3DTEE-Based Modeling of the Mitral Valve: A Study on Chordal Apparatus Impact and Optimization.

Mitral Valve (MV) can be affected by a variety of complex diseases. Mitral valve regurgitation (MVR) represents the most prevalent valvular disorder observed in adult patients with cardiac valve diseases. MVR is characterized by the abnormal retrograde blood flow through the MV from the left ventricle into the left atrium during systole. The etiology of the regurgitation can be degenerative, rheumatic or functional, and most of them are characterized by deviations of the sub-valvular apparatus, made by papillary muscles (PMs) and chordae tendineae (CTs), from its healthy, homeostatic state. The chordal rupture is frequent, leading to leaflet prolapse and blood leakage. Finite element method (FE) models are an important instrument for investigating physiological and pathophysiological mechanisms of MV, helping surgical strategy and treatment. Nowadays, the prevalent treatment recommended is MV repair. Repairment may involve CTs modifications related to their number, configuration and distribution. Therefore, it is evident that there is an increasing need to develop numerical models with a reasonable CTs organization to understand their role better and improve surgical approach. The present study aims to understand how different descriptions of CTs spatial distribution can impact on the behavior of a regurgitant MV apparatus, through FEM models. Real-time transesophageal echocardiographic (3DTEE) imaging was acquired from healthy and diseased subjects. Based on an in-house reconstruction algorithm, the stress-free MV geometry was automatically reproduced in the 3D space at end diastole (ED) and peak-systole (PS) from manual tracing of annulus, leaflets and PMs tips, where visible. The CTs are not visible from 3DTEE imaging: therefore, the MV model was completed with three different CTs models, adapted from literature. The first model assumes a uniform distribution, with 17 insertions per cm². The second model is based on a density map that divides the valve into 35 regions. The number of CTs per region is determined using an insertion map derived from the average distribution of insertions observed in ex-vivo human MVs. The third model accurately replicates the anatomical distribution of insertions, distinguishing four zones on the anterior leaflet and five on the posterior leaflet, with insertions assigned based on anatomical data. Notably, all models treat each CT as a single strand extending from the PM to its insertion point on the leaflet without considering ramifications. Leaflet mechanics was modeled through the May-Newman material model, while CTs response was evaluated with two constitutive models, describing a hyperelastic isotropic and incompressible response: the Weiss model, incorporating an isotropic matrix and preferential collagen fiber orientation, and the Drach-Sacks model. A simulation workflow, implemented in Abaqus/Explicit (Dassault Systèmes), was used to generate the FE model of the MV. Upon fine-tuning CTs’ initial length to maximize the consistency between the computed leaflet configuration at PS and the corresponding ground-truth imaging, systolic MV closure was simulated by replicating the motion of annulus and PMs, applying a physiological trans-valvular pressure load on the leaflets. From the closure simulations, stress and deformation data are extracted to evaluate the valve's biomechanics. For each healthy valve analyzed, all apparatus models successfully closed the valve and supported the closure mechanism. In general, the second model, despite being formulated based on average population data, exhibited the highest instability in terms of stress and deformation within the valve. It also resulted in the smallest coaptation area. On the other hand, both the first and third models produced more stable stress and deformation distributions, with larger coaptation areas. However, the first model does not accurately represent the anatomical CT.