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%).

Introduction Cystic pancreatic neoplasms (CPN) are frequently diagnosed due to better diagnostic techniques and patients becoming older. However, diagnostic accuracy of endoscopic ultrasound (EUS) and value of follow-up are still unclear. Material and Methods The aim of our retrospective study was to investigate the frequency of different cystic pancreatic neoplasms (intraductal papillary mucinous neoplasm [IPMN], serous and mucinous cystadenoma, solid pseudopapillary neoplasia), diagnostic accuracy, size progression, and rate of malignancy using EUS in a tertiary reference center in Germany. Between January 1, 2012 and December 31, 2018, 455 patients were diagnosed with cystic pancreatic lesions (798 EUS examinations). Results Endoscopic ultrasound diagnosed 223 patients with cystic pancreatic neoplasms, including 138 (61.9%) patients with branch duct IPMN, 16 (7.2%) with main duct IPMN, and five (2.2%) with mixed-type IPMN. In the largest subgroup of branch duct IPMN, cysts were size progressive in 20 patients (38.5%). Fine needle aspiration (FNA) was performed in 21 patients, and confirmed the suspected diagnosis in 12/21 patients. 28 surgical resections were performed, in 7/28 patients (25%), high-grade dysplasia or cancer was diagnosed. Endoscopic ultrasound diagnosis of serous and mucinous cystic pancreatic neoplasms was correct in 68.4%. Conclusions Endoscopic ultrasound differential diagnosis of CPNs is challenging. Even in a tertiary expert center, differentiation of serous and mucinous cystic neoplasia is not guaranteed. Relevant size progression of CPN, however, is rare, as is the rate of malignancy. The data of this study suggest that morphologic criteria to assess pancreatic cysts alone are not sufficient to allow a clear diagnosis. Hence, for the improved assessment of pancreatic cysts, EUS should be combined with additional tests and techniques such as MRT/MRCP, contrast-enhanced EUS, and/or FNA/fine needle biopsy including fluid analysis. The combination and correlation of imaging studies with EUS findings is mandatory.

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