Estimating an equivalent wall-thickness of a cerebral aneurysm through surface parameterization and a non-linear spring system

Abstract

Cerebral aneurysms are an enlargement of a brain blood-vessel due to a weakened wall and can pose significant health risks. Computational simulations have been thus utilized to help doctors in the understanding of cerebral aneurysms. In order to provide more accurate patient-specific simulations, not only does geometry for the fluid domain need to be created from medical image data, but more accurate wall-models need to be generated as well. However, the wall-thickness and material properties are very difficult to obtain experimentally, and thus most computational simulations, except for a few we have seen in the recent years, are performed using walls with uniform thickness and constant material properties. To provide a more accurate computational model for the weakened wall-structure, this paper presents a novel estimation of an equivalent cerebral aneurysm wall-thickness by deforming a healthy vessel onto an aneurysm through surface parameterization and a non-linear spring system. The resulting wall-model is thinnest over the dome of the aneurysm, and for the patient-specific models used has an average thickness of 75µm. Fluid–structure interaction simulations of three patient-specific cerebral aneurysms are carried out. Compared with using a uniform wall-thickness, using the equivalent wall-thickness gives a more accurate prediction of the rupture site. Copyright © 2010 John Wiley & Sons, Ltd.