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Table 3: Multivariate ROC analysis showing AUC±SE values for various combinations of FDG-PET and MRI parameters in the detection of glioma recurrence^{^a}
rCBV_mean (0.680 ± 0.011) ADC_mean (0.752 ± 0.085) Cho/Cr (0.861 ± 0.080) ADC_mean + rCBV_mean (0.781 ± 0.079) ADC_mean + Cho/Cr (0.912 ± 0.051) rCBV_mean + Cho/Cr (0.860 ± 0.083) ADC_mean + rCBV_mean + Cho/Cr (0.913 ± 0.053)
ADC_mean (0.752 ± 0.085) 0.781 ± 0.079 
Cho/Cr (0.861 ± 0.080) 0.860 ± 0.083 0.912 ± 0.051 0.913 ± 0.053^{^b} 
TBR_max (0.827 ± 0.078) 0.831 ± 0.081 0.848 ± 0.072 0.894 ± 0.059 0.850 ± 0.073 0.935 ± 0.044 0.889 ± 0.061 0.932 ± 0.046
TBR_mean (0.888 ± 0.059) 0.884 ± 0.063 0.888 ± 0.058 0.935 ± 0.044 0.897 ± 0.057 0.935 ± 0.046^{^b.^c} 0.928 ± 0.047 0.932 ± 0.048^{^b}
↵a Each entry represents the AUC±SE of a combination of parameters mentioned in the respective rows and columns. Values in parentheses represent AUC±SE of that particular parameter or combination. Blank cells are left to avoid repetition of values.
↵b A combination of FDG-PET and MR imaging parameters has a better AUC±SE than a combination of MR imaging parameters.
↵c Note that the maximum AUC was achieved with a combination of ADC_mean, Cho/Cr, and TBR_mean.