Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors

Table 4 Variables with independent predictive value obtained from combining different magnetic resonance techniques (multivariate logistic regression) in primary brain tumors

MR Technique	N	Predictor variables	OR	95% CI	P	Coefficient (β)	Standard error	AUC	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
MRI	129	Enhancement	23.37	5.85-93.25	<0.0001	3.15	0.71	0.890	95.9	70	91.3	84
MRI	129	Necrosis	9.04	2.61-31.25	0.001	2,20	0.63	0.890	95.9	70	91.3	84
MRI	71	Enhancement	11.63	2.35-58.82	0.003	2.46	0.81	0.871	98.2	46.7	87.3	87.5
PWI
DWI
DWI		Necrosis	8.48	1.95-37.04	0.005	2.13	0.77
MRS		Necrosis	8.48	1.95-37.04	0.005	2.13	0.77
MRI		Enhancement	16.95	3.89-71.43	<0.0001	2.83	0.75
PWI	120	Necrosis	5.40	1.32-21.74	0.019	1.69	0.72	0.923	98.9	75.9	92.8	95.6
DWI		rADC	0.22	0.50-0.97	0.045	−1.51	0.75

AUC, area under the receiver operating characteristic curve; CI, confidence interval; DWI, diffusion-weighted imaging; MRI, magnetic resonance imaging; MRS, MR spectroscopy; N, number of cases from which each classifier was constructed; PWI, perfusion-weighted imaging; rADC, relative apparent diffusion coefficient; OR, odds ratio; PPV, positive predictive value; NPV, negative predictive value.

ISSN: 1470-7330