Paper Info
Title
On the role of material properties in ascending thoracic aortic aneurysms.
Abstract
One of the obstacles standing before the biomechanical analysis of an ascending thoracic aortic aneurysm (ATAA) is the difficulty in obtaining patient-specific material properties. This study aimed to evaluate differences on ATAA-related stress predictions resulting from the elastostatic analysis based on the optimization of arbitrary material properties versus the application of patient-specific material properties determined from ex-vivo biaxial testing. Specifically, the elastostatic analysis relies the on the fact that, if the aortic wall stress does not depend on material properties, the aorta has to be statistically determinate. Finite element analysis (FEA) was applied to a group of nine patients who underwent both angio-CT imaging to reconstruct ATAA anatomies and surgical repair of diseased aorta to collect tissue samples for experimental material testing. Tissue samples cut from excised ATAA rings were tested under equibiaxial loading conditions to obtain experimentally-derived material parameters by fitting stress-strain profiles. FEAs were carried out using both optimized and experimentally-derived material parameters to predict and compare the stress distribution using the mean absolute percentage error (MAPE). Although physiological strains were below yield point (range of 0.08–0.25), elastostatic analysis led to errors on the stress predictions that depended on the type of constitutive model (highest MAPE of 0.7545 for Yeoh model and 0.7683 for Fung model) and ATAA geometry (lowest MAPE of 0.0349 for patient P.7). Elastostatic analysis needs better understanding of its application for determining aneurysm mechanics, and patient-specific material parameters are essential for reliable accurate stress predictions in ATAAs.
Year
DOI
Venue
2019
10.1016/j.compbiomed.2019.04.022
Computers in Biology and Medicine
Keywords
Field
DocType
Ascending aortic aneurysm,Inverse approach,Material parameters,Aortic aneurysm failure,Finite-element analysis
Thoracic aortic aneurysm,Biomedical engineering,Aortic aneurysm,Pattern recognition,Computer science,Aneurysm,Yield (engineering),Finite element method,Artificial intelligence,Yeoh,Material properties,Constitutive equation
Journal
Volume
ISSN
Citations 
109
0010-4825
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Federica Cosentino100.34
Valentina Agnese200.68
Giuseppe Maria Raffa301.01
Giovanni Gentile400.68
Diego Bellavia511.64
Massimiliano Zingales6156.14
Michele Pilato701.01
Salvatore Pasta813.67