Hypertrophic Cardiomyopathy (HCM) is a pathological condition characterized by an abnormal thickening of the myocardium. When it affects the medio-basal portion of the septum, it is named Hypertrophic Obstructive Cardiomyopathy because it induces a flow obstruction in the left ventricle outflow tract, which may compromise the cardiac function and possibly lead to cardiac death. In this work, we investigate the hemodynamics of different HCM patients by means of computational hemodynamics, aiming at quantifying the effects of this pathology on blood flow and pressure gradients and thus providing clinical indications that may help diagnosis and the design of surgical treatment (septal myectomy). To this aim, we employ an enhanced version of an image-based computational pipeline proposed in a previous work, integrating fluid dynamics simulations with geometrical and functional data reconstructed from standard cine-MRI acquisitions. Blood flow is modelled as an incompressible Newtonian fluid, The corresponding Navier-Stokes equations are solved in a moving domain obtained from cine-MRI, whereas the valve leaflets are accounted for by a resistive method.
Optimal B-Spline Mapping of Flow Imaging Data for Imposing Patient-Specific Velocity Profiles in Computational Hemodynamics
