR. Importantly, the ability to identify such factors pre-surgically could be used to guide optimal treatment methods to reduce post-surgical IMR recurrence.

On Valve Interstitial Cell Signaling: The Link Between Multiscale Mechanics and Mechanobiology

Heart valves function in one of the most mechanically demanding environments in the body to ensure unidirectional blood flow. The resident valve interstitial cells respond to this mechanical environment and maintain the structure and integrity of the heart valve tissues to preserve homeostasis. While the mechanics of organ-tissue-cell heart valve function has progressed, the intracellular signaling network downstream of mechanical stimuli has not been fully elucidated. This has hindered efforts to both understand heart valve mechanobiology and rationally identify drug targets for treating valve disease. In the present work, we review the current literature on VIC mechanobiology and then propose mechanistic mathematical modeling of the mechanically-stimulated VIC signaling response to comprehend the coupling between VIC mechanobiology and valve mechanics.

Manifold learning based data-driven modeling for soft biological tissues

Data-driven modeling directly utilizes experimental data with machine learning techniques to predict a material's response without the necessity of using phenomenological constitutive models. Although data-driven modeling presents a promising new approach, it has yet to be extended to the modeling of large-deformation biological tissues. Herein, we extend our recent local convexity data-driven (LCDD) framework (He and Chen, 2020) to model the mechanical response of a porcine heart mitral valve posterior leaflet. The predictability of the LCDD framework by using various combinations of biaxial and pure shear training protocols are investigated, and its effectiveness is compared with a full structural, phenomenological model modified from Zhang et al. (2016) and a continuum phenomenological Fung-type model (Tong and Fung, 1976). We show that the predictivity of the proposed LCDD nonlinear solver is generally less sensitive to the type of loading protocols (biaxial and pure shear) used in the data set, while more sensitive to the insufficient coverage of the experimental data when compared to the predictivity of the two selected phenomenological models. While no pre-defined functional form in the material model is necessary in LCDD, this study reinstates the importance of having sufficiently rich data coverage in the date-driven and machine learning type of approaches. It is also shown that the proposed LCDD method is an enhancement over the earlier distance-minimization data-driven (DMDD) against noisy data. This study demonstrates that when sufficient data is available, data-driven computing can be an alternative method for modeling complex biological materials.

On the role of predicted in vivo mitral valve interstitial cell deformation on its biosynthetic behavior

Ischemic mitral regurgitation (IMR), a frequent complication of myocardial infarction, is characterized by regurgitation of blood from the left ventricle back into the left atrium. Physical interventions via surgery or less-invasive techniques are the only available therapies for IMR, with valve repair via undersized ring annuloplasty (URA) generally preferred over valve replacement. However, recurrence of IMR after URA occurs frequently and is attributed to continued remodeling of the MV and infarct region of the left ventricle. The mitral valve interstitial cells (MVICs) that maintain the tissue integrity of the MV leaflets are highly mechanosensitive, and altered loading post-URA is thought to lead to aberrant MVIC-directed tissue remodeling. Although studies have investigated aspects of mechanically directed VIC activation and remodeling potential, there remains a substantial disconnect between organ-level biomechanics and cell-level phenomena. Herein, we utilized an extant multiscale computational model of the MV that linked MVIC to organ-level MV biomechanical behaviors to simulate changes in MVIC deformation following URA. A planar biaxial bioreactor system was then used to cyclically stretch explanted MV leaflet tissue, emulating the in vivo changes in loading following URA. This simulation-directed experimental investigation revealed that post-URA deformations resulted in decreased MVIC activation and collagen mass fraction. These results are consistent with the hypothesis that URA failures post-IMR are due, in part, to reduced MVIC-mediated maintenance of the MV leaflet tissue resulting from a reduction in physical stimuli required for leaflet tissue homeostasis. Such information can inform the development of novel URA strategies with improved durability.

Mitral valve leaflet response to ischaemic mitral regurgitation: from gene expression to tissue remodelling

Ischaemic mitral regurgitation (IMR), a frequent complication following myocardial infarction (MI), leads to higher mortality and poor clinical prognosis if untreated. Accumulating evidence suggests that mitral valve (MV) leaflets actively remodel post MI, and this remodelling increases both the severity of IMR and the occurrence of MV repair failures. However, the mechanisms of extracellular matrix maintenance and modulation by MV interstitial cells (MVICs) and their impact on MV leaflet tissue integrity and repair failure remain largely unknown. Herein, we sought to elucidate the multiscale behaviour of IMR-induced MV remodelling using an established ovine model. Leaflet tissue at eight weeks post MI exhibited significant permanent plastic radial deformation, eliminating mechanical anisotropy, accompanied by altered leaflet composition. Interestingly, no changes in effective collagen fibre modulus were observed, with MVICs slightly rounder, at eight weeks post MI. RNA sequencing indicated that YAP-induced genes were elevated at four weeks post MI, indicating elevated mechanotransduction. Genes related to extracellular matrix organization were downregulated at four weeks post MI when IMR occurred. Transcriptomic changes returned to baseline by eight weeks post MI. This multiscale study suggests that IMR induces plastic deformation of the MV with no functional damage to the collagen fibres, providing crucial information for computational simulations of the MV in IMR.

An investigation of layer-specific tissue biomechanics of porcine atrioventricular valve anterior leaflets

Atrioventricular heart valves (AHVs) are composed of structurally complex and morphologically heterogeneous leaflets. The coaptation of these leaflets during the cardiac cycle facilitates unidirectional blood flow. Valve regurgitation is treated preferably by surgical repair if possible or replacement based on the disease state of the valve tissue. A comprehensive understanding of valvular morphology and mechanical properties is crucial to refining computational models, serving as a patient-specific diagnostic and surgical tool for preoperative planning. Previous studies have modeled the stress distribution throughout the leaflet's thickness, but validations with layer-specific biaxial mechanical experiments are missing. In this study, we sought to fill this gap in literature by investigating the impact of microstructure constituents on mechanical behavior throughout the thickness of the AHVs' anterior leaflets. Porcine mitral valve anterior leaflets (MVAL) and tricuspid valve anterior leaflets (TVAL) were micro-dissected into three layers (atrialis/spongiosa, fibrosa, and ventricular) and two layers (atrialis/spongiosa and fibrosa/ventricularis), respectively, based on their relative distributions of extracellular matrix components as quantified by histological analyses: collagen, elastin, and glycosaminoglycans. Our results suggest that (i) for both valves, the atrialis/spongiosa layer is the most extensible and anisotropic layer, possibly due to its relatively low collagen content as compared to other layers, (ii) the intact TVAL response is stiffer than the atrialis/spongiosa layer but more compliant than the fibrosa/ventricularis layer, and (iii) the MVAL fibrosa and ventricularis layers behave nearly isotropic. These novel findings emphasize the biomechanical variances throughout the AHV leaflets, and our results could better inform future AHV computational model developments. STATEMENT OF SIGNIFICANCE: This study, which is the first of its kind for atrioventricular heart valve (AHV) leaflet tissue layers, rendered a mechanical characterization of the biaxial mechanical properties and distributions of extracellular matrix components (collagen, elastin, and glycosaminoglycans) of the mitral and tricuspid valve anterior leaflet layers. The novel findings from the present study emphasize the biomechanical variances throughout the thickness of AHV leaflets, and our results indicate that the previously-adopted homogenous leaflet in the AHV biomechanical modeling may be an oversimplification of the complex leaflet anatomy. Such improvement in the understanding of valvular morphology and tissue mechanics is crucial to future refinement of AHV computational models, serving as a patient-specific diagnostic and surgical tool, at the preoperative stage, for treating valvular heart diseases.

Quantifying heart valve interstitial cell contractile state using highly tunable poly(ethylene glycol) hydrogels

Valve interstitial cells (VIC) are the primary cell type residing within heart valve tissues. In many valve pathologies, VICs become activated and will subsequently profoundly remodel the valve tissue extracellular matrix (ECM). A primary indicator of VIC activation is the upregulation of α-smooth muscle actin (αSMA) stress fibers, which in turn increase VIC contractility. Thus, contractile state reflects VIC activation and ECM biosynthesis levels. In general, cell contraction studies have largely utilized two-dimensional substrates, which are a vastly different micro mechanical environment than 3D native leaflet tissue. To address this limitation, hydrogels have been a popular choice for studying cells in a three-dimensional environment due to their tunable properties and optical transparency, which allows for direct cell visualization. In the present study, we extended the use of hydrogels to study the active contractile behavior of VICs. Aortic VICs (AVIC) were encapsulated within poly(ethylene glycol) (PEG) hydrogels and were subjected to flexural-deformation tests to assess the state of AVIC contraction. Using a finite element model of the experimental setup, we determined the effective shear modulus μ of the constructs. An increase in μ resulting from AVIC active contraction was observed. Results further indicated that AVIC contraction had a more pronounced effect on μ in softer gels (72 ± 21% increase in μ within 2.5 kPa gels) and was dependent upon the availability of adhesion sites (0.5-1 mM CRGDS). The transparency of the gel allowed us to image AVICs directly within the hydrogel, where we observed a time-dependent decrease in volume (time constant τ=3.04 min) when the AVICs were induced into a hypertensive state. Our results indicated that AVIC contraction was regulated by both the intrinsic (unseeded) gel stiffness and the CRGDS peptide concentrations. This finding suggests that AVIC contractile state can be profoundly modulated through their local micro environment using modifiable PEG gels in a 3D micromechanical-emulating environment. Moving forward, this approach has the potential to be used towards delineating normal and diseased VIC biomechanical properties using highly tunable PEG biomaterials. STATEMENT OF SIGNIFICANCE.

Some Effects of Different Constitutive Laws on FSI Simulation for the Mitral Valve

In this paper, three different constitutive laws for mitral leaflets and two laws for chordae tendineae are selected to study their effects on mitral valve dynamics with fluid-structure interaction. We first fit these three mitral leaflet constitutive laws and two chordae tendineae laws with experimental data. The fluid-structure interaction is implemented in an immersed boundary framework with finite element extension for solid, that is the hybrid immersed boundary/finite element(IB/FE) method. We specifically compare the fluid-structure results of different constitutive laws since fluid-structure interaction is the physiological loading environment. This allows us to look at the peak jet velocity, the closure regurgitation volume, and the orifice area. Our numerical results show that different constitutive laws can affect mitral valve dynamics, such as the transvalvular flow rate, closure regurgitation and the orifice area, while the differences in fiber strain and stress are insignificant because all leaflet constitutive laws are fitted to the same set of experimental data. In addition, when an exponential constitutive law of chordae tendineae is used, a lower closure regurgitation flow is observed compared to that of a linear material model. In conclusion, combining numerical dynamic simulations and static experimental tests, we are able to identify suitable constitutive laws for dynamic behaviour of mitral leaflets and chordae under physiological conditions.

Analyzing valve interstitial cell mechanics and geometry with spatial statistics

Understanding cell geometric and mechanical properties is crucial to understanding how cells sense and respond to their local environment. Moreover, changes to cell mechanical properties under varied micro-environmental conditions can both influence and indicate fundamental changes to cell behavior. Atomic Force Microscopy (AFM) is a well established, powerful tool to capture geometric and mechanical properties of cells. We have previously demonstrated substantial functional and behavioral differences between aortic and pulmonary valve interstitial cells (VIC) using AFM and subsequent models of VIC mechanical response. In the present work, we extend these studies by demonstrating that to best interpret the spatially distributed AFM data, the use of spatial statistics is required. Spatial statistics includes formal techniques to analyze spatially distributed data, and has been used successfully in the analysis of geographic data. Thus, spatially mapped AFM studies of cell geometry and mechanics are analogous to more traditional forms of geospatial data. We are able to compare the spatial autocorrelation of stiffness in aortic and pulmonary valve interstitial cells, and more accurately capture cell geometry from height recordings. Specifically, we showed that pulmonary valve interstitial cells display higher levels of spatial autocorrelation of stiffness than aortic valve interstitial cells. This suggests that aortic VICs form different stress fiber structures than their pulmonary counterparts, in addition to being more highly expressed and stiffer on average. Thus, the addition of spatial statistics can contribute to our fundamental understanding of the differences between cell types. Moving forward, we anticipate that this work will be meaningful to enhance direct analysis of experimental data and for constructing high fidelity computational of VICs and other cell models.

An investigation of the glycosaminoglycan contribution to biaxial mechanical behaviours of porcine atrioventricular heart valve leaflets

The atrioventricular heart valve (AHV) leaflets have a complex microstructure composed of four distinct layers: atrialis, ventricularis, fibrosa and spongiosa. Specifically, the spongiosa layer is primarily proteoglycans and glycosaminoglycans (GAGs). Quantification of the GAGs' mechanical contribution to the overall leaflet function has been of recent focus for aortic valve leaflets, but this characterization has not been reported for the AHV leaflets. This study seeks to expand current GAG literature through novel mechanical characterizations of GAGs in AHV leaflets. For this characterization, mitral and tricuspid valve anterior leaflets (MVAL and TVAL, respectively) were: (i) tested by biaxial mechanical loading at varying loading ratios and by stress-relaxation procedures, (ii) enzymatically treated for removal of the GAGs and (iii) biaxially mechanically tested again under the same protocols as in step (i). Removal of the GAG contents from the leaflet was conducted using a 100 min enzyme treatment to achieve approximate 74.87% and 61.24% reductions of all GAGs from the MVAL and TVAL, respectively. Our main findings demonstrated that biaxial mechanical testing yielded a statistically significant difference in tissue extensibility after GAG removal and that stress-relaxation testing revealed a statistically significant smaller stress decay of the enzyme-treated tissue than untreated tissues. These novel findings illustrate the importance of GAGs in AHV leaflet behaviour, which can be employed to better inform heart valve therapeutics and computational models.

The Three-Dimensional Microenvironment of the Mitral Valve: Insights into the Effects of Physiological Loads

INTRODUCTION

In the mitral valve (MV), numerous pathological factors, especially those resulting from changes in external loading, have been shown to affect MV structure and composition. Such changes are driven by the MV interstitial cell (MVIC) population via protein synthesis and enzymatic degradation of extracellular matrix (ECM) components.

METHODS

While cell phenotype, ECM composition and regulation, and tissue level changes in MVIC shape under stress have been studied, a detailed understanding of the three-dimensional (3D) microstructural mechanisms are lacking. As a first step in addressing this challenge, we applied focused ion beam scanning electron microscopy (FIB-SEM) to reveal novel details of the MV microenvironment in 3D.

RESULTS

We demonstrated that collagen is organized into large fibers consisting of an average of 605 ± 113 fibrils, with a mean diameter of 61.2 ± 9.8 nm. In contrast, elastin was organized into two distinct structural subtypes: (1) sheet-like lamellar elastin, and (2) circumferentially oriented elastin struts, based on both the aspect ratio and transmural tilt. MVICs were observed to have a large cytoplasmic volume, as evidenced by the large mean surface area to volume ratio 3.68 ± 0.35, which increased under physiological loading conditions to 4.98 ± 1.17.

CONCLUSIONS

Our findings suggest that each MVIC mechanically interacted only with the nearest 3-4 collagen fibers. This key observation suggests that in developing multiscale MV models, each MVIC can be considered a mechanically integral part of the local fiber ensemble and is unlikely to be influenced by more distant structures.

An investigation of the anisotropic mechanical properties and anatomical structure of porcine atrioventricular heart valves

Valvular heart diseases are complex disorders, varying in pathophysiological mechanism and affected valve components. Understanding the effects of these diseases on valve functionality requires a thorough characterization of the mechanics and structure of the healthy heart valves. In this study, we performed biaxial mechanical experiments with extensive testing protocols to examine the mechanical behaviors of the mitral valve and tricuspid valve leaflets. We also investigated the effect of loading rate, testing temperatures, species (porcine versus ovine hearts), and age (juvenile vs adult ovine hearts) on the mechanical responses of the leaflet tissues. In addition, we evaluated the structure of chordae tendineae within each valve and performed histological analysis on each atrioventricular leaflet. We found all tissues displayed a characteristic nonlinear anisotropic mechanical response, with radial stretches on average 30.7% higher than circumferential stretches under equibiaxial physiological loading. Tissue mechanical responses showed consistent mechanical stiffening in response to increased loading rate and minor temperature dependence in all five atrioventricular heart valve leaflets. Moreover, our anatomical study revealed similar chordae quantities in the porcine mitral (30.5 ± 1.43 chords) and tricuspid valves (35.3 ± 2.45 chords) but significantly more chordae in the porcine than the ovine valves (p < 0.010). Our histological analyses quantified the relative thicknesses of the four distinct morphological layers in each leaflet. This study provides a comprehensive database of the mechanics and structure of the atrioventricular valves, which will be beneficial to development of subject-specific atrioventricular valve constitutive models and toward multi-scale biomechanical investigations of heart valve function to improve valvular disease treatments.