Table 2:

Comparative diagnostic accuracy of investigated parameters differentiating IDH-mutant from IDH-wild-type gliomasa

Models and ParametersAUC95% CIOptimal CutoffSensitivity (%)Specificity (%)P Value
Nondiffusion
 Enhancementb0.770.66–0.880.5 ↓88.265.2<.001
 Necrosisb0.850.77–0.940.5 ↓79.491.3<.001
 T2LFMb0.570.44–0.700.5 ↑13.0100.03
 Hemorrhageb0.780.67–0.880.5 ↓61.893.5<.001
ADC
 ADCc0.820.73–0.921.206 ↑67.491.2<.001
DTI
 FA0.590.45–0.730.174 ↓50.082.6.050
 MDc0.830.75–0.920.945 ↑89.164.7<.001
DKI
 AK0.900.83–0.970.583 ↓88.284.8<.001
 RK0.900.83–0.970.593 ↓94.178.3<.001
 MK0.900.83–0.970.567 ↓94.178.3<.001
 KFA0.550.42–0.680.807 ↑63.284.2.73
 MKT0.910.84–0.980.619 ↓88.284.8<.001
SMT
 LMDc0.620.48–0.752.967 ↑73.958.8.009
 TMDc0.870.79–0.950.528 ↑78.391.2<.001
 µFA0.910.84–0.980.535 ↓91.284.8<.001
 µFA30.910.84–0.980.153 ↓91.284.8<.001
 MMDc0.850.77–0.941.369 ↑67.491.2<.001
 INVF0.910.84–0.980.339 ↓91.284.8<.001
 IDc0.720.61–0.832.006 ↑69.670.6<.001
 ETMDc0.770.66–0.871.301 ↑76.167.6<.001
 EMMDc0.650.53–0.781.502 ↑67.467.6.01
  • Note:—T2LFM indicates T2-FLAIR mismatch; FA, fractional anisotropy; MD, mean diffusivity; KFA, kurtosis fractional anisotropy; LMD, longitudinal microscopic diffusivity; µFA3, microscopic fractional anisotropy to the third power; MMD, microscopic mean diffusivity; ID, intrinsic diffusivity, ETMD, extra-neurite transverse microscopic diffusivity; EMMD, extra-neurite microscopic mean diffusivity.

  • a Optimal cutoff levels to predict IDH type were assessed by the Youden index. Cutoffs were evaluated by sensitivity and specificity. An upward arrow (↑) indicates a positive correlation, in which values above the cutoff point predict an IDH-mutant glioma, whereas a downward arrow (↓) indicates a negative correlation, in which values below the cutoff point predict an IDH-mutant glioma. P values were computed by comparing the AUC against chance performance.

  • b Binary variable, indicating the presence or absence of the feature.

  • c Units in mm2/s × 10−3.