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Research ArticleImaging

Assessing the Correlation Between 68Ga-PSMA-11 Renal PET Parameters and Renal Function Tests

Jan-Henning Schierz, Ismet Sarikaya, Ahmed N. Albatineh and Ali Sarikaya
Journal of Nuclear Medicine Technology March 2022, 50 (1) 43-48; DOI: https://doi.org/10.2967/jnmt.121.262462
Jan-Henning Schierz
1Department of Radiology, Municipal Hospital Dresden, Dresden, Germany;
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Ismet Sarikaya
2Department of Nuclear Medicine, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait;
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Ahmed N. Albatineh
3Department of Community Medicine and Behavioral Sciences, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; and
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Ali Sarikaya
4Department of Nuclear Medicine, Faculty of Medicine, Trakya University, Edirne, Turkey
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  • FIGURE 1.
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    FIGURE 1.

    Example of VOI placement. Ovoid VOI is placed around kidney (black arrow). Software automatically traces edge with previously defined lower boundary of SUVmax of 10, thus establishing isocontour VOI with whole cortical kidney volume (white arrow).

  • FIGURE 2.
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    FIGURE 2.

    Example of VOI placement for liver (A), spleen (B), and blood pool (C). VOIs for liver and blood pool are drawn by software, whereas splenic VOI had to be drawn manually. Color version of this figure is available as supplemental file at http://tech.snmjournals.org.

  • FIGURE 3.
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    FIGURE 3.

    Example of excluded patient. Because of the large portion of calyceal tracer (circled), patient was omitted from measurement as software would add this area, falsifying measured values.

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    FIGURE 4.

    Example of strong asymmetry between kidneys. Because of mechanic outflow obstruction, right kidney atrophied and, later, nephrostomy was placed. Shown are PET (A), PET/CT (B), and contrast-enhanced CT (C). Color version of this figure is available as supplemental file at http://tech.snmjournals.org.

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    TABLE 1.

    Descriptive Statistics for Patient Characteristics (n = 25)

    CovariatenMeanSDMinimumMaximum
    Age2571.69.843482
    Weight2588.413.7268116
    Height25175.45.07163182
    Body mass index2528.704.022.737.6
    GFR2578.6417.7153134
    Creatinine2585.3217.0250114
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    TABLE 2.

    Measured Values for Renal PSMA PET Parameters (n = 25)

    CovariatenMeanSDMinimumMaximum
    Mean SUVmax2557.7520.6821.90100.95
    Mean SUVmean2527.6810.6812.9757.75
    Mean SULmax2541.8613.915.466.97
    Mean SULmean2518.194.599.1225.8
    SUVmean liver254.461.382.16.8
    SUVmean bp251.160.320.51.70
    SUVmean spleen256.132.422.811.4
    Renal SUVmax/liver ratio2514.336.953.2232.65
    Renal SUVmax/bp ratio2553.6122.9419.91100.95
    Renal SUVmax/spleen ratio2510.996.212.5528.84
    Renal SUVmean/liver ratio256.943.891.9119.48
    Renal SUVmean/bp ratio2526.1713.039.4357.75
    Renal SUVmean/spleen ratio255.234.861.5116.50
    Sum volume2535493.61194567
    Sum TLG259,968.85,042.72,52026,999
    Sum TLG (SUL)257,758.44,093.81,772.319,112.9
    Sum counts258,077.53,985.82,17617,473
    • bp = blood pool.

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    TABLE 3.

    Spearman Rank Correlation Coefficient Estimate Between GFR and Creatinine, with Several Covariates Along with Their CI Using Bootstrapping with Bias-Corrected and Accelerated Method Based on 2,000 Resamples

    GFRCreatinine ρ
    CovariateρP95% CIρP95% CI
    SUVmean liver−0.3100.132−0.634, 0.1180.2180.295−0.246, 0.606
    SUVmean bp−0.4150.039−0.753, 0.0640.3460.090−0.105, 0.723
    SUVmean spleen−0.1300.535−0.519, 0.2850.0570.786−0.423, 0.514
    Mean SUVmax0.1990.340−0.224, 0.596−0.2260.278−0.583, 0.161
    Mean SUVmean0.3170.123−0.090, 0.645−0.3290.108−0.653, 0.063
    Renal SUVmax/liver ratio0.4020.0460.028, 0.706−0.3640.074−0.731, 0.124
    Renal SUVmax/bp ratio0.4710.0180.115, 0.736−0.4220.036−0.738, 0.017
    Renal SUVmax/spleen ratio0.2450.237−0.160, 0.614−0.2100.314−0.631, 0.287
    Renal SUVmean/liver ratio0.5050.0100.102, 0.786−0.4510.024−0.800, 0.041
    Renal SUVmean/bp ratio0.5740.0030.220, 0.832−0.5150.008−0.820, −0.075
    Renal SUVmean/spleen ratio0.3530.083−0.075, 0.689−0.3040.140−0.708, 0.209
    Sum counts0.1240.554−0.245, 0.467−0.1590.446−0.537, 0.269
    Sum volume−0.0050.982−0.391, 0.397−0.0380.856−0.398, 0.324
    Sum TLG0.2250.280−0.166, 0.570−0.2680.195−0.617, 0.164
    Age−0.6830.001−0.907, −0.3440.5650.0030.175, 0.839
    Weight0.1330.528−0.224, 0.473−0.1750.402−0.530, 0.220
    Height0.1580.452−0.279, 0.513−0.1940.354−0.546, 0.217
    Body mass index0.0610.773−0.392, 0.466−0.1000.635−0.481, 0.341
    Mean SULmean0.3430.093−0.031, 0.622−0.3290.108−0.640, 0.075
    Mean SULmax0.1710.413−0.229, 0.532−0.1900.362−0.555, 0.230
    Sum TLG (SUL)0.3340.103−0.080, 0.644−0.3610.076−0.653, 0.031
    • bp = blood pool; ρ = estimated Spearman rank correlation coefficient.

    • P values are based on 2-sided test.

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Journal of Nuclear Medicine Technology: 50 (1)
Journal of Nuclear Medicine Technology
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March 1, 2022
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Assessing the Correlation Between 68Ga-PSMA-11 Renal PET Parameters and Renal Function Tests
Jan-Henning Schierz, Ismet Sarikaya, Ahmed N. Albatineh, Ali Sarikaya
Journal of Nuclear Medicine Technology Mar 2022, 50 (1) 43-48; DOI: 10.2967/jnmt.121.262462

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Assessing the Correlation Between 68Ga-PSMA-11 Renal PET Parameters and Renal Function Tests
Jan-Henning Schierz, Ismet Sarikaya, Ahmed N. Albatineh, Ali Sarikaya
Journal of Nuclear Medicine Technology Mar 2022, 50 (1) 43-48; DOI: 10.2967/jnmt.121.262462
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