Doyle Barry J, McGloughlin Timothy M, Miller Karol, Powell Janet T, Norman Paul E
Intelligent Systems for Medicine Laboratory, School of Mechanical and Chemical Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA, Australia,
Cardiovasc Intervent Radiol. 2014 Jun;37(3):815-8. doi: 10.1007/s00270-014-0864-7. Epub 2014 Feb 20.
Predicting the wall stress in abdominal aortic aneurysm (AAA) using computational modeling may be a useful adjunct to traditional clinical parameters that indicate the risk of rupture. Maximum diameter has been shown to have many limitations, and using current technology it is possible to provide a patient-specific computational risk assessment using routinely acquired medical images. We present a case of AAA rupture where the exact rupture point was clearly visible on the computed tomography (CT) images. A blind computational study based on CT scans acquired 4 months earlier predicted elevated wall stresses in the same region that later experienced rupture.
