Table 3 Performance metrics from each of the Logistic Regression and Random Forest classifier models, where low grade tumours have Gleason Score <  = 3 + 4 / Grade Group <  = 2 and high grade tumours have Gleason Score >  = 4 + 3 / Grade Group >  = 3. The best performing metrics when comparing the two classifiers are in bold. Ktrans and Ve were computed using the Parker AIF

Low Grade Tumours

Sensitivity

Specificity

Accuracy (%)

Sensitivity

Specificity

Accuracy (%)

T2w + ADC

0.21

0.89

60

0.40

0.70

58

T2w + ADC + Ktrans

0.25

0.88

63

0.44

0.77

63

T2w + ADC + Ktrans + Ve

0.38

0.84

65

0.57

0.81

71

T2w + ADC + TTP + IRE + AUC

0.48

0.79

66

0.63

0.83

74

T2w + ADC + Ktrans + Ve + TTP + AUC

0.47

0.79

66

0.68

0.86

78

High Grade Tumours

Sensitivity

Specificity

Accuracy (%)

Sensitivity

Specificity

Accuracy (%)

T2w + ADC

0.65

0.81

74

0.63

0.79

72

T2w + ADC + Ktrans

0.64

0.82

75

0.68

0.84

77

T2w + ADC + Ktrans + Ve

0.65

0.83

75

0.72

0.86

80

T2w + ADC + TTP + IRE + AUC

0.65

0.82

75

0.76

0.87

82

T2w + ADC + Ktrans + Ve + TTP + AUC

0.65

0.83

76

0.79

0.89

85

All Tumours

Sensitivity

Specificity

Accuracy (%)

Sensitivity

Specificity

Accuracy (%)

T2w + ADC

0.56

0.74

66

0.54

0.69

62

T2w + ADC + Ktrans

0.56

0.76

66

0.57

0.77

68

T2w + ADC + Ktrans + Ve

0.60

0.75

68

0.64

0.79

72

T2w + ADC + TTP + IRE + AUC

0.62

0.74

69

0.68

0.81

75

T2w + ADC + Ktrans + Ve + TTP + AUC

0.61

0.75

68

0.72

0.84

80