Visceral adipose tissue reduction measured by deep neural network architecture improved reflux esophagitis endoscopic grade.

Abstract

BACKGROUND AND AIMS Visceral obesity is a risk factor for reflux esophagitis (RE). We investigated the risk of RE according to visceral adipose tissue (VAT) measured by deep neural network architecture using computed tomography and evaluated the longitudinal association between abdominal adipose tissue changes and the disease course of RE. METHODS Individuals receiving health checkups who underwent esophagogastroduodenoscopy (EGD) and abdominal computed tomography (CT) at Seoul National University Healthcare System Gangnam Center between 2015 and 2016 were included. Visceral and subcutaneous adipose tissue areas and volumes were measured using a deep neural network architecture and CT. The association between the abdominal adipose tissue area and volume and the risk of RE was evaluated. Participants who underwent follow-up EGD and abdominal CT were selected; the effects of changes in abdominal adipose tissue area and volume on RE endoscopic grade were investigated using Cox proportional hazards regression. RESULTS We enrolled 6570 patients who underwent EGD and abdomen CT on the same day. RE was associated with male sex, hypertension, diabetes, excessive alcohol intake, current smoking status, and levels of physical activity. The VAT area and volume increased the risk of RE dose-dependently. A decreasing VAT volume was significantly associated with improvement in RE endoscopic grade (HR:3.22, 95%CI:1.82-5.71). Changes in subcutaneous adipose tissue volume and the disease course of RE were not significantly correlated. CONCLUSIONS Visceral obesity is strongly associated with RE. VAT volume reduction was prospectively associated with improvement in RE endoscopic grade dose-dependently. Visceral obesity is a potential target for RE treatment.