Optimization of the geometry of a drug-eluting stent

Drug eluting stents
Image 1: Parametric model of a coronary drug-eluting stent.
In clinical trials stents were shown to lead to decreased restenosis rates when compared with balloon angioplasty alone [1], [2], [3]. Although stents have been effective in reducing the elastic recoil and partly vascular remodeling, they may lead to adverse effects such as in-stent restenosis, which is associated with neointimal hyperplasia.
The systemic administration of a variety of pharmacological agents has not had a significant impact on post- angioplasty restenosis rates [4]. However, the concept of using stents as vehicles for prolonged and sufficient intramural drug delivery is appealing. Stents represent an ideal platform for local drug delivery because of their permanent scaffolding properties, which prevent vessel recoil and negative remodeling. In addition, they represent drug reservoirs, whose properties are governed by the quantity of medications released from various coatings at certain time intervals. The achievement of a well designed relationship between stent, coating matrix, drug and vessel wall is extremely challenging and is known as a drug-eluting stent.
Numerical model

The original stent geometry was digitized and represented by smooth surfaces in a dedicated CAD software. The software allows to fully parameterize the stent. This was important to carry out the optimization as a function of several design parameters.

The finite-element model was built directly from the smooth CAD surfaces. This procedure allowed to perform adaptive mesh refinement while retaining even the finest details of the original model. The adaptivity utilizes an error estimator that is suitable for nonlinear problems.
The model is based on a hexahedral mesh because of the superior performance when compared to tetrahedral meshes. For the stent material a shape-memory alloy was utilized. The simulation was carried out in Cucuma, an object oriented finite element software that allows to deal with numerical problems on a highly abstract (and therefore efficient) level.
For the pharmacokinetic interaction a specially developed 3D version of the model described in [5] was used.

Image 2: Stress distribution in the stent struts due to interaction with a human stenosis.

A large number of design parameters had to be optimized, since the stent not only acts as mechanical but also as a drug eluting device. Stress distributions in the struts were analyzed to allow for maximum lateral stiffness while retaining longitudinal flexibility (which is necessary when maneuvering through turtuous vessels). On the pharmacokinetic side, several parameters associated with drug release had to be optimized.

[1] D.L. Fischman, M.B. Leon, D.S. Baim, R.A. Schatz, M.P. Savage, I. Penn, K. Detre, L. Veltri, D. Ricci, M. Nobuyushi et al., A randomized comparison of coronary-stent placement and balloon angioplasty in the treatment of coronary artery disease. Stent Restenosis Study Investigators, New Engl. J. Med., 331:496-501, 1994.
[2] Serruys PW, de Jaegere P, Kiemeneij F, Macaya C, Rutsch W, Heyndrickx G, Emanuelsson H, Marco J, Legrand V, Materne P, et al., A comparison of balloon-expandable-stent implantation with balloon angioplasty in patients with coronary artery disease. Benestent Study Group, New Engl. J. Med., 331:489-495, 1994.
[3] Betriu A, Masotti M, Serra A, Alonso J, Fernandez-Aviles F, Gimeno F, Colman T, Zueco J, Delcan JL, Garcia E, Calabuig J., Randomized comparison of coronary stent implantation and balloon angioplasty in the treatment of de novo coronary artery lesions (START): a four-year follow-up, Am. J. Cardiol, 34:1498-1506, 1999.
[4] M.N. Babapulle and M.J. Eisenberg. Coated stents for the prevention of restenosis: Part I. Circ., 106:2734-2740,2002.
[5] D.V. Sakharov, L.V. Kalachev and D.C. Rijken. Numerical simulation of local pharmacokinetics of a drug after intravascular delivery with an eluting stent. J. Drug Target, 10:507-513, 2002.

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