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Table 2 Statistical differences of radiomic features determined by using RF classifier between pseudoprogression and true progression

From: Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T1-weighted Contrast-enhanced Imaging

Feature

Gini Importance

True progression

Pseudoprogression

p value

Median

Interquartile range

Median

Interquartile Range

Feature1

3.73

0.998

0.995–0.999

0.996

0.993–0.999

 < .001

Feature2

2.91

1.30 × 10–5

2.0 × 10–6–6.8 × 10–5

3.39 × 10–5

7.34 × 10–6–1.19 × 10–4

 < .001

Feature3

2.08

3.0 × 10–13

1.04 × 10–14–4.2 × 10–12

5.59 × 10–13

1.26 × 10–13–7.91 × 10–12

.079

Feature4

2.08

− 0.20

− 1.21–0.83

− 0.58

− 1.79–1.09

 < .001

Feature5

1.98

1.14 × 104

1725.0–72,802.4

2.03 × 104

9098.51–56,899.20

.015

Feature6

1.53

3.32 × 10–4

1.44 × 10–4–7.51 × 10–4

4.65 × 10–4

1.71 × 10–4–7.57 × 10–4

 < .001

Feature7

1.45

16.22

1.20–241.05

37.06

11.14–254.88

.137

Feature8

1.42

221.32

14.89–5051.62

349.15

89.95–5227.03

.765

Feature9

1.39

5.25 × 10–6

2.45 × 10–7–2.04 × 10–5

6.44 × 10–7

2.43 × 10–7–8.2 × 10–6

.828

Feature10

1.32

5.35 × 108

2.20 × 107–1.64 × 1011

2.34 × 109

1.85 × 108–9.06 × 1010

.374

Feature11

1.25

4.84 × 10–5

1.3 × 10–5–1.96 × 10–4

7.3 × 10–5

5.74 × 10–6–1.75 × 10–4

.008

Feature12

1.25

14.49

1.08–342.81

35.44

2.47–189.35

.244

Feature13

1.24

− 2393.65

− 61,416.60–36,264.10

− 1.26 × 104

− 152 × 105–5.76 × 104

.015

Feature14

1.09

1.5 × 10–13

5.05 × 10–15–8.51 × 10–9

2.72 × 10–13

8.2 × 10–14–1.83 × 10–11

.445

Feature15

1.07

1.8 × 10–5

1.22 × 10–6–7.55 × 10–5

2.8 × 10–5

5.75 × 10–6–1.08 × 10–4

.005

Feature16

1.01

0.998

0.994–0.999

0.996

0.993–0.999

 < .001

Feature17

0.93

3.27 × 10–5

− 3.14 × 10–4–7.18 × 10–4

1.47 × 10–4

− 5.47 × 10–4–4.69 × 10–4

.050

Feature18

0.93

− 744.67

− 1.68 × 104–1.03 × 104

748.24

− 11,634.40–18,560.10

.138

Feature19

0.89

0.12

1.91 × 10–4–8.93

0.14

5.95 × 10–4–5.43

.197

Feature20

0.82

0.55

0.35–0.66

0.56

0.50–0.73

.028

Feature21

0.81

1.3 × 10–13

1.20 × 10–14–2.97 × 10–12

2.52 × 10–13

5.05 × 10–14–2.07 × 10–9

.161

Feature22

0.76

1.83 × 109

6.18 × 107–7.80 × 1010

6.48 × 109

7.02 × 108–9.28 × 1010

.048

Feature23

0.75

0.998

0.994–0.999

0.997

0.994–0.998

.256

Feature24

0.74

0.998

0.994–1.000

0.998

0.997–0.999

.347

Feature25

0.73

5.1 × 10–12

1.53 × 1013–4.33 × 1010

1.44 × 10–11

1.17 × 10–12–3.16 × 10–8

.141

Feature26

0.72

1.73 × 10–4

− 2.99 × 10–4–7.68 × 10–4

1.69 × 10–4

3.13 × 10–6–7.69 × 10–4

.060

Feature27

0.71

3.72 × 10–4

2.19 × 10–4–1.06 × 10–3

4.43 × 10–4

3.16 × 10–4–1.04 × 10–3

.006

Feature28

0.70

7.47 × 103

999.18–41,102.90

1.16 × 104

1287.42–25,000.80

.111

Feature29

0.69

− 342.35

− 4559.64–8392.05

672.42

− 8078.63–28,881.70

.208

Feature30

0.68

− 1.02 × 103

− 5065.29–1823.32

− 600.96

− 2031.27–3107.47

.125

Feature31

0.66

6.80 × 108

2.59 × 107–1.87 × 1010

2.12 × 109

3.88 × 107–3.44 × 1011

.103

Feature32

0.65

843.33

160.59–1046.56

753.13

258.74–1333.93

.147

Feature33

0.62

− 9.8 × 10–5

− 5.9 × 10–4–3.22 × 10–4

− 8.60 × 10–5

− 3.36 × 10–4–1.4 × 10–4

.799

Feature34

0.62

967.43

69.37–6660.59

2441.03

149.65–10,040.5

.002

Feature35

0.60

5.83 × 10–6

1.51 × 10–6–1.89 × 10–5

8.91 × 10–6

2.43 × 10–6–2.95 × 10–5

.015

Feature36

0.58

1.69 × 104

9790.15–26,645.1

18,893.30

13,895.80–32,379.50

.008

Feature37

0.58

1.99 × 10–4

− 3.4 × 10–4–8.7 × 10–4

2.87 × 10–4

− 7.65 × 10–5–1.44 × 10–3

.060

Feature38

0.53

− 467.89

− 3.00 × 104–1.79 × 104

799.64

− 35,322.10–20,325.90

.575

Feature39

0.53

4.95 × 10–9

1.34 × 10–9–1.60 × 10–8

5.83 × 10–9

5.38 × 10–10–3.45 × 10–8

.037

Feature40

0.53

14.17

− 5.15 × 103–1.25 × 104

− 939.69

− 27,364.50–5113.09

.026

Feature41

0.52

− 259.96

− 16,902.50–9521.71

1264.01

− 10,087.90–6781.62

.121

Feature42

0.52

− 1.20

− 2.52–0.10

− 0.81

− 2.07–0.20

.043

Feature43

0.52

2.22

0.30–12.95

2.76

1.54–5.43

.536

Feature44

0.52

9.53 × 1010

1.10 × 1010–4.10 × 1012

2.30 × 1011

4.82 × 109–7.26 × 1012

.023

Feature45

0.52

1.04 × 105

2.21 × 104–5.96 × 105

1.40 × 105

37,793.10–516,907.00

.025

Feature46

0.52

3.30 × 105

1.23 × 105–2.56 × 106

4.29 × 105

1.27 × 105–1.39 × 106

.505

Feature47

0.51

9.1 × 10–14

9.09 × 10–14–9.42 × 10–15

1.96 × 1013

4.65 × 10–14–8.41 × 10–13

.110

Feature48

0.50

0.51

0.39–0.64

0.48

0.38–0.62

.074

Feature49

0.49

6.27 × 10–7

5.39 × 10–8–4.22 × 10–6

1.37 × 10–6

1.71 × 10–7–4.76 × 10–6

.005

Feature50

0.49

− 4.9 × 10–3

− 0.55–0.50

0.06

− 0.68–0.63

.414

  1. Feature relevance was assessed by using mean decrease in Gini index–based feature importance
  2. P values are adjusted for false-discovery rate by using Benjamini–Hochberg method. 1–50 features are the same as in Fig. 4