Annals of Biomedical Engineering

, Volume 40, Issue 4, pp 860–870 | Cite as

In Vivo Validation of Numerical Prediction for Turbulence Intensity in an Aortic Coarctation

  • Amirhossein Arzani
  • Petter Dyverfeldt
  • Tino Ebbers
  • Shawn C. ShaddenEmail author


This paper compares numerical predictions of turbulence intensity with in vivo measurement. Magnetic resonance imaging (MRI) was carried out on a 60-year-old female with a restenosed aortic coarctation. Time-resolved three-directional phase-contrast (PC) MRI data was acquired to enable turbulence intensity estimation. A contrast-enhanced MR angiography (MRA) and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics (CFD) modeling. A 3D model of the aortic coarctation and surrounding vasculature was constructed from the MRA data, and physiologic boundary conditions were modeled to match 2D PCMRI and pressure pulse measurements. Blood flow velocity data was subsequently obtained by numerical simulation. Turbulent kinetic energy (TKE) was computed from the resulting CFD data. Results indicate relative agreement (error ≈10%) between the in vivo measurements and the CFD predictions of TKE. The discrepancies in modeled vs. measured TKE values were within expectations due to modeling and measurement errors.


Computational fluid dynamics Phase-contrast magnetic resonance imaging Turbulent kinetic energy Blood flow 



The authors would like to gratefully acknowledge the support of the Fulbright Commission, the Swedish Heart-Lung Foundation, the Swedish Brain Foundation, the Swedish Research Council and the Center for Industrial Information Technology.


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Copyright information

© Biomedical Engineering Society 2011

Authors and Affiliations

  • Amirhossein Arzani
    • 1
  • Petter Dyverfeldt
    • 2
    • 3
    • 5
  • Tino Ebbers
    • 2
    • 3
    • 4
  • Shawn C. Shadden
    • 1
    Email author
  1. 1.Department of Mechanical, Materials and Aerospace EngineeringIllinois Institute of TechnologyChicagoUSA
  2. 2.Division of Applied Thermodynamics and Fluid Mechanics, Department of Management and EngineeringLinköping UniversityLinköpingSweden
  3. 3.Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
  4. 4.Division of Cardiovascular Medicine, Department of Medical and Health SciencesLinköping UniversityLinköpingSweden
  5. 5.Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoUSA

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