Artificial intelligence in screening colonoscopy

Background Colorectal cancer (CRC) is still one of the leading causes of cancer death despite the fact that effective prevention is available using colonoscopy. The number of endoscopically removed polyps correlates with increased protection from recurrence; however, the occurrence of interval cancer after colonoscopy remains a clinically relevant problem. Artificial intelligence (AI) is thought to be a measure for improvement in this field. With the help of neuronal networks and deep learning a real-time distinction between normal mucosa and polyps as well as a differentiation between adenomas and hyperplastic polyps can be achieved. Objective This review highlights the current state of AI in colonoscopy for a better detection of polyps and adenomas for cancer prevention. Material and methods Publications from MEDLINE (R) (U.S. National Library of Medicine (R), Bethesda, MD USA) on this topic were collected and evaluated. Results With the help of AI a significantly better adenoma detection rate (ADR) could be recently displayed in multiple studies independent of the morphology or location. Data for sessile serrated lesions are inconclusive at the moment. The results were only statistically significant for polyps Discussion There is hope that AI could reduce the incidence of interval cancer and improve survival of CRC in addition to improvement of the ADR. A cost reduction by differentiating hyperplastic polyps and leaving them in situ is already being discussed.