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基于克里金代理模型的支架及其扩张球囊的设计优化

Design optimization of stent and its dilatation balloon using kriging surrogate model.

作者信息

Li Hongxia, Liu Tao, Wang Minjie, Zhao Danyang, Qiao Aike, Wang Xue, Gu Junfeng, Li Zheng, Zhu Bao

机构信息

School of Mechanical Engineering, Dalian University of Technology, Dalian, 116023, Liaoning, China.

College of Life Science and Bioengineering, Beijing University of Technology, Beijing, 100124, China.

出版信息

Biomed Eng Online. 2017 Jan 11;16(1):13. doi: 10.1186/s12938-016-0307-6.

DOI:10.1186/s12938-016-0307-6
PMID:28086895
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5234108/
Abstract

BACKGROUND

Although stents have great success of treating cardiovascular disease, it actually undermined by the in-stent restenosis and their long-term fatigue failure. The geometry of stent affects its service performance and ultimately affects its fatigue life. Besides, improper length of balloon leads to transient mechanical injury to the vessel wall and in-stent restenosis. Conventional optimization method of stent and its dilatation balloon by comparing several designs and choosing the best one as the optimal design cannot find the global optimal design in the design space. In this study, an adaptive optimization method based on Kriging surrogate model was proposed to optimize the structure of stent and the length of stent dilatation balloon so as to prolong stent service life and improve the performance of stent.

METHODS

A finite element simulation based optimization method combing with Kriging surrogate model is proposed to optimize geometries of stent and length of stent dilatation balloon step by step. Kriging surrogate model coupled with design of experiment method is employed to construct the approximate functional relationship between optimization objectives and design variables. Modified rectangular grid is used to select initial training samples in the design space. Expected improvement function is used to balance the local and global searches to find the global optimal result. Finite element method is adopted to simulate the free expansion of balloon-expandable stent and the expansion of stent in stenotic artery. The well-known Goodman diagram was used for the fatigue life prediction of stent, while dogboning effect was used for stent expansion performance measurement. As the real design cases, diamond-shaped stent and sv-shaped stent were studied to demonstrate how the proposed method can be harnessed to design and refine stent fatigue life and expansion performance computationally.

RESULTS

The fatigue life and expansion performance of both the diamond-shaped stent and sv-shaped stent are designed and refined, respectively. (a) diamond-shaped stent: The shortest distance from the data points to the failure line in the Goodman diagram was increased by 22.39%, which indicated a safer service performance of the optimal stent. The dogboning effect was almost completely eliminated, which implies more uniform expansion of stent along its length. Simultaneously, radial elastic recoil (RR) at the proximal and distal ends was reduced by 40.98 and 35% respectively and foreshortening (FS) was also decreased by 1.75%. (b) sv-shaped stent: The shortest distance from the data point to the failure line in the Goodman diagram was increased by 15.91%. The dogboning effect was also completely eliminated, RR at the proximal and distal ends was reduced by 82.70 and 97.13%, respectively, and the FS was decreased by 16.81%. Numerical results showed that the fatigue life of both stents was refined and the comprehensive expansion performance of them was improved.

CONCLUSIONS

This article presents an adaptive optimization method based on the Kriging surrogate model to optimize the structure of stents and the length of their dilatation balloon to prolong stents fatigue life and decreases the dogboning effect of stents during expansion process. Numerical results show that the adaptive optimization method based on Kriging surrogate model can effectively optimize the design of stents and the dilatation balloon. Further investigations containing more design goals and more effective multidisciplinary design optimization method are warranted.

摘要

背景

尽管支架在治疗心血管疾病方面取得了巨大成功,但实际上它受到支架内再狭窄及其长期疲劳失效的影响。支架的几何形状会影响其使用性能,并最终影响其疲劳寿命。此外,球囊长度不当会导致血管壁受到短暂的机械损伤和支架内再狭窄。传统的通过比较几种设计并选择最佳设计作为优化设计的支架及其扩张球囊的优化方法,无法在设计空间中找到全局最优设计。在本研究中,提出了一种基于克里金代理模型的自适应优化方法,以优化支架结构和支架扩张球囊的长度,从而延长支架使用寿命并提高支架性能。

方法

提出了一种结合克里金代理模型的基于有限元模拟的优化方法,逐步优化支架的几何形状和支架扩张球囊的长度。采用克里金代理模型与实验设计方法相结合,构建优化目标与设计变量之间的近似函数关系。使用改进的矩形网格在设计空间中选择初始训练样本。采用期望改进函数来平衡局部搜索和全局搜索,以找到全局最优结果。采用有限元方法模拟球囊扩张式支架的自由膨胀以及支架在狭窄动脉中的扩张。使用著名的古德曼图进行支架的疲劳寿命预测,而采用狗骨效应来测量支架的扩张性能。以菱形支架和sv形支架作为实际设计案例,研究如何利用所提出的方法通过计算来设计和优化支架的疲劳寿命和扩张性能。

结果

分别对菱形支架和sv形支架的疲劳寿命和扩张性能进行了设计和优化。(a)菱形支架:古德曼图中数据点到失效线的最短距离增加了22.39%,这表明优化后的支架具有更安全的使用性能。狗骨效应几乎完全消除,这意味着支架沿其长度方向的扩张更加均匀。同时,近端和远端的径向弹性回缩(RR)分别降低了40.98%和35%,缩短率(FS)也降低了1.75%。(b)sv形支架:古德曼图中数据点到失效线的最短距离增加了15.91%。狗骨效应也完全消除,近端和远端的RR分别降低了82.70%和97.13%,FS降低了16.81%。数值结果表明,两种支架的疲劳寿命都得到了优化,其综合扩张性能得到了提高。

结论

本文提出了一种基于克里金代理模型的自适应优化方法,以优化支架结构及其扩张球囊的长度,从而延长支架的疲劳寿命并减少支架在扩张过程中的狗骨效应。数值结果表明,基于克里金代理模型的自适应优化方法能够有效地优化支架和扩张球囊的设计。有必要进行包含更多设计目标和更有效的多学科设计优化方法的进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/08dc71430a07/12938_2016_307_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/87e07072f760/12938_2016_307_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/3feac9e8624e/12938_2016_307_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/08dc71430a07/12938_2016_307_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/87e07072f760/12938_2016_307_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/3feac9e8624e/12938_2016_307_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9f4b/5234108/08dc71430a07/12938_2016_307_Fig5_HTML.jpg

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