Ranno, AnnaAnnaRannoManjunatha, KiranKiranManjunathaKoritzius, ThoreThoreKoritziusSteinbrecher, IvoIvoSteinbrecherHosters, NorbertNorbertHostersNachtsheim, MaximilianMaximilianNachtsheimNilcham, PakhwanPakhwanNilchamSchaaps, NicoleNicoleSchaapsTuroni-Glitz, AnneAnneTuroni-GlitzDatz, JaninaJaninaDatzPopp, AlexanderAlexanderPoppLinka, KevinKevinLinkaVogt. FelixBehr, MarekMarekBehr2025-11-192025-11-192025-11-10Scientific Reports 15: 39229: (2025)https://hdl.handle.net/11420/58839Despite advances in stent technology, in-stent restenosis remains a critical challenge following percutaneous coronary intervention. In this work, we propose a comprehensive fluid-solid computational model to simulate restenosis after drug-eluting stent implantation. We develop a three-dimensional continuum-based framework that couples the complex interplay of hemodynamics, pharmacokinetics, and restenosis-induced arterial growth. Within the arterial wall, a continuum model of cell dynamics and tissue growth predicts neointimal thickening. Drug release is modeled by direct diffusion from the abluminal stent surface and one-way absorption of hydrophobic drug from the bloodstream at the lumen-wall interface. We incorporate blood flow influence into growth mechanics through the effect of non-physiological wall shear stresses on endothelial cells morphology. Due to the short time scale inherent in the fluid model, we adopt a quasi-steady approach that efficiently homogenizes hemodynamic-related quantities over clinically relevant time scales for restenosis and drug release. We verify the components of the computational model and the quasi-steady assumption using a test case with an idealized cylindrical artery and a one-ring stent. The framework is further extended to patient-specific geometries obtained from optical coherence tomography and virtual stent implantation. Our results showcase how stent design, drug elution, and hemodynamics can collectively modulate restenosis progression, and the proposed coupling framework could, in the long term, contribute to the development of clinical decision-support tools.en2045-2322202515Springer Science and Business Media LLChttps://creativecommons.org/licenses/by/4.0/Technology::616: DeseasesTechnology::620: Engineering::620.1: Engineering Mechanics and Materials ScienceJournal Articlehttps://doi.org/10.15480/882.1616710.1038/s41598-025-22291-w10.15480/882.16167Journal Article