Research ArticleClinical Investigations

18F-Fluoromisonidazole Quantification of Hypoxia in Human Cancer Patients Using Image-Derived Blood Surrogate Tissue Reference Regions

Mark Muzi, Lanell M. Peterson, Janet N. O’Sullivan, James R. Fink, Joseph G. Rajendran, Lena J. McLaughlin, John P. Muzi, David A. Mankoff and Kenneth A. Krohn
Journal of Nuclear Medicine August 2015, 56 (8) 1223-1228; DOI: https://doi.org/10.2967/jnumed.115.158717

Article Figures & Data

Figures

  • FIGURE 1.
    FIGURE 1.

    18F-FMISO image analysis. MR image (A) registered to a PET 18F-FMISO image (B) showing placement of 2-cm-diameter cerebellar regions of interest to determine surrogate blood activity. Example of cardiac (3-cm diameter) and aortic region of interest (1-cm diameter) on low-dose CT scan used for attenuation correction (C) and PET 18F-FMISO scan (D). Patient examples of 18F-FMISO tumor uptake appear in supplemental materials.

  • FIGURE 2.
    FIGURE 2.

    Correlation of blood and ID blood. (A) Normalized injected dose (MBq/kg) showed poor correlation (R2 = 0.42, n = 223) to measured blood activity (kBq/mL). (B) Bland–Altman plot of data shows unusual structure with points generally lying obliquely to mean, indicating poor linear relationship. Regression (C) and Bland–Altman (D) plots between measured blood and surrogate blood regions (ID blood) showed high correlation at R2 = 0.84.

  • FIGURE 3.
    FIGURE 3.

    Correlation of hypoxia parameters. (A) Regression plot of TBmax vs. ID TBmax for 269 surrogate blood regions shows strong relationship with small coefficient of variation (SEE/mean). (B) Bland–Altman plot shows clustering around mean with little bias. Plots of HV vs. ID HV values in C and D show similar profile.

  • FIGURE 4.
    FIGURE 4.

    Kaplan–Meier survival analysis. Hypoxia parameters were used to stratify 38 pretreatment glioma patients with respect to 2-y survival and TTP. Kaplan–Meier plots for TBmax demonstrated significantly shorter survival (A) and TTP (B) in high-risk patients (red line) whose tumors possessed TBmax ratios greater than median (TBmax > 1.83) relative to low-risk patients (black line). Using cerebellum as blood surrogate produced hypoxia parameter ID TBmax (dotted lines, median ID TBmax = 1.77) that had nearly predictive power nearly identical to TBmax. Kaplan–Meier plots and results for HV appear in supplemental materials.

Tables

  • TABLE 1

    18F-FMISO Patient Region Summary

    ID blood regions
    Cancer typeCerebellumAortaHeart
    Brain93
    H&N7543
    Sarcoma22117
    Breast1515
    Lung108
    Lymphoma22
    Melanoma11
    Total regions1705346

    • Two hundred twenty-three studies on 187 patients were selected on the basis of presence of detectable surrogate normoxic tissue.

  • TABLE 2

    Blood and Hypoxia Parameter Mean Values

    ParameterCerebellum (170*)Aorta (53*)Heart (46*)
    Blood†1.51 ± 0.221.46 ± 0.241.45 ± 0.25
    ID blood†1.50 ± 0.211.42 ± 0.231.45 ± 0.25
    TBmax1.77 ± 0.551.72 ± 0.681.74 ± 0.70
    ID TBmax1.77 ± 0.561.78 ± 0.721.77 ± 0.78
    HV (mL)20.6 ± 38.535.1 ± 57.034.5 ± 53.5
    ID HV (mL)20.9 ± 42.235.4 ± 56.035.7 ± 55.3

    • ↵* No. of regions analyzed for each blood surrogate.

    • ↵† Values for blood and ID blood are SUV.

    • Values presented are mean ± SD. Blood, TBmax, and HV values were derived from blood sampling. ID blood, ID TBmax, and ID HV were determined from blood reference tissue regions.

  • TABLE 3

    Correlation of Blood to ID Blood Surrogates

    Blood surrogatenR2SlopeρSEE/mean
    Cerebellum1700.840.890.920.06
    Heart460.840.920.920.07
    Aorta530.830.870.910.07
    Overall2690.840.890.910.06

    • Correlation results of ID to sampled blood activity. Correlation parameters are R2 (coefficient of determination), slope from linear regression, Pearson ρ, and SEE/mean as a measure of coefficient of variation of regression.

  • TABLE 4

    Results of Univariate Analysis for Predictors of Outcome in Pretreatment Glioma Patients (n = 38)

    SurvivalTTP
    PredictorHazardPHazardP
    Age1.730.0051.730.004
    Sex1.770.1441.800.131
    KPS*0.630.0190.670.028
    HV2.30<0.0012.07<0.001
    ID HV2.69<0.0012.45<0.001
    TBmax2.51<0.0012.34<0.001
    ID TBmax2.41<0.0012.31<0.001
    Resection†1.210.6041.160.664

    • ↵* Karnofsky performance score.

    • ↵† Resection is dichotomized as biopsy or other (gross/subtotal resection).

    • Univariate analysis of hypoxia and clinical variables shows the hazard ratio with P values associated with the outcome variables survival and TTP at 2 y.

  • TABLE 5

    Results of Multivariate Cox Regression Analysis for Predictors of Outcome in Pretreatment Glioma Patients (n = 38)

    Survival (0.390)*TTP (0.466)
    PredictorHazardPHazardP
    Age1.260.4211.440.158
    Sex1.770.5251.430.440
    KPS†0.780.3240.880.554
    TBmax2.37<0.0012.31<0.001
    Resection‡0.760.5160.750.463
    Survival (0.394)TTP (0.485)
    PredictorHazardPHazardP
    Age1.220.4831.380.210
    Sex1.230.6761.310.559
    KPS0.750.2440.820.378
    ID TBmax2.30<0.0012.30<0.001
    Resection0.810.6160.770.519

    • ↵* The coefficient of determination (R2) is given for each table.

    • ↵† Karnofsky performance score.

    • ↵‡ Resection is dichotomized as biopsy or other (gross/subtotal resection).

    • Multivariate analysis shows that after adjusting for clinical variables using a multivariate Cox model, greater tumor TBmax was still associated with shorter survival and TTP. Multivariate results for HV and ID HV appear in supplemental materials.

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