Geometry-prescribed 2D-CFD model to analyse left ventricular blood flow under stress from cycle ergometer CMR.

Motivation: Blood flow in the left ventricle is highly modified by exercise and analysing the adaptation to exercise in patients may unravel new biomarkers and pathological remodeling. Goal(s): We applied a previously described patient-specific MR-based computational fluid dynamics (CFD) model at rest and after exercise in healthy individuals. Approach: Blood flow inside the left ventricle was simulated taking as input the segmentation of the left ventricle from Cine-MRI 3 chamber-view at rest and following a cycle ergometer protocol. Results: Wall shear stress parameters increased in all patients and more vortices were created during diastole under stress compared to resting conditions. Impact: Our geometry-prescribed 2D-CFD model, based on short acquisition time and fully automated, allowed to extract cardiac hemodynamic forces under stress with high repeatability. A similar application in patients at risk of cardiovascular diseases could unravel new biomarkers of cardiac dysfunction.