Mitral valve regurgitation (MVR) can cause serious complications like heart failure stroke, and in severe cases death. MVR occurs when blood leaks back to the left atrium during ventricular contraction due to the incomplete closure of the mitral valve (MV). Interestingly, all forms of MVR are characterized by morphological alterations in the normal configuration of the MV apparatus. Thus, surgical procedures to treat MVR seek to restore the MV to a functional geometric state. While some recent studies strongly suggest that the MV repair is the “gold standard” treatment, other follow-up investigations have revealed an undesirable high rate of failure and regurgitation recurrence for repairs. Furthermore, there remains an uncertainty over the optimal shape of annuloplasty rings for successful repair of regurgitant valves. Thus, in spite of the ever-increasing rate of MVR incidence, the available treatment options still need to be greatly improved.
Over the past two decades, computational simulations have made marked advancements towards providing powerful predictive tools to better understand valvular function and improve treatments for MV disease. One ongoing challenge is the development of a pipeline to quantitatively characterize and represent MV leaflet surface geometry. We have developed a methodology that utilizes 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 in a range of geometric detail, allowing identification of the complexity required to achieve predictive MV simulations to a desired accuracy level.
Next, we note that there is a lack of complete in-vivo geometric information, which presents significant challenges in the development of patient-specific computational models. To address this issue, we have developed a novel pipeline for building attribute-rich computational models of MV of varying fidelity from in-vitro imaging data. The approach combined high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high resolution, attribute-rich computational model. Subsequent lower resolution models were then developed, and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then established required levels of fidelity for building predictive MV models in the diseased and post-repaired states, demonstrating that a model with a feature size of ∼5 mm and mesh size of ∼1 mm was sufficient to predict overall MV shape, stress, and strain distributions with high accuracy. However, more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables appropriate fidelity level models for the biomechanical simulations of MV under different physiological states for a range of modeling goals.
Finally, we note that the MV is not just a passive flap made from inert material, but is rather a living soft tissue. As such, it has long been noted that mechanical stress is one of the major etiological factors underlying soft tissue remodeling. A lower level challenge is thus how altered tissue stress states lead to deviations from cellular homeostasis, resulting in subsequent cellular activation and extracellular matrix (ECM) remodeling. This requires a quantitative link between alterations in the organ-level in vivo state and in vitro-based mechanobiology studies is yet to be made. We thus developed an integrated experimental-computational approach to elucidate heart valve 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 valve 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 behavior. 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 remodeling and failure.