Exploring flow disturbances at the carotid bifurcation through an integrated computational hemodynamics & complex networks-based approach

Hemodynamics plays a key role in vascular disease. In particular, in the carotid bifurcation (CB) the onset/progression of atherosclerosis has been associated with an altered shear stress distribution at the luminal surface, which is mitigated by helical fluid structures establishing inside the bifurcation and transportated by the common carotid artery (CCA). Here, the Complex Networks (CNs) theory is applied for the first time to a dataset of 10 patient-specific computational hemodynamic models of human CB. Technically a two-points Helicity Density- (Hk-), WSS magnitude- (|WSS|-) and Velocity-based (V-) correlation strategy was proposed to test CNs ability in detecting disturbed flows.