Structure Design of Vascular Stents

Liu, Yaling; Yang, Jie; Zhou, Yi‐Hua; Hu, Jia

doi:10.1002/9781118402955.ch16

Cited by 14 publications

(12 citation statements)

References 22 publications

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“…The Palmaz-Schatz type of stent [26–29] with a length of 15 mm is implanted in the middle of channel, embedded into the channel wall tightly. The inner diameter of the stent is 3 mm, same as the channel diameter; the outer diameter of stent is 3.2 mm.…”

Section: Methodsmentioning

confidence: 99%

Computational modeling of magnetic nanoparticle targeting to stent surface under high gradient field

et al. 2014

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A multi-physics model was developed to study the delivery of magnetic nanoparticles (MNPs) to the stent-implanted region under an external magnetic field. The model is firstly validated by experimental work in literature. Then, effects of external magnetic field strength, magnetic particle size, and flow velocity on MNPs’ targeting and binding have been analyzed through a parametric study. Two new dimensionless numbers were introduced to characterize relative effects of Brownian motion (BM), magnetic force induced particle motion, and convective blood flow on MNPs motion. It was found that larger magnetic field strength, bigger MNP size, and slower flow velocity increase the capture efficiency of MNPs. The distribution of captured MNPs on the vessel along axial and azimuthal directions was also discussed. Results showed that the MNPs density decreased exponentially along axial direction after one-dose injection while it was uniform along azimuthal direction in the whole stented region (averaged over all sections). For the beginning section of the stented region, the density ratio distribution of captured MNPs along azimuthal direction is center-symmetrical, corresponding to the center-symmetrical distribution of magnetic force in that section. Two different generation mechanisms are revealed to form four main attraction regions. These results could serve as guidelines to design a better magnetic drug delivery system.

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Section: Methodsmentioning

confidence: 99%

Computational modeling of magnetic nanoparticle targeting to stent surface under high gradient field

et al. 2014

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“…Moreover, the loss function of Adaboost will be modified to consider the classification costs. Moreover, we will also investigate the application of the proposed algorithm to information security [41,43,53,42,41,52,18], bioinformatics [40,24,57], medial imaging [56,55,54], computer vision [38,23,22,36,37,19,17,46,44,45,15], reinforcement learning [27,28], cloud computing [50,51] and microprocessor reliability modeling [8,6,7,5,59,61,60].…”

Section: Discussionmentioning

confidence: 99%

Online classifier adaptation for cost-sensitive learning

Zhang

García

2015

Neural Comput & Applic

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In this paper, we propose the problem of online cost-sensitive classifier adaptation and the first algorithm to solve it. We assume we have a base classifier for a cost-sensitive classification problem, but it is trained with respect to a cost setting different to the desired one. Moreover, we also have some training data samples streaming to the algorithm one by one. The problem is to adapt the given base classifier to the desired cost setting using the steaming training samples online. To solve this problem, we propose to learn a new classifier by adding an adaptation function to the base classifier, and update the adaptation function parameter according to the streaming data samples. Given a input data sample and the cost of misclassifying it, we update the adaptation function parameter by minimizing cost weighted hinge loss and respecting previous learned parameter simultaneously. The proposed algorithm is compared to both online and off-line cost-sensitive algorithms on two cost-sensitive classification problems, and the experiments show that it not only outperforms them one classification performances, but also requires significantly less running time.

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“… Atherosclerosis of blood vessels and in-stents restenosis: ( a ) Atherosclerosis [ 1 ]; ( b ) ISR [ 7 ]. …”

Section: Figurementioning

confidence: 99%

“…In addition, there are other properties. In addition to these features mentioned, 13 different properties of ideal stent were listed in the review article of Liu et al [ 7 ], which provides a great help for the design of vascular stents. And Liu et al also pointed out that there were no perfect stents.…”

Section: Introductionmentioning

confidence: 99%

“…Although there have been some reviews about vascular stents [ 7 , 25 ], with the continuous development of stent design, it is very helpful to guide the structural design to supplement and improve review by updating the latest stent structure. This paper aims to summarize the types of vascular stent structure designed in recent decades, make a new classification of the existing stent structure, evaluate the influence of structure on mechanical properties, and predict the future direction of the design of vascular stent, and summarize the progress of the research on the design of vascular stent structure.…”

Section: Introductionmentioning

confidence: 99%

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Structural Design of Vascular Stents: A Review

Pan

Han

2021

Micromachines

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Percutaneous Coronary Intervention (PCI) is currently the most conventional and effective method for clinically treating cardiovascular diseases such as atherosclerosis. Stent implantation, as one of the ways of PCI in the treatment of coronary artery diseases, has become a hot spot in scientific research with more and more patients suffering from cardiovascular diseases. However, vascular stent implanted into vessels of patients often causes complications such as In-Stent Restenosis (ISR). The vascular stent is one of the sophisticated medical devices, a reasonable structure of stent can effectively reduce the complications. In this paper, we introduce the evolution, performance evaluation standards, delivery and deployment, and manufacturing methods of vascular stents. Based on a large number of literature pieces, this paper focuses on designing structures of vascular stents in terms of “bridge (or link)” type, representative volume unit (RVE)/representative unit cell (RUC), and patient-specific stent. Finally, this paper gives an outlook on the future development of designing vascular stents.

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Structure Design of Vascular Stents

Cited by 14 publications

References 22 publications

Computational modeling of magnetic nanoparticle targeting to stent surface under high gradient field

Computational modeling of magnetic nanoparticle targeting to stent surface under high gradient field

Online classifier adaptation for cost-sensitive learning

Structural Design of Vascular Stents: A Review

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