AI-Assisted Detection of Early Gastric Cancer via Visualization of Mucosal Acidity Compromise During Endoscopy.

ABSTRACT: Accurate localization of early gastric cancer (EGC) remains challenging due to its morphological resemblance to gastritis. This study presents an artificial intelligence (AI)-assisted bedside diagnostic system to enhance EGC detection by visualizing gastric mucosal acidity. The ATPase H⁺/K⁺ transport β subunit (ATP4B), a key regulator of acid secretion, is progressively downregulated in gastric mucosal atrophy and intestinal metaplasia, and significantly reduced in EGC. A surface-enhanced Raman scattering (SERS) microarray is developed to map mucosal pH in 50 patient specimens (1,516 points), with founding compared to pathological images. A multi-model neural network is trained and validated internally on data from 40 patients (1,127 points) and externally validated o

SUBMITTER: Yan H 

PROVIDER: S-EPMC12697849 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature