Document Type : Research Paper

Authors

1 Department of Mechanical Engineering, Collage of Engineering, University of Al-Qadisiyah, Ad-Diwaniyah, Iraq.

2 College of Technical Engineering, University of Al-Kafeel, Iraq: Al-Najaf

3 Department of Mechanical Aerospace and Civil Engineering, The University of Manchester, M13 9PL, UK

Abstract

Abdominal aortic aneurysm (AAA) is a life-threatening cardio-vascular condition. Current surgical intervention is based on the maximum diameter threshold of 5.5 cm. Over the past years, two indicators to predict potential rupture, Rupture Potential Index (RPI) and Finite Element Analysis Rupture Index (FEARI), had been developed using finite element analysis (FEA), based on the predicted maximum wall stress and statistical or local wall strength. The purpose of this study is to develop a numerical model using extended finite element method (XFEM) to understand the initiation/growth of potential rupture and predict its location in abdominal aortic aneurysm wall by involving the parameters of failure: the wall stress, wall strength and strain, as well as, investigating the use of 3D-US AAA models instead of CT models. Failure analyses were conducted on numerical models of AAA derived from 3D-US and CT images for four elected patients to examine the initiation and growth of potential rupture under three different pressures of 120, 140 and 160 mmHg and three different wall strengths of 0.33, 1.34 and 2.36 MPa respectively. The majority of AAAs showed insignificant differences in stress distributions between 3D-US and CT models, except one patient where the 3D-US model remarkably showed higher stress compared to the CT model. The location of rupture initiation was predicted reliably for both the models of AAA  which have been independently verfied with visual predictions by cardio-vascular surgeons. However, the predicted length of rupture and the potential penetration (full damage of the wall) varied between the models depending upon the applied pressure and the strength of the wall.

Keywords

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