S1277 Performance of Novel AI Software for Colorectal Adenoma Detection in At-Risk Patient Population

Introduction: Though the field is rapidly developing, there is still a paucity of data on the application of artificial intelligence (AI) in computer-aided detection of colorectal polyps among various patient populations. We aimed to evaluate the effect of the latest generation of AI software on colonoscopy quality metrics within a diverse, at-risk patient population. Methods: AI software (GI Genius, Medtronic) was implemented at our institution in November 2022; the latest generation AI software (ColonPro, Medtronic) was integrated in February 2025. In our safety net healthcare system, colonoscopies are performed for positive stool-based screening tests or symptoms. Three time intervals were evaluated: pre-AI (8/1/22-10/31/22), AI GI Genius (3/1/23-4/30/23), and AI ColonPro (2/15/25-5/27/25). Data on patient demographics, procedure indication, bowel preparation, polyp size, location, and histology were collected. Polyp detection rates (PDR), adenoma detection rates (ADR), advanced ADR (AADR), and non-neoplastic PDR (NNPDR) were calculated. All colonoscopies were performed by or under the supervision of expert endoscopists (>3,000 colonoscopies) with routine “second look” examination or retroflexion in right colon. Results: We evaluated 1018 polyps/829 colonoscopies (278 pre-AI, 285 AI GI Genius, and 266 AI ColonPro). The mean age was 56.6; 63% were Hispanic/Latino. FIT positivity was the most common indication 237/829 (28.6%). Bowel preparation was excellent/good/fair in 780/829 (94.1%) and poor in 49/829 (5.9%). The most common polyp size was <5 mm (643/1018, 63.1%), followed by 5-10 mm (217/1018, 21.3%), >10 mm (129/1018, 12.7%), and unspecified size (29/1018, 2.8%). The PDRs of pre-AI, AI GI Genius, and AI ColonPro groups were 166/278 (59.7%), 161/285 (56.5%, P = 0.44), and 119/266 (44.7%, P = 0.16), respectively. The ADR of pre-AI cohort was 106/278 (38.1%), 114/285 (40.0%, P = 0.65) in AI GI Genius, and 71/266 (26.7%, P = 0.16) in AI ColonPro. AADR for pre-AI was 45/278 (16.2%), 43/285 (15.1%, P = 0.72) for AI GI Genius, and 43/266 (16.2%, P = 0.16) for AI ColonPro, with NNPDRs of 83/278 (30%), 77/285 (27%, P = 0.46), and 72/266 (27%, P = 0.16), respectively. Conclusion: In our experience, the latest generation AI software did not significantly impact colonoscopy quality metrics. Our findings highlight a complex relationship between AI technology, endoscopist experience, and patient factors suggesting the effectiveness of AI may be limited in high-quality diagnostic colonoscopy.