Artificial intelligence for endoscopic correlates of Correa’s cascade in gastric precancerous lesions and early neoplasia

Table 4 Summary of artificial intelligence studies targeting endoscopic assessment of gastric atrophy

Tier1	Study	Modality	Task and unit	Reference standard2	Dataset and validation3	AI method4	Clinical maturity5	Key results
4C	Guimarães et al[37], 2020	WLI	CADx; binary CAG classification; image-level	H&E biopsy histopathology; updated Sydney system	270 images; retrospective image-based evaluation	CNN (VGG16)	Retrospective image-based study	ACC 92.9%; SEN 100.0%; SPE 87.5%
4C	Zhang et al[38], 2020	WLI	CADx; binary CAG classification; image-level	Biopsy histopathology	5470 images; retrospective image-based evaluation	CNN (DenseNet121)	Retrospective image-based study	ACC 94.2%; SEN 94.5%; SPE 94.0%
4C	Shi et al[39], 2023	WLI	CADx; binary CAG classification; image-/video-level	Biopsy histopathology	10960 images and 118 videos; external image- and video-based testing	CNN (GAM-EfficientNet)	External validation; video-based evaluation	External image/video ACC 93.50%/92.37%; SEN 93.00%/96.23%; SPE 94.00%/89.23%
4D	Luo et al[40], 2022	WLI	CADx; antral atrophy severity grading and binary CAG classification; image-level	Biopsy histopathology; updated Sydney system; OLGA system	12325 images; retrospective image-based evaluation	CNN (two ResNet50 models)	Retrospective image-based study; severity grading	ACC 0.890 for antral atrophy; ACC 0.590 for severity; binary model ACC 0.854-0.916
4D	Kodaka et al[42], 2022	WLI	CADx; site-level GA classification and patient-level severity assessment	Biopsy histopathology; Kimura-Takemoto, Kyoto, and OLGA systems	19221 images; patient-level rule-based aggregation	CNN (ResNet34 with rule-based aggregation)	Patient-level risk stratification	Patient-level ACC 67.4% vs Kimura-Takemoto; 68.1% vs Kyoto; 62.2% vs OLGA; AUC 0.746 using the modified Kyoto classification
4D	Zhao et al[43], 2023 (earlier:[86])	NBI	Segmentation and CADx; site-level atrophy and patient-level OLGA risk assessment; video-level	Biopsy histopathology; Kimura-Takemoto classification	5290 images and 907 patients; test set and prospective cohort	CNN (U-Net)	Prospective evaluation; real-time video feasibility; patient-level risk stratification	Test/prospective ACC 92.73%/89.89%; SEN 92.24%/89.31%; SPE 92.63%/90.46%
4D	Tao et al[44], 2024	WLI	Segmentation and CADx; site-level GA and patient-level risk assessment; image-/video-level	Biopsy histopathology; Kimura-Takemoto classification	11538 images and 119 videos; image- and video-based evaluation	CNN (UNet++/ResNet50 plus site-identification model[87,88])	Video-based evaluation; patient-level risk stratification	Image/video ACC 92.52%/94.12%; SEN 92.72%/94.87%; SPE 92.31%/92.68%
4D	Liu et al[41], 2024	WLI, NBI	CADx; Kyoto gastritis score prediction; image-level	Kyoto classification of gastritis	29013 images; retrospective image-based evaluation	CNN (five GAM-EfficientNet models)	Retrospective image-based study; score prediction	Average ACC 78.70%; SEN 78.70%; SPE 91.92%

¹Tier definitions and clinical decision impact: 4C: Chronic atrophic gastritis diagnosis, supporting recognition of atrophic changes and biopsy planning; 4D: Gastric atrophy severity classification and risk stratification, supporting assessment of disease extent, surveillance planning, and patient-level risk stratification.

²Reference standard indicates the clinical verification method used to assign or confirm the dataset labels.

³Dataset counts refer to non-augmented original images, videos, or patients, when reported. Validation design is summarized according to the study design reported in the original article.

⁴Artificial intelligence method denotes the primary artificial intelligence pipeline used for the main results and is reported at the architecture-family level, with key components noted where relevant. If a study evaluated multiple models, the best-performing or clinically emphasized configuration is reported.

⁵Clinical maturity is categorized according to the highest level of validation or deployment relevance reported, including retrospective image-based study, external validation, prospective evaluation, real-time video feasibility, video-level evaluation, patient-level risk stratification, or score prediction.

ACC: Accuracy; AI: Artificial intelligence; AUC: Area under the curve; CADx: Computer-aided diagnosis; CAG: Chronic atrophic gastritis; CNN: Convolutional neural network; GA: Gastric atrophy; GAM: Global attention module; HE: Hematoxylin and eosin; NBI: Narrow-band imaging; OLGA: Operative Link on Gastritis Assessment; SEN: Sensitivity; SPE: Specificity; WLI: White-light imaging.