Taking the Next Steps in Endoscopic Visual Assessment of Barrett's Esophagus: A Pilot Study

• Published in: Clinical and experimental gastroenterology Vol. 14; pp. 113 - 122
• Main Authors: Chis, Roxana, Hew, Simon, Hopman, Wilma, Hookey, Lawrence, Bechara, Robert
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2021; Taylor & Francis Ltd; Dove; Dove Medical Press
• Subjects: barrett’s esophagus; Biopsy; Classification; Comparative analysis; Dysplasia; Endoscopy; enhanced endoscopy; esophageal adenocarcinoma; Esophageal cancer; Esophagus; Gastroenterology; Medical prognosis; Medical research; Optical instruments industry; Original Research; Pathology; Patients; Surveillance; Canada; United States; dysplasia; Barrett’s esophagus; enhanced endoscopy; BE; esophageal adenocarcinoma
• ISSN: 1178-7023; 1178-7023
• DOI: 10.2147/CEG.S293477

Patients with Barrett's esophagus (BE) undergo surveillance endoscopies to assess for pre-cancerous changes. We developed a simple endoscopic classification method for predicting non-dysplastic BE (NDBE), low-grade dysplasia (LGD)/indefinite for dysplasia (ID) and high-grade dysplasia (HGD)/early esophageal adenocarcinoma (EAC). Twenty-two patients with BE underwent endoscopy using the PENTAX Medical MagniView gastroscope and OPTIVISTA processor. Sixty-six video-still images were analyzed to characterize the microsurface, microvasculature and the presence of a demarcation line. Class A was characterized by regular microvascular and microsurface patterns and absence of a demarcation line, class B by changes in the microvascular and/or microsurface patterns compared to the background mucosa with presence of a demarcation line, and class C by irregular microvascular and/or irregular microsurface patterns with presence of a demarcation line. Of the class A images, 97.9% were NDBE. For class B, 69.2% were LGD/ID and 30.8% NDBE. One hundred percent of the class C samples were HGD/EAC. The sensitivity of our classification system was 93.8%, specificity 92%, positive predictive value 78.9%, negative predictive value 97.9% and an accuracy 92.4%. In this study, we developed a simple classification system for the prediction of NDBE, LGD/ID and HGD/EAC. Its real-time clinical applicability will be validated prospectively.