Application of computed tomography-based radiomics in differential diagnosis of adenocarcinoma and squamous cell carcinoma at the esophagogastric junction

Table 1 Model performance for differentiating squamous cell carcinoma of the esophagogastric junction and adenocarcinoma of the esophagogastric junction in the training and validation groups

	2D-ROI models			3D-ROI models
Model	Artery	Venous	Artery + venous	Artery	Venous	Artery + venous
Training group
AUC	0.808	0.849	0.869	0.876	0.877	0.904
95%CI	0.744-0.872	0.792-0.905	0.818-0.920	0.827-0.926	0.827-0.927	0.861-0.947
Threshold	0.095	-0.101	-0.370	-0.149	-0.352	0.043
Specificity	0.802	0.758	0.681	0.813	0.780	0.879
Sensitivity	0.736	0.802	0.890	0.824	0.857	0.802
Accuracy	0.769	0.780	0.786	0.819	0.819	0.841
NPV	0.753	0.793	0.861	0.822	0.845	0.816
PPV	0.788	0.768	0.736	0.815	0.796	0.869
Validation group
AUC	0.752	0.831	0.845	0.824	0.879	0.901
95%CI	0.640-0.864	0.742-0.921	0.763-0.928	0.732-0.917	0.798-0.960	0.830-0.973
Threshold	0.095	-0.101	-0.370	-0.149	-0.352	0.043
Specificity	0.795	0.692	0.718	0.769	0.667	0.821
Sensitivity	0.641	0.769	0.769	0.744	0.872	0.795
Accuracy	0.718	0.731	0.744	0.756	0.769	0.808
NPV	0.689	0.750	0.757	0.750	0.839	0.800
PPV	0.758	0.714	0.732	0.763	0.723	0.816

ROI: Region of interest; AUC: Area under the curve; NPV: Negative predictive value; PPV: Positive predictive value.

Table 2 Model optimism estimation by 1000-times bootstrap in the training group

Index	Model	Apparent AUC1	AUC Bootstrap-test2 (mean, 95%CI)	Optimism
1	2D-arterial model	0.808	0.770 (0.767-0.772)	0.050
2	2D-venous model	0.849	0.820 (0.817-0.822)	0.036
3	3D-arterial model	0.876	0.815 (0.812-0.880)	0.080
4	3D-venous model	0.877	0.833 (0.830-0.835)	0.056

¹The area under the curve of predictive model developed in the whole training dataset.

²The averaged model performance in the “out-of-bag” test set after 1000-times bootstrap. AUC: Area under the curve.