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Research ArticleHead and Neck Imaging

Differentiation of Jugular Foramen Paragangliomas versus Schwannomas Using Golden-Angle Radial Sparse Parallel Dynamic Contrast-Enhanced MRI

A. Pires, G. Nayak, E. Zan, M. Hagiwara, O. Gonen and G. Fatterpekar
American Journal of Neuroradiology October 2021, 42 (10) 1847-1852; DOI: https://doi.org/10.3174/ajnr.A7243
A. Pires
aFrom the New York University School of Medicine, New York, New York
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G. Nayak
aFrom the New York University School of Medicine, New York, New York
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E. Zan
aFrom the New York University School of Medicine, New York, New York
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M. Hagiwara
aFrom the New York University School of Medicine, New York, New York
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O. Gonen
aFrom the New York University School of Medicine, New York, New York
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G. Fatterpekar
aFrom the New York University School of Medicine, New York, New York
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  • FIG 1.
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    FIG 1.

    Example of a paraganglioma in the right jugular foramen on postcontrast imaging (A) with an associated time-intensity curve (B) demonstrating a type 3 TIC (blue) with wash-in and washout characteristics similar to those in the blood pool control obtained from the sigmoid sinus (red).

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    FIG 2.

    An example of a schwannoma in the right jugular foramen extending inferiorly into the carotid space on postcontrast imaging with an associated time-intensity curve demonstrating a type 1 TIC (blue) with gradual wash-in and a continuous gradual washout of contrast. The curve obtained from the blood pool within the sigmoid sinus (red) shows the expected rapid wash-in and washout of contrast, suggesting a good bolus of administered contrast.

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    FIG 3.

    A, The predictor space model clearly shows differential group clustering for schwannomas and paragangliomas based on the wash-in and washout measures. B, The predictor space model clearly shows differential group clustering for schwannomas and paragangliomas based on the wash-in and washout measures. P indicates paraganglioma; S, schwannoma.

Tables

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    Table 1:

    Quantitative summary statistics for paragangliomas and schwannomasa

    ParagangliomasSchwannomas
    Age (yr)52.0 (SD, 14.8)43.7 (SD, 16.9)
    Sex (% female)77.2%33.3%
    AUC0.86 (SD, 0.19)0.45 (SD, 0.15)
    Peak intensity0.86 (SD, 0.21)0.43 (SD, 0.13)
    TME1.04 (SD, 0.24)3.13 (SD, 0.64)
    Wash-in1.00 (SD, 0.12)0.25 (SD, 0.13)
    Washout1.00 (SD, 0.14)0.12 (SD, 0.18)
    Ve0.06 (SD, 0.17)0.53 (SD, 0.25)
    SER148.1 (SD, 23.1)61.5 (SD, 19.6)
    Kep0.46 (SD, 0.78)0.55 (SD, 0.32)
    Vp0.47 (SD, 0.19)0.087 (SD, 0.81)
    Ktrans0.08 (SD, 0.22)0.29 (SD, 0.28)
    • ↵a Data are means unless otherwise indicated.

    • View popup
    Table 2:

    Semiquantitative perfusion metrics of jugular foramen tumors normalized to the sigmoid sinusa

    AUCPeakTMEWash-inWashout
    Paraganglioma0.86 (SD, 0.19)0.86 (SD, 0.21)1.04 (SD, 0.24)1.00 (SD, 0.12)1.00 (SD, 0.14)
    Schwannoma0.45 (SD, 0.15)0.43 (SD, 0.13)3.13 (SD, 0.64)0.25 (SD, 0.13)0.12 (SD, 0.18)
    P value<.001<.001<.001<.001<.001
    • ↵a There is a statistically significant difference between paragangliomas and schwannomas when comparing their values for AUC, peak enhancement, wash-in, and washout. Of note, most paragangliomas had wash-in and washout values of ≥1.0, which means that these lesions demonstrated permeability characteristics similar to those of the blood pool because all values were normalized to the sigmoid sinus. Data are means unless otherwise indicated. (Tables 2 and 3 separated for formatting purposes).

    • View popup
    Table 3:

    Kinetic permeability metrics of jugular foramen tumorsa

    VeSERKepVpKtrans
    Paraganglioma0.06 (SD, 0.17)148.1 (SD, 23.1)0.46 (SD, 0.78)0.47 (SD, 0.19)0.08 (SD, 0.22)
    Schwannoma0.53 (SD, 0.25)61.5 (SD, 19.6)0.55 (SD, 0.32)0.087 (SD, 0.81)0.29 (SD, 0.28)
    P value<.001<.001.77<.001.10
    • ↵a There is a statistically significant difference between paragangliomas and schwannomas when comparing their values for VE, SER, and VP. Data are means unless otherwise indicated.

    • View popup
    Table 4:

    Subgroup comparison of paragangliomas with prior radiation treatment (n = 9) and with no radiation treatment (n = 13) using normalized semiquantitative perfusion metricsa

    AUCPeakTMEWash-inWashout
    Para-RT0.80 (SD, 0.15)0.84 (SD, 0.19)1.04 (SD, 0.33)0.96 (SD, 0.12)1.00 (SD, 0.16)
    Para-NT0.90 (SD, 0.2)0.87 (SD, 0.22)1.04 (SD, 0.17)1.03 (SD, 0.12)1.01 (SD, 0.14)
    P value.22.68.97.20.86
    • Note:—NT indicates no radiation treatment; RT, radiation treatment, Para, paraganglioma.

    • ↵a There was no statistical difference between these subcategories of paragangliomas in terms of semiquantitative perfusion parameters. Data are means unless otherwise indicated.

    • View popup
    Table 5:

    Subgroup comparison of paragangliomas with prior radiation treatment (n = 9) and with no radiation treatment (n = 13) using kinetic permeability metricsa

    VeSERKepVpKtrans
    Para-RT0.03 (SD, 0.07)143.2 (SD, 14.4)0.68 (SD, 1.03)0.54 (SD, 0.19)0.079 (SD, 0.14)
    Para-NT0.08 (SD, 0.21)151.4 (SD, 27.7)0.31 (SD, 0.54)0.43 (SD, 0.18)0.09 (SD, 0.27)
    P value.43.38.34.21.78
    • ↵a There was no statistical difference between these subcategories of paragangliomas in terms of kinetic permeability parameters. Data are means unless otherwise indicated.

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American Journal of Neuroradiology: 42 (10)
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A. Pires, G. Nayak, E. Zan, M. Hagiwara, O. Gonen, G. Fatterpekar
Differentiation of Jugular Foramen Paragangliomas versus Schwannomas Using Golden-Angle Radial Sparse Parallel Dynamic Contrast-Enhanced MRI
American Journal of Neuroradiology Oct 2021, 42 (10) 1847-1852; DOI: 10.3174/ajnr.A7243

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Differentiation of Jugular Foramen Paragangliomas versus Schwannomas Using Golden-Angle Radial Sparse Parallel Dynamic Contrast-Enhanced MRI
A. Pires, G. Nayak, E. Zan, M. Hagiwara, O. Gonen, G. Fatterpekar
American Journal of Neuroradiology Oct 2021, 42 (10) 1847-1852; DOI: 10.3174/ajnr.A7243
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