Skip to main content

Table 3 Performances for the manual model

From: MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study

 

Construction set: centre A + centre B

 

AUC

(95% CI)

ACC %

(95% CI)

[rate]

SE %

(95% CI)

[rate]

SP %

(95% CI)

[rate]

NPV %

(95% CI)

[rate]

PPV %

(95% CI)

[rate]

MRMR+EL (AdaBoost)

1.00

(93–100)

99

(92–100)

100

(97–100)

98

(87–100)

100

(80–99)

96

(95–100)

[66/67]

[39/39]

[27/28]

[27/27]

[39/40]

Ranking+EL (Bag)

0.99

(92–100)

94

(85–98)

97

(80–98)

90

(81–100)

96

(74–96)

93

(84–100)

[63/67]

[37/38]

[26/29]

[26/27]

[37/40]

Ranking+SVM Gaussian

0.87

(79–95)

81

(69–89)

93

(76–99)

73

(67–88)

94

(79–98)

69

(58–79)

[54/67]

[25/27]

[29/40]

[29/31]

[25/36]

Ranking+LR stepwise

0.69

(67–85)

80

(69–89)

[54/67]

89

(71–98)

[24/27]

75

(59–87)

[30/40]

91

(77–97)

[30/33]

70

(57–80)

[24/34]

Ranking+SVM polynomial

0.90

(82–97)

83

(71–90)

[55/67]

85

(66–96)

[23/27]

80

(64–91)

[32/40]

89

(76–95)

[32/36]

74

(60–84)

[23/31]

 

Validation set: centre C

Ranking+SVM polynomial

0.61

(52–74)

68

(48–84)

[19/28]

60

(32–83)

[9/15]

77

(47–95)

[10/13]

63

(46–76)

[10/16]

75

(60–90)

[9/12]

  1. AUC Area under the curve, ACC Accuracy, NPV Negative predictive value, PPV Positive predictive value, SE Sensitivity, SP Specificity