M. L. Raghavan, M. Fillinger, S. P. Marra, F. Kennedy
{"title":"An Automated Methdology for Investigating the Correlation Between Abdominal Aortic Aneurysm Wall Stress and Risk of Rupture","authors":"M. L. Raghavan, M. Fillinger, S. P. Marra, F. Kennedy","doi":"10.1115/imece2001/bed-23119","DOIUrl":null,"url":null,"abstract":"\n Clinical experience with regard to predicting abdominal aortic aneurysm (AAA) rupture has shown that although AAA diameter is a good indicator, there are likely other risk factors. Some researchers have explored a biomechanical approach to predicting aneurysm rupture risk [1,2] based on the hypothesis that aneurysm rupture occurs when the mechanical stresses in the aortic wall exceed the wall failure strength. Therefore, knowledge of wall stresses in a particular AAA may help identify impending rupture. Recently, researchers have used patients’ abdominal CT scan data and blood pressure to estimate in-vivo AAA wall stresses [3]. In the present project, an improved automated methodology is used to predict AAA wall stress. The underlying correlation between mechanical stress and aneurysm wall rupture is also investigated.","PeriodicalId":7238,"journal":{"name":"Advances in Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2001-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Bioengineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/imece2001/bed-23119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Clinical experience with regard to predicting abdominal aortic aneurysm (AAA) rupture has shown that although AAA diameter is a good indicator, there are likely other risk factors. Some researchers have explored a biomechanical approach to predicting aneurysm rupture risk [1,2] based on the hypothesis that aneurysm rupture occurs when the mechanical stresses in the aortic wall exceed the wall failure strength. Therefore, knowledge of wall stresses in a particular AAA may help identify impending rupture. Recently, researchers have used patients’ abdominal CT scan data and blood pressure to estimate in-vivo AAA wall stresses [3]. In the present project, an improved automated methodology is used to predict AAA wall stress. The underlying correlation between mechanical stress and aneurysm wall rupture is also investigated.