Modeling Mitral Valve Dynamics: From Experimental Validation to Patient-Specific Simulations

The heart consists of four chambers, two atria and two ventricles, separated by four valves that ensure unidirectional blood flow and efficient cardiac function. Among these, the mitral valve regulates blood flow between the left atrium and left ventricle and is one of the most mechanically loaded structures in the heart, stabilized by the chordae tendineae, which are connective structures. Consequently, mitral valve disease can have severe consequences. Approximately 1% of children are born with congenital heart defects, some of which involve mitral valve abnormalities such as stenosis (restricted opening) or regurgitation (leakage). Both conditions can be life-threatening and often require surgical repair. However, predicting post-surgical valve function remains challenging. Patient-specific computational modeling could, in the future, complement imaging modalities such as echocardiography and magnetic resonance imaging (MRI) by providing additional insights into valve function and hemodynamics. Such models may also allow virtual testing of surgical strategies, supporting pre-operative planning and personalized treatment.This thesis represents an initial step toward developing and validating a computational model capable of predicting mitral valve function and flow dynamics following surgical intervention. The model is based on fluid-structure interaction (FSI), which couples solid and fluid mechanics to capture the interplay between blood flow and valve motion. In Study I, a simplified left heart phantom was developed to provide experimental data for model validation. The setup was exposed to pulsatile flow under physiological conditions, while valve opening, velocity, and pressure were measured using echocardiography, MRI, and pressure probes. The system demonstrated minimal cycle-to-cycle variation. The resulting dataset was made publicly available to support future validation efforts of cardiac-inspired FSI models. In Study II, the same geometry and flow conditions were used in computational simulations to validate the developed FSI framework. The simulated transmitral velocities and pressure differences showed good agreement with the experimental data, with clinically acceptable error margins. Qualitative comparisons of flow streamlines further confirmed the model’s ability to reproduce realistic hemodynamic patterns.Building on this, Study III extended the framework to simulate mitral valve function in healthy humans. Echocardiographic data from ten volunteers were used to generate patient-specific valve geometries and derive individualized flow boundary conditions from left ventricular volume measurements. The simulated results matched echocardiographic observations throughout the cardiac cycle, confirming that the model captured valvular motion and hemodynamics in the atrium and ventricle. With a validated pipeline for patient-specific simulations, Study IV applied the model to pediatric patients with mitral regurgitation. Pre- and post-operative echocardiograms were used to reconstruct valve geometries before and after surgery. Simulated hemodynamics and valve function were compared with echocardiographic data, demonstrating the model’s ability to reproduce clinically relevant parameters used to grade regurgitation. Finally, Study V explored biomechanical parameters, specifically valve strain and chordal forces, as potential diagnostic indicators. Significant differences in leaflet strain were found between healthy and regurgitant valves, while regurgitant valves exhibited higher diastolic chordal forces, suggesting leaflet tethering and altered loading conditions.In summary, the overarching aim of this thesis was to develop and validate a clinically feasible FSI framework for patient-specific modeling of mitral valve function and hemodynamics. The work demonstrates both the challenges and potential of modeling the complex interaction between blood flow and valve motion. It also illustrates the value of simulation-based approaches for improving understanding of valve mechanics and evaluating surgical repair strategies. This framework represents an important step toward a computational tool that could assist clinicians in planning and optimizing mitral valve repair.