A Prospective Study to Evaluate the Performance of a Real-time System in the Estimation of Colorectal Polyp Size (EndoAIM)

Colorectal polyp size is related to the risk of exhibiting advanced histological features. Moreover, polyps larger than 10 mm are associated with an elevated risk of metachronous advanced neoplasia and colorectal cancer (CRC). Consequently, accurate measurement of polyp size, especially at the 10 mm threshold is critical for risk stratification and surveillance intervals. Furthermore, polyp size is also important for the choice of the appropriate resection procedures. Underestimation may lead to delayed diagnosis, thereby increasing the risk of colorectal cancer, while overestimation may result in unnecessary surveillance endoscopies.

Study Overview

• Status: Recruiting
• Conditions: Colonic Polyps; CRC (Colorectal Cancer); Artificial Intelligence (AI)
• Intervention / Treatment: Device: EndoAIM

Detailed Description

Concerns regarding polyp size measurement are increasing. In daily practice, polyp size is mostly estimated based on visual size estimation by the endoscopist, which has proven to be inaccurate, with reported accuracies ranging from 54% to 65%. Furthermore, a prevalent terminal digit preference has been observed, with clustering of size measurements at 5-mm intervals. Additionally, inappropriate surveillance recommendations based on endoscopists' visual assessment have been documented for up to 35% of polyps. Some endoscopists routinely use non-calibrated instruments such as biopsy forceps or polypectomy snares to improve polyp size estimation. However, this approach has proven to be costly and time-consuming. Besides, endoscopes' fisheye lens can lead to size distortions depending on placement of an instrument in the center or periphery of the endoscope image.

AI-assisted systems, such as Virtual Scale Endoscopy (Fujifilm, Tokyo, Japan) and ENDOANGEL-CPS (Renmin Hospital of Wuhan University, Wuhan, China), have been developed to increase the accuracy of polyp size measurement. However, these systems have primarily been tested in video-based studies, which may not accurately reflect real-time conditions. Recently, a new artificial intelligence system (EndoAIM) has been developed that allows polyp size measurement during real-time endoscopy. This system can automatically estimate the diameter of polyps. Preclinical studies have shown promising performance for EndoAIM, with an overall accuracy of 0.98 in discriminating polyp size at the 10 mm threshold. However, its measurement accuracy has not been tested in real patients during real-time endoscopy.

In this research project, we aim to evaluate the measurement accuracy of EndoAIM for estimating colorectal polyp size in real patients during real-time endoscopy.

• Study Type: Interventional
• Enrollment (Estimated): 278
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Louis HS Lau, FRCP; Phone Number: 26370428; Email: louishslau@cuhk.edu.hk
• Study Contact Backup: Name: Felix Sia, MSc; Phone Number: 852-2637-0428; Email: felixsia@cuhk.edu.hk

Study Locations

• Hong Kong
  • Shatin, Hong Kong
    • Recruiting
    • Prince of Wales Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

Subjects are eligible if:

1. They have received colonoscopy for screening, surveillance or symptom investigation;
2. Aged 18 years older or above;
3. Written informed consent obtained.

Exclusion Criteria:

Subjects are excluded if they have:

1. Contraindication to colonoscopy (e.g. intestinal obstruction or perforation)
2. Contraindication or conditions precluding polyp resection (e.g. active gastrointestinal bleeding, uninterrupted anticoagulation or dual antiplatelets)
3. Advanced comorbid conditions (defined as American Society of Anesthesiologists grade 4 or above)

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: ENDOAIM used arm; ENDOAIM will be used during withdrawal phase of colonoscopy	Device: EndoAIM; EndoAIM will be used during the withdrawal process of the colonoscopy

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The primary endpoint is the difference in percentage for each measurement in discriminating polyp size at the 10mm threshold	The primary endpoint is the difference in percentage for each measurement in discriminating polyp size at the 10mm threshold	During the colonoscopy

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The percentage of correctness of each measurement in discriminating polyp size at the 5 mm threshold	The percentage of correctness of each measurement in discriminating polyp size at the 5 mm threshold	During the colonoscopy
The percentage of correct accuracy of measurement	The percentage of correct accuracy of measurement	During the colonoscopy
Proportion of polyps	Proportion of polyps undersized, oversized or accurately sized within 10%	During the colonoscopy
Proportion of subjects	Proportion of subjects with change in surveillance intervals due to change in polyp size measurement, according to the US Multi-Society Task Force (USMSTF) guideline.	During the colonoscopy

Collaborators and Investigators

• Sponsor: Chinese University of Hong Kong
• Investigators: Principal Investigator: Louis HS Lau, FRCP, Chinese University of Hong Kong

Study record dates

Study Major Dates

• Study Start (Actual): May 13, 2025
• Primary Completion (Estimated): May 1, 2027
• Study Completion (Estimated): January 1, 2028

Study Registration Dates

• First Submitted: April 9, 2025
• First Submitted That Met QC Criteria: April 25, 2025
• First Posted (Actual): May 4, 2025

Study Record Updates

• Last Update Posted (Actual): April 23, 2026
• Last Update Submitted That Met QC Criteria: April 20, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: artificial intelligence; polyp size measurement; surveillance intervals
• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Pathological Conditions, Anatomical; Intestinal Diseases; Gastrointestinal Neoplasms; Digestive System Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Colonic Diseases; Polyps; Intestinal Polyps; Pathological Conditions, Signs and Symptoms; Colorectal Neoplasms; Colonic Polyps
• Other Study ID Numbers: 2024.608

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data will not be shared.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No