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Rupture behaviour of abdominal aortic aneurysms: an experimental and computational investigation

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dc.contributor.advisor McGloughlin, Timothy M.
dc.contributor.author Doyle, Barry J.
dc.date.accessioned 2009-10-20T15:05:39Z
dc.date.available 2009-10-20T15:05:39Z
dc.date.issued 2009
dc.identifier.uri http://hdl.handle.net/10344/216
dc.description non-peer-reviewed
dc.description.abstract Abdominal aortic aneurysm (AAAs) is a permanent and irreversible dilation of the infrarenal section of the aorta. These aneurysms are typically defined as having a diameter 50% greater than the normal aortic diameter. If left untreated, AAAs will continually expand until rupture, with rupture usually resulting in death. Currently, the decision to surgically repair an AAA is determined by the maximum transverse diameter. If this diameter exceeds 5cm the AAA is deemed a high rupture-risk and subsequently repaired, by either open repair or by the minimally invasive technique of endovascular aneurysm repair (EVAR). There is continued debate as to the appropriateness of the maximum-diameter criterion as a “one-size fits all” approach to AAA management, as AAAs are known to be patient-specific in terms of geometry, and ultimately wall stress and strength. This thesis aims to explore alternative approaches to AAA severity assessment using both computational and experimental methodologies and attempt to provide new insights into AAA rupture, thereby improving the overall clinical assessment. In this study it was found that 80% of realistic experimental AAAs rupture at areas experiencing peak wall stress and not at regions of maximum diameter. These regions of elevated wall stress can be identified by the finite element method or the surface curvature of the AAA. Surface defects affect rupture location as they shift the site of rupture from regions of high wall stress to the areas of localised irregularities. These experimental surface defects are comparable to calcifications, blebs and localised hypoxia in the AAA wall in vivo. Idealised AAA models were also shown to rupture at regions of complex surface curvature and not at the maximum diameter. A range of silicone rubbers were created that allow improved AAA analogues to be produced. These silicones have varying wall strengths which can be determined non-destructively using a colour analysis technique, resulting in experimental AAAs more akin to the in vivo situation. Bench-top models were manufactured using an injection-moulding lostwax technique that create anatomically-correct AAA replications and can be used in a variety of experimental methods. A direct correlation between numerically predicted posterior wall stress and vessel asymmetry was identified, and the study showed that asymmetry may be as significant as diameter in determining the severity of a particular AAA. A new computational approach to AAA rupture assessment was also created. This index, described as the Finite Element Analysis Rupture Index (FEARI), indicates that not all AAAs may be at a high risk of rupture, and is independent to diameter. Results suggest that similar diameter AAAs may have contrasting rupture potentials. All computational AAA analyses stem from 3D reconstructions of medical images. These virtual 3D models not only allow further investigation with techniques such as the finite element method, but also allow pre-operative planning once surgery is decided upon. Clinical guidance in the form of stent-graft sizing is possible and anatomical complications can be foreseen and subsequently overcome. The results and conclusions presented throughout this thesis may further contribute to the understanding of AAA biomechanics and rupture potential, and in the future may help provide improved clinical guidance on the timing of surgery for AAA treatment. en
dc.language.iso eng en
dc.subject abdominal aortic aneurysm
dc.title Rupture behaviour of abdominal aortic aneurysms: an experimental and computational investigation en
dc.type Doctoral thesis en
dc.type.supercollection all_ul_research
dc.type.supercollection ul_theses_dissertations
dc.type.restriction none en


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