Computational Fluid Dynamics (CFD) has become, in the last few decades, even more an important tool to investigate local hemodynamics and its possible association with atherosclerosis genesis and progressions, to plan patient-specific interventions and to design and evaluate vascular devices. The combination of CFD and medical imaging allows, in fact, to quantify a variety of descriptors that would be difficult to be measured in vivo, with a spatial and temporal resolution unreachable with other clinical methodology in a patient specific manner. However, the accuracy of CFD predictions is strongly influenced by modelling assumptions which introduce sources of uncertainty. An example is represented by the inflow boundary conditions (BCs) which starts from in vivo flow rate estimation depending on the method used and may provide different flow rate values.