The degree of restoration of pump function by ventricular pacing depends on the pacing site and timing of pacing. Numerical models of cardiac electromechanics could be used to investigate the relation between the ventricular pacing site and timing on the one side, and pump function on the other. In patient-specific models, these numerical models could be used to optimize location and timing for best pump function. The aim of this study was to demonstrate the potential for modeling patient-specific electromechanic during ventricular pacing by means of the extension of an existing three-dimensional finite-element model of LV electromechanics with the right ventricle. A parametrized geometry of the LV and RV was made from canine (non-invasively obtained) cine-MR short axis images. Depolarization was modeled using the eikonal-diffusion equation. Mechanics was computed from balance of momentum, with nonlinear anisotropic passive and time-, strain-, and strainrate-dependent uniaxial active behavior. Simulations of complete cardiac cycles were performed for a normal heart beat with synchronous activation and ventricular pacing at the right ventricular apex and left ventricular free wall. We focused on timing of LV and RV hemodynamics, asynchrony in depolarization and myofiber shortening, regional stroke work, and systolic septal motion. In the simulation of sinus rhytm, ventricular ejection was found to start earlier for the right side than for the left side, which is in agreement with experimental data. In simulations with ventricular pacing, results agreed with experimental findings in the following aspects: 1) depolarization sequence; 2) the spatial distributions of sarcomere length and stroke work density depended mainly on timing of depolarization; 3) maximum pressure and maximum increase of pressure were lower than during sinus rhythm; 4) the earliest activated ventricle had the earliest start of ejection, and 5) the septum moved towards the last activated ventricle at the onset of systole. As a first step, the potential of patient-specific modeling in simulating conduction disturbances has been demonstrated by inserting a ventricular geometry, obtained from non-invasively measured short axis MR images. Later steps would include the implementation of adaptation models to estimate patient myofiber orientation and to assess the effects of pacing in the long term.
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