Background: Magnifying narrow-band imaging (NBI) endoscopy clearly visualizes superficial gastric mucosal patterns and capillary patterns. Objective: To investigate gastric mucosal patterns by using magnifying NBI endoscopy and identify any relationship between those patterns and Helicobacter pylori-induced gastritis. Design: Gastric mucosal patterns seen with magnifying NBI in uninvolved gastric corpus were divided into the following categories: normal-small, round pits with regular subepithelial capillary networks; type 1-slightly enlarged, round pits with unclear or irregular subepithelial capillary networks; type 2-obviously enlarged, oval or prolonged pits with increased density of irregular vessels; and type 3-well-demarcated oval or tubulovillous pits with clearly visible coiled or wavy vessels. Setting: Department of Gastroenterology, Fujita Health University. Patients: This study involved 106 participants undergoing upper endoscopy. Results: H pylori infection-positive ratios of normal and types 1, 2, and 3 patterns were 7.5%, 92.9%, 94.5%, and 66.7%, respectively. Sensitivity and specificity for types 1 + 2 + 3 for detection of H pylori positivity and type 3 for detection of intestinal metaplasia were 95.2%, 82.2%, 73.3%, and 95.6%, respectively. Development of mucosal patterns from normal to types 1, 2, and 3 was correlated with all histological parameters (P < .0001), lower pepsinogen I/II ratios (P < .0001), and degree of endoscopic atrophy (P < .0001). Sensitivity and specificity of type 3 for the prediction of severe histological atrophy was also better than those of serum pepsinogen level and standard endoscopy. Limitations: Only 1 endoscopist performed endoscopic procedures, and interobserver agreement could not be assessed. Conclusions: Magnifying NBI endoscopy is useful for predicting H pylori infection and the histological severity of gastritis and is valuable for predicting gastric atrophy in the entire stomach.
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging