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

An Inverse Modeling Approach to Estimate Three-Dimensional Aortic Valve Interstitial Cell Stress Fiber Force Levels

Within the aortic valve (AV) leaflet exists a population of interstitial cells (AVICs) that maintain the constituent tissues by extracellular matrix (ECM) secretion, degradation, and remodeling. AVICs can transition from a quiescent, fibroblast-like phenotype to an activated, myofibroblast phenotype in response to growth or disease. AVIC dysfunction has been implicated in AV disease processes, yet our understanding of AVIC function remains quite limited. A major characteristic of the AVIC phenotype is its contractile state, driven by contractile forces generated by the underlying stress fibers (SF). However, direct assessment of the AVIC SF contractile state and structure within physiologically mimicking three-dimensional environments remains technically challenging, as the size of single SFs are below the resolution of light microscopy. Therefore, in the present study, we developed a three-dimensional (3D) computational approach of AVICs embedded in 3D hydrogels to estimate their SF local orientations and contractile forces. One challenge with this approach is that AVICs will remodel the hydrogel, so that the gel moduli will vary spatially. We thus utilized our previous approach (Khang et al. 2023, "Estimation of Aortic Valve Interstitial Cell-Induced 3D Remodeling of Poly (Ethylene Glycol) Hydrogel Environments Using an Inverse Finite Element Approach," Acta Biomater., 160, pp. 123-133) to define local hydrogel mechanical properties. The AVIC SF model incorporated known cytosol and nucleus mechanical behaviors, with the cell membrane assumed to be perfectly bonded to the surrounding hydrogel. The AVIC SFs were first modeled as locally unidirectional hyperelastic fibers with a contractile force component. An adjoint-based inverse modeling approach was developed to estimate local SF orientation and contractile force. Substantial heterogeneity in SF force and orientations were observed, with the greatest levels of SF alignment and contractile forces occurring in AVIC protrusions. The addition of a dispersed SF orientation to the modeling approach did not substantially alter these findings. To the best of our knowledge, we report the first fully 3D computational contractile cell models which can predict locally varying stress fiber orientation and contractile force levels.

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.

The effects of strain history on aortic valve interstitial cell activation in a 3D hydrogel environment

Aortic valves (AVs) undergo unique stretch histories that include high rates and magnitudes. While major differences in deformation patterns have been observed between normal and congenitally defective bicuspid aortic valves (BAVs), the relation to underlying mechanisms of rapid disease onset in BAV patients remains unknown. To evaluate how the variations in stretch history affect AV interstitial cell (AVIC) activation, high-throughput methods were developed to impart varied cyclical biaxial stretch histories into 3D poly(ethylene) glycol hydrogels seeded with AVICs for 48 h. Specifically, a physiologically mimicking stretch history was compared to two stretch histories with varied peak stretch and stretch rate. Post-conditioned AVICs were imaged for nuclear shape, alpha smooth muscle actin (αSMA) and vimentin (VMN) polymerization, and small mothers against decapentaplegic homologs 2 and 3 (SMAD 2/3) nuclear activity. The results indicated that bulk gel deformations were accurately transduced to the AVICs. Lower peak stretches lead to increased αSMA polymerization. In contrast, VMN polymerization was a function of stretch rate, with SMAD 2/3 nuclear localization and nuclear shape also trending toward stretch rate dependency. Lower than physiological levels of stretch rate led to higher SMAD 2/3 activity, higher VMN polymerization around the nucleus, and lower nuclear elongation. αSMA polymerization did not correlate with VMN polymerization, SMAD 2/3 activity, nor nuclear shape. These results suggest that a negative feedback loop may form between SMAD 2/3, VMN, and nuclear shape to maintain AVIC homeostatic nuclear deformations, which is dependent on stretch rate. These novel results suggest that AVIC mechanobiological responses are sensitive to stretch history and provide insight into the mechanisms of AV disease.

Utilization of Engineering Advances for Detailed Biomechanical Characterization of the Mitral-Ventricular Relationship to Optimize Repair Strategies: A Comprehensive Review

The geometrical details and biomechanical relationships of the mitral valve-left ventricular apparatus are very complex and have posed as an area of research interest for decades. These characteristics play a major role in identifying and perfecting the optimal approaches to treat diseases of this system when the restoration of biomechanical and mechano-biological conditions becomes the main target. Over the years, engineering approaches have helped to revolutionize the field in this regard. Furthermore, advanced modelling modalities have contributed greatly to the development of novel devices and less invasive strategies. This article provides an overview and narrative of the evolution of mitral valve therapy with special focus on two diseases frequently encountered by cardiac surgeons and interventional cardiologists: ischemic and degenerative mitral regurgitation.

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

Degenerative mitral valve disease is the main cause of primary mitral regurgitation with two phenotypes: fibroelastic deficiency (FED) often with localized myxomatous degeneration and diffuse myxomatous degeneration or Barlow's disease. Myxomatous degeneration disrupts the microstructure of the mitral valve leaflets, particularly the collagen fibers, which affects the mechanical behavior of the leaflets. The present study uses biaxial mechanical tests and second harmonic generation microscopy to examine the mechanical behavior of Barlow and FED tissue. Three tissue samples were harvested from a FED patient and one sample is from a Barlow patient. Then we use an appropriate constitutive model by excluding the collagen fibers under compression. Finally, we built an FE model based on the echocardiography of patients diagnosed with FED and Barlow and the characterized material model and collagen fiber orientation. The Barlow sample and the FED sample from the most affected segment showed different mechanical behavior and collagen structure compared to the other two FED samples. The FE model showed very good agreement with echocardiography with 2.02±1.8 mm and 1.05±0.79 mm point-to-mesh distance errors for Barlow and FED patients, respectively. It has also been shown that the exclusion of collagen fibers under compression provides versatility for the material model; it behaves stiff in the belly region, preventing excessive bulging, while it behaves very softly in the commissures to facilitate folding. STATEMENT OF SIGNIFICANCE: None.

Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond

Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown significant promising results, ML for the prediction of biomechanics such as blood flow or tissue dynamics is in its infancy. This perspective article discusses some of the challenges in using ML for replacing well-established physics-based models in cardiovascular biomechanics. Specifically, we discuss the large landscape of input features in 3D patient-specific modeling as well as the high-dimensional output space of field variables that vary in space and time. We argue that the end purpose of such ML models needs to be clearly defined and the tradeoff between the loss in accuracy and the gained speedup carefully interpreted in the context of translational modeling. We also discuss several exciting venues where ML could be strategically used to augment traditional physics-based modeling in cardiovascular biomechanics. In these applications, ML is not replacing physics-based modeling, but providing opportunities to solve ill-defined problems, improve measurement data quality, enable a solution to computationally expensive problems, and interpret complex spatiotemporal data by extracting hidden patterns. In summary, we suggest a strategic integration of ML in cardiovascular biomechanics modeling where the ML model is not the end goal but rather a tool to facilitate enhanced modeling.

Mechano-regulated cell-cell signaling in the context of cardiovascular tissue engineering

Cardiovascular tissue engineering (CVTE) aims to create living tissues, with the ability to grow and remodel, as replacements for diseased blood vessels and heart valves. Despite promising results, the (long-term) functionality of these engineered tissues still needs improvement to reach broad clinical application. The functionality of native tissues is ensured by their specific mechanical properties directly arising from tissue organization. We therefore hypothesize that establishing a native-like tissue organization is vital to overcome the limitations of current CVTE approaches. To achieve this aim, a better understanding of the growth and remodeling (G&R) mechanisms of cardiovascular tissues is necessary. Cells are the main mediators of tissue G&R, and their behavior is strongly influenced by both mechanical stimuli and cell-cell signaling. An increasing number of signaling pathways has also been identified as mechanosensitive. As such, they may have a key underlying role in regulating the G&R of tissues in response to mechanical stimuli. A more detailed understanding of mechano-regulated cell-cell signaling may thus be crucial to advance CVTE, as it could inspire new methods to control tissue G&R and improve the organization and functionality of engineered tissues, thereby accelerating clinical translation. In this review, we discuss the organization and biomechanics of native cardiovascular tissues; recent CVTE studies emphasizing the obtained engineered tissue organization; and the interplay between mechanical stimuli, cell behavior, and cell-cell signaling. In addition, we review past contributions of computational models in understanding and predicting mechano-regulated tissue G&R and cell-cell signaling to highlight their potential role in future CVTE strategies.

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.

Biology and Biomechanics of the Heart Valve Extracellular Matrix

Heart valves are dynamic structures that, in the average human, open and close over 100,000 times per day, and 3 × 10⁹ times per lifetime to maintain unidirectional blood flow. Efficient, coordinated movement of the valve structures during the cardiac cycle is mediated by the intricate and sophisticated network of extracellular matrix (ECM) components that provide the necessary biomechanical properties to meet these mechanical demands. Organized in layers that accommodate passive functional movements of the valve leaflets, heart valve ECM is synthesized during embryonic development, and remodeled and maintained by resident cells throughout life. The failure of ECM organization compromises biomechanical function, and may lead to obstruction or leaking, which if left untreated can lead to heart failure. At present, effective treatment for heart valve dysfunction is limited and frequently ends with surgical repair or replacement, which comes with insuperable complications for many high-risk patients including aged and pediatric populations. Therefore, there is a critical need to fully appreciate the pathobiology of biomechanical valve failure in order to develop better, alternative therapies. To date, the majority of studies have focused on delineating valve disease mechanisms at the cellular level, namely the interstitial and endothelial lineages. However, less focus has been on the ECM, shown previously in other systems, to be a promising mechanism-inspired therapeutic target. Here, we highlight and review the biology and biomechanical contributions of key components of the heart valve ECM. Furthermore, we discuss how human diseases, including connective tissue disorders lead to aberrations in the abundance, organization and quality of these matrix proteins, resulting in instability of the valve infrastructure and gross functional impairment.

Age related extracellular matrix and interstitial cell phenotype in pulmonary valves

Heart valve disease is a common manifestation of cardiovascular disease and is a significant cause of cardiovascular morbidity and mortality worldwide. The pulmonary valve (PV) is of primary concern because of its involvement in common congenital heart defects, and the PV is usually the site for prosthetic replacement following a Ross operation. Although effects of age on valve matrix components and mechanical properties for aortic and mitral valves have been studied, very little is known about the age-related alterations that occur in the PV. In this study, we isolated PV leaflets from porcine hearts in different age groups (~ 4-6 months, denoted as young versus ~ 2 years, denoted as adult) and studied the effects of age on PV leaflet thickness, extracellular matrix components, and mechanical properties. We also conducted proteomics and RNA sequencing to investigate the global changes of PV leaflets and passage zero PV interstitial cells in their protein and gene levels. We found that the size, thickness, elastic modulus, and ultimate stress in both the radial and circumferential directions and the collagen of PV leaflets increased from young to adult age, while the ultimate strain and amount of glycosaminoglycans decreased when age increased. Young and adult PV had both similar and distinct protein and gene expression patterns that are related to their inherent physiological properties. These findings are important for us to better understand the physiological microenvironments of PV leaflet and valve cells for correctively engineering age-specific heart valve tissues.

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.

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.

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.

Non-Destructive Reflectance Mapping of Collagen Fiber Alignment in Heart Valve Leaflets

Collagen fibers are the primary structural elements that define many soft-tissue structure and mechanical function relationships, so that quantification of collagen organization is essential to many disciplines. Current tissue-level collagen fiber imaging techniques remain limited in their ability to quantify fiber organization at macroscopic spatial scales and multiple time points, especially in a non-contacting manner, requiring no modifications to the tissue, and in near real-time. Our group has previously developed polarized spatial frequency domain imaging (pSFDI), a reflectance imaging technique that rapidly and non-destructively quantifies planar collagen fiber orientation in superficial layers of soft tissues over large fields-of-view. In this current work, we extend the light scattering models and image processing techniques to extract a critical measure of the degree of collagen fiber alignment, the normalized orientation index (NOI), directly from pSFDI data. Electrospun fiber samples with architectures similar to many collagenous soft tissues and known NOI were used for validation. An inverse model was then used to extract NOI from pSFDI measurements of aortic heart valve leaflets and clearly demonstrated changes in degree of fiber alignment between opposing sides of the sample. These results show that our model was capable of extracting absolute measures of degree of fiber alignment in superficial layers of heart valve leaflets with only general a priori knowledge of fiber properties, providing a novel approach to rapid, non-destructive study of microstructure in heart valve leaflets using a reflectance geometry.

Development of a Functionally Equivalent Model of the Mitral Valve Chordae Tendineae Through Topology Optimization

Ischemic mitral regurgitation (IMR) is a currently prevalent disease in the US that is projected to become increasingly common as the aging population grows. In recent years, image-based simulations of mitral valve (MV) function have improved significantly, providing new tools to refine IMR treatment. However, clinical implementation of MV simulations has long been hindered as the in vivo MV chordae tendineae (MVCT) geometry cannot be captured with sufficient fidelity for computational modeling. In the current study, we addressed this challenge by developing a method to produce functionally equivalent MVCT models that can be built from the image-based MV leaflet geometry alone. We began our analysis using extant micron-resolution 3D imaging datasets to first build anatomically accurate MV models. We then systematically simplified the native MVCT structure to generate a series of synthetic models by consecutively removing key anatomic features, such as the thickness variations, branching patterns, and chordal origin distributions. In addition, through topology optimization, we identified the minimal structural complexity required to capture the native MVCT behavior. To assess the performance and predictive power of each synthetic model, we analyzed their performance by comparing the mismatch in simulated MV closed shape, as well as the strain and stress tensors, to ground-truth MV models. Interestingly, our results revealed a substantial redundancy in the anatomic structure of native chordal anatomy. We showed that the closing behavior of complete MV apparatus under normal, diseased, and surgically repaired scenarios can be faithfully replicated by a functionally equivalent MVCT model comprised of two representative papillary muscle heads, single strand chords, and a uniform insertion distribution with a density of 15 insertions/cm2. Hence, even though the complete sub-valvular structure is mostly missing in in vivo MV images, we believe our approach will allow for the development of patient-specific complete MV models for surgical repair planning.

A noninvasive method for the determination of in vivo mitral valve leaflet strains

Assessment of mitral valve (MV) function is important in many diagnostic, prognostic, and surgical planning applications for treatment of MV disease. Yet, to date, there are no accepted noninvasive methods for determination of MV leaflet deformation, which is a critical metric of MV function. In this study, we present a novel, completely noninvasive computational method to estimate MV leaflet in-plane strains from clinical-quality real-time three-dimensional echocardiography (rt-3DE) images. The images were first segmented to produce meshed medial-surface leaflet geometries of the open and closed states. To establish material point correspondence between the two states, an image-based morphing pipeline was implemented within a finite element (FE) modeling framework in which MV closure was simulated by pressurizing the open-state geometry, and local corrective loads were applied to enforce the actual MV closed shape. This resulted in a complete map of local systolic leaflet membrane strains, obtained from the final FE mesh configuration. To validate the method, we utilized an extant in vitro database of fiducially labeled MVs, imaged in conditions mimicking both the healthy and diseased states. Our method estimated local anisotropic in vivo strains with less than 10% error and proved to be robust to changes in boundary conditions similar to those observed in ischemic MV disease. Next, we applied our methodology to ovine MVs imaged in vivo with rt-3DE and compared our results to previously published findings of in vivo MV strains in the same type of animal as measured using surgically sutured fiducial marker arrays. In regions encompassed by fiducial markers, we found no significant differences in circumferential(P = 0.240) or radial (P = 0.808) strain estimates between the marker-based measurements and our novel noninvasive method. This method can thus be used for model validation as well as for studies of MV disease and repair.