Integration of AI in Barrett’s Esophagus Clinical Practice: A New Way Forward

Barrett’s esophagus is the only known precursor for esophageal adenocarcinoma. The stepwise progression of nondysplastic Barrett’s to low-grade dysplasia, high-grade dysplasia, intramucosal carcinoma, and invasive cancer provides an opportunity for endoscopic surveillance, with the goal to detect and effectively treat early neoplastic changes endoscopically, in order to avoid surgery and chemoradiation. Multiple limitations in the current endoscopic surveillance practice have led to missed early neoplasia and therefore reduced the effectiveness of the current surveillance practice. Artificial intelligence (AI)-based clinical decision support systems have been developed to provide additional assistance to physicians performing diagnostic and therapeutic gastrointestinal endoscopy. In this article, we review the current endoscopic surveillance practice for Barrett’s esophagus, its limitations, the potential role of AI to improve these limitations, and our suggested framework to integrate AI into Barrett’s clinical practice.