Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Endoscopy ; h5-index 58.0

BACKGROUND AND AIMS : Adenoma detection rate (ADR) varies significantly between endoscopists with up to 26% adenoma miss rate (AMR). Artificial intelligence (AI) systems may improve endoscopic quality and reduce the rate of interval cancer. We evaluated the efficacy of an AI system in real time colonoscopy and its influence on the AMR and the ADR.

PATIENTS AND METHODS : In this prospective non-randomized comparative study we analyzed 150 patients (age 65±14, 69 women, 81 men) undergoing diagnostic colonoscopy at a single endoscopy center in Germany from June to October 2020. Every patient was examined concurrently by an endoscopist and AI using two opposing screens. The AI system GI Genius (Medtronic), overseen by a second observer, was not visible to the endoscopist. AMR was the primary outcome. Both methods were compared by the McNemar Test.

RESULTS : There was no significant and no clinically relevant difference (p=0.754) in AMR between the AI system (6/197, 3.0%, 95%CI [1.1-6.5]) and routine colonoscopy (4/197, 2.0%, 95%CI [0.6-5.1]). The polyp miss rate of the AI system (14/311, 4.5%, 95%CI [2.5-7.4]) was not significantly different (p=0.720) from routine colonoscopy (17/311, 5.5%, 95%CI [3.2-8.6]). There was no significant difference (p=0.500) between the ADR with routine colonoscopy (78/150, 52.0%, 95%CI [43.7-60.2]) and the AI system (76/150, 50.7%, 95%CI [42.4-58.9]). Routine colonoscopy detected adenomas in two patients that were missed by the AI system.

CONCLUSION : The AI system had a comparable performance to experienced endoscopists during real-time colonoscopy with similar high ADR (>50%).

Zippelius Carolin, Alqahtani Saleh A, Schedel Jörg, Brookman-Amissah Dominic, Muehlenberg Klaus, Federle Christoph, Salzberger Andrea, Schorr Wolfgang, Pech Oliver

2021-Jul-22