Application of convolutional neural network-based endoscopic imaging in esophageal cancer or high-grade dysplasia: A systematic review and meta-analysis

Table 1 Characteristics of the still image-based studies

Ref.	Format	Scale	Continent	Case type	Architecture of CNN	Image type	Histological type	Real-time	External validation	Quality	Endoscopist control	Patients training set	Images training set	Patients test set	Images test set	TP	FP	FN	TN
Li et al[17], 2021	Retrospective	Multicenter	Asia	Image	Visual geometry group	NBI/WLI	ESCC	No	No	High	20	647	4735	112	632	252	37	14	329
Ohmori et al[20], 2020	Retrospective	Unicenter	Asia	Patient	SSD	NBI/BLI	ESCC	No	No	High	15	NM	22562	237	727	51	16	1	34
Cai et al[34], 2019	Retrospective	Multicenter	Asia	Image	8-layer convolutional neural network	WLI	ESCC	No	No	High	16	746	2428	52	187	89	14	2	82
Ebigbo et al[35], 2019	Prospective	Unicenter	Europe	Image	ResNet	WLI/NBI	EAC	No	No	High	13	113	248	62	74	32	5	1	36
Ghatwary et al[36], 2019	Retrospective	Unicenter	Public	Image	R-CNN, Fast R-CNN, Faster R-CNN, SSD	WLI	EAC	No	No	High	No	21	NM	39	100	48	4	2	46
Kumagai et al[37], 2019	Retrospective	Unicenter	Asia	Patient	GoogLeNet	ECS	ESCC	No	No	High	No	240	4715	55	1520	25	3	2	25
Zhao et al[38], 2019	Retrospective	Unicenter	Asia	IPCLs image	ImageNet VGG-16	ME-NBI	ESCC	No	No	High	9	NM	261	NM	1383	1023	33	153	174
Liu et al[39], 2020	Retrospective	Unicenter	Asia	Image	Inception-ResNet	WLI	ESCC/EAC	No	No	High	No	NM	1017	NM	127	27	4	8	88
Guo et al[40], 2020	Retrospective	Multicenter	Public	Image	SegNet	NBI	ESCC	Yes	Yes	High	No	549	6473	2123	6671	1451	258	29	4933
Ebigbo et al[41], 2020	Retrospective	Unicenter	Europe	Image	ResNet	WLI	EAC	Yes	No	Low	No	NM	129	14	62	30	0	6	26
Hashimoto et al[42], 2020	Retrospective	Unicenter	Ameica	Image	Inception-ResNet v2	NBI/WLI	Barrett’s neoplasia (HGD/EAC)	Yes	No	High	No	100	1832	39	458	217	13	8	220
de Groof et al[43], 2020	Prospective	Multicenter	Europe	Patient	ResNet/U-Net	WLI	Barrett’s neoplasia (HGD/EAC)	Yes	Yes	High	53	NM	1544	20	144	25	15	8	96
de Groof et al[44], 2020	Retrospective	Multicenter	Europe	Image	ResNet/U-Net	WLI	Barrett’s neoplasia (HGD/EAC)	Yes	Yes	Low	53	15700	495611	255	457	186	31	23	217
Du et al[45], 2021	Retrospective	Unicenter	Asia	Image	DenseNet	WLI	ESCC/EAC	No	No	Low	No	3253	16771	824	4194	1106	109	103	2876
Tang et al[46], 2021	Retrospective	Multicenter	Asia	Image	ResNet50	WLI	ESCC	Yes	Yes	High	10	1078	4002	243	1033	297	87	6	643
Yang et al[47], 2021	Retrospective	Unicenter	Asia	Image	Yolo V3	WLI/ME-OE	ESCC	No	No	High	6	6215	32373	NM	1123	263	13	5	774
Wang et al[48], 2021	Retrospective	Unicenter	Asia	Patient	SSD	WLI/NBI	ESCN (HGD/ESCC)	No	No	High	No	46	936	202	264	169	5	2	26
Gong et al[49], 2022	Prospective	Multicenter	Asia	Image	Grad-CAM	WLI	ESCC/EAC	No	Yes	High	No	NM	4387	NM	1611	631	58	21	901
Zhao et al[50], 2022	Retrospective	Unicenter	Asia	Patient	GoogLeNet-Inception V3	NBI	ESCC/EAC	No	No	High	2	200	NM	100	NM	45	4	5	46

WLI: White-light imaging; NBI: Narrow-band imaging; BLI: Blue-laser imaging; ECS: Endocytoscopic system; ME: Magnifying endoscopy; OE: Optical enhancement; TP: True positive; FP: False positive; FN: False negative; TN: True negative; EAC: Esophageal adenocarcinoma; ESCC: Esophageal squamous cell carcinoma; ESCN: Esophageal squamous cell neoplasia; HGD: High-grade dysplasia; IPCL: Intrapapillary capillary loop classification; NM: Not mentioned; CNN: Convolutional neural network.