Mitral valve (MV) closure depends upon the proper function of each component of the valve apparatus, which includes the annulus, leaflets, and chordae tendineae (CT). Geometry plays a major role in MV mechanics and thus highly impacts the accuracy of computational models simulating MV function and repair. While the physiological geometry of the leaflets and annulus have been previously investigated, little effort has been made to quantitatively and objectively describe CT geometry. The CT constitute a fibrous tendon-like structure projecting from the papillary muscles (PMs) to the leaflets, thereby evenly distributing the loads placed on the MV during closure. Because CT play a major role in determining the shape and stress state of the MV as a whole, their geometry must be well characterized. In the present work, a novel and comprehensive investigation of MV CT geometry was performed to more fully quantify CT anatomy. In vitro micro-tomography 3D images of ovine MVs were acquired, segmented, then analyzed using a curve-skeleton transform. The resulting data was used to construct B-spline geometric representations of the CT structures, enriched with a continuous field of cross-sectional area (CSA) data. Next, Reeb graph models were developed to analyze overall topological patterns, along with dimensional attributes such as segment lengths, 3D orientations, and CSA. Reeb graph results revealed that the topology of ovine MV CT followed a full binary tree structure. Moreover, individual chords are mostly planar geometries that together form a 3D load-bearing support for the MV leaflets. We further demonstrated that, unlike flow-based branching patterns, while individual CT branches became thinner as they propagated further away from the PM heads towards the leaflets, the total CSA almost doubled. Overall, our findings indicate a certain level of regularity in structure, and suggest that population-based MV CT geometric models can be generated to improve current MV repair procedures.

Background Annuloplasty ring dehiscence is a well described mechanism of mitral valve repair failure. Defining the mechanisms underlying dehiscence may facilitate its prevention. Methods Factors governing suture dehiscence were examined using an ovine model. Following undersized ring annuloplasty in live animals (N=5), Cyclic Force (FC) acting on sutures during cardiac contraction were measured using custom transducers. FC was measured at 10 suture positions, throughout cardiac cycles with peak left ventricular pressure (LVPmax) of 100, 125, and 150mmHg. Suture pullout testing was conducted on explanted mitral annuli (N=12) to determine suture holding strength at each position. Finally, relative collagen density differences at suture sites around the annulus were assessed by two-photon excitation fluoroscopy. Results Anterior FC exceeded posterior at each LVPmax (e.g. 2.8±1.3 vs. 1.8±1.2N at LVPmax=125mmHg, p<0.01). Anterior holding strength exceeded posterior (6.4±3.6 vs. 3.9±1.6N, p<0.0001). Based on FC at LVPmax=150mmHg, margin of safety before suture pullout was vastly higher between the trigones (exclusive) versus elsewhere (4.8±0.9 versus 1.9±0.5N, p<0.001). Margin of safety exhibited strong correlation to collagen density (R2=0.947). Conclusions Despite lower cyclic loading on posterior sutures, the weaker posterior mitral annular tissue creates higher risk of dehiscence, apparently due to reduced collagen content. Sutures placed atop the trigones are less secure than predicted, due to a combination of reduced collagen and higher overall rigidity in this region. These findings highlight the inter-trigonal tissue as the superior anchor, and have implications on the design and implantation techniques for next-generation mitral prostheses.

The diversity of mitral valve (MV) geometries and multitude of surgical options for correction of MV diseases necessitates the use of computational modeling. Numerical simulations of the MV would allow surgeons and engineers to evaluate repairs, devices, procedures, and concepts before performing them and before moving on to more costly testing modalities. Constructing, tuning, and validating these models rely upon extensive in vitro characterization of valve structure, function, and response to change due to diseases. Micro-computed tomography ([Formula: see text]CT) allows for unmatched spatial resolution for soft tissue imaging. However, it is still technically challenging to obtain an accurate geometry of the diastolic MV. We discuss here the development of a novel technique for treating MV specimens with glutaraldehyde fixative in order to minimize geometric distortions in preparation for [Formula: see text]CT scanning. The technique provides a resulting MV geometry which is significantly more detailed in chordal structure, accurate in leaflet shape, and closer to its physiological diastolic geometry. In this paper, computational fluid-structure interaction (FSI) simulations are used to show the importance of more detailed subject-specific MV geometry with 3D chordal structure to simulate a proper closure validated against [Formula: see text]CT images of the closed valve. Two computational models, before and after use of the aforementioned technique, are used to simulate closure of the MV.