Investigation of hemodynamic flow patterns caused by aortic stenosis using a combined 4D Flow MRI-CFD framework

Abstract Purpose Aortic stenosis (AS) leads to alterations of supra-valvular flow patterns. These patterns might lead to, inter alia, an increased damage of red blood cell (RBC) membranes. The aim of this work was to elucidate these patient-specific patterns between a healthy subject and a patient suffering from severe AS through a 4D Flow MRI-based CFD methodology. Material and methods Computational models of subject-specific aortic geometries were created using in-vivo medical imaging data. Temporally and spatially resolved boundary conditions derived from 4D Flow MRI were implemented. After validation of the in-silico results with in-vivo data, the numerical flow fields were investigated regarding their blood flow characteristics, i.e. shear stresses on RBCs and helicity. These insights were used to determine the potential RBC damage in AS. Results The accuracy of the 4D Flow MRI-based CFD model was proven with excellent agreement between in-vivo and in-silico velocity fields and R² = 0.9. A pathological high shear stress region in the bulk flow was present during late systole with an increase of 125% compared to the healthy flow. The physiological bihelical structure with predominantly right-handed helices vanished for the pathological state. Instead, a left-handed helix appeared, accompanied by an overall increase in turbulent kinetic energy in areas of accumulated left-handed helicity. These alterations could cause RBC damage. Conclusion Validated 4D Flow MRI-based CFD models of healthy and AS patients suggest that altered turbulent and helical structures in the bulk flow are the cause for increased, potentially damaging forces acting upon RBCs in AS.