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Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models

Overview of attention for article published in BioMedical Engineering OnLine, April 2015
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Title
Aortic dissection simulation models for clinical support: fluid-structure interaction vs. rigid wall models
Published in
BioMedical Engineering OnLine, April 2015
DOI 10.1186/s12938-015-0032-6
Pubmed ID
Authors

Mona Alimohammadi, Joseph M Sherwood, Morad Karimpour, Obiekezie Agu, Stavroula Balabani, Vanessa Díaz-Zuccarini

Abstract

The management and prognosis of aortic dissection (AD) is often challenging and the use of personalised computational models is being explored as a tool to improve clinical outcome. Including vessel wall motion in such simulations can provide more realistic and potentially accurate results, but requires significant additional computational resources, as well as expertise. With clinical translation as the final aim, trade-offs between complexity, speed and accuracy are inevitable. The present study explores whether modelling wall motion is worth the additional expense in the case of AD, by carrying out fluid-structure interaction (FSI) simulations based on a sample patient case. Patient-specific anatomical details were extracted from computed tomography images to provide the fluid domain, from which the vessel wall was extrapolated. Two-way fluid-structure interaction simulations were performed, with coupled Windkessel boundary conditions and hyperelastic wall properties. The blood was modelled using the Carreau-Yasuda viscosity model and turbulence was accounted for via a shear stress transport model. A simulation without wall motion (rigid wall) was carried out for comparison purposes. The displacement of the vessel wall was comparable to reports from imaging studies in terms of intimal flap motion and contraction of the true lumen. Analysis of the haemodynamics around the proximal and distal false lumen in the FSI model showed complex flow structures caused by the expansion and contraction of the vessel wall. These flow patterns led to significantly different predictions of wall shear stress, particularly its oscillatory component, which were not captured by the rigid wall model. Through comparison with imaging data, the results of the present study indicate that the fluid-structure interaction methodology employed herein is appropriate for simulations of aortic dissection. Regions of high wall shear stress were not significantly altered by the wall motion, however, certain collocated regions of low and oscillatory wall shear stress which may be critical for disease progression were only identified in the FSI simulation. We conclude that, if patient-tailored simulations of aortic dissection are to be used as an interventional planning tool, then the additional complexity, expertise and computational expense required to model wall motion is indeed justified.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
United States 1 <1%
Unknown 176 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 23%
Researcher 28 16%
Student > Master 23 13%
Student > Doctoral Student 15 8%
Student > Bachelor 12 7%
Other 29 16%
Unknown 30 17%
Readers by discipline Count As %
Engineering 75 42%
Medicine and Dentistry 24 13%
Psychology 6 3%
Biochemistry, Genetics and Molecular Biology 5 3%
Computer Science 5 3%
Other 23 13%
Unknown 40 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 June 2015.
All research outputs
#18,412,793
of 22,808,725 outputs
Outputs from BioMedical Engineering OnLine
#565
of 824 outputs
Outputs of similar age
#192,714
of 263,964 outputs
Outputs of similar age from BioMedical Engineering OnLine
#16
of 21 outputs
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