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Research ArticleOncology

Metabolic Subtyping of Pheochromocytoma and Paraganglioma by 18F-FDG Pharmacokinetics Using Dynamic PET/CT Scanning

Anouk van Berkel, Dennis Vriens, Eric P. Visser, Marcel J.R. Janssen, Martin Gotthardt, Ad R.M.M. Hermus, Lioe-Fee de Geus-Oei and Henri J.L.M. Timmers
Journal of Nuclear Medicine June 2019, 60 (6) 745-751; DOI: https://doi.org/10.2967/jnumed.118.216796
Anouk van Berkel
1Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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Dennis Vriens
2Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Eric P. Visser
3Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; and
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Marcel J.R. Janssen
3Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; and
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Martin Gotthardt
3Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; and
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Ad R.M.M. Hermus
1Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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Lioe-Fee de Geus-Oei
2Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
4MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
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Henri J.L.M. Timmers
1Division of Endocrinology, Department of Internal Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
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  • FIGURE 1.
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    FIGURE 1.

    Irreversible 2-tissue-compartment model for 18F-FDG metabolism. Measured PET signal is combination of intracellular activity concentration of free 18F-FDG (nonmetabolized 18F-FDG in tissue), intracellular activity concentration of 18F-FDG-6-phosphate (metabolized 18F-FDG-6-PO4 in tissue), and fraction of activity concentration of 18F-FDG in blood plasma (Vb). By using dynamic PET/CT, pharmacokinetic rate-constants K1 and k2 (rate constants of transport of 18F-FDG into and out of tumor cell by glucose transporters, in mL/g/min), k3 (rate constant of cytoplasmic phosphorylation of 18F-FDG by hexokinase, per minute), and Vb (in milliliters of blood per milliliter of tumor) can be determined using nonlinear least-squares regression of dynamic PET/CT data. Vertical dashed line represents cell membrane

  • FIGURE 2.
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    FIGURE 2.

    Dynamic 18F-FDG PET/CT results in patient 24, with primary sporadic PPGL in left adrenal. (A) Parametric image of MRglc from dynamic 18F-FDG PET scan. (B) Static 18F-FDG PET/CT scan. (C) CT scan. (D) Image-derived input function and tumor time–activity curve. (E) Patlak plot. Slope of Patlak plot equals influx constant Ki

  • FIGURE 3.
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    FIGURE 3.

    Scatterplots showing MRglc (A) and 18F-FDG SUVmax (B) in PPGLs across different genotypes. Horizontal bar represents median and interquartile range. Diamonds represent 3 different tumor locations in same patient (patient 7, Table 1). All SUVs are normalized for body weight and decay. P values are from Kruskal–Wallis with Dunn post hoc testing, and groups are compared as indicated. ns = not significant.

  • FIGURE 4.
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    FIGURE 4.

    Pharmacokinetic rate-constants (K1, k2, and k3) and blood volume fraction (Vb) in PPGLs across different genotypes. Horizontal bar represents median and interquartile range (IQR). Diamonds represent 3 different tumor locations in same patient (patient 7). P values are from Kruskal–Wallis with Dunn post hoc testing, and groups are compared as indicated. ns = not significant.

  • FIGURE 5.
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    FIGURE 5.

    Receiver-operating-characteristic curve for pharmacokinetic rate-constant k3 (A) and SUVmax (B). This curve was constructed from k3 and SUVmax of cluster 1 tumors vs. other (cluster 2 and sporadic) tumors in patients with PPGL. Diagonal line represents line of no discrimination.

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    TABLE 1

    Patient Characteristics

    Patient no.SexGenotypeAge (y)Tumor locationStatusMaximum tumor diameter (cm)Biochemical phenotype
    1MNF166LAPrimary1.2E + NE
    2FNF131LAPrimary4.0E + NE
    3FRET62LAPrimary3.4E + NE
    4FRET20RAPrimary3.5E + NE
    5MRET35RAPrimary2.1E + NE
    6MRET70LAPrimary3.0E
    7FSDHA63LAPrimaryNANE + DA
    EA (thoracic spine)MetastaticNANE + DA
    EA (paraaortic lymph node)MetastaticNANE + DA
    8MSDHA35EA (retroaortic lymph node)MetastaticNADA
    9MSDHB46EA (dorsolateral bladder)RecurrentNANE + DA
    10MSDHD64RAPrimary1.5NE + DA
    11MVHL48RAPrimary2.2NE
    12FSporadic55LAPrimary11.0E + NE
    13FSporadic34RAPrimary5.0E + NE
    14MSporadic51EA (retrocaval lymph node)Metastatic2.0NE
    15FSporadic33LAPrimary4.0E + NE
    16FSporadic56EA (paraaortic lymph node)Primary1.4NE
    17MSporadic66LAPrimary1.8E
    18MSporadic85RAPrimaryNANE
    19MSporadic55LAPrimary3.5E + NE
    20MSporadic43LAPrimary10.0E + NE
    21FSporadic73LAPrimary12.5NE + DA
    22FSporadic55RAPrimary1.5E
    23MSporadic64RAPrimary5.0E + NE
    24FSporadic55LAPrimary6.0E + NE
    • LA = left adrenal; RA = right adrenal; EA = extraadrenal; NA = not available; E = epinephrine; NE = norepinephrine; DA = dopamine.

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    TABLE 2

    18F-FDG PET/CT Parameters

    ParameterAll tumor lesions (n = 26)Primary tumors (n = 22)Metastases (n = 4)
    MRglc (nmol⋅mL−1⋅min−1)53.6 (13.2–412.4)49.4 (13.2–412.4)137.6 (14.6–219.8)
    SUVmax (g⋅cm−3)4.7 (1.3–21.1)4.6 (1.3–19.6)7.1 (2.0–21.1)
    K1 (mL⋅g−1⋅min−1)0.42 (0.10–3.25)0.41 (0.18–3.25)0.46 (0.96–0.51)
    k2 (min−1)0.95 (0.13–2.82)0.93 (0.13–2.83)1.04 (0.24–1.15)
    k3 (min−1)0.032 (0.011–0.170)0.032 (0.014–0.151)0.049 (0.011–0.170)
    Vb (mL⋅mL−1)0.148 (0.037–0.738)0.144 (0.037–0.738)0.182 (0.080–0.390)
    • Data are median followed by range in parentheses. No significant differences were observed between 2 groups (Mann–Whitney U test).

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    TABLE 3

    18F-FDG Pharmacokinetic Rate-Constants for Primary and Metastatic PPGLs

    Rate constantHereditary cluster 1 tumors (SDHx, VHL) (n = 7)Hereditary cluster 2 tumors (RET, NF1) (n = 6)Sporadic tumors (n = 13)
    K1 (mL⋅g−1⋅min−1)0.28 (0.10–3.25)0.44 (0.23–0.65)0.50 (0.18–1.01)
    k2 (min−1)0.79 (0.13–2.82)1.08 (0.54–1.50)0.99 (0.47–1.49)
    k3 (min−1)0.084 (0.015–0.170)*0.041 (0.015–0.062)0.025 (0.011–0.059)
    Vb (mL⋅mL−1)0.219 (0.080–0.738)†0.105 (0.037–0.128)0.151 (0.072–0.300)
    • ↵* Significantly higher than sporadic tumor values (P < 0.01, Kruskal–Wallis with post hoc Dunn test).

    • ↵† Significantly higher than hereditary cluster 2 values (P < 0.01, Kruskal–Wallis with post hoc Dunn test).

    • Data are median followed by range in parentheses.

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    TABLE 4

    Determinants of MRglc

    MRglc (nmol⋅mL−1⋅min−1)
    ParameterR2 (95% CI)P
    SUVmax0.475 (0.291 to 0.882)0.001*
    K1 (mL⋅g−1⋅min−1)0.066 (−0.629 to 0.156)0.228
    k2 (min−1)0.145 (−0.732 to 0.073)0.067
    k3 (min−1)0.358 (0.181 to 0.832)0.002*
    Vb (mL⋅mL−1)0.107 (−0.103 to 0.677)0.118
    • ↵* P < 0.01.

    • CI = confidence interval.

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Journal of Nuclear Medicine: 60 (6)
Journal of Nuclear Medicine
Vol. 60, Issue 6
June 1, 2019
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Metabolic Subtyping of Pheochromocytoma and Paraganglioma by 18F-FDG Pharmacokinetics Using Dynamic PET/CT Scanning
Anouk van Berkel, Dennis Vriens, Eric P. Visser, Marcel J.R. Janssen, Martin Gotthardt, Ad R.M.M. Hermus, Lioe-Fee de Geus-Oei, Henri J.L.M. Timmers
Journal of Nuclear Medicine Jun 2019, 60 (6) 745-751; DOI: 10.2967/jnumed.118.216796

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Metabolic Subtyping of Pheochromocytoma and Paraganglioma by 18F-FDG Pharmacokinetics Using Dynamic PET/CT Scanning
Anouk van Berkel, Dennis Vriens, Eric P. Visser, Marcel J.R. Janssen, Martin Gotthardt, Ad R.M.M. Hermus, Lioe-Fee de Geus-Oei, Henri J.L.M. Timmers
Journal of Nuclear Medicine Jun 2019, 60 (6) 745-751; DOI: 10.2967/jnumed.118.216796
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