. 2021 Jan 20;187(2):535–545. doi: 10.1007/s10549-020-06074-7

Table 3.

Summary of predictive models based on pre-contrast images and percentage change in radiomics features between pre- and post-contrast images

	AUROC	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Accuracy (%)
Pre-contrast	0.514 (0.299–0.728)	15.3 (1.8–42.8)	79.2 (49.2–95.3)	34.8 (11.6–77.3)	48.7 (39.3–56.5)	53.6 (27.5–66.1)
Percentage change	0.540 (0.329–0.752)	22.8 (4.7–50.8)	86.0 (57.2–98.2)	57.5 (22.7–88.4)	53.0 (43.5–60.7)	60.7 (33.9–72.5)

AUROC

Sensitivity (%)

Specificity (%)

PPV (%)

NPV (%)

Accuracy (%)

Pre-contrast

0.514

(0.299–0.728)

15.3

(1.8–42.8)

79.2

(49.2–95.3)

34.8

(11.6–77.3)

48.7

(39.3–56.5)

53.6

(27.5–66.1)

Percentage change

0.540

(0.329–0.752)

22.8

(4.7–50.8)

86.0

(57.2–98.2)

57.5

(22.7–88.4)

53.0

(43.5–60.7)

60.7

(33.9–72.5)

Models were created using gaussian support vector machines (SVMs) and are presented with confidence intervals

AUROC area under the receiver operating curve, NPV negative predictive value, PPV positive predictive value