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.

Table 2 Full detail and meta-analysis and subgroup analysis convolutional neural network model for the diagnosis of esophageal cancers or neoplasms in the still image-based analysis

	Number of studies	Sensitivity (95%CI)	Specificity (95%CI)	PLR (95%CI)	NLR (95%CI)	DOR (95%CI)	AUC (95%CI)	P value
CNN	19	0.95 (0.92-0.97)	0.92 (0.89-0.94)	11.5 (8.3-16.0)	0.06 (0.04-0.09)	205 (115-365)	0.98 (0.96-0.99)
Continent								0.65
Asian	12	0.95 (0.92-0.97)	0.91 (0.87-0.95)	11.1 (7.0-17.5)	0.05 (0.03-0.09)	222 (110-444)	0.98 (0.96-0.99)
Europe/Ameica	5	0.91 (0.86-0.94)	0.90 (0.87-0.92)	9.3 (7.0-12.3)	0.10 (0.06-0.16)	91 (45-186)	0.95 (0.93-0.97)
Public	2
Scale								0.61
Unicenter	12	0.94 (0.90-0.97)	0.93 (0.88-0.96)	13.2 (7.8-22.5)	0.06 (0.03-0.11)	219 (103-465)	0.98 (0.96-0.99)
Multicenter	7	0.95 (0.91-0.98)	0.90 (0.87-0.93)	10.0 (7.3-13.8)	0.05 (0.03-0.10)	191 (78-471)	0.97 (0.95-0.98)
External validation or not								0.94
External validation	5	0.95 (0.88-0.98)	0.91 (0.87-0.94)	10.5 (6.9-16.0)	0.06 (0.02-0.14)	186 (55-635)	0.97 (0.95-0.98)
No external validation	14	0.95 (0.91-0.97)	0.92 (0.88-0.95)	12.1 (7.7-19.1)	0.06 (0.03-0.09)	213 (111-407)	0.98 (0.96-0.99)
Format								0.84
Retrospective	16	0.95 (0.92-0.97)	0.92 (0.88-0.95)	12.0 (8.1-17.7)	0.05 (0.03-0.09)	223 (121-411)	0.98 (0.96-0.99)
Prospective	3
Case type								0.1
Image	14	0.95 (0.92-0.97)	0.93 (0.90-0.95)	13.7 (9.6-19.6)	0.05 (0.03-0.09)	252 (132-478)	0.98 (0.96-0.99)
Patient	5	0.95 (0.84-0.98)	0.84 (0.75-0.90)	5.8 (3.8-8.9)	0.06 (0.02-0.19)	94 (34-265)	0.92 (0.90-0.94)
Real-time or not								0.9
Real-time	7	0.94 (0.88-0.97)	0.91 (0.88-0.94)	11.0 (7.6-16.0)	0.06 (0.03-0.13)	175 (65-471)	0.96 (0.94-0.98)
No real-time	12	0.95 (0.92-0.97)	0.91 (0.87-0.95)	11.1 (7.0-17.7)	0.05 (0.03-0.09)	210 (103-430)	0.98 (0.96-0.99)
Histological type								0.01
ESCN	9	0.97 (0.94-0.98)	0.90 (0.83-0.94)	9.6 (5.6-16.3)	0.04 (0.02-0.06)	272 (106-699)	0.98 (0.97-0.99)
Barrett’s neoplasia	6	0.92 (0.85-0.96)	0.91 (0.87-0.93)	9.7 (6.7-14.1)	0.09 (0.05-0.17)	108 (43-272)	0.96 (0.93-0.97)
ESCC/EAC	4	0.92 (0.85-0.96)	0.96 (0.94-0.97)	23.0 (17.2-30.6)	0.08 (0.04-0.16)	283 (178-450)	0.98 (0.96-0.99)
Image type								0.07
WLI	13	0.95 (0.91-0.97)	0.89 (0.85-0.92)	8.3 (6.2-11.0)	0.06 (0.03-0.11)	143 (75-273)	0.96 (0.94-0.97)
Advanced imaging	10	0.95 (0.91-0.97)	0.93 (0.88-0.96)	13.6 (7.5-24.6)	0.06 (0.03-0.10)	237 (107-525)	0.98 (0.96-0.99)
Quality								0.1
High	16	0.96 (0.93-0.97)	0.91 (0.88-0.94)	10.7 (7.6-15.2)	0.05 (0.03-0.08)	223 (115-434)	0.98 (0.96-0.99)
Low	3

CI: Confidence interval; PLR: Positive likelihood ratio; NLR: Negative likelihood ratio; DOR: Diagnostic odds ratio; AUC: Area under the curve; WLI: Wight-light imaging; ESCN: Esophageal squamous cell neoplasia; EAC: Adenocarcinoma; ESCC: Esophageal squamous cell carcinoma; CNN: Convolutional neural network.

Table 3 Characteristics of the still video-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	Videos training set	Patients test set	Videos test set	TP	FP	FN	TN
de Groof et al[43], 2020	Prospective	Multicenter	Europe	Video	ResNet/U-Net	WLI	Barrett’s neoplasia (HGD/EAC)	Yes	Yes	Hgh	53	NM	1544	20	20	9	3	1	7
Yang et al[47], 2021	Retrospective	Unicenter	Asia	Video	Yolo V3	WLI	ESCC	No	No	High	6	6215	32373 image/104 video	NM	68	39	2	1	26
Fukuda et al[51], 2020	Retrospective	Unicenter	Asia	Video	SSD/VGG-16	NBI/BLI	ESCC	Yes	Yes	High	13	2002	28333	NM	238	80	53	10	95
Struyvenberg et al[52], 2021	Retrospective	Multicenter	Europe	Video	ResNet/U-Net	NBI	Barrett’s neoplasia (HGD/EAC)	Yes	Yes	High	No	15700	495611	50	471	141	58	36	236
Waki et al[53], 2021	Retrospective	Multicenter	Asia	Video	ResNet/ImageNet	WLI/NBI/BLI	ESCC	Yes	No	High	21	1572	18797	113	200	103	66	23	34
Shiroma et al[54], 2021	Retrospective	Unicenter	Asia	Video	SSD	NBI	ESCC	Yes	No	High	18	nm	8428	40	80	11	4	9	16
Yuan et al[55], 2022	Retrospective	Multicenter	Asia	Video	YOLO v3	WLI	ESCC	Yes	Yes	High	11	2621 image/19 video	53933 image/142 video	NM	38	17	5	2	14
Tajiri et al[56], 2022	Retrospective	Unicenter	Asia	Video	ResNet/ImageNet	WLI/NBI/BLI	ESCC	No	No	High	19	1843	29794	130	147	71	16	12	48

WLI: White-light imaging; NBI: Narrow-band imaging; BLI: Blue-laser imaging; TP: True positive; FP: False positive; FN: False negative; TN: True negative; EAC: Esophageal adenocarcinoma; ESCC: Esophageal squamous cell carcinoma; HGD: High-grade dysplasia; NM: Not mentioned; CNN: Convolutional neural network.

Table 4 Full detail and meta-analysis and subgroup analysis convolutional neural network model for the diagnosis of esophageal cancers or neoplasms in the video-based analysis

	Number of studies	Sensitivity (95%CI)	Specificity (95%CI)	PLR (95%CI)	NLR (95%CI)	DOR (95%CI)	AUC (95%CI)	P value
CNN		0.85 (0.77-0.91)	0.73 (0.59-0.83)	3.1 (1.9-5.0)	0.20 (0.12-0.34)	15 (6-38)	0.87 (0.84-0.90)
Continent								0.73
Asian	6	0.86 (0.76-0.93)	0.71 (0.53-0.85)	3.0 (1.6-5.5)	0.19 (0.09-0.40)	16 (5-54)	0.87 (0.84-0.90)
Europe/Ameica	2
Scale								0.55
Unicenter	4	0.87 (0.68-0.96)	0.77 (0.62-0.87)	3.8 (2.0-7.0)	0.17 (0.06-0.49)	23 (5-106)	0.87 (0.84-0.90)
Multicenter	4	0.81 (0.77-0.85)	0.65 (0.43-0.82)	2.3 (1.3-4.2)	0.29 (0.20-0.41)	8 (3-20)	0.82 (0.78-0.85)
External validation or not								0.94
External validation		0.85 (0.78-0.91)	0.73 (0.63-0.80)	3.1 (2.4-4.1)	0.20 (0.14-0.29)	16 (10-24)	0.87 (0.84-0.90)
No external validation		0.85 (0.66-0.94)	0.74 (0.45-0.90)	3.2 (1.2-8.5)	0.20 (0.07-0.60)	16 (2-106)	0.87 (0.84-0.90)
Format								0.89
Retrospective	5	0.85 (0.76-0.91)	0.73 (0.58-0.84)	3.1 (1.9-5.3)	0.21 (0.12-0.36)	15 (6-41)	0.87 (0.84-0.90)
Prospective	1
Real-time or not								0.13
Real-time	6	0.82 (0.74-0.87)	0.68 (0.52-0.80)	2.5 (1.6-3.9)	0.27 (0.19-0.39)	9 (5-18)	0.83 (0.80-0.86)
No real-time	2
Histological type								0.73
ESCN	6	0.86 (0.76-0.93)	0.71 (0.53-0.85)	3.0 (1.6-5.5)	0.19 (0.09-0.40)	16 (5-54)	0.87 (0.84-0.90)
Barrett’s neoplasia	2
Image type								0.76
WLI	4	0.83 (0.71-0.91)	0.49 (0.27-0.71)	1.6 (0.9-2.8)	0.34 (0.13-0.88)	5 (1-20)	0.80 (0.77-0.84)
Advanced imaging	5	0.83 (0.77-0.88)	0.71 (0.56-0.82)	2.9 (1.9-4.3)	0.24 (0.19-0.30)	12 (8-19)	0.86 (0.82-0.88)

CI: Confidence interval; PLR: Positive likelihood ratio; NLR: Negative likelihood ratio; DOR: Diagnostic odds ratio; AUC: Area under the curve; WLI: Wight-light imaging; ESCN: Esophageal squamous cell neoplasia; CNN: Convolutional neural network.

Table 5 Characteristics of the studies about diagnosis of invasion depth of esophageal cancers

Ref.	Format	Scale	Continent	Depth	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
Horie et al[29], 2019	Retrospective	Unicenter	Asia	T1a, T1b vs T2-4	SSD	WLI/NBI	ESCC/EAC	Yes	No	High	No	384	8428	NM	168	142	2	1	23
Nakagawa et al[31], 2019	Retrospective	Unicenter	Asia	pEP-SM1, pEP-MM	SSD	WLI/NBI/BLI	ESCC	No	No	High	16	804	14338	155	914	714	24	60	132
Tokai et al[57], 2020	Retrospective	Unicenter	Asia	pEP-SM1	SSD	NBI/WLI	ESCC	No	No	High	13	NM	10179	NM	279	159	24	30	66

WLI: White-light imaging; NBI: Narrow-band imaging; BLI: Blue-laser imaging; TP: True positive; FP: False positive; FN: False negative; TN: True negative; EAC: Esophageal adenocarcinoma; ESCC: Esophageal squamous cell carcinoma; HGD: High-grade dysplasia; NM: Not mentioned; CNN: Convolutional neural network; pEP-SM1: Pathological intraepithelial-submucosal microinvasive; pEP-MM: Pathological intraepithelial-muscularis mucosa.