Optimization of stent-balloon system based on surrogate modeling technique / 医用生物力学

Objective To make the stent expand uniformly along the axial, an improved kriging optimization algorithm is applied for to the optimal design of stent-balloon system to find the optimal length of the balloon. Methods Based on finite element method results, kriging surrogate model combining with Latin hypercube sampling (LHS) approach and expected improvement (EI) function was employed for the optimization of balloon length to reduce stent dog-boning effect during its dilation. Results The kriging surrogate model could approximately establish the relationship between stent dog-boning rate and balloon length and so to replace the expensive reanalysis of stent dilation. Sample points from LHS could perfectly represent the vector space. EI function could be used to effectively find out the global optimal solution with high probability. The optimal length of balloon could make the stent expand uniformly. Conclusions This adaptive optimization method based on kriging surrogate model can optimize the design of stent–balloon system effectively.

Fatigue life optimization for coronary stent under the effect of blood flow / 医用生物力学

Objective To evaluate the fatigue life of coronary stent under the effect of blood flow and thus optimize the stent design.MethodsA simplified model of the stent, blood, plaque and artery was established using Pro/Engineering, and the periodic blood flow impact on the vascular stent was simulated by finite element method via ANSYS. The result on hemodynamics from such stent was then used to evaluate its fatigue life. The geometric parameters of the stent were chosen as design variables for optimization. By using Latin Hypercubic sampling and ANSYS program, responses of the sample points could be obtained and the Kriging surrogate model was then constructed to optimize the fatigue life of the coronary stent.Results Goodman’s method showed that the optimized stent was safe. The cumulative damage method indicated that the largest damage occurred at the second cross-section of the bridge struts. The fatigue life of the optimized stent could be enhanced by 30.55%. Conclusions The finite element method can be used to evaluate the fatigue life of the coronary stent, and the optimization of stent by establishing Kriging model can effectively enhance the fatigue life of the stent.