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Research ArticleNeurointervention

Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics

J.R. Cebral, F. Mut, B.J. Chung, L. Spelle, J. Moret, F. van Nijnatten and D. Ruijters
American Journal of Neuroradiology June 2017, 38 (6) 1180-1186; DOI: https://doi.org/10.3174/ajnr.A5158
J.R. Cebral
aFrom the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia
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F. Mut
aFrom the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia
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B.J. Chung
aFrom the Bioengineering Department (J.R.C., F.M., B.J.C.), Volgenau School of Engineering, George Mason University, Fairfax, Virginia
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L. Spelle
bFaculté de Médecine Paris-Sud (L.S.), Le Kremlin-Bicetre, France
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J. Moret
cInterventional Neuroradiology (J.M.), Beaujon University Hospital, Clichy, France
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F. van Nijnatten
dImage Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.
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D. Ruijters
dImage Guided Therapy Innovation (F.v.N., D.R.), Philips Healthcare, Best, the Netherlands.
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  • Fig 1.
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    Fig 1.

    A, Linear correlation between the MAFA and VEL. Red dots represent cases discarded from the regression analysis due to substantial overlap between the aneurysm and surrounding vessels in the selected DSA view. B, Ratio of MAFA/VEL as a function of the number of frames needed for a particle to traverse the aneurysm diameter (mean aneurysm transit time).

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    Fig 2.

    Examples of 4 aneurysms (rows) with vortex structures with varying alignment with the line of sight of DSA sequences. From left to right, columns show the following: reconstructed CFD model, visualization of 3D flow field by using streamlines, 2D DSA flow field, and 2D projected MEAN CFD flow field. Dotted red lines indicate the location of the vortex in the 3D flow. Yellow arrows indicate flow artifacts (divergence of particle paths) in the DSA flow reconstruction aligned with the vortex centers.

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    Fig 3.

    Top row: an example of when the DSA flow visualization does not depict the intrasaccular flow split. Center and bottom rows: an example of when the DSA flow visualizations from 2 roughly normal projections depict the intrasaccular flow split and allow understanding of the 3D flow structure. From left to right, columns show the reconstructed CFD model, visualization of 3D flow field by using streamlines, 2D DSA flow field, and the 2D projected MEAN CFD flow field. Yellow arrows point to the region of flow split. Red dotted line indicates center of rotation, and red arrows, the “convergent vectors” effect.

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    Fig 4.

    Examples of the effects of vessel overlaps on 4 aneurysms (rows). From left to right, columns show the following: the reconstructed CFD model, visualization of the 3D flow field by using streamlines, 2D DSA flow field, 2D projected MEAN CFD flow field, and 2D projected MIP CFD flow field. Red arrows show false vortex structures in projected CFD fields, while yellow arrows indicate false aneurysm inflow regions.

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    Fig 5.

    Examples of undersampling DSA flow fields in 2 aneurysms (rows). From left to right, columns show the following: the reconstructed CFD model, visualization of the 3D flow field by using streamlines, 2D DSA flow field, and 2D projected MEAN CFD flow field. Arrows point to the regions where fluid particles are observed to move across streamlines.

Tables

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  • Similarity of DSA and MEAN CFD projected flow fields in the region of the vessel, aneurysm, and both regions combined

    PatientViewVesselAneurysmCombined
    1180.3%66.0%76.2%
    2193.9%52.7%76.7%
    3180.5%46.4%76.3%
    291.3%39.4%86.0%
    4159.6%55.9%57.9%
    273.4%50.2%67.9%
    5191.4%−23.0%48.0%
    281.9%−64.6%20.3%
    6171.4%66.8%70.7%
    271.3%41.8%66.8%
    7157.6%−1.0%46.8%
    274.3%9.8%64.7%
    8178.9%12.5%71.2%
    277.3%−2.0%66.9%
    9180.0%32.8%69.5%
    285.2%65.0%79.6%
    10166.8%67.9%67.3%
    283.0%84.9%83.7%
    11188.5%25.7%73.3%
    281.5%11.5%68.7%
    12171.4%46.1%66.4%
    282.9%44.2%76.8%
    13177.5%63.1%72.6%
    293.6%9.8%72.5%
    14174.2%15.3%62.8%
    258.3%25.5%52.1%
    15173.2%−0.6%43.2%
    280.5%26.8%56.2%
    Mean78.4% ± 10.1%30.4% ± 32.0%66.0% ± 13.7%
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American Journal of Neuroradiology: 38 (6)
American Journal of Neuroradiology
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Cite this article
J.R. Cebral, F. Mut, B.J. Chung, L. Spelle, J. Moret, F. van Nijnatten, D. Ruijters
Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics
American Journal of Neuroradiology Jun 2017, 38 (6) 1180-1186; DOI: 10.3174/ajnr.A5158

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Understanding Angiography-Based Aneurysm Flow Fields through Comparison with Computational Fluid Dynamics
J.R. Cebral, F. Mut, B.J. Chung, L. Spelle, J. Moret, F. van Nijnatten, D. Ruijters
American Journal of Neuroradiology Jun 2017, 38 (6) 1180-1186; DOI: 10.3174/ajnr.A5158
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