A comprehensive pipeline for multi-resolution modeling of the mitral valve: Validation, computational efficiency, and predictive capability

Effect of Parametric Variation of Chordae Tendineae Structure on Simulated Atrioventricular Valve Closure

Purpose

Many approaches have been used to model chordae tendineae geometries in finite element simulations of atrioventricular heart valves. Unfortunately, current "functional" chordae tendineae geometries lack fidelity (e.g., branching) that would be helpful when informing clinical decisions. The objectives of this work are (i) to improve synthetic chordae tendineae geometry fidelity to consider branching and (ii) to define how the chordae tendineae geometry affects finite element simulations of valve closure.

Methods

In this work, we develop an open-source method to construct synthetic chordae tendineae geometries in the SlicerHeart Extension of 3D Slicer. The generated geometries are then used in FEBio finite element simulations of atrioventricular valve function to evaluate how variations in chordae tendineae geometry influence valve behavior. Effects are evaluated using functional and mechanical metrics.

Results

Our findings demonstrated that altering the chordae tendineae geometry of a stereotypical mitral valve led to changes in clinically relevant valve metrics (regurgitant orifice area, contact area, and billowing volume) and valve mechanics (first principal strains). Specifically, cross sectional area had the most influence over valve closure metrics, followed by chordae tendineae density, length, radius and branches. We then used this information to showcase the flexibility of our new workflow by altering the chordae tendineae geometry of two additional geometries (mitral valve with annular dilation and tricuspid valve) to improve finite element predictions.

Conclusion

This study presents a flexible, open-source method for generating synthetic chordae tendineae with realistic branching structures. Further, we establish relationships between the chordae tendineae geometry and valve functional/mechanical metrics. This research contribution helps enrich our opensource workflow and brings the finite element simulations closer to use in a patient-specific clinical setting.

MV-GNN: Generation of continuous geometric representations of mitral valve motion from 3D+t echocardiography

We present a geometric deep-learning method for reconstructing a temporally continuous mitral valve surface mesh from 3D transesophageal echocardiography sequences. Our approach features a supervised end-to-end deep learning architecture that combines a convolutional neural network-based voxel encoder and decoder with a graph neural network-based multi-resolution mesh decoder, all trained on sparse landmark annotations. Key elements of our methodology include a tube-shaped prototype mesh with labeled vertices, a specialized loss function to preserve the known inlet and outlet, and a rigid alignment system for anatomical landmarks. A custom term in the loss function prevents self-intersecting geometries within the valve mesh, promoting point correspondence and facilitating a continuous representation of valve anatomy over time. An ablation study evaluates the impact of different loss term configurations on model performance, highlighting the effectiveness of each individual loss term. Our Mitral Valve Graph Neural Network (MV-GNN) outperforms existing deep-learning methods on most distance metrics for the annulus and leaflets. The continuous valve motion representations generated by our approach (3D+t) exhibit distance measures comparable to our 3D solution, demonstrating its potential for analyzing mitral valve dynamics and enhancing personalized simulations for hemodynamic assessment and therapy planning.

Computational simulation model of transcatheter edge-to-edge mitral valve repair: a proof-of-concept study

AIMS

As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in pre-procedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element computational simulation model to predict the results of transcatheter edge-to-edge repair (TEER) interventions.

METHODS AND RESULTS

We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. The 3D trans-oesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after the simulation of the clip implantation was compared with the clinical results obtained at the end of the intervention. We analysed the degree and location of residual MR and the shape and area of the diastolic MV area. We performed computational simulation on five patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area.

CONCLUSION

In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in five patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic MV area.

A Computational Pipeline for Patient-Specific Prediction of the Postoperative Mitral Valve Functional State

While mitral valve (MV) repair remains the preferred clinical option for mitral regurgitation (MR) treatment, long-term outcomes remain suboptimal and difficult to predict. Furthermore, pre-operative optimization is complicated by the heterogeneity of MR presentations and the multiplicity of potential repair configurations. In the present work, we established a patient-specific MV computational pipeline based strictly on standard-of-care pre-operative imaging data to quantitatively predict the post-repair MV functional state. First, we established human mitral valve chordae tendinae (MVCT) geometric characteristics obtained from five CT-imaged excised human hearts. From these data, we developed a finite-element model of the full patient-specific MV apparatus that included MVCT papillary muscle origins obtained from both the in vitro study and the pre-operative three-dimensional echocardiography images. To functionally tune the patient-specific MV mechanical behavior, we simulated pre-operative MV closure and iteratively updated the leaflet and MVCT prestrains to minimize the mismatch between the simulated and target end-systolic geometries. Using the resultant fully calibrated MV model, we simulated undersized ring annuloplasty (URA) by defining the annular geometry directly from the ring geometry. In three human cases, the postoperative geometries were predicted to 1 mm of the target, and the MV leaflet strain fields demonstrated close agreement with noninvasive strain estimation technique targets. Interestingly, our model predicted increased posterior leaflet tethering after URA in two recurrent patients, which is the likely driver of long-term MV repair failure. In summary, the present pipeline was able to predict postoperative outcomes from pre-operative clinical data alone. This approach can thus lay the foundation for optimal tailored surgical planning for more durable repair, as well as development of mitral valve digital twins.

Patient-Specific Quantitative In-Vivo Assessment of Human Mitral Valve Leaflet Strain Before and After MitraClip Repair

PURPOSE

Mitral regurgitation (MR) is a highly prevalent and deadly cardiac disease characterized by improper mitral valve (MV) leaflet coaptation. Among the plethora of available treatment strategies, the MitraClip is an especially safe option, but optimizing its long-term efficacy remains an urgent challenge.

METHODS

We applied our noninvasive image-based strain computation pipeline [1] to intraoperative transesophageal echocardiography datasets taken from ten patients undergoing MitraClip repair, spanning a range of MR etiologies and MitraClip configurations. We then analyzed MV leaflet strains before and after MitraClip implementation to develop a better understanding of (1) the pre-operative state of human regurgitant MV, and (2) the MitraClip's impact on the MV leaflet deformations.

RESULTS

The MV pre-operative strain fields were highly variable, underscoring both the heterogeneity of the MR in the patient population and the need for patient-specific treatment approaches. Similarly, there were no consistent overall post-operative strain patterns, although the average A2 segment radial strain difference between pre- and post-operative states was consistently positive. In contrast, the post-operative strain fields were better correlated to their respective pre-operative strain fields than to the inter-patient post-operative strain fields. This quantitative result implies that the patient specific pre-operative state of the MV guides its post-operative deformation, which suggests that the post-operative state can be predicted using pre-operative data-derived modelling alone.

CONCLUSIONS

The pre-operative MV leaflet strain patterns varied considerably across the range of MR disease states and after MitraClip repair. Despite large inter-patient heterogeneity, the post-operative deformation appears principally dictated by the pre-operative deformation state. This novel finding suggests that though the variation in MR functional state and MitraClip-induced deformation were substantial, the post-operative state can be predicted from the pre-operative data alone. This study suggests that, with use of larger patient cohort and corresponding long-term outcomes, quantitative predictive factors of MitraClip durability can be identified.

Simulation of Mitral Valve Plasticity in Response to Myocardial Infarction

Left ventricular myocardial infarction (MI) has broad and debilitating effects on cardiac function. In many cases, MI leads to ischemic mitral regurgitation (IMR), a condition characterized by incompetency of the mitral valve (MV). IMR has many deleterious effects as well as a high mortality rate. While various clinical treatments for IMR exist, success of these procedures remains limited, in large part because IMR dramatically alters the geometry and function of the MV in ways that are currently not well understood. Previous investigations of post-MI MV remodeling have elucidated that MV tissues have a significant ability to undergo a form of permanent inelastic deformations in the first phase of the post-MI period. These changes appear to be attributable to the altered loading and boundary conditions on the MV itself, as opposed to an independent pathophysiological process. Mechanistically, these results suggest that the MV mostly responds passively to MI during the first 8 weeks post-MI by undergoing a permanent deformation. In the present study, we developed the first computational model of this post-MI MV remodeling process, which we term "mitral valve plasticity." Integrating methodologies and insights from previous studies of in vivo ovine MV function, image-based patient-specific model development, and post-MI MV adaptation, we constructed a representative geometric model of a pre-MI MV. We then performed finite element simulations of the entire MV apparatus under time-dependent boundary conditions and accounting for changes to material properties equivalent to those observed 0-8 weeks post-MI. Our results suggest that during this initial period of adaptation, the MV response to MI can be accurately modeled using a soft tissue plasticity approach, similar to permanent set frameworks that have been applied previously in the context of exogenously crosslinked tissues.

Neural Network Approaches for Soft Biological Tissue and Organ Simulations

Given the functional complexities of soft tissues and organs, it is clear that computational simulations are critical in their understanding and for the rational basis for the development of therapies and replacements. A key aspect of such simulations is accounting for their complex, nonlinear, anisotropic mechanical behaviors. While soft tissue material models have developed to the point of high fidelity, in-silico implementation is typically done using the finite element (FE) method, which remains impractically slow for translational clinical time frames. As a potential path toward addressing the development of high fidelity simulations capable of performing in clinically relevant time frames, we review the use of neural networks (NN) for soft tissue and organ simulation using two approaches. In the first approach, we show how a NN can learn the responses for a detailed meso-structural soft tissue material model. The NN material model not only reproduced the full anisotropic mechanical responses but also demonstrated a considerable efficiency improvement, as it was trained over a range of realizable fibrous structures. In the second approach, we go a step further with the use of a physics-based surrogate model to directly learn the displacement field solution without the need for raw training data or FE simulation datasets. In this approach we utilize a finite element mesh to define the domain and perform the necessary integrations, but not the finite element method (FEM) itself. We demonstrate with this approach, termed neural network finite element (NNFE), results in a trained NNFE model with excellent agreement with the corresponding "ground truth" FE solutions over the entire physiological deformation range on a cuboidal myocardium specimen. More importantly, the NNFE approach provided a significantly decreased computational time for a range of finite element mesh sizes. Specifically, as the FE mesh size increased from 2744 to 175,615 elements, the NNFE computational time increased from 0.1108 s to 0.1393 s, while the "ground truth" FE model increased from 4.541 s to 719.9 s, with the same effective accuracy. These results suggest that NNFE run times are significantly reduced compared with the traditional large-deformation-based finite element solution methods. We then show how a nonuniform rational B-splines (NURBS)-based approach can be directly integrated into the NNFE approach as a means to handle real organ geometries. While these and related approaches are in their early stages, they offer a method to perform complex organ-level simulations in clinically relevant time frames without compromising accuracy.

In vivo assessment of mitral valve leaflet remodelling following myocardial infarction

Each year, more than 40,000 people undergo mitral valve (MV) repair surgery domestically to treat regurgitation caused by myocardial infarction (MI). Although continual MV tissue remodelling following repair is believed to be a major contributor to regurgitation recurrence, the effects of the post-MI state on MV remodelling remain poorly understood. This lack of understanding limits our ability to predict the remodelling of the MV both post-MI and post-surgery to facilitate surgical planning. As a necessary first step, the present study was undertaken to noninvasively quantify the effects of MI on MV remodelling in terms of leaflet geometry and deformation. MI was induced in eight adult Dorset sheep, and real-time three-dimensional echocardiographic (rt-3DE) scans were collected pre-MI as well as at 0, 4, and 8 weeks post-MI. A previously validated image-based morphing pipeline was used to register corresponding open- and closed-state scans and extract local in-plane strains throughout the leaflet surface at systole. We determined that MI induced permanent changes in leaflet dimensions in the diastolic configuration, which increased with time to 4 weeks, then stabilised. MI substantially affected the systolic shape of the MV, and the range of stretch experienced by the MV leaflet at peak systole was substantially reduced when referred to the current time-point. Interestingly, when we referred the leaflet strains to the pre-MI configuration, the systolic strains remained very similar throughout the post-MI period. Overall, we observed that post-MI ventricular remodeling induced permanent changes in the MV leaflet shape. This predominantly affected the MV's diastolic configuration, leading in turn to a significant decrease in the range of stretch experienced by the leaflet when referenced to the current diastolic configuration. These findings are consistent with our previous work that demonstrated increased plastic (i.e. non-recoverable) leaflet deformations post-MI, that was completely accounted for by the associated changes in collagen fiber structure. Moreover, we demonstrated through noninvasive methods that the state of the MV leaflet can elucidate the progression and extent of MV adaptation following MI and is thus highly relevant to the design of current and novel patient specific minimally invasive surgical repair strategies.

Quantitative in vivo assessment of human mitral valve coaptation area after undersized ring annuloplasty repair for ischemic mitral regurgitation

Objectives

Long-term outcomes of mitral valve repair procedures to correct ischemic mitral regurgitation remain unpredictable, due to an incomplete understanding of the disease process and the inability to reliably quantify the coaptation zone using echocardiography. Our objective was to quantify patient-specific mitral valve coaptation behavior from clinical echocardiographic images obtained before and after repair to assess coaptation restoration and its relationship with long-term repair durability.

Methods

To circumvent the limitations of clinical imaging, we applied a simulation-based shape-matching technique that allowed high-fidelity reconstructions of the complete mitral valve in the systolic configuration. We then applied this method to an extant database of human regurgitant mitral valves before and after undersized ring annuloplasty to quantify the effect of the repair on mitral valve coaptation geometry.

Results

Our method was able to successfully resolve the coaptation zone into distinct contacting and redundant regions. Results indicated that in patients whose regurgitation recurred 6 months postrepair, both the contacting and redundant regions were larger immediately postrepair compared with patients with no recurrence (P < .05), even when normalized to account for generally larger recurrent valves.

Conclusions

Although increasing leaflet coaptation area is an intuitively obvious way to improve long-term repair durability, this study has implied that this may not be a reliable target for mitral valve repair. This study underscores the importance of a rigorous understanding of the consequences of repair techniques on mitral valve behavior, as well as a patient-specific approach to ischemic mitral regurgitation treatment within the context of mitral valve and left ventricle function.

A Computational Framework for Atrioventricular Valve Modeling Using Open-Source Software

Atrioventricular valve regurgitation is a significant cause of morbidity and mortality in patients with acquired and congenital cardiac valve disease. Image-derived computational modeling of atrioventricular valves has advanced substantially over the last decade and holds particular promise to inform valve repair in small and heterogeneous populations, which are less likely to be optimized through empiric clinical application. While an abundance of computational biomechanics studies has investigated mitral and tricuspid valve disease in adults, few studies have investigated its application to vulnerable pediatric and congenital heart populations. Further, to date, investigators have primarily relied upon a series of commercial applications that are neither designed for image-derived modeling of cardiac valves nor freely available to facilitate transparent and reproducible valve science. To address this deficiency, we aimed to build an open-source computational framework for the image-derived biomechanical analysis of atrioventricular valves. In the present work, we integrated an open-source valve modeling platform, SlicerHeart, and an open-source biomechanics finite element modeling software, FEBio, to facilitate image-derived atrioventricular valve model creation and finite element analysis. We present a detailed verification and sensitivity analysis to demonstrate the fidelity of this modeling in application to three-dimensional echocardiography-derived pediatric mitral and tricuspid valve models. Our analyses achieved an excellent agreement with those reported in the literature. As such, this evolving computational framework offers a promising initial foundation for future development and investigation of valve mechanics, in particular collaborative efforts targeting the development of improved repairs for children with congenital heart disease.

Texas TriValve 1.0 : a reverse‑engineered, open model of the human tricuspid valve

Nearly 1.6 million Americans suffer from a leaking tricuspid heart valve. To make matters worse, current valve repair options are far from optimal leading to recurrence of leakage in up to 30% of patients. We submit that a critical step toward improving outcomes is to better understand the "forgotten" valve. High-fidelity computer models may help in this endeavour. However, the existing models are limited by averaged or idealized geometries, material properties, and boundary conditions. In our current work, we overcome the limitations of existing models by (reverse) engineering the tricuspid valve from a beating human heart in an organ preservation system. The resulting finite-element model faithfully captures the kinematics and kinetics of the native tricuspid valve as validated against echocardiographic data and others' previous work. To showcase the value of our model, we also use it to simulate disease-induced and repair-induced changes to valve geometry and mechanics. Specifically, we simulate and compare the effectiveness of tricuspid valve repair via surgical annuloplasty and via transcatheter edge-to-edge repair. Importantly, our model is openly available for others to use. Thus, our model will allow us and others to perform virtual experiments on the healthy, diseased, and repaired tricuspid valve to better understand the valve itself and to optimize tricuspid valve repair for better patient outcomes.

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 Three-Dimensional Ultrasound Derived Computational Modeling of the Mitral Valve

Several new techniques to repair the mitral valve affected by functional mitral regurgitation are in development. However, due to the heterogeneity of valve lesions between patients, predicting the outcomes of novel treatment approaches is challenging. We present a patient-specific, 3D ultrasound-derived computational model of the mitral valve for procedure planning, that faithfully mimics the pathological valve dynamics. 3D ultrasound images were obtained in three pigs induced with heart failure and which developed functional mitral regurgitation. For each case, images were segmented, and finite element model of mitral valve was constructed. Annular and papillary muscle dynamics were extracted and imposed as kinematic boundary conditions, and the chordae were pre-strained to induce valve tethering. Valve closure was simulated by applying physiologic transvalvular pressure on the leaflets. Agreement between simulation results and truth datasets was confirmed, with accurate location of regurgitation jets and coaptation defects. Inclusion of kinematic patient-specific boundary conditions was necessary to achieve these results, whereas use of idealized boundary conditions deviated from the truth dataset. Due to the impact of boundary conditions on the model, the effect of repair strategies on valve closure varied as well, indicating that our approach of using patient-specific boundary conditions for mitral valve modeling is valid.

Capturing contact in mitral valve dynamic closure with fluid-structure interaction simulation

PURPOSE

Realistic fluid-structure interaction (FSI) simulation of the mitral valve opens the way toward planning for surgical repair. In the literature, blood leakage is identified by measuring the flow rate, but detailed information about closure efficiency is missing. We present in this paper an FSI model that improves the detection of blood leakage by building a map of contact.

METHODS

Our model is based on the immersed boundary method that captures a map of contact and perfect closure of the mitral valve, without the presence of orifice holes, which often appear with existing methods. We also identified important factors influencing convergence issues.

RESULTS

The method is demonstrated in three typical clinical situations: mitral valve with leakage, bulging, and healthy. In addition to the classical ways of evaluating MV closure, such as stress distribution and flow rate, the contact map provides easy detection of leakage with identification of the sources of leakage and a quality assessment of the closure.

CONCLUSIONS

Our method significantly improves the quality of the simulation and allows the identification of regurgitation as well as a spatial evaluation of the quality of valve closure. Comparably fast simulation, ability to simulate large deformation, and capturing detailed contact are the main aspects of the study.

Clinical Impact of Computational Heart Valve Models

This paper provides a review of engineering applications and computational methods used to analyze the dynamics of heart valve closures in healthy and diseased states. Computational methods are a cost-effective tool that can be used to evaluate the flow parameters of heart valves. Valve repair and replacement have long-term stability and biocompatibility issues, highlighting the need for a more robust method for resolving valvular disease. For example, while fluid-structure interaction analyses are still scarcely utilized to study aortic valves, computational fluid dynamics is used to assess the effect of different aortic valve morphologies on velocity profiles, flow patterns, helicity, wall shear stress, and oscillatory shear index in the thoracic aorta. It has been analyzed that computational flow dynamic analyses can be integrated with other methods to create a superior, more compatible method of understanding risk and compatibility.

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.

Interactive editing of virtual chordae tendineae for the simulation of the mitral valve in a decision support system

PURPOSE

Decision support systems for mitral valve disease are an important step toward personalized surgery planning. A simulation of the mitral valve apparatus is required for decision support. Building a model of the chordae tendineae is an essential component of a mitral valve simulation. Due to image quality and artifacts, the chordae tendineae cannot be reliably detected in medical imaging.

METHODS

Using the position-based dynamics framework, we are able to realistically simulate the opening and closing of the mitral valve. Here, we present a heuristic method for building an initial chordae model needed for a successful simulation. In addition to the heuristic, we present an interactive editor to refine the chordae model and to further improve pathology reproduction as well as geometric approximation of the closed valve.

RESULTS

For evaluation, five mitral valves were reconstructed based on image sequences of patients scheduled for mitral valve surgery. We evaluated the approximation of the closed valves using either just the heuristic chordae model or a manually refined model. Using the manually refined models, prolapse was correctly reproduced in four of the five cases compared to two of the five cases when using the heuristic. In addition, using the editor improved the approximation in four cases.

CONCLUSIONS

Our approach is suitable to create realistically parameterized mitral valve apparatus reconstructions for the simulation of normally and abnormally closing valves in a decision support system.

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.

Advanced Methodology and Preliminary Measurements of Molecular and Mechanical Properties of Heart Valves under Dynamic Strain

Mammalian heart valves are soft tissue assemblies with multi-scale material properties. This is because they are constructs comprising both muscle and non-contractile extracellular matrix proteins (such as collagens and proteoglycans) and transition regions where one form of tissue structure becomes another, significantly different form. The leaflets of the mitral and tricuspid valves are connected to chordae tendinae which, in turn, bind through papillary muscles to the cardiac wall of the ventricle. The transition regions between these tissue subsets are complex and diffuse. Their material composition and mechanical properties have not been previously described with both micro and nanoscopic data recorded simultaneously, as reported here. Annotating the mechanical characteristics of these tissue transitions will be of great value in developing novel implants, improving the state of the surgical simulators and advancing robot-assisted surgery. We present here developments in multi-scale methodology that produce data that can relate mechanical properties to molecular structure using scanning X-ray diffraction. We correlate these data to corresponding tissue level (macro and microscopic) stress and strain, with particular emphasis on the transition regions and present analyses to indicate points of possible failure in these tissues.

Modeling the mitral valve

This work is concerned with modeling and simulation of the mitral valve, one of the four valves in the human heart. The valve is composed of leaflets, the free edges of which are supported by a system of chordae, which themselves are anchored to the papillary muscles inside the left ventricle. First, we examine valve anatomy and present the results of original dissections. These display the gross anatomy and information on fiber structure of the mitral valve. Next, we build a model valve following a design-based methodology, meaning that we derive the model geometry and the forces that are needed to support a given load and construct the model accordingly. We incorporate information from the dissections to specify the fiber topology of this model. We assume the valve achieves mechanical equilibrium while supporting a static pressure load. The solution to the resulting differential equations determines the pressurized configuration of the valve model. To complete the model, we then specify a constitutive law based on a stress-strain relation consistent with experimental data that achieves the necessary forces computed in previous steps. Finally, using the immersed boundary method, we simulate the model valve in fluid in a computer test chamber. The model opens easily and closes without leak when driven by physiological pressures over multiple beats. Further, its closure is robust to driving pressures that lack atrial systole or are much lower or higher than normal.

A computational multi-scale approach to investigate mechanically-induced changes in tricuspid valve anterior leaflet microstructure

The tricuspid valve is an atrioventricular valve that prevents blood backflow from the right ventricle into the right atrium during ventricular contractions. It is important to study mechanically induced microstructural alterations in the tricuspid valve leaflets, as this aids both in understanding valvular diseases and in the development of new engineered tissue replacements. The structure and composition of the extracellular matrix (ECM) fiber networks are closely tied to an overall biomechanical function of the tricuspid valve. In this study, we conducted experiments and implemented a multiscale modeling approach to predict ECM microstructural changes to tissue-level mechanical responses in a controlled loading environment. In particular, we characterized a sample of a porcine anterior leaflet at a macroscale using a biaxial mechanical testing method. We then generated a three-dimensional finite element model, to which computational representations of corresponding fiber networks were incorporated based on properties of the microstructural architecture obtained from small angle light scattering. Using five different biaxial boundary conditions, we performed iterative simulations to obtain model parameters with an overall R² value of 0.93. We observed that mechanical loading could markedly alter the underlying ECM architecture. For example, a relatively isotropic fiber network (with an anisotropy index value α of 28%) became noticeably more anisotropic (with an α of 40%) when it underwent mechanical loading. We also observed that the mechanical strain was distributed in a different manner at the ECM/fiber level as compared to the tissue level. The approach presented in this study has the potential to be implemented in pathophysiologically altered biomechanical and structural conditions and to bring insights into the mechanobiology of the tricuspid valve. STATEMENT OF SIGNIFICANCE: Quantifying abnormal cellar/ECM-level deformation of tricuspid valve leaflets subjected to a modified loading environment is of great importance, as it is believed to be linked to valvular remodeling responses. For example, developing surgical procedures or engineered tissue replacements that maintain/mimic ECM-level mechanical homeostasis could lead to more durable outcomes. To quantify leaflet deformation, we built a multiscale framework encompassing the contributions of disorganized ECM components and organized fibers, which can predict the behavior of the tricuspid valve leaflets under physiological loading conditions both at the tissue level and at the ECM level. In addition to future in-depth studies of tricuspid valve pathologies, our model can be used to characterize tissues in other valves of the heart.

On the simulation of mitral valve function in health, disease, and treatment

The mitral valve (MV) is the heart valve that regulates blood ?ow between the left atrium and left ventricle (LV). In situations where the MV fails to fully cover the left atrioventricular ori?ce during systole, the resulting regurgitation causes pulmonary congestion, leading to heart failure and/or stroke. The causes of MV insuf?ciency can be either primary (e.g. myxomatous degeneration) where the valvular tissue is organically diseased, or secondary (typically inducded by ischemic cardiomyopathy) termed ischemic mitral regurgitation (IMR), is brought on by adverse LV remodeling. IMR is present in up to 40% of patients and more than doubles the probability of cardiovascular morbidity after 3.5 years. There is now agreement that adjunctive procedures are required to treat IMR caused by lea?et tethering. However, there is no consensus regarding the best procedure. Multicenter registries and randomized trials would be necessary to prove which procedure is superior. Given the number of proposed procedures and the complexity and duration of such studies, it is highly unlikely that IMR procedure optimization will be achieved by prospective clinical trials. There is thus an urgent need for cell and tissue physiologically based quantitative assessments of MV function to better design surgical solutions and associated therapies. Novel computational approaches directed towards optimized surgical repair procedures can substantially reduce the need for such trial-and-error approaches. We present the details of our MV modeling techniques, with an emphasis on what is known and investigated at various length scales.

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.

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.

Numerical simulation of transapical off-pump mitral valve repair with neochordae implantation

BACKGROUND

Transapical off-pump mitral valve (MV) repair is a novel minimally-invasive surgical technique, allowing to correct mitral regurgitation (MR) caused by chordae tendineae rupture. While numerical simulation of the MV structure has proven to be useful to evaluate the effects of the MV surgical repair techniques, no numerical simulation studies on the outcomes of transapical MV repair have been done up to now.

OBJECTIVE

The purpose of this study is to evaluate the transapical MV repair using finite element modeling and to determine the effect of the neochordal length on the function of the prolapsing MV.

METHODS

The reconstruction of the MV geometry based on the patient-specific data was performed. In order to simulate prolapse, chordae inserted into the middle segment of the posterior leaflet (P2) were ruptured. A total of four virtual transapical repairs using neochordae of different length were performed. The function of the MV before and after virtual repairs was simulated.

RESULTS

The evaluation of the effect of the neochordal length on post-repair MV function showed that the length of the implanted neochordae has a significant impact on the correction of MR caused by chordae tendineae rupture.

CONCLUSIONS

The presented results can improve the understanding of the effects of transapical MV repair.

Tissue loading and microstructure regulate the deformation of embedded nerve fibres: predictions from single-scale and multiscale simulations

Excessive deformation of nerve fibres (axons) in the spinal facet capsular ligaments (FCLs) can be a cause of pain. The axons are embedded in the fibrous extracellular matrix (ECM) of FCLs, so understanding how local fibre organization and micromechanics modulate their mechanical behaviour is essential. We constructed a computational discrete-fibre model of an axon embedded in a collagen fibre network attached to the axon by distinct fibre-axon connections. This model was used to relate the axonal deformation to the fibre alignment and collagen volume concentration of the surrounding network during transverse, axial and shear deformations. Our results showed that fibre alignment affects axonal deformation only during transverse and axial loading, but higher collagen volume concentration results in larger overall axonal strains for all loading cases. Furthermore, axial loading leads to the largest stretch of axonal microtubules and induces the largest forces on axon's surface in most cases. Comparison between this model and a multiscale continuum model for a representative case showed that although both models predicted similar averaged axonal strains, strain was more heterogeneous in the discrete-fibre model.

Computational methods for the aortic heart valve and its replacements

INTRODUCTION

Replacement with a prosthetic device remains a major treatment option for the patients suffering from heart valve disease, with prevalence growing resulting from an ageing population. While the most popular replacement heart valve continues to be the bioprosthetic heart valve (BHV), its durability remains limited. There is thus a continued need to develop a general understanding of the underlying mechanisms limiting BHV durability to facilitate development of a more durable prosthesis. In this regard, computational models can play a pivotal role as they can evaluate our understanding of the underlying mechanisms and be used to optimize designs that may not always be intuitive. Areas covered: This review covers recent progress in computational models for the simulation of BHV, with a focus on aortic valve (AV) replacement. Recent contributions in valve geometry, leaflet material models, novel methods for numerical simulation, and applications to BHV optimization are discussed. This information should serve not only to infer reliable and dependable BHV function, but also to establish guidelines and insight for the design of future prosthetic valves by analyzing the influence of design, hemodynamics and tissue mechanics. Expert commentary: The paradigm of predictive modeling of heart valve prosthesis are becoming a reality which can simultaneously improve clinical outcomes and reduce costs. It can also lead to patient-specific valve design.

Multi-resolution geometric modeling of the mitral heart valve leaflets

An essential element of cardiac function, the mitral valve (MV) ensures proper directional blood flow between the left heart chambers. Over the past two decades, computational simulations have made marked advancements toward providing powerful predictive tools to better understand valvular function and improve treatments for MV disease. However, challenges remain in the development of robust means for the quantification and representation of MV leaflet geometry. In this study, we present a novel modeling pipeline to quantitatively characterize and represent MV leaflet surface geometry. Our methodology utilized a two-part additive decomposition of the MV geometric features to decouple the macro-level general leaflet shape descriptors from the leaflet fine-scale features. First, the general shapes of five ovine MV leaflets were modeled using superquadric surfaces. Second, the finer-scale geometric details were captured, quantified, and reconstructed via a 2D Fourier analysis with an additional sparsity constraint. This spectral approach allowed us to easily control the level of geometric details in the reconstructed geometry. The results revealed that our methodology provided a robust and accurate approach to develop MV-specific models with an adjustable level of spatial resolution and geometric detail. Such fully customizable models provide the necessary means to perform computational simulations of the MV at a range of geometric accuracies in order to identify the level of complexity required to achieve predictive MV simulations.

Regulation of valve interstitial cell homeostasis by mechanical deformation: implications for heart valve disease and surgical repair

Mechanical stress is one of the major aetiological factors underlying soft-tissue remodelling, especially for the mitral valve (MV). It has been hypothesized that altered MV tissue stress states lead to deviations from cellular homeostasis, resulting in subsequent cellular activation and extracellular matrix (ECM) remodelling. However, a quantitative link between alterations in the organ-level in vivo state and in vitro-based mechanobiology studies has yet to be made. We thus developed an integrated experimental-computational approach to elucidate MV tissue and interstitial cell responses to varying tissue strain levels. Comprehensive results at different length scales revealed that normal responses are observed only within a defined range of tissue deformations, whereas deformations outside of this range lead to hypo- and hyper-synthetic responses, evidenced by changes in α-smooth muscle actin, type I collagen, and other ECM and cell adhesion molecule regulation. We identified MV interstitial cell deformation as a key player in leaflet tissue homeostatic regulation and, as such, used it as the metric that makes the critical link between in vitro responses to simulated equivalent in vivo behaviour. Results indicated that cell responses have a delimited range of in vivo deformations that maintain a homeostatic response, suggesting that deviations from this range may lead to deleterious tissue remodelling and failure.