Abstract
In this work, a methodology for the in-silico evaluation of drug eluting stents (DES) is presented. A stent model developed by Rontis S.A. has been employed. For modeling purposes two different stent parts have been considered: the metal core and the coating. For the arterial models, we used animal specific imaging data and realistic geometries were reconstructed which were used as input to the drug-delivery model. More specifically, optical coherence tomography (OCT) imaging data from two coney iliac arterial segments were 3D reconstructed, and the preprocessed 3D stent was deployed in-silico. The deformed geometries of the in-silico deployed stents and the dilated arterial segments were used as input to the drug elution model. The same reconstructed arteries were used in three different cases: (i) Case A. The coatings contain retinoic acid at an initial concentration 49.2% w/w. (ii) Case B. The coatings contain retinoic acid at an initial concentration 1% w/w. (iii) Case C. The coatings contain sirolimus at an initial concentration 0.85% w/w. In each case, two different coatings were examined: (a) polylactic acid and (b) polylactic-co-glycolic acid. The results proved that retinoic acid is a very promising drug candidate for DES due to its binding time to the smooth muscle cells of the arterial wall that exceeds the corresponding time of sirolimus, while being non-toxic to the smooth muscle cells.