Key result
The multi-objective optimization method based on the Kriging surrogate model reduced the absolute value of the dogboning ratio at 32 ms by 94.21% and the average radial elastic recoil by 15.17% compared to the original stent design.
Why the study?
Does multi-objective optimization using a Kriging surrogate model reduce dogboning effect and radial elastic recoil in a coronary stent model?
Does multi-objective optimization using a Kriging surrogate model reduce dogboning effect and radial elastic recoil in a coronary stent model?
Effect estimate: 94.21% reduction
Absolute Event Rate: 0.0036% vs 0.0622%
A multi-objective optimization method using a Kriging surrogate model effectively reduced the dogboning effect and radial elastic recoil in a computational model of a coronary stent.
May streamline multi-objective stent design computationally; leaves open whether optima improve clinical outcomes.
BACKGROUND: In stent design optimization, the functional relationship between design parameters and design goals is nonlinear, complex, and implicit and the multi-objective design of stents involves a number of potentially conflicting performance criteria. Therefore it is hard and time-consuming to find the optimal design of stent either by experiment or clinic test. Fortunately, computational methods have been developed to the point whereby optimization and simulation tools can be used to systematically design devices in a realistic time-scale. The aim of the present study is to propose an adaptive optimization method of stent design to improve its expansion performance. METHODS: Multi-objective optimization method based on Kriging surrogate model was proposed to decrease the dogboning effect and the radial elastic recoil of stents to improve stent expansion properties and thus reduce the risk of vascular in-stent restenosis injury. Integrating design of experiment methods and Kriging surrogate model were employed to construct the relationship between measures of stent dilation performance and geometric design parameters. Expected improvement, an infilling sampling criterion, was employed to balance local and global search with the aim of finding the global optimal design. A typical diamond-shaped coronary stent-balloon system was taken as an example to test the effectiveness of the optimization method. Finite element method was used to analyze the stent expansion of each design. RESULTS: 27 iterations were needed to obtain the optimal solution. The absolute values of the dogboning ratio at 32 and 42 ms were reduced by 94.21 and 89.43%, respectively. The dogboning effect was almost eliminated after optimization. The average of elastic recoil was reduced by 15.17%. CONCLUSION: This article presents FEM based multi-objective optimization method combining with the Kriging surrogate model to decrease both the dogboning effect and radial elastic recoil of stents. The numerical results prove that the proposed optimization method effectively decreased both the dogboning effect and radial elastic recoil of stent. Further investigations containing more design goals and more effective multidisciplinary design optimization method are warranted.
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Li et al. (2016) studied Coronary artery disease (stent design optimization). Multi-objective optimization based on Kriging surrogate model vs. Original stent design was evaluated on Dogboning ratio at 32 ms (94.21% reduction). The multi-objective optimization method based on the Kriging surrogate model reduced the absolute value of the dogboning ratio at 32 ms by 94.21% and the average radial elastic recoil by 15.17% compared to the original stent design.
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