In Vivo Three-Dimensional Geometric Reconstruction of the Mouse Aortic Heart Valve.

Aortic valve (AV) disease is a common valvular lesion in the United States, present in about 5% of the population at age 65 with increasing prevalence with advancing age. While current replacement heart valves have extended life for many, their long-term use remains hampered by limited durability. Non-surgical treatments for AV disease do not yet exist, in large part because our understanding of AV disease etiology remains incomplete. The direct study of human AV disease remains hampered by the fact that clinical data is only available at the time of treatment, where the disease is at or near end stage and any time progression information has been lost. Large animal models, long used to assess replacement AV devices, cannot yet reproduce AV disease processes. As an important alternative mouse animal models are attractive for their ability to perform genetic studies of the AV disease processes and test potential pharmaceutical treatments. While mouse models have been used for cellular and genetic studies of AV disease, their small size and fast heart rates have hindered their use for tissue- and organ-level studies. We have recently developed a novel ex vivo micro-CT-based methodology to 3D reconstruct murine heart valves and estimate the leaflet mechanical behaviors (Feng et al. in Sci Rep 13(1):12852, 2023). In the present study, we extended our approach to 3D reconstruction of the in vivo functional murine AV (mAV) geometry using high-frequency four-dimensional ultrasound (4DUS). From the resulting 4DUS images we digitized the mAV mid-surface coordinates in the fully closed and fully opened states. We then utilized matched high-resolution µCT images of ex vivo mouse mAV to develop mAV NURBS-based geometric model. We then fitted the mAV geometric model to the in vivo data to reconstruct the 3D in vivo mAV geometry in the closed and open states in n = 3 mAV. Results demonstrated high fidelity geometric results. To our knowledge, this is the first time such reconstruction was ever achieved. This robust assessment of in vivo mAV leaflet kinematics in 3D opens up the possibility for longitudinal characterization of murine models that develop aortic valve disease.

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.

Hydrogel-polyurethane fiber composites with enhanced microarchitectural control for heart valve replacement.

Polymeric heart valves offer the potential to overcome the limited durability of tissue based bioprosthetic valves and the need for anticoagulant therapy of mechanical valve replacement options. However, developing a single-phase material with requisite biological properties and target mechanical properties remains a challenge. In this study, a composite heart valve material was developed where an electrospun mesh provides tunable mechanical properties and a hydrogel coating confers an antifouling surface for thromboresistance. Key biological responses were evaluated in comparison to glutaraldehyde-fixed pericardium. Platelet and bacterial attachment were reduced by 38% and 98%, respectively, as compared to pericardium that demonstrated the antifouling nature of the hydrogel coating. There was also a notable reduction (59%) in the calcification of the composite material as compared to pericardium. A custom 3D-printed hydrogel coating setup was developed to make valve composites for device-level hemodynamic testing. Regurgitation fraction (9.6 ± 1.8%) and effective orifice area (1.52 ± 0.34 cm2 ) met ISO 5840-2:2021 requirements. Additionally, the mean pressure gradient was comparable to current clinical bioprosthetic heart valves demonstrating preliminary efficacy. Although the hemodynamic properties are promising, it is anticipated that the random microarchitecture will result in suboptimal strain fields and peak stresses that may accelerate leaflet fatigue and degeneration. Previous computational work has demonstrated that bioinspired fiber microarchitectures can improve strain homogeneity of valve materials toward improving durability. To this end, we developed advanced electrospinning methodologies to achieve polyurethane fiber microarchitectures that mimic or exceed the physiological ranges of alignment, tortuosity, and curvilinearity present in the native valve. Control of fiber alignment from a random fiber orientation at a normalized orientation index (NOI) 14.2 ± 6.9% to highly aligned fibers at a NOI of 85.1 ± 1.4%. was achieved through increasing mandrel rotational velocity. Fiber tortuosity and curvilinearity in the range of native valve features were introduced through a post-spinning annealing process and fiber collection on a conical mandrel geometry, respectively. Overall, these studies demonstrate the potential of hydrogel-polyurethane fiber composite as a heart valve material. Future studies will utilize the developed advanced electrospinning methodologies in combination with model-directed fabrication toward optimizing durability as a function of fiber microarchitecture.

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.

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.

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.

Functional differences in human aortic valve interstitial cells from patients with varying calcific aortic valve disease.

Calcific aortic valve disease (CAVD) is characterized by progressive stiffening of aortic valve (AV) tissues, inducing stenosis and insufficiency. Bicuspid aortic valve (BAV) is a common congenital defect in which the AV has two leaflets rather than three, with BAV patients developing CAVD decades years earlier than in the general population. Current treatment for CAVD remains surgical replacement with its continued durability problems, as there are no pharmaceutical therapies or other alternative treatments available. Before such therapeutic approaches can be developed, a deeper understanding of CAVD disease mechanisms is clearly required. It is known that AV interstitial cells (AVICs) maintain the AV extracellular matrix and are typically quiescent in the normal state, transitioning into an activated, myofibroblast-like state during periods of growth or disease. One proposed mechanism of CAVD is the subsequent transition of AVICs into an osteoblast-like phenotype. A sensitive indicator of AVIC phenotypic state is enhanced basal contractility (tonus), so that AVICs from diseased AV will exhibit a higher basal tonus level. The goals of the present study were thus to assess the hypothesis that different human CAVD states lead to different biophysical AVIC states. To accomplish this, we characterized AVIC basal tonus behaviors from diseased human AV tissues embedded in 3D hydrogels. Established methods were utilized to track AVIC-induced gel displacements and shape changes after the application of Cytochalasin D (an actin polymerization inhibitor) to depolymerize the AVIC stress fibers. Results indicated that human diseased AVICs from the non-calcified region of TAVs were significantly more activated than AVICs from the corresponding calcified region. In addition, AVICs from the raphe region of BAVs were more activated than from the non-raphe region. Interestingly, we observed significantly greater basal tonus levels in females compared to males. Furthermore, the overall AVIC shape changes after Cytochalasin suggested that AVICs from TAVs and BAVs develop different stress fiber architectures. These findings are the first evidence of sex-specific differences in basal tonus state in human AVICs in varying disease states. Future studies are underway to quantify stress fiber mechanical behaviors to further elucidate CAVD disease mechanisms.

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.

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.

A multi-scale computational model for the passive mechanical behavior of right ventricular myocardium.

We have previously demonstrated the importance of myofiber-collagen mechanical interactions in modeling the passive mechanical behavior of right ventricle free wall (RVFW) myocardium. To gain deeper insights into these coupling mechanisms, we developed a high-fidelity, micro-anatomically realistic 3D finite element model of right ventricle free wall (RVFW) myocardium by combining high-resolution imaging and supercomputer-based simulations. We first developed a representative tissue element (RTE) model at the sub-tissue scale by specializing the hyperelastic anisotropic structurally-based constitutive relations for myofibers and ECM collagen, and equi-biaxial and non-equibiaxial loading conditions were simulated using the open-source software FEniCS to compute the effective stress-strain response of the RTE. To estimate the model parameters of the RTE model, we first fitted a 'top-down' biaxial stress-strain behavior with our previous structurally based (tissue-scale) model, informed by the measured myofiber and collagen fiber composition and orientation distributions. Next, we employed a multi-scale approach to determine the tissue-level (5 x 5 x 0.7 mm specimen size) RVFW biaxial behavior via 'bottom-up' homogenization of the fitted RTE model, recapitulating the histologically measured myofiber and collagen orientation to the biaxial mechanical data. Our homogenization approach successfully reproduced the tissue-level mechanical behavior of our previous studies in all biaxial deformation modes, suggesting that the 3D micro-anatomical arrangement of myofibers and ECM collagen is indeed a primary mechanism driving myofiber-collagen interactions.

Estimation of aortic valve interstitial cell-induced 3D remodeling of poly(ethylene glycol) hydrogel environments using an inverse finite element approach.

Aortic valve interstitial cells (AVICs) reside within the leaflet tissues of the aortic valve and maintain and remodel its extracellular matrix components. Part of this process is a result of AVIC contractility brought about by underlying stress fibers whose behaviors can change in various disease states. Currently, it is challenging to directly investigate AVIC contractile behaviors within dense leaflet tissues. As a result, optically clear poly (ethylene glycol) hydrogel matrices have been used to study AVIC contractility via 3D traction force microscopy (3DTFM). However, the local stiffness of the hydrogel is difficult to measure directly and is further confounded by the remodeling activity of the AVIC. Ambiguity in hydrogel mechanics can lead to large errors in computed cellular tractions. Herein, we developed an inverse computational approach to estimate AVIC-induced remodeling of the hydrogel material. The model was validated with test problems comprised of an experimentally measured AVIC geometry and prescribed modulus fields containing unmodified, stiffened, and degraded regions. The inverse model estimated the ground truth data sets with high accuracy. When applied to AVICs assessed via 3DTFM, the model estimated regions of significant stiffening and degradation in the vicinity of the AVIC. We observed that stiffening was largely localized at AVIC protrusions, likely a result of collagen deposition as confirmed by immunostaining. Degradation was more spatially uniform and present in regions further away from the AVIC, likely a result of enzymatic activity. Looking forward, this approach will allow for more accurate computation of AVIC contractile force levels. STATEMENT OF SIGNIFICANCE: The aortic valve (AV), positioned between the left ventricle and the aorta, prevents retrograde flow into the left ventricle. Within the AV tissues reside a resident population of aortic valve interstitial cells (AVICs) that replenish, restore, and remodel extracellular matrix components. Currently, it is technically challenging to directly investigate AVIC contractile behaviors within the dense leaflet tissues. As a result, optically clear hydrogels have been used to study AVIC contractility through means of 3D traction force microscopy. Herein, we developed a method to estimate AVIC-induced remodeling of PEG hydrogels. This method was able to accurately estimate regions of significant stiffening and degradation induced by the AVIC and allows a deeper understanding of AVIC remodeling activity, which can differ in normal and disease conditions.

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.

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.

The Accelerated Transcatheter Heart Valve Testing Environment: Loading, Motion, and Fluid Dynamics.

Transcatheter aortic valve replacements (TAVRs) are an increasingly common treatment for aortic valve disease due to their minimally invasive delivery. As TAVR designs require thinner leaflets to facilitate catheter-based delivery, they experience greater leaflet operational stresses and potentially greater durability issues than conventional surgical valves. Yet, our understanding of TAVR durability remains largely unexplored. Currently, preclinical TAVR durability is evaluated within an ISO:5840 compliant accelerated wear tester (AWT) up to a required 200 × 106 cycles, corresponding to approximately five years in vivo. While AWTs use high cycle frequencies (10-20 Hz) to achieve realistic timeframes, the resulting valve loading behaviors and fluid dynamics are not representative of the in vivo environment and thus may not accurately predict failure mechanisms. Despite the importance of fatigue and failure predictions for replacement heart valves, surprisingly, little quantitative information exists on the dynamic AWT environment. To better understand this environment, we examined frequency and diastolic period effects for the first time using high-speed enface imaging and particle image velocimetry to quantify valve motion and flow, respectively, using a Durapulse™ AWT at frequencies of 10, 15, and 20 Hz. Regardless of operating condition, no waveform achieved a physiologically relevant transvalvular loading pressure, despite having an ISO compliant geometric orifice area (GOA) and waveform. General fluid mechanics were consistent with in vivo but the AWT geometry developed secondary flow structures, which could impact mechanical loading. Therefore, the nonphysiologic loading and variability induced by changes in operating condition must be carefully regulated to ensure physiologically relevant fatigue.

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.

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.

Mechanical Interaction of the Pericardium and Cardiac Function in the Normal and Hypertensive Rat Heart.

The pericardium is a thin connective tissue membrane that surrounds the heart and is an integral regulatory component of cardiopulmonary performance. Pathological growth and remodeling of the right ventricle (RV) stemming from structural heart diseases are thought to include a significant role of the pericardium, but its exact role remains unclear. The objective of this study was to investigate potential biomechanical adaptations of the pericardium in response to pulmonary hypertension and their effects on heart behavior. Integrated computational-experimental modeling of the heart offers a robust platform to achieve this objective. We built upon our recently developed high-fidelity finite-element models of healthy and hypertensive rodent hearts via addition of the pericardial sac. In-silico experiments were performed to investigate changes in pericardium reserve elasticity and their effects on cardiac function in hypertensive hearts. Our results suggest that contractile forces would need to increase in the RV and decrease in the left ventricle (LV) in the hypertensive heart to compensate for reductions in pericardium reserve elasticity. The discrepancies between chamber responses to pericardium addition result, in part, from differences in the impact of pericardium on the RV and LV preload. We further demonstrated the capability of our platform to predict the effect of pericardiectomy on heart function. Consistent with previous results, the effect of pericardiectomy on the chamber pressure-volume loop was the largest in the hypertensive RV. These insights are expected to motivate further computational investigations of the effect of pericardiectomy on cardiac function which remains an important factor in surgical planning of constrictive pericarditis and coronary artery bypass grafting.

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.

Simulation of the 3D Hyperelastic Behavior of Ventricular Myocardium using a Finite-Element Based Neural-Network Approach.

High-fidelity cardiac models using attribute-rich finite element based models have been developed to a very mature stage. However, such finite-element based approaches remain time consuming, which have limited their clinical use. There remains a need for alternative methods for novel cardiac simulation methods of capable of high fidelity simulations in clinically relevant time frames. Surrogate models are one approach, which traditionally use a data-driven approach for training, requiring the generation of a sufficiently large number of simulation results as the training dataset. Alternatively, a physics-informed neural network can be trained by minimizing the PDE residuals or energy potentials. However, this approach does not provide for a general method to easily using existing finite element models. To address these challenges, we developed a hybrid approach that seamlessly bridged a neural network surrogate model with a differentiable finite element domain representation (NNFE). Given its importance in cardiac simulations, we applied this approach to simulations of the hyperelastic mechanical behavior of ventricular myocardium from recent 3D kinematic constitutive model (J Mech Behav Biomed Mater, 2020 doi: 10.1016/j.jmbbm.2019.103508). We utilized cuboidal domain and conducted numerical studies of individual myocardium specimens discretized by a finite element mesh and assigned with experimentally obtained myofiber architectures. Both parameterized Dirichlet and Neumann boundary conditions were studied. We developed a second-order Newton optimization method, instead of using stochastic gradient descent method, to train the neural network efficiently. The resulting trained neural network surrogate model demonstrated excellent agreement with the corresponding 'ground truth' finite element solutions over the entire physiological deformation range. More importantly, the NNFE approach provided a significantly decreased computational time for a range of finite element mesh sizes for online predictions. For example, as the finite element mesh sized increased from 2744 to 175615 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. These results suggests that NNFE run times can be significantly reduced compared with the traditional large-deformation based finite element solution methods. The trade off is to train the NNFE off-line within a range of anticipated physiological responses. However, training time would only have to be performed once before any number of application uses. Moreover, since the NNFE is an analytical function its computational performance will be amplified when the corresponding problem becomes more complex.