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Arterioscler Thromb Vasc Biol. 2010 Sep;30(9):1687-94. doi: 10.1161/ATVBAHA.110.204529. Epub 2010 May 27.

New approaches to abdominal aortic aneurysm rupture risk assessment: engineering insights with clinical gain.

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Centre for Applied Biomedical Engineering Research, Department of Mechanical and Aeronautical Engineering, and Materials and Surface Science Institute, University of Limerick, Ireland.


Abdominal aortic aneurysm (AAA) rupture remains a significant cause of death in the developed world. Current treatment approaches rely heavily on the size of the aneurysm to decide on the most appropriate time for clinical intervention and treatment. However, in recent years, several alternative rupture risk indicators have been proposed. This brief review examines some of these new approaches to AAA rupture risk assessment, from both numeric and experimental aspects and also what the future may hold for AAA rupture risk. Although numerically predicted wall stress, finite element analysis rupture index, rupture potential index, severity parameter, and geometric factors, such as asymmetry, have all been developed and show promise in possibly helping to predict AAA rupture risk, validation of these tools remains a significant challenge. Validation of biomechanics-based rupture indicators may be feasible by combining in vitro modeling of realistic AAA analogues with both retrospective and prospective monitoring and modeling of AAA cases. Peak wall stress is arguably the primary result obtained from numeric analyses; however, as the majority of ruptures occur in the posterior and posterior-lateral regions, the role of posterior wall stress has also recently been highlighted as potentially significant. It is also known that wall stress alone is not enough to cause rupture, as wall strength plays an equal role. Therefore, should a biomechanics-based rupture risk be implemented? There have been some significant steps, both numerically and experimentally, toward answering this and other questions relating to AAA rupture risk prediction, yet regardless of the efforts that are under way in several laboratories, the introduction of a numerically predicted rupture risk parameter into the clinicians' decision-making process may still be quite some time away.

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