Multi-objective optimization of coronary stent using Kriging surrogate model.
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%.


CONCLUSIONS
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.
School of Mechanical Engineering, Dalian University of Technology, Dalian, 116023, Liaoning, China.
Hongxia
H
Li
State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian, 116023, Liaoning, China.
Junfeng
J
Gu
School of Mechanical Engineering, Dalian University of Technology, Dalian, 116023, Liaoning, China.
Minjie
M
Wang
School of Mechanical Engineering, Dalian University of Technology, Dalian, 116023, Liaoning, China.
Danyang
D
Zhao
State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian, 116023, Liaoning, China.
Zheng
Z
Li
College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China.
Aike
A
Qiao
School of Materials Science and Engineering, Dalian University of Technology, Dalian, 116023, Liaoning, China. bzhu@dlut.edu.cn.
Bao
B
Zhu
D000465:Algorithms; D000792:Angiography; D003198:Computer Simulation; D023903:Coronary Restenosis; D023921:Coronary Stenosis / Q000503:physiopathology*; D004548:Elasticity; D020342:Finite Element Analysis; D006801:Humans; D008955:Models, Cardiovascular; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D011312:Pressure; D011474:Prosthesis Design; D015203:Reproducibility of Results; D012306:Risk; D015607:Stents; D013314:Stress, Mechanical
Black-box techniques; Design optimization; Dogboning; Kriging surrogate model; Radial elastic recoil; Stent