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Computational fluid dynamic simulation of human carotid artery bifurcation based on anatomy and volumetric blood flow rate measured with magnetic resonance imaging

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Abstract

Blood flow patterns and local hemodynamic parameters have been widely associated with the onset and progression of atherosclerosis in the carotid artery. Assessment of these parameters can be performed noninvasively using cine phase-contrast (PC) magnetic resonance imaging (MRI). In addition, in the last two decades, computational fluid dynamics (CFD) simulation in three dimensional models derived from anatomic medical images has been employed to investigate the blood flow in the carotid artery. This study developed a workflow of a subject-specific CFD analysis using MRI to enhance estimating hemodynamics of the carotid artery. Time-of-flight MRI scans were used to construct three-dimensional computational models. PC-MRI measurements were utilized to impose the boundary condition at the inlet and a 0-dimensional lumped parameter model was employed for the outflow boundary condition. The choice of different viscosity models of blood flow as a source of uncertainty was studied, by means of the axial velocity, wall shear stress, and oscillatory shear index. The sequence of workflow in CFD analysis was optimized for a healthy subject using PC-MRI. Then, a patient with carotid artery stenosis and its hemodynamic parameters were examined. The simulations indicated that the lumped parameter model used at the outlet gives physiologically reasonable values of hemodynamic parameters. Moreover, the dependence of hemodynamics parameters on the viscosity models was observed to vary for different geometries. Other factors, however, may be required for a more accurate CFD analysis, such as the segmentation and smoothness of the geometrical model, mechanical properties of the artery’s wall, and the prescribed velocity profile at the inlet.

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Acknowledgments

Authors gratefully acknowledge the support, in part, by the National Heart, Lung, and Blood Institute of the National Institutes of Health (R21HL113857) and National Science Foundation (CMMI-1150376). The contents of solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Authors would also like to gratefully acknowledge Simmetrix, Inc. (http://www.simmetrix.com) for offering software licensing of the MeshSim mesh generation library, and Dr. Nathan Wilson for offering SimVascular software package and his assistance.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Michigan State University, East Lansing, MI, USA

    Hamidreza Gharahi, Byron A. Zambrano & Seungik Baek

  2. Department of Radiology, Michigan State University, East Lansing, MI, USA

    David C. Zhu & J. Kevin DeMarco

  3. Department of Psychology, Michigan State University, East Lansing, MI, USA

    David C. Zhu

  4. Cognitive Imaging Research Center, Michigan State University, East Lansing, MI, USA

    David C. Zhu

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  1. Hamidreza Gharahi
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Gharahi, H., Zambrano, B.A., Zhu, D.C. et al. Computational fluid dynamic simulation of human carotid artery bifurcation based on anatomy and volumetric blood flow rate measured with magnetic resonance imaging. Int J Adv Eng Sci Appl Math 8, 46–60 (2016). https://doi.org/10.1007/s12572-016-0161-6

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