Accurate polyp size measurements are essential for risk stratification, selection of polypectomy techniques, and surveillance interval assignments. Evidence indicated that the clinical implementation of artificial intelligence is an optimal tool to improve the measurement of polyps during colonoscopy. This study aimed to evaluate the performance of a computer-aided measuring (CAM) system (EndoDASS) and compare its accuracy with routine sizing methods during real-time colonoscopy.

This study will be conducted in 2 phases: the first phase will evaluate the value of the application of the computer-aided measuring (CAM) system for polyp size measurement accuracy in a small sample of clinical videos, recording the corresponding clinical videos for CAM measurements after measuring polyp size using real-time visual assessment and non-scaled device (open biopsy forceps or snare) assessment, and comparing the different methods of polyp size measurement through a video-based analysis [Autonomous artificial intelligence (AI) measurement, AI-assisted human measurement, non-scaled device assessment, and visual assessment] with different groups of endoscopists ( experts, gastroenterologists, surgeons, fellows) evaluating the corresponding clinical videos during real-time measurements, to obtain pilot data on the relative accuracy of polyp size measurement when using the CAM system, to test the feasibility of size measurement of freshly resected polyp specimens and to determine the sample size and reference for evaluating the CAM system in the subsequent phases of a randomized controlled trial of the study. The second phase will assess the value of using the AI-assisted human measurement versus the non-scaled device assessment for polyp size measurement accuracy in a clinical randomized controlled trial using a prospective, multicenter, patient-single-blind, randomized controlled trial design in which subjects are randomly assigned to the CAM group and the non-scaled device measurement group in a 1:1 ratio. Each patient will have a maximum of 3 polyps included in the study.

Inclusion Criteria:

1. Adults aged 18-75, any gender; 76-85 years eligible case-by-case based on health status.
2. Colonoscopy screening, surveillance, or diagnostic participants.
3. Informed consent obtained.

Exclusion Criteria:

1. Anticoagulant use (e.g., aspirin, warfarin) within 7 days prior to colonoscopy or coagulopathy.
2. Inflammatory bowel disease.
3. Aronchick score >3 at entry.
4. Incomplete Case Report Form (CRF) data.
5. Emergency colonoscopy.
6. Pregnancy or lactation.
7. Gastrointestinal obstruction.
8. Refusal to participate.

IPD data can be shared with investigators who propose to use the data under the approval of an independent review committee. Data can only be used for the goals specified in the proposal. Data sharing will be implemented between 6-18 months after article publication with a data-sharing agreement signed. Yu Bai can be contacted at the corresponding email.

Randomization will be concealed. The patient will be blind to the assigned groups. The endoscopist will be blind to the allocated groups until the polyp is identified.