Haemodynamic impact of stent–vessel (mal)apposition following carotid artery stenting: mind the gaps!

Abstract

Carotid artery stenting (CAS) has emerged as a minimally invasive alternative to endarterectomy but its use in clinical treatment is limited due to the post-stenting complications. Haemodynamic actors, related to blood flow in the stented vessel, have been suggested to play a role in the endothelium response to stenting, including adverse reactions such as in-stent restenosis and late thrombosis. Accessing the flow-related shear forces acting on the endothelium in vivo requires space and time resolutions which are currently not achievable with non-invasive clinical imaging techniques but can be obtained from image-based computational analysis. In this study, we present a framework for accurate determination of the wall shear stress (WSS) in a mildly stenosed carotid artery after the implantation of a stent, resembling the commercially available Acculink (Abbott Laboratories, Abbott Park, Illinois, USA). Starting from angiographic CT images of the vessel lumen and a micro-CT scan of the stent, a finite element analysis is carried out in order to deploy the stent in the vessel, reproducing CAS in silico. Then, based on the post-stenting anatomy, the vessel is perfused using a set of boundary conditions: total pressure is applied at the inlet, and impedances that are assumed to be insensitive to the presence of the stent are imposed at the outlets. Evaluation of the CAS outcome from a geometrical and haemodynamic perspective shows the presence of atheroprone regions (low time-average WSS, high relative residence time) colocalised with stent malapposition and stent strut interconnections. Stent struts remain unapposed in the ostium of the external carotid artery disturbing the flow and generating abnormal shear forces, which could trigger thromboembolic events.

Keywords::

• carotid artery stenting
• computational fluid dynamics
• pyFormex
• finite element analysis
• image-based analysis
• impedance model

Acknowledgements

Gianluca De Santis' research is supported by a BOF grant from Ghent University. Joris Degroote gratefully acknowledges a postdoctoral fellowship of the Research Foundation Flanders (FWO).