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Artificial Intelligence Approaches to Assessing Primary Cilia
Published on: May 1, 2021
Taking the Guess Work Out of Endoscopic Polyp Measurement: From Traditional Methods to AI
Anthony Kerbage1, Tarek Souaid1, Kailash Singh2
1Department of Internal Medicine.
Abstract:
Colonoscopy is a crucial tool for evaluating lower gastrointestinal disease, monitoring high-risk patients for colorectal neoplasia, and screening for colorectal cancer. In the United States, over 14 million colonoscopies are performed annually, with a significant portion dedicated to post-polypectomy follow-up. Accurate measurement of colorectal polyp size during colonoscopy is essential, as it influences patient management, including the determination of surveillance intervals, resection strategies, and the assessment of malignancy risk. Despite its importance, many endoscopists typically rely on visual estimation alone, which is often imprecise due to technological and human biases, frequently leading to overestimations of polyp size and unnecessarily shortened surveillance intervals. To address these challenges, multiple tools and technologies have been developed to enhance the accuracy of polyp size estimation. The review examines the evolution of polyp measurement techniques, ranging from through-the-scope tools to computer-based and artificial intelligence-assisted technologies.

