Mechano-electrical-fluid interaction left-ventricle model for numerical evaluation of aortic valve hemodynamics

Aortic valve simulation has a crucial meaning for clinical applications like the prediction of transcatheter aortic valve implantation or the Ozaki procedure. One of the main aspects is the inflow boundary condition because it has a strong effect on hemodynamic flow simulation results. Most researchers adopt a 2-D profile derived from ultrasound measurements for 3-D fluid-structure interaction simulations that do not take into account several physiological effects.

A model including left ventricle contraction and blood flow in the aorta segment with aortic valve leaflets was developed. A mechano-electrical-fluidic interaction model of the left ventricle was developed to assess a 3-D profile of blood passing to the aortic valve. The effect of complex fiber architecture in the left ventricle geometry model was taken into account. After that, this profile was set as an inlet in the aorta segments to perform 2-way FSI blood flow for numerical evaluation of aortic valve hemodynamics.

It was shown that during the cardiac cycle, the left ventricle's electric potential varies between -80 mV and 20 mV. At the systolic peak, the maximum deformations of the left ventricle range from 38% to 60%. The trajectories of the left ventricle apex and torsion angle were derived. The displacement of the myocardial tissue does not differ significantly among the cases, ranging from 15 to 20 mm, with the greatest shift occurring in the opposite direction. Flow velocities were up to 1.8 m·s^-1 at the moment of full opening of the aortic valve leaflets. Additionally, the influence of the left ventricle's shape and size on the left ventricle outflow velocity vector field and the aortic valve leaflets' behavior was analyzed.

The findings suggest that ventricular geometry significantly influences the stress distribution in the aortic valve leaflets and the flow velocities, consistent with previous computational studies. Understanding these relationships is crucial for predicting valve performance and identifying potential areas of high stress that may contribute to valvular pathologies such as calcification and leaflet fatigue.