Detection of minimal mucosal esophageal lesions in non-erosive gastroesophageal reflux disease using optical enhancement plus optical magnification

Abstract

Background and study aims The aim of this study was to evaluate the diagnostic yield of endoscopy using optical enhancement (OE system) with optical magnification to predict reflux in non-erosive reflux disease (NERD) patients. Patients and methods A prospective, non-randomized, single-blind study was performed from September 2015 to January 2016. Participants suffered from gastroesophageal reflux disease (GERD) symptoms and were assigned to the NERD group or the non-reflux disease control group based on endoscopic findings and a 24-hour pH-impedance-monitoring test. Endoscopy using the OE system with optical magnification was performed in all patients to detect minimal mucosal esophageal lesions (MMEL), specifically abnormalities in the numbers, dilation, and tortuosity of intrapapillary capillary loops (IPCLs). Biopsies were obtained from each esophageal segment, and diagnoses from images were compared to diagnoses of reflux and inflammation using 24-hour pH-impedance monitoring and histology, respectively. Results Fifty-seven patients were included (36 in the NERD group, 21 in the control group). IPCLs were observed in 94.4 % of cases in the NERD group and 38 % of cases in the control group (P < 0.05). There were significant differences in IPCL abnormalities between groups that were associated with histologically identified inflammation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 94.4 %, 61.9 %, 80.9 %, 86.6 %, and 82.4 %, respectively. The 24-hour pH-impedance-monitoring test was used as the gold standard. The Kappa interobserver and intraobserver values were 0.85 and 0.90, respectively. Conclusion The OE system with optical magnification can detect MMEL and predict NERD with high sensitivity, accuracy, and interobserver and intraobserver agreement. Presence of IPCLs highly correlates with histologically identified inflammation.