Influence of vessel curvature and plaque composition on drug transport in the arterial wall following drug-eluting stent implantation

• Published in: Biomechanics and modeling in mechanobiology 2021-04, Vol.20 (2), p.767-786
• Main Authors: Escuer, Javier, Aznar, Irene, McCormick, Christopher, Peña, Estefanía, McGinty, Sean, Martínez, Miguel A.
• Format: Article
• Language: English
• Subjects: Biological and Medical Physics; Biomedical Engineering and Bioengineering; Biophysics; Blood flow; Blood vessels; Composition; Computational fluid dynamics; Computer applications; Curvature; Drug delivery; Endothelium; Engineering; Filtration; Implantation; Implants; Influence; Mathematical models; Original Paper; Space life sciences; Spatial distribution; Stents; Surgical implants; Temporal distribution; Theoretical and Applied Mechanics; Transport processes
• ISSN: 1617-7959; 1617-7940
• DOI: 10.1007/s10237-020-01415-3

In the last decade, many computational models have been developed to describe the transport of drug eluted from stents and the subsequent uptake into arterial tissue. Each of these models has its own set of limitations: for example, models typically employ simplified stent and arterial geometries, some models assume a homogeneous arterial wall, and others neglect the influence of blood flow and plasma filtration on the drug transport process. In this study, we focus on two common limitations. Specifically, we provide a comprehensive investigation of the influence of arterial curvature and plaque composition on drug transport in the arterial wall following drug-eluting stent implantation. The arterial wall is considered as a three-layered structure including the subendothelial space, the media and the adventitia, with porous membranes separating them (endothelium, internal and external elastic lamina). Blood flow is modelled by the Navier–Stokes equations, while Darcy’s law is used to calculate plasma filtration through the porous layers. Our findings demonstrate that arterial curvature and plaque composition have important influences on the spatiotemporal distribution of drug, with potential implications in terms of effectiveness of the treatment. Since the majority of computational models tend to neglect these features, these models are likely to be under- or over-estimating drug uptake and redistribution in arterial tissue.