A multi-parameter performance correlation model to advance the customized design of vascular stents

The clinical performance of vascular stents hinges on a delicate balance between radial support and bending flexibility. Existing theoretical models are further limited by their focus on single materials or specific geometries, offering little guidance for complex hybrid or functionally graded designs. To overcome these limitations, we present a multi-parameter performance-correlation model (PCM) that unifies material properties, topological features, and cross-sectional parameters into a single analytical framework aimed at accelerating stent design. The PCM derives its governing dimensional relationships from analytical mechanics and is calibrated using a comprehensive finite element analysis database encompassing three representative architectures, four materials, and nine cross-sectional configurations. The model accurately predicts stent mechanical responses, and key analysis reveals that strut width contributes to radial stiffness through a cubic scaling law, significantly stronger than the linear dependence on strut thickness. This finding identifies width enhancement as a more effective strategy for improving radial support without substantially compromising flexibility. Case studies further demonstrate that non-uniform stents yield greater luminal gain at lesion sites, while hybrid designs achieve a functional decoupling of support and compliance. Overall, the proposed PCM offers an efficient tool for early-stage concept screening and design optimization of multi-material, functionally graded vascular stents.