RESUMEN
Background and study aims Endoscopic optical diagnosis is crucial to the therapeutic strategy for early gastrointestinal cancer. It accurately (>â85â%) predicts pT category based on microsurface (SP) and vascular patterns (VP). However, interobserver variability is a major problem. We have visualized and digitalized the graded irregularities based on bioinformatically enhanced quantitative endoscopic image analysis (BEE) of high-definition white-light images. Methods In a pilot study of 26 large colorectal lesions (LCLs, mean diameter 39âmm), we retrospectively compared BEE variables with corresponding histopathology of the resected LCLs. Results We included 10 adenomas with low-grade intraepithelial neoplasia (LGIN), nine with high-grade intraepithelial neoplasia (HGIN) and early adenocarcinoma (EAC), and seven deeply submucosal invasive carcinomas. Quantified density (d) and nonuniformity (C U ) of vascular and surface structures correlated with histology (r s d VP: -0.77, r s C U VP: 0.13, r s d SP: -0.76, and r s C U SP: 0.45, respectively). A computed BEE score showed a sensitivity and specificity of 90â% and 100â% in the group with LGINs, 89â% and 41â% in the group with HGINs and EACs, and 100â% and 95â% in the group with deeply invasive carcinoma, respectively. Conclusions In this pilot study, BEE showed promise as a tool for endoscopic characterization of LCLs during routine endoscopy. Prospective clinical studies are needed.
