Multi-objective optimization of auxetic coronary stents based on finite element simulation and surrogate modeling.

High cost of clinical trials hinders further enhancement of comprehensive mechanical properties of bioresorbable scaffolds (BRS). Therefore, a multi-objective optimization method combining surrogate modeling and finite element simulation is proposed, based on the evaluation of stents with various auxetic structures and materials. The results demonstrated that re-entrant hexagon stent made of PLA (PLA-RH stent) was a more ideal candidate, with superior radial recoil and force. Following optimization, PLA-RH stent decreased bending stiffness by 60.12%, without compromising radial performances. This method enables more precise and efficient optimization and the proposed auxetic structure introduces innovative concepts for future design of stents.