Journal Article

Wall Stress and Geometry Measures in Electively Repaired Abdominal Aortic Aneurysms

Rengarajan, Balaji, De Oliveira, Victor, Finol, Ender A, Wu, Wei, Muluk, Satish C, Thirugnanasambandam, Mirunalini, Gomez, Raymond, Parikh, Shalin

2019

Overview

Abdominal aortic aneurysm (AAA) is a vascular disease characterized by the enlargement of the infrarenal segment of the aorta. A ruptured AAA can cause internal bleeding and carries a high mortality rate, which is why the clinical management of the disease is focused on preventing aneurysm rupture. AAA rupture risk is estimated by the change in maximum diameter over time (i.e., growth rate) or if the diameter reaches a prescribed threshold. The latter is typically 5.5 cm in most clinical centers, at which time surgical intervention is recommended. While a size-based criterion is suitable for most patients who are diagnosed at an early stage of the disease, it is well known that some small AAA rupture or patients become symptomatic prior to a maximum diameter of 5.5 cm. Consequently, the mechanical stress in the aortic wall can also be used as an integral component of a biomechanics-based rupture risk assessment strategy. In this work, we seek to identify geometric characteristics that correlate strongly with wall stress using a sample space of 100 asymptomatic, unruptured, electively repaired AAA models. The segmentation of the clinical images, volume meshing, and quantification of up to 45 geometric measures of each AAA were done using in-house Matlab scripts. Finite element analysis was performed to compute the first principal stress distributions from which three global biomechanical parameters were calculated: peak wall stress, 99th percentile wall stress and spatially averaged wall stress. Following a feature reduction approach consisting of Pearson’s correlation matrices with Bonferroni correction and linear regressions, a multivariate stepwise regression analysis was conducted to find the geometric measures most highly correlated with each of the biomechanical parameters. Our findings indicate that wall stress can be predicted by geometric indices with an accuracy of up to 94% when AAA models are generated with uniform wall thickness and up to 67% for patient specific, non-uniform wall thickness AAA. These geometric predictors of wall stress could be used in lieu of complex finite element models as part of a geometry-based protocol for rupture risk assessment.

• Publisher: Springer Nature B.V
• Subject: Aneurysms / Aorta / Aortic aneurysms / Biomechanics / Bleeding / Correlation analysis / Disease control / Enlargement / Finite element method / Geometric accuracy / Growth rate / Image processing / Image segmentation / Mathematical models / Matrix methods / Meshing / Parameters / Patients / Regression analysis / Risk assessment / Rupture / Rupturing / Stress / Vascular diseases / Wall thickness