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Research ArticleInterventional

Optimizing the Quality of 4D-DSA Temporal Information

K.L. Ruedinger, E.C. Harvey, S. Schafer, M.A. Speidel and C.M. Strother
American Journal of Neuroradiology December 2019, 40 (12) 2124-2129; DOI: https://doi.org/10.3174/ajnr.A6290
K.L. Ruedinger
aFrom the Department of Biomedical Engineering (K.L.R.)
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E.C. Harvey
cDepartment of Medical Physics (E.H., M.A.S.)
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S. Schafer
eSiemens Healthineers Forchheim Germany (S.S.), Hoffman Estates, Illinois.
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M.A. Speidel
cDepartment of Medical Physics (E.H., M.A.S.)
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C.M. Strother
dDepartment of Radiology (C.M.S.), University of Wisconsin-Madison, Madison, Wisconsin
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Figures

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  • Fig 1.
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    Fig 1.

    Closed-loop flow system. Setup includes a pulsatile pump, flow transducer, power injector, patient-specific vascular model, flow-diverting loop to simulate systemic vasculature, a compliance chamber, and location of the x-ray detector.

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    Fig 2.

    TDCs from both trials of the 5 different injection rates, 1.5, 2.0, 2.5, 3.0, 3.5 mL/s. TDCs show differences in contrast intensity from varying injection rates. Variation at the 1.5-mL/s injection rate in model 2 stems from contrast layering.

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    Fig 3.

    SBR and amplitude of oscillation within the TDC for model 1. The median SBR at different injection rates is presented for the entire inlet section for the combination of trials (lower bar graph). A higher SBR corresponds to stronger contrast pulsatility, with an injection rate of 2.5 mL/s producing the highest SBR. The amplitude of oscillation is studied in 2 cubes that transect the vessel diameter at 2 locations within the inlet of model 1. The median of the oscillation amplitude and median absolute derivation within each cube of voxels are presented for each trial (upper bar graphs). AU indicates Arbitrary Units, and the error bars show SBR variance from the voxels within the 2 cubes.

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    Fig 4.

    SBR and amplitude of oscillation within the TDC for model 2. The median SBR at different injection rates is presented for the entire inlet section for the combination of trials (lower bar graph). A high SBR represents strong contrast pulsatility; 1.5 mL/s is abnormally high due to contrast layering causing an erroneous signal in the 4D-DSA reconstruction. The amplitude of oscillation is studied in 2 cubes that transect the vessel diameter at 2 locations within the inlet of model 2. The median of the oscillation amplitude and median absolute derivation within each cube of voxels are presented for each trial (upper bar graphs). AU indicates Arbitrary Units, and the error bars show SBR variance from the voxels within the 2 cubes.

  • Fig 5.
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    Fig 5.

    Left, effect of contrast layering on volumetric reconstruction. The absolute difference (millimeters) between the inlet diameter measurement using the workstation tool and the ground truth inlet diameter from micro-CT measurements is shown in the bar graphs (right). The greatest geometric difference in both models occurs with the 1.5-mL/s injection rate. Error bars represent variance in absolute differences based on multiple measurements.

Tables

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  • Hemodynamic parameters characterizing flow profiles achieved from various injection rates within the closed-loop flow setupa

    Injection RateQf (mL/min)Vf (cm/s)Vc (cm/s)RefRecCt
    1.5120.30101.60.69
    2160.40135.50.52
    2.525222.27200.50328.72169.30.41
    3240.60203.20.35
    3.5280.70237.00.30
    1.5120.30101.60.70
    2160.40135.50.52
    2.526022.43200.50335.05169.30.42
    3240.60203.20.35
    3.5280.70237.00.30
    • Note:—Significant figures varied depending on the hemodynamic parameter. Qf indicates flow rate of working fluid; Vf, velocity of working fluid; Vc, velocity contrast; Ref = Reynolds number of working fluid; Rec, Reynolds number of contrast.

    • ↵a Upper half refers to model 1, and bottom half refers to model 2.

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American Journal of Neuroradiology: 40 (12)
American Journal of Neuroradiology
Vol. 40, Issue 12
1 Dec 2019
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Cite this article
K.L. Ruedinger, E.C. Harvey, S. Schafer, M.A. Speidel, C.M. Strother
Optimizing the Quality of 4D-DSA Temporal Information
American Journal of Neuroradiology Dec 2019, 40 (12) 2124-2129; DOI: 10.3174/ajnr.A6290

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Optimizing the Quality of 4D-DSA Temporal Information
K.L. Ruedinger, E.C. Harvey, S. Schafer, M.A. Speidel, C.M. Strother
American Journal of Neuroradiology Dec 2019, 40 (12) 2124-2129; DOI: 10.3174/ajnr.A6290
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