Efficiently simulating an endograft deployment : a methodology for detailed CFD analyses

Tools

Kyriakou, Faidon and Maclean, Craig and Dempster, William and Nash, David (2020) Efficiently simulating an endograft deployment : a methodology for detailed CFD analyses. Annals of Biomedical Engineering, 48 (10). pp. 2449-2465. ISSN 0090-6964 (https://doi.org/10.1007/s10439-020-02519-8)

[thumbnail of Kyriakou-etal-ABE-2020-Efficiently-simulating-an-endograft-deployment]
Preview
 Text. Filename: Kyriakou_etal_ABE_2020_Efficiently_simulating_an_endograft_deployment.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (5MB)| Preview

Abstract

Numerical models of endografts for the simulation of endovascular aneurysm repair are increasingly important in the improvement of device designs and patient outcomes. Nevertheless, current finite element analysis (FEA) models of complete endograft devices come at a high computational cost, requiring days of runtime, therefore restricting their applicability. In the current study, an efficient FEA model of the Anaconda™ endograft (Terumo Aortic, UK) was developed, able to yield results in just over 4 h, an order of magnitude less than similar models found in the literature. The model was used to replicate a physical device that was deployed in a 3D printed aorta and comparison of the two shapes illustrated a less than 5 mm placement error of the model in the regions of interest, consistent with other more computationally intensive models in the literature. Furthermore, the final goal of the study was to utilize the deployed fabric model in a hemodynamic analysis that would incorporate realistic fabric folds, a feature that is almost always omitted in similar simulations. By successfully exporting the deployed graft geometry into a flow analysis, it was illustrated that the inclusion of fabric wrinkles enabled clinically significant flow patterns such as flow stagnation and recirculation to be detected, paving the way for this modelling methodology to be used in future for stent design optimisation.

ORCID iDs

Kyriakou, Faidon ORCID logoORCID: https://orcid.org/0000-0001-6759-8033, Maclean, Craig, Dempster, William ORCID logoORCID: https://orcid.org/0000-0001-8918-3832 and Nash, David;
CORE (COnnecting REpositories)