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      Geometric Determinants of Local Hemodynamics in Severe Carotid Artery Stenosis

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          Abstract

          In cases of severe carotid artery stenosis (CAS), carotid endarterectomy (CAE) is performed to recover lumen patency and alleviate stroke risk. Under current guidelines, the decision to surgically intervene relies primarily on the percent loss of native arterial lumen diameter within the stenotic region (i.e. the degree of stenosis). An underlying premise is that the degree of stenosis modulates flow-induced wall shear stress elevations at the lesion site, and thus indicates plaque rupture potential and stroke risk. Here, we conduct a retrospective study on pre-CAE computed tomography angiography (CTA) images from 50 patients with severe internal CAS (>60% stenosis) to better understand the influence of plaque and local vessel geometry on local hemodynamics, with geometrical descriptors that extend beyond the degree of stenosis. We first processed CTA images to define a set of multipoint geometric metrics characterizing the stenosed region, and next performed computational fluid dynamics simulations to quantify local wall shear stress and associated hemodynamic metrics. Correlation and regression analyses were used to relate obtained geometric and hemodynamic metrics, with inclusion of patient sub-classification based on the degree of stenosis. Our results suggest that in the context of severe CAS, prediction of shear stress-based metrics can be enhanced by consideration of readily available, multipoint geometric metrics in addition to the degree of stenosis.

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          Author and article information

          Journal
          1250250
          3132
          Comput Biol Med
          Comput. Biol. Med.
          Computers in biology and medicine
          0010-4825
          1879-0534
          17 September 2019
          05 September 2019
          November 2019
          01 November 2020
          : 114
          : 103436
          Affiliations
          [1 ]Biomedical Engineering Program, College of Engineering and Computing, University of South Carolina, Columbia, South Carolina, USA
          [2 ]Exponent, Inc., Philadelphia, Pennsylvania, USA
          [3 ]Department of Cell Biology and Anatomy, University of South Carolina School of Medicine, Columbia, South Carolina, USA
          [4 ]Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
          [5 ]Department of Mechanical Engineering, College of Engineering and Computing, University of South Carolina, Columbia, SC, USA
          Author notes
          [§ ]Corresponding author: Tarek Shazly, PhD, Associate Professor of Biomedical Engineering, shazly@ 123456cec.sc.edu , Phone: 803-777-4678
          [*]

          Indicates equal contribution

          Article
          PMC6817414 PMC6817414 6817414 nihpa1539671
          10.1016/j.compbiomed.2019.103436
          6817414
          31521900
          efd10b83-f3bc-460e-83b4-23f48bdbce2a
          History
          Categories
          Article

          Carotid endarterectomy,Prediction models,Plaque geometry,Computational fluid dynamics,Carotid stenosis

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