Computational Approach to Quantifying Hemodynamic Forces in Giant Cerebral Aneurysms

Document Type

Article

Abstract

BACKGROUND AND PURPOSE: The options for treating giant fusiform basilar aneurysms are limited, and the potential impact of planned interventions is difficult to assess. We developed a computational framework to evaluate the impact that interventions might have on hemodynamic conditions. METHODS: A computational fluid dynamics approach was used to determine the velocity field, wall shear stress, and pressure distribution within a model of a basilar artery before and after a simulated occlusion of one vertebral artery. The vascular geometry in a patient with a giant fusiform basilar artery aneurysm was determined by using contrast-enhanced MR angiography, and the numerical simulation approach was used to calculate the flow fields in the presenting geometry and to predict the flow field that would occur if a vertebral artery were occluded. RESULTS: In the model geometry, computational fluid dynamics indicated that there would be a symmetric flow pattern with a strong central stream and large recirculation zones at the walls. After simulated occlusion of one vertebral artery, the primary stream was diverted to one side, resulting in high pressure and increased wall shear stress. For the patient-specific geometry, flow patterns were shown to depend strongly on how much flow there was in each vertebral artery. CONCLUSION: Contrast-enhanced MR angiography is an effective tool for demonstrating the luminal boundaries of large intracranial aneurysms. Computational fluid dynamics is a powerful tool for determining the prevailing flow conditions in vascular territories and for modeling the possible alterations of the flow field that would result from interventional treatments.

Publication Date

10-1-2003

Publication Title

American Journal of Neuroradiology

ISSN

01956108

Volume

24

Issue

9

First Page

1804

Last Page

1810

PubMed ID

14561606

This document is currently not available here.

Share

COinS