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

Table 1 Cascade-aware framework linking cascade-related targets with visible endoscopic phenotypes, artificial intelligence task formulation, reference standards, clinical decision impacts, and comparability limitations in gastric endoscopy

Cascade-related target/histopathological entity	Visible endoscopic phenotype	Typical AI task	Reference standard	Clinical decision impact	Main comparability limitation
H. pylori-associated chronic gastritis	Diffuse or spotty redness; enlarged folds; altered RAC pattern	CADx for infection-status classification	UBT, RUT, histopathology, serology, stool antigen testing, or composite testing1	Supports infection diagnosis and guides eradication therapy	Post-eradication mucosal changes; heterogeneous reference standards
Gastric atrophy	Pale mucosa; visible submucosal vessels; atrophic border; reduced gastric folds	CADx; severity staging; segmentation	Histopathology, updated Sydney system, OLGA, Kimura-Takemoto, Kyoto classification	Supports risk stratification, biopsy targeting, and surveillance planning	Multifocal disease; sampling error; underestimation from single-image analysis
Intestinal metaplasia	Whitish plaques; villous pattern; LBC; MTB; patchy redness	CADx; extent grading; segmentation	Biopsy histopathology, EGGIM, OLGIM	Supports targeted biopsy, assessment of IM extent, and surveillance planning	Patchy distribution; sampling error; modality-dependent visualization
Gastric dysplasia/early neoplasia	Subtle color change; irregular surface or vascular pattern; flat or depressed lesion	CADe or CADx for dysplasia/neoplasia	Biopsy or resection histopathology; Vienna classification	Supports referral, targeted biopsy, and treatment planning	Interobserver variability; lesion coexistence; coarse reference labels
Early gastric cancer detection and delineation	Well-demarcated lesion; irregular MS or MV pattern; surface depression or elevation; fold convergence	CADe; CADx; lesion segmentation	Biopsy, expert endoscopic delineation, ESD or surgical histopathology, TNM staging	Supports lesion detection, margin delineation, and endoscopic treatment planning	Reference-margin heterogeneity; resection-enriched cohorts; verification bias
Invasion depth and curability assessment	Fold convergence; ulceration; wall stiffness; surface depression; non-lifting sign	Invasion-depth prediction; histologic differentiation prediction; treatment-curability assessment	Endoscopic resection or surgical histopathology	Supports selection of endoscopic resection vs surgical management	Verification bias; resection-enriched cohorts; invasion-depth label imbalance; limited external validation

¹Composite testing refers to the use of two or more diagnostic tests as the reference standard.

AI: Artificial intelligence; CADe: Computer-aided detection; CADx: Computer-aided diagnosis; EGGIM: Endoscopic Grading of Gastric Intestinal Metaplasia; ESD: Endoscopic submucosal dissection; H. pylori: Helicobacter pylori; LBC: Light-blue crest; MS: Microsurface; MTB: Marginal turbid band; MV: Microvascular; OLGA: Operative Link on Gastritis Assessment; OLGIM: Operative Link on Gastric Intestinal Metaplasia Assessment; RAC: Regular arrangement of collecting venules; RUT: Rapid urease test; TNM: Tumor-node-metastasis; UBT: Urea breath test; IM: Intestinal metaplasia.