Fluid Structure Interaction of Patient Specific Abdominal Aortic Aneurysms: a Comparison with Solid Stress Models

Overview

Journal Biomed Eng Online

Publisher Biomed Central

Specialty Biomedical Engineering

Date 2006 May 23

PMID 16712729

Citations 32

Authors

James H Leung

Andrew R Wright

Nick Cheshire

Jeremy Crane

Simon A Thom

Alun D Hughes

Yun Xu

Affiliations

Soon will be listed here.

Abstract

Background: Abdominal aortic aneurysm (AAA) is a dilatation of the aortic wall, which can rupture, if left untreated. Previous work has shown that, maximum diameter is not a reliable determinant of AAA rupture. However, it is currently the most widely accepted indicator. Wall stress may be a better indicator and promising patient specific results from structural models using static pressure, have been published. Since flow and pressure inside AAA are non-uniform, the dynamic interaction between the pulsatile flow and wall may influence the predicted wall stress. The purpose of the present study was to compare static and dynamic wall stress analysis of patient specific AAAs.

Method: Patient-specific AAA models were created from CT scans of three patients. Two simulations were performed on each lumen model, fluid structure interaction (FSI) model and static structural (SS) model. The AAA wall was created by dilating the lumen with a uniform 1.5 mm thickness, and was modeled as a non-linear hyperelastic material. Commercial finite element code Adina 8.2 was used for all simulations. The results were compared between the FSI and SS simulations.

Results: Results are presented for the wall stress patterns, wall shear stress patterns, pressure, and velocity fields within the lumen. It is demonstrated that including fluid flow can change local wall stresses slightly. However, as far as the peak wall stress is concerned, this effect is negligible as the difference between SS and FSI models is less than 1%.

Conclusion: The results suggest that fully coupled FSI simulation, which requires considerable computational power to run, adds little to rupture risk prediction. This justifies the use of SS models in previous studies.

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