Table 3:

Comparative diagnostic accuracy of investigated parameters differentiating glioma grades^{^a}

Models and Parameters	AUC	95% CI	Optimal Cutoff	Sensitivity (%)	Specificity (%)	P Value
Nondiffusion
Enhancement^{^b}	0.76	0.65–0.87	0.5 ↑	81.4	70.2	<.001
Necrosis^{^b}	0.81	0.71–0.91	0.5 ↑	67.4	94.6	<.001
T2LFM^{^b}	0.58	0.46–0.71	0.5 ↓	16.2	100	.006
Hemorrhage^{^b}	0.73	0.61–0.84	0.5 ↑	51.2	94.6	<.001
ADC
ADC^{^c}	0.88	0.80–0.96	1.217 ↓	75.7	88.4	<.001
DTI
FA	0.64	0.52–0.77	0.174 ↑	46.5	86.5	.01
MD^{^c}	0.88	0.80–0.95	1.134 ↓	83.8	76.7	<.001
DKI
AK	0.93	0.87–1.00	0.494 ↑	97.7	75.7	<.001
RK	0.93	0.88–1.00	0.627 ↑	83.7	91.9	<.001
MK	0.93	0.88–1.00	0.539 ↑	93.0	81.1	<.001
KFA	0.53	0.40–0.67	0.219 ↓	78.4	44.2	.85
MKT	0.94	0.88–0.99	0.564 ↑	88.4	86.5	<.001
SMT
LMD^{^c}	0.66	0.53–0.79	2.967 ↓	83.8	55.8	<.001
TMD^{^c}	0.91	0.84–0.97	2.958 ↓	91.9	79.1	<.001
µFA	0.94	0.88–0.99	0.509 ↑	90.7	86.5	<.001
µFA³	0.94	0.88–0.99	0.132 ↑	90.7	86.5	<.001
MMD^{^c}	0.90	0.83–0.97	1.311 ↓	89.2	76.7	<.001
INVF	0.94	0.88–0.99	0.319 ↑	90.7	86.5	<.001
ID^{^c}	0.77	0.67–0.88	1.946 ↓	83.8	65.1	<.001
ETMD^{^c}	0.82	0.72–0.91	1.208 ↓	94.6	60.5	<.001
EMMD^{^c}	0.72	0.60–0.84	1.502 ↓	75.7	67.4	<.001

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, extraneurite transverse microscopic diffusivity; EMMD, extraneurite microscopic mean diffusivity.
↵a Optimal cutoff levels to predict glioma grade (low-grade versus high-grade) 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 a high-grade glioma, whereas a downward arrow (↓) indicates a negative correlation, in which values below the cutoff point predict a high-grade 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 mm²/s × 10⁻³.