Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Clinical Trial
. 2012 Apr;40(4):860-70.
doi: 10.1007/s10439-011-0447-6. Epub 2011 Oct 21.

In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation

Affiliations
Clinical Trial

In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation

Amirhossein Arzani et al. Ann Biomed Eng. 2012 Apr.

Abstract

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.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
MRA data and derived geometric model used for CFD analysis: (a) maximum intensity projection and (b) 3D computer model.
FIGURE 2
FIGURE 2
Fluctuation intensity fields for each method (0.17 s after the start of systole). Note that the mesh type and resolution for the volume render of the temporal fluctuation intensity field were different than for the rest of the renders: (a) PCMRI, (b) spatiotemporal, (c) temporal, and (d) spatial.
FIGURE 3
FIGURE 3
Percentage of the descending aorta (boxed region) with fluctuation intensity above various thresholds values at time 0.17 s after the start of systole.
FIGURE 4
FIGURE 4
Integral of the fluctuation intensity field over the descending aorta vs. time.

Similar articles

Cited by

References

    1. Boussel L, Rayz V, Martin A, Acevedo-Bolton G, Lawton MT, Higashida R, Smith WS, Young WL, Saloner D. Phase-contrast magnetic resonance imaging measurements in intracranial aneurysms in vivo of flow patterns, velocity fields, and wall shear stress: comparison with computational fluid dynamics. Magn Reson Med. 2009;61(2):409–417. - PMC - PubMed
    1. Deissler RG. Turbulent Fluid Motion. Philadelphia: Taylor and Francis; 1998.
    1. Dyverfeldt P, Gardhagen R, Sigfridsson A, Karlsson M, Ebbers T. On MRI turbulence quantification. Magn Reson Med. 2009;27(7):913–922. - PubMed
    1. Dyverfeldt P, Kvitting JPE, Sigfridsson A, Engvall J, Bolger AF, Ebbers T. Assessment of fluctuating velocities in disturbed cardiovascular blood flow: in vivo feasibility of generalized phase-contrast MRI. J Magn Reson Imaging. 2008;28(3):655–663. - PubMed
    1. Dyverfeldt P, Sigfridsson A, Kvitting JPE, Ebbers T. Quantification of intravoxel velocity standard deviation and turbulence intensity by generalizing phase-contrast MRI. Magn Reson Med. 2006;56(4):850–858. - PubMed

Publication types

LinkOut - more resources