Usefulness of artificial intelligence in early gastric cancer

Table 1 Studies involving computer-aided diagnosis for early gastric cancer detection

Ref.	Study design	Endoscopic modality	Main study aim	Subjects for validation
Kubota et al[53], 2012	Retrospective	WLI	Prediction of invasion depth	344 patients
Miyaki et al[63], 2013	Retrospective	ME-FICE	Differentiation of cancerous areas from non-cancerous areas	46 patients
Miyaki et al[64], 2015	Retrospective	ME-BLI	Differentiation of cancerous areas from non-cancerous areas	95 patients
Kanesaka et al[65], 2018	Retrospective	ME-NBI	Delineation of cancerous areas	81 images
Hirasawa et al[14], 2018	Retrospective	WLI, CE, NBI	Delineation of cancer	69 patients
Zhu et al[54], 2019	Retrospective	WLI, NBI	Prediction of invasion depth	203 lesions
Cho et al[50], 2019	Prospective validation dataset	WLI	Differentiation of cancerous areas from non-cancerous areas	200 patients
Ishioka et al[55], 2019	Retrospective	WLI	Detection of GC	62 patients
Yoon et al[56], 2019	Retrospective	WLI	Detection of GC	800 patients
Tang et al[57], 2020	Retrospective	WLI	Differentiation of cancerous areas from non-cancerous areas	279 patients
Namikawa et al[58], 2020	Retrospective	WLI	Differentiation of cancerous areas from non-cancerous areas	220 lesions
Li et al[66], 2020	Retrospective	ME-NBI	Detection of cancer	341 images
An et al[62], 2020	Retrospective	WLI, CE, ME-NBI	Delineation of EGC margins	355 images
Horiuki et al[67], 2020	Retrospective	ME-NBI	Differentiation of cancerous areas from non-cancerous areas	258 images
Nagao et al[45], 2020	Retrospective	WLI, CE, NBI	Prediction of invasion depth of GC	1084 GC
Wu et al[52], 2021	Prospective	WLI	Detection of Blind spotsAnd early gastric cancer	1050 patients
Ueyama et al[59], 2021	Retrospective	ME-NBI	Differentiation of cancerous areas from non-cancerous areas	2300 images
Ling et al[48], 2021	Retrospective	ME-NBI	Differentiation status and margins for EGC	139 + 58 + 87 EGCs
Ikenoyama et al[46], 2021	Retrospective	WLI, CE, NBI	Detection of cancer	140 lesions
Hu et al[68], 2021	Retrospective	ME-NBI	Detection of cancer	295 lesions
Oura et al[60], 2021	Retrospective	WLI	Missing GC and point out low-quality images	855 lesions + 50 lesions
Zhang et al[61], 2021	Retrospective	WLI	Detection of cancer	1091 images
Wu et al[51], 2021	Prospective	WLI	Screening gastric lesions	10000 patients
Hamada et al[69], 2022	Retrospective	WLI, CE, BLI	Depth of invasion of EGC	68 patients
Nam et al[47], 2022	Retrospective	WLI	Lesion detection, differentiation and depth	1366 patients
Wu et al[49], 2022	Prospective	ME-NBI	GC and EGC detection, EGC invasion depth and differentiation status

BLI: Blue laser imaging; CE: Color enhancement; EGC: Early gastric cancer; ME-NBI: Magnification endoscopy; NBI: Narrow-band imaging; WLI: White light imaging.

Table 2 Endpoints of the extracted studies

Ref.	Main outcome
[45,53,54,69]	Accuracy rate of diagnosing the depth of wall invasion of gastric cancer
[64]	Detection rate of gastric cancer
[63]	Identification rate of cancerous lesions, reddened lesions and surrounding tissue
[48,62,65]	Detection rate of early gastric cancer and its margins
[14]	Identification rate of gastric cancer and gastric ulcer
[50]	Identification rate of advanced gastric cancer, early gastric cancer, high grade dysplasia, low grade dysplasia and non-neoplasm
[46,51,55,57,59,60,66,68]	Detection rate of early gastric cancer
[56]	Detection rate of early gastric cancer and its localization. Accuracy rate of diagnosing the depth of wall invasion of gastric cancer
[58]	Identification rate of early gastric cancer, advanced gastric cancer and benign gastric ulcer
[67]	Identification rate of early gastric cancer and gastritis
[52]	Identification rate of early gastric cancer and number of blind spots
[61]	Identification rate of early gastric cancer and other gastric lesions (high grade dysplasia, peptic ulcer, advanced gastric cancer, gastric submucosal tumors and normal gastric mucosa)
[47]	Identification rate of early gastric cancer, advanced gastric cancer and benign gastric ulcer. Accuracy rate of diagnosing the depth of wall invasion of gastric cancer
[49]	Detection rate of early gastric cancer. Accuracy rate of diagnosing the depth of wall invasion of gastric cancer