Computational Flow Dynamics in Abdominal Aortic Aneurysm Using Multislice Computed Tomography

Yamamoto, Saburo; Maruyama, Shigeru; Nakahara, Yü̅suke; Yoneyama, Shigeru; Tanifuji, Shin‐ichiro; Wada, Shigeo; Hamada, Seiki; Komizu, Mitsuru; Johkoh, Takeshi; Doi, Masao; Yamaguchi, Takami

doi:10.6009/jjrt.62.115

Cited by 10 publications

(4 citation statements)

References 9 publications

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“…Besides biomimetic spinning, finite element method (FEM) calculation has also been applied to flow analyses in the fields of biology and medicine because the intricacy of the system can be captured by the model. [44][45][46] For instance, Breslauer et al performed FEM analysis of the non-Newtonian flow of proteins in the silk gland to understand the role of fluidic forces on silk. [13] Kojic et al elucidated the underlying mechanisms governing formation and growth of e-gel by FEM.…”

Section: Introductionmentioning

confidence: 99%

Flow Analysis of Regenerated Silk Fibroin/Cellulose Nanofiber Suspensions via a Bioinspired Microfluidic Chip

Lü

Fan

Geng

et al. 2021

Adv Materials Technologies

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The outstanding performance of silk, especially in terms of mechanical properties, can be attributed to the sophisticated silk gland and specialized spinning method that exists in nature. In addition, the gland, with decreasing diameter, has been proven to be an outstanding actuator of the sophisticated spinning system. [5,9] It has been qualitatively demonstrated that a region of contracting geometry of the S-shaped duct of silk gland can induce stretching of protein molecules, phase separation, and self-assembly due to shear and elongation flow. [10][11][12][13][14][15] During the subsequent spinning process in air, the protein ultimately aggregates into fibers with spectacular and distinctive properties. However, the mechanisms within the glands with exponential decaying diameter and their ability to dynamically change the conformation of the proteins is yet to be elucidated. [6] At present, various biomimetic spinning methods have been used to fabricate high-performance artificial silk and reveal the relationship between the spinning channel and silk performance. For example, the microfluidic device with miniaturized channels of designed configurations can easily control the physicochemical microenvironment, while using trace amounts of reagents. [6,10,[16][17][18][19][20] The sophisticated, compact, and highly functional microfluidic devices have been widely used to understand the geometry confinements, control overflow, and synthesis of artificially regenerated silk fibroin (RSF) fibers. [21][22][23][24][25][26][27][28][29][30] For example, Rammensee et al. prepared assembled spider dragline silk fibers through a microfluidic device. [31] Kinahan et al. adopted the same method to fabricate functional fibers with expected properties by controlling flow conditions. [32] Based on these studies, Zhang's group designed microfluidic chips mimicking the first-order and second-order exponential decay function of silk glands and prepared high-performance artificial silk fibers. [24][25][26]33,34] In our previous work, [35,36] statistics of spider's major ampullate (MA) gland of Nephila edulis were extracted from the work of Knight et al., [12] and then a microfluidic chip was prepared which fitted well to the second-order exponential decay function. The bioinspired chip possessed excellent similarity with the MA gland of spider, and was used to prepare RSF/cellulose nanofibers (CNF) hybrid fibers. However, there were some differences between the size of our microfluidic chip and the ampullate gland of spider. First, the actual diameter of lumen in the MA gland of N. edulis is from ≈250 to 8 µm. [12] However, high concentration of RSF/CNF suspensions (30 wt%) cannot flow through Microfluidic spinning has been used to mimic and discover the natural spinning process of silk. However, it is still challenging to understand the orientation and alignment of silk-spinning through microfluidic chips. Here, flow analysis is performed for a bioinspired microfluidic chip mimicking the shape of a spider's major ampullate gland a...

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Section: Introductionmentioning

confidence: 99%

Flow Analysis of Regenerated Silk Fibroin/Cellulose Nanofiber Suspensions via a Bioinspired Microfluidic Chip

Lü

Fan

Geng

et al. 2021

Adv Materials Technologies

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“…The authors as well as other researchers are currently employing three-dimensional CFD analysis 20 21 22 23 24 25 32. An additional limitation of the model is that the artery is represented a rigid tube.…”

Section: Discussionmentioning

confidence: 99%

“…Current approaches include the use of computational fluid dynamics (CFD) and biomorphometric techniques which combine three-dimensional x ray angiography and CFD 19 20 21 22 23 24 25…”

mentioning

confidence: 99%

Computational fluid dynamic simulation to assess flow characteristics of an in vitro aneurysm model

Lott¹,

Siegel²,

Chaudhry³

et al. 2009

J NeuroIntervent Surg

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Computer generated aneurysm flow models, when carefully developed, reproduce flow events within in vitro aneurysms providing objective data on biophysical parameters. Effective flow modeling of aneurysms depends on flow input, size of the parent vessel and aneurysm, and other factors. These data suggest that neck and proximal dome configuration, independent of size, are important characteristics of flow.

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“…Recent developments in imaging technologies and computer power have enabled image-based CFD in which the anatomically realistic geometry of a blood vessel is defined from medical images. The imaging modalities that have been used to provide geometric information for CFD are Doppler ultrasound (52)- (54) , digital subtraction angiography (55)- (57) , computed tomography (58), (59) , and magnetic resonance imaging (MRI) (60)- (64) . Among these, recent studies have tended to use MRI because it has the advantage of providing not only blood vessel geometry but also time-resolved velocity images that can be used as boundary conditions and to validate simulated results.…”

Section: Computational Analysis Of the Intracardiac And Aortic Flowsmentioning

confidence: 99%

Computational Blood Flow Analysis -New Trends and Methods

Yamaguchi

Ishikawa

Tsubota

et al. 2006

JBSE

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Over the past few decades, a large number of novel numerical methods have been proposed to analyze blood flows and to understand the relationship between vascular diseases and hemodynamics. In this paper, we review recent computational fluid dynamics studies on macroscale hemodynamics such as blood flow in the heart and large arteries, microscale blood flows in small vessels in which blood is assumed to be a suspension of red blood cells in plasma, and single red blood cell motions in an induced flow field. The advantages and disadvantages of numerical methods are discussed, and current trends in these research fields are introduced.

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Computational Flow Dynamics in Abdominal Aortic Aneurysm Using Multislice Computed Tomography

Cited by 10 publications

References 9 publications

Flow Analysis of Regenerated Silk Fibroin/Cellulose Nanofiber Suspensions via a Bioinspired Microfluidic Chip

Flow Analysis of Regenerated Silk Fibroin/Cellulose Nanofiber Suspensions via a Bioinspired Microfluidic Chip

Computational fluid dynamic simulation to assess flow characteristics of an in vitro aneurysm model

Computational Blood Flow Analysis -New Trends and Methods

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