Design Optimisation of Coronary Artery Stent Systems

Bressloff, Neil W.; Ragkousis, Giorgos; Curzen, Nick

doi:10.1007/s10439-015-1373-9

Cited by 39 publications

(19 citation statements)

References 46 publications

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“…Additionally, this technique could facilitate the large-scale production of nanostructures due to its room temperature operating environment. As a result, this technique could be generalized to develop industrial scale coating facilities, which could be used in Lithium-ion battery production as well as other industries, such as: biomedical applications [96][97][98][99][100], oil and gas extraction plants [101][102][103][104], and nanoparticles technologies [105]. Finally, these Sn nanowires' production technique should be optimized by using the proposed electrochemical synthesizing procedure, and be examined in assembled Lithium-ion batteries to accurately measure their capacity as well as efficiency in order to achieve higher cyclability.…”

Section: Discussionmentioning

confidence: 99%

Fabrication of Highly Ordered Sn Nanowires in Anodic Aluminum Oxide Templates by Using AC Electrochemical Method

Sm¹,

Saba²

2018

Preprint

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Sn and its nanostructures are one of the promising candidates to replace graphite in the anode of Lithium-ion batteries due to their higher capacity. One of the challenges, which limited the usage of Sn anodes for the Lithium-ion batteries, is Tin's high volumetric strain and its low cyclability. On the other hand, nanostructures show lower volume change during charge/discharge and as a result could address the cyclability issues. In this research, an alternating current (AC) electrochemical method is developed in order to facilitate the industrial scale production of Sn nanowires. The developed electrodeposition technique shows reliable controllability over chemical composition and crystalline structure of Sn nanowires. Also, the order structure of nanowires could be adjusted more accurately in comparison to conventional fabrication techniques. As a result, the Sn nanowires as well as Aluminum Oxide templates synthesized by using the developed electrochemical method are examined due to their morphology, chemical composition, and their crystalline structure in order to develop a practical relation between electrochemical composition of the solution and materials properties of Sn nanowires. The results show that the proposed electrodeposition method maintains a highly-ordered morphology as well as industrially acceptable controllability over crystalline structure of nanowires, which could be used to optimize the procedure for industrial applications due to low cost and simple experimental setup.

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Section: Discussionmentioning

confidence: 99%

Fabrication of Highly Ordered Sn Nanowires in Anodic Aluminum Oxide Templates by Using AC Electrochemical Method

Sm¹,

Saba²

2018

Preprint

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“…The number of levels in the jth dimension is q j . Then the approach is performed as follows:Narrow the range of variables as Perform rectangular grid (RG) sampling [25] in the narrowed space as Add a stochastic movement of each sample point in each dimension as …”

Section: Methodsmentioning

confidence: 99%

Multi-objective optimization of coronary stent using Kriging surrogate model

Wang

et al. 2016

BioMed Eng OnLine

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BackgroundIn 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.MethodsMulti-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.Results27 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%.ConclusionThis 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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“…Through fluid simulations, many perturbations of device designs or treatment options can be simulated in silico before either high cost surgery or further in vitro experiments. CFD simulations have been used to evaluate the design of Y-grafts for Fontan operations [83–85], anastomosis design [86], stents [87, 88], and flow-diverters [89, 90]. To enable predictive treatment planning, the mesh representing the vascular geometry is modified to represent different potential surgical outcomes.…”

Section: Treatment Planning and Device Designmentioning

confidence: 99%

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease

Randles

Leopold

2017

Trends in Biotechnology

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Non-invasive engineering models are now being used for diagnosing and planning the treatment of cardiovascular disease. Techniques in computational modeling and additive manufacturing have matured concurrently, and results from simulations can inform and enable the design and optimization of therapeutic devices and treatment strategies. The emerging synergy between large-scale simulations and 3D printing is having a two-fold benefit: first, 3D printing can be used to validate the complex simulations, and second, the flow models can be used to improve treatment planning for cardiovascular disease. In this review, we summarize and discuss recent methods and findings for leveraging advances in both additive manufacturing and patient-specific computational modeling, with an emphasis on new directions in these fields and remaining open questions.

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Design Optimisation of Coronary Artery Stent Systems

Cited by 39 publications

References 46 publications

Fabrication of Highly Ordered Sn Nanowires in Anodic Aluminum Oxide Templates by Using AC Electrochemical Method

Fabrication of Highly Ordered Sn Nanowires in Anodic Aluminum Oxide Templates by Using AC Electrochemical Method

Multi-objective optimization of coronary stent using Kriging surrogate model

Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease

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