On automated analysis of flow patterns in cerebral aneurysms based on vortex identification

It is hypothesized that the risk of rupture of cerebral aneurysms is related to geometrical and mechanical properties of the arterial wall as well as to local hemodynamics. In order to gain better understanding of the hemodynamical factors involved in intra-aneurysmal flows, a thorough analysis of the 3D velocity field within an idealized geometry is needed. This includes the identification and quantification of features like vortices and stagnation regions. The aim of our research is to develop experimentally validated computational methods to analyse intra-aneurysmal vortex patterns and, eventually, define candidate hemodynamical parameters (e.g. vortex strength) that could be predictive for rupture risk. A computational model based on a standard Galerkin finite-element approximation and an Euler implicit time integration has been applied to compute the velocity field in an idealized aneurysm geometry and the results have been compared to Particle Image Velocimetry (PIV) measurements in an in vitro model. In order to analyze the vortices observed in the aneurysmal sac, the vortex identification scheme as proposed by Jeong and Hussain (JFM 285:69-94, 1995) is applied. The 3D intra-aneurysmal velocity fields reveal complex vortical structures. This study indicates that the computational method predicts well the vortex structure that is found in the in vitro model and that a 3D analysis method like the vortex identification as proposed is needed to fully understand and quantify the vortex dynamics of intra-aneurysmal flow. Furthermore, such an automated analysis method would allow the definition of parameters predictive for rupture in clinical practice. © The Author(s) 2009