Ultrasomics in liver cancer: Developing a radiomics model for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma using contrast-enhanced ultrasound

Table 3 Area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predict value, and negative predict value of radiomics models in different cohorts

Parameter	Training				Validation				Test
	US	AE + PE	US + AE + PE	US + AE + PE + CL	US	AE + PE	US + AE + PE	US + AE + PE + CL	US	AE + PE	US + AE + PE	US + AE + PE + CL
AUC (95%CI)	0.885 (0.825, 0.889)	0.955 (0.919, 0.962)	0.966 (0.934, 0.972)	0.975 (0.941, 0.975)	0.822 (0.738, 0.863)	0.956 (0.856, 0.962)	0.964 (0.907, 0.977)	0.973 (0.933, 0.983)	0.816 (0.690, 0.825)	0.919 (0.876, 0.959)	0.955 (0.907, 0.967)	0.971 (0.916, 0.980)
Sensitivity	0.766	0.933	0.900	0.911	0.727	0.909	0.818	0.863	0.607	0.714	0.928	0.892
Specificity	0.853	0.842	0.876	0.921	0.681	0.818	0.909	0.954	0.857	0.857	0.857	0.928
Accuracy	0.810	0.888	0.888	0.916	0.704	0.863	0.863	0.909	0.732	0.785	0.892	0.910
PPV	0.841	0.857	0.880	0.921	0.695	0.833	0.900	0.950	0.809	0.833	0.866	0.925
NPV	0.783	0.925	0.896	0.911	0.714	0.900	0.833	0.875	0.685	0.750	0.923	0.896

AE: Arterial enhancement; AUC: Area under the receiver operating characteristic curve; CI: Confidence interval; CL: Clinical data; NPV: Negative predict value; PE: Portal enhancement; PPV: Positive predict value; US: Ultrasound.