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

Table 1 Binary logistic regression analysis for microvascular invasion prediction

Variables	β	SE	Wald	df	P value	OR (95%CI)
Tumor maximum diameter	-0.074	0.588	0.016	1	0.900	0.929 (0.293-2.942)
Pseudocapsule	2.093	0.639	10.733	1	0.001	8.111 (2.318-28.373)
Tumor blood vessels	2.051	0.788	6.775	1	0.009	7.775 (1.660-36.421)
Cystic degeneration or necrosis	0.098	0.677	0.021	1	0.885	1.103 (0.293-4.4155)

OR: Odds ratio; CI: Confidence interval.

Table 2 The dominant texture features selected after microvascular invasion dimensionality reduction

T2WI	AP	VP	DP	Multiparametric
GrSkewness	Z_ShrtREmp	Z_LngREmph	Perc.01% 3D	AP-S (0, 1, 0) SumAverg
135dr_GLevNonU	Z_Fraction	Z_Fraction	S (0, 0, 1) InvDfMom	AP-Horzl_Fraction
45dgr_GLevNonU	Z_LngREmph	S (1, 0, 0) SumAverg	GrMean	AP-Horzl_ShrtREmp
Horzl_GLevNonU	45dgr_ShrtREmp	S (0, 0, 1) SumAverg	Z_LngREmph	AP-Horzl_LngREmph
Z_RLNonUni	S (0, 0, 1) InvDfMom	S (1, 1, 0) SumAverg	Z_ShrtREmp	AP-S (0, 0, 1) InvDfMom
135dr_ShrtREmp	S (0, 0, 1) SumAverg	Vertl_RLNonUni	S (1, -1, 0) SumAverg	VP- 45dgr_RLNonUni
Horzl_Fraction	Skewness 3D	135dr_RLNonUni	S (1, -1, 0) SumVarnc	VP-Vertl_RLNonUni
135dr_RLNonUni	GrSkewness	Z_ShrtREmp	Z_Fraction	VP-S (0, 0, 1) SumAverg
Z_GLevNonU	45dgr_Fraction	Perc.10% 3D	S (0, 1, 0) SumVarnc	VP-Z_ShrtREmp
Vertl_GLevNonU	Kurtosis 3D	S (0, 1, 0) SumAverg	Perc.10% 3D	VP-Z_LngREmph

T2WI: T2-weighted imaging; 3D: Three-dimensional; AP: Arterial phases; VP: Venous phase; DP: Delayed phase.

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.