Development of a narrow-band imaging classification to reduce the need for routine biopsies of gastric polyps

Abstract

Abstract Background Most incidental gastric polyps identified during upper endoscopy are considered low-risk. However, current guidelines recommend sampling all gastric polyps for histopathologic analysis. We aimed to devise a simple narrow-band imaging (NBI) classification to reduce the need for routine biopsies of low-risk gastric polyps. Methods Pairs of NBI and white-light images were collected from 73 gastric polyps for which concurrent histopathologic diagnosis was available. A diagnostic accuracy cohort study was performed. Two blinded endoscopists independently analysed NBI features of each polyp for color, vessel pattern, surface pattern, and any combinations thereof to develop a classification scheme to differentiate low-risk polyps (fundic-gland or hyperplastic) from high-risk polyps (adenomatous or adenocarcinoma) and fundic-gland polyps (FGPs) from non-FGPs. Results An isolated lacy vessel pattern and a homogenous absence of surface pattern successfully differentiated low-risk from high-risk gastric polyps. Combining both descriptors into a single algorithm resulted in a negative predictive value (NPV) of 100% [95% confidence interval (CI): 100%–100%], positive predictive value (PPV) of 13.7% (95% CI: 2.6–24.8), sensitivity of 100% (95% CI: 100%–100%), and specificity of 53.7% (95% CI: 45.3%–62.0%) for high-risk polyps. This would reduce the number of polyps requiring biopsy by 50%, while still capturing all high-risk polyps. Regarding FGPs, using a rule not to biopsy polyps with isolated lacy vessels resulted in a 94.9% NPV (95% CI: 89.2%–100%), 63.2% PPV (95% CI: 47.2%–79.2%), 94.8% sensitivity (95% CI: 89.5%–100%), and 63.6% specificity (95% CI: 51.3%–76.0%) for non-FGPs. Conclusion In this derivation cohort study, NBI is helpful for differentiating between high-risk and low-risk gastric polyps, thereby reducing the need for routine sampling of low-risk polyps. These results need to be validated in a separate test population.