Although braided stents are widely adopted for intracranial aneurysm treatment, current designs still struggle with simultaneously satisfying the conflicting demands of mechanical properties including radial pressure, bending moment and foreshortening. This study proposed a multi-objective optimization framework based on an improved response surface model (IRSM) for the personalized design of braided stents, to enhance their adaptability to specific lesions. The IRSM was constructed for the aforementioned mechanical properties and integrated with design of experiments to accurately characterize intrinsic relationships between design parameters and mechanical properties. Based on 45 training samples, the IRSM demonstrated high accuracy in modeling the intrinsic relationships between design parameters and mechanical properties. Assessed using leave-one-out cross-validation, it achieved a coefficient of determination R2 > 0.9580 and a mean squared error MSE < 0.0410. Then, multi-objective optimization was implemented to obtain the Pareto-optimal solutions by the non-dominated sorting genetic algorithm II. Finite element simulations were performed separately for both the commercial stent pipeline and the selected Pareto-optimal solution. The comparative results revealed that this selected Pareto-optimal solution effectively increases radial pressure and reduces foreshortening, while inevitably leading to an increase in bending moment, thereby highlighting the importance of conducting coordinated trade-offs and optimizations of multiple objectives based on specific clinical scenarios in personalized stent design.
Zheng et al. (Sun,) studied this question.