Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.

Intracardiac hemodynamics plays a crucial role in the onset and progression of cardiac and valvular diseases. Simulations of blood flow in the left ventricle (LV) have proven valuable for elucidating LV hemodynamics. While fully coupled fluid-solid modeling of the LV remains challenging due to the complex passive-active behavior of the LV myocardial wall, integrating imaging-driven quantification of structural motion with computational fluid dynamics (CFD) modeling in the LV holds promise for feasible and personalized characterization of LV hemodynamics. In this study, we propose developing individualized LV models by integrating two magnetic resonance imaging (MRI) modalities with a moving-boundary CFD method to characterize patient-specific intracardiac LV hemodynamics. Our method uses standard cine cardiac magnetic resonance (CMR) images to assess four-dimensional endocardial motion via non-rigid image registration (NRIR), eliminating the need for complex myocardial material modeling to produce LV wall behavior. In addition, phase-contrast MRI (PC-MRI) was used to obtain time-resolved mitral inflow rates, applied as a spatially and temporally varying inflow velocity at the mitral orifice in the CFD simulations. CFD flow patterns, including velocity streamlines, vortex rings, and kinetic energy, were computed and compared to the available clinical data. Moreover, leveraging the NRIR framework, relationships between LV wall kinematic markers and flow characteristics were determined. The fidelity of the simulation was quantitatively evaluated by comparing the flow rate at the aortic outflow tract with the corresponding PC-MRI measurements. The proposed methodology offers a novel, feasible approach that leverages standard PC-CMR protocols to improve patient-specific clinical assessment of LV characteristics for prognostic studies and surgical planning.