S1281 A Comparative Analysis of AI-Assisted vs Traditional Screening and Surveillance Colonoscopies in High-Risk Patients

Introduction: Colonoscopy remains the gold standard for colorectal cancer (CRC) screening, though variability in adenoma detection rates (ADR) among gastroenterologists persists. Recent advances in artificial intelligence (AI), such as computer aided detection (CAD-e) systems, may enhance real-time polyp recognition and reduce ADR variability. This study compares the efficacy between AI-assisted colonoscopy versus traditional colonoscopy in high-risk patients. Methods: We performed a retrospective chart review of screening and surveillance colonoscopies in high-risk patients between February 2023 and September 2024 at a large tertiary academic center. High-risk criteria included personal or family history of CRC or adenomas, inflammatory bowel disease, or genetic syndromes such as familial adenomatous polyposis and Lynch syndrome. Two different CAD-e systems were utilized. We evaluated patient demographics, cecal intubation rate, ADR, number of adenomas identified and removed, and sessile serrated polyp (SSP) detection rate. Categorical variables were analyzed using chi-square test, and continuous variables were analyzed using 2-sided t-tests. Results: 3,023 colonoscopies were analyzed, with CAD-e used in 33.5% of cases. Patients in the AI-assisted cases were 1.9 years older (P < 0.001), had longer withdrawal times (863 vs 789 seconds, P < 0.001), and had higher cecal intubation rates (96.9% vs 94.4%, P < 0.001). AI-assisted cases had a 33% increase in ADR (95% CI 1.24-1.43, P < 0.001). No significant differences were found in detection of adenocarcinomas, advanced neoplasms, or >10 adenomas. However, AI-assisted cases increased the detection rate of hyperplastic polyps, 1-2 adenomas, and 3-10 adenomas (P < 0.001 for each). For SSPs <1 cm, detection increased by 78% (95% CI 1.34-2.36, P < 0.001). Unassisted cases retrieved 0.78 fewer polyps on average compared to AI-assisted (P < 0.001). Conclusion: Use of CAD-e systems may increase ADR in high-risk patients, especially when adenomas are rare and diminutive. Cecal intubation rate is unlikely to be truly affected by use of AI. Age may have impacted the results, as older patients are more likely to have adenomas. Lastly, the use of CAD-e systems may precipitate longer case and withdrawal times due to retrieval of more adenomas and hyperplastic polyps; however, we expect withdrawal times to decrease with improvement in AI technology that facilitates the differentiation between adenomatous and hyperplastic polyps.

Publication Details

Journal
The American Journal of Gastroenterology
Published
2025-10-01
DOI
https://doi.org/10.14309/01.ajg.0001132584.02682.4f
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
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article

S1281 A Comparative Analysis of AI-Assisted vs Traditional Screening and Surveillance Colonoscopies in High-Risk Patients

The American Journal of Gastroenterology
Colorectal Cancer Screening and Detection
article

S1281 A Comparative Analysis of AI-Assisted vs Traditional Screening and Surveillance Colonoscopies in High-Risk Patients

article en

Abstract

Introduction: Colonoscopy remains the gold standard for colorectal cancer (CRC) screening, though variability in adenoma detection rates (ADR) among gastroenterologists persists. Recent advances in artificial intelligence (AI), such as computer aided detection (CAD-e) systems, may enhance real-time polyp recognition and reduce ADR variability. This study compares the efficacy between AI-assisted colonoscopy versus traditional colonoscopy in high-risk patients. Methods: We performed a retrospective chart review of screening and surveillance colonoscopies in high-risk patients between February 2023 and September 2024 at a large tertiary academic center. High-risk criteria included personal or family history of CRC or adenomas, inflammatory bowel disease, or genetic syndromes such as familial adenomatous polyposis and Lynch syndrome. Two different CAD-e systems were utilized. We evaluated patient demographics, cecal intubation rate, ADR, number of adenomas identified and removed, and sessile serrated polyp (SSP) detection rate. Categorical variables were analyzed using chi-square test, and continuous variables were analyzed using 2-sided t-tests. Results: 3,023 colonoscopies were analyzed, with CAD-e used in 33.5% of cases. Patients in the AI-assisted cases were 1.9 years older (P < 0.001), had longer withdrawal times (863 vs 789 seconds, P < 0.001), and had higher cecal intubation rates (96.9% vs 94.4%, P < 0.001). AI-assisted cases had a 33% increase in ADR (95% CI 1.24-1.43, P < 0.001). No significant differences were found in detection of adenocarcinomas, advanced neoplasms, or >10 adenomas. However, AI-assisted cases increased the detection rate of hyperplastic polyps, 1-2 adenomas, and 3-10 adenomas (P < 0.001 for each). For SSPs <1 cm, detection increased by 78% (95% CI 1.34-2.36, P < 0.001). Unassisted cases retrieved 0.78 fewer polyps on average compared to AI-assisted (P < 0.001). Conclusion: Use of CAD-e systems may increase ADR in high-risk patients, especially when adenomas are rare and diminutive. Cecal intubation rate is unlikely to be truly affected by use of AI. Age may have impacted the results, as older patients are more likely to have adenomas. Lastly, the use of CAD-e systems may precipitate longer case and withdrawal times due to retrieval of more adenomas and hyperplastic polyps; however, we expect withdrawal times to decrease with improvement in AI technology that facilitates the differentiation between adenomatous and hyperplastic polyps.

The American Journal of GastroenterologyVol. 120(10S2)
Good health and well-being
Openalex Percentile: Top 33%
Colorectal Cancer Screening and Detection
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