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

Area of Science:

• Biomaterials Engineering
• Medical Device Design
• Computational Mechanics

Background:

• High costs of clinical trials impede the optimization of mechanical properties for bioresorbable scaffolds (BRS).
• Existing BRS designs require significant investment for performance enhancement.
• Need for cost-effective optimization strategies for advanced medical devices.

Purpose of the Study:

• To develop a cost-effective, multi-objective optimization method for bioresorbable scaffolds (BRS).
• To evaluate the impact of auxetic structures and materials on stent mechanical performance.
• To identify an optimal BRS design with enhanced comprehensive mechanical properties.

Main Methods:

• Combined surrogate modeling and finite element simulation for multi-objective optimization.
• Evaluated various auxetic structures and materials for stent design.
• Focused on optimizing radial recoil, force, and bending stiffness.

Main Results:

• The re-entrant hexagon stent made of polylactic acid (PLA-RH stent) demonstrated superior radial recoil and force.
• Optimized PLA-RH stent achieved a 60.12% reduction in bending stiffness.
• Mechanical performance, particularly radial properties, was maintained post-optimization.

Conclusions:

• The proposed optimization method offers precise and efficient design improvements for BRS.
• The auxetic structure presents an innovative concept for future stent design.
• PLA-RH stent is a promising candidate for advanced bioresorbable scaffolds.