Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study

Table 3 Hepatocellular carcinoma microvascular invasion prediction results from artificial neural network models constructed on different features, n (%)

Sequence	MCR (n = 97)	Sensitivity (%)	Specificity (%)	AUC (95%CI)
T2WI	25 (25.77)	80.70	65.00	0.729
AP	19 (19.59)	100.00	52.50	0.762
VP	24 (24.74)	70.17	82.50	0.763
DP	23 (23.71)	70.17	85.00	0.776
AP + VP	17 (17.53)	94.73	65.00	0.799
1Combined	13 (13.40)	80.70	97.50	0.891

¹Combined = Pseudocapsule + tumor blood vessels + arterial phases + venous phase.

T2WI: T2-weighted imaging; MCR: Misclassification rate; AUC: Area under curve; AP: Arterial phases; VP: Venous phase; DP: Delayed phase; CI: Confidence interval.