Which factors make Barrett’s esophagus lesions difficult to diagnose?

Background and study aims Although the Japan Esophageal Society’s magnifying endoscopic classification for Barrett’s epithelium (JES-BE) offers high diagnostic accuracy, some cases are challenging to diagnose as dysplastic or non-dysplastic in daily clinical practice. Therefore, we investigated the diagnostic accuracy of this classification and the clinicopathological features of Barrett’s esophagus cases that are difficult to diagnose correctly. Patients and methods Five endoscopists with experience with fewer than 10 cases of magnifying observation for superficial Barrett’s esophageal carcinoma reviewed 132 images of Barrett’s mucosa or carcinoma (75 dysplastic and 57 non-dysplastic cases) obtained using high-definition magnification endoscopy with narrow-band imaging (ME-NBI). They diagnosed each image as dysplastic or non-dysplastic according to the JES-BE classification, and the diagnostic accuracy was calculated. To identify risk factors for misdiagnosed images, images with a correct rate of less than 40 % were defined as difficult-to-diagnose, and those with 60 % or more were defined as easy-to-diagnose. Logistic regression analysis was performed to identify risk factors for difficult-to-diagnose images. Results The sensitivity, specificity and overall accuracy were 67 %, 80 % and 73 %, respectively. Of the 132 ME-NBI images, 34 (26 %) were difficult-to-diagnose and 99 (74 %) were easy-to-diagnose. Logistic regression analysis showed low-grade dysplasia (LGD) and high-power magnification images were each significant risk factors for difficult-to-diagnose images (OR: 6.80, P = 0.0017 and OR: 3.31, P = 0.0125, respectively). Conclusions This image assessment study suggested feasibility of the JES-BE classification for diagnosis of Barrett’s esophagus by non-expert endoscopists and risk factors for difficult diagnosis as high-power magnification and LGD histology. For non-experts, high-power magnification images are better evaluated in combination with low-power magnification images.