NCT06715384

Brief Summary

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.

Trial Health

57
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Trial has exceeded expected completion date
Enrollment
168

participants targeted

Target at P75+ for not_applicable

Timeline
Completed

Started Dec 2024

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

November 26, 2024

Completed
8 days until next milestone

First Posted

Study publicly available on registry

December 4, 2024

Completed
11 days until next milestone

Study Start

First participant enrolled

December 15, 2024

Completed
4 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 1, 2025

Completed
29 days until next milestone

Study Completion

Last participant's last visit for all outcomes

April 30, 2025

Completed
Last Updated

February 19, 2025

Status Verified

November 1, 2024

Enrollment Period

4 months

First QC Date

November 26, 2024

Last Update Submit

February 15, 2025

Conditions

Keywords

Artificial IntelligencePolyp SizeDeep LearningColonoscopyDepth Map

Outcome Measures

Primary Outcomes (1)

  • Evaluation of the computer-aided measuring (CAM) system

    To evaluate the relative accuracies of the computer-aided measuring (CAM) system measurement (Autonomous AI measurement and AI-assisted human measurement), non-scaled device (open biopsy forceps or snare) assessment or visual assessment for measuring polyp size compared to with measurement of freshly resected polyp specimens by a digital vernier caliper as reference standard. Relative accuracy is defined as "\[1-(CAM system measurement - ground truth measurement)/ground truth measurement\] x100%". Scale: 0-100. Higher score is a better outcome.

    7 days

Secondary Outcomes (5)

  • video-based analysis

    7 days

  • Reliability between CAM system measurement and ground truth measurement

    7 days

  • Time taken for polyp size measurement

    7 days

  • Percentage differences between the AI-assisted human measurement and non-scaled device assessment

    7 days

  • Instances of overestimation or underestimation by the AI-assisted human measurement and non-scaled device assessment

    7 days

Study Arms (2)

Polyp size measurement with Artificial intelligence (AI)

EXPERIMENTAL

Colonoscopies will be performed according to the standard of care. Patients will have colonoscopies performed using the computer-aided measuring (CAM) system. All measured fresh polyp specimens will be immediately sized in vitro as the ground truth.

Diagnostic Test: Polyp size measurement using autonomous AI measurement or AI-assisted human measurement with the CAM system

Polyp size measurement without AI

NO INTERVENTION

Colonoscopies will be performed according to the standard of care without the CAM system. Patients will undergo a standard colonoscopy. Polyp size measurement will be assessed visually and non-scaled device (open biopsy forceps or snare). All measured fresh polyp specimens will be immediately sized in vitro as the ground truth.

Interventions

The study of real-time polyp size measurement using the CAM system will be conducted in two phases. Phase I (pilot phase, n=24 polyps, about 27 patients) will be used to assess the feasibility of applying the CAM system in real-time in a clinical video in order to obtain pilot data on the relative accuracy of assessing polyp sizes using autonomous AI measurement and AI-assisted human measurement and to determine the relative accuracy of assessing polyp size in Phase II of the study ( Randomized Controlled Trial) to assess the sample size and reference standards for the CAM system. The sample size for the second phase of the randomized controlled trial (comparing AI-assisted human measurement to non-scaled device) will be based on pilot data in order to compare the relative accuracy of polyp size measurement with AI-assisted human measurement versus non-scaled device in clinical practice.

Also known as: Polyp size measurement with the CAM system
Polyp size measurement with Artificial intelligence (AI)

Eligibility Criteria

Age18 Years - 85 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Changhai Hospital, Naval Medical University

Shanghai, Shanghai Municipality, 200433, China

RECRUITING

Related Publications (32)

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Study Officials

  • Sheng-Bing Zhao, MD

    Department of Gastroenterology, National Clinical Research Center for Digestive Diseases, Changhai Hospital, Naval Medical University, Shanghai 200433, China.

    PRINCIPAL INVESTIGATOR
  • Yu Bai, MD

    Department of Gastroenterology, National Clinical Research Center for Digestive Diseases, Changhai Hospital, Naval Medical University, Shanghai 200433, China.

    STUDY DIRECTOR
  • En-Da Yu, MBBS

    Department of Colorectal Surgery and Gastrointestinal Endoscopy Center, Changhai hospital, Naval Medical University, Shanghai 200433, China.

    STUDY DIRECTOR
  • Zhao-Shen Li, MD, PhD

    Department of Gastroenterology, National Clinical Research Center for Digestive Diseases, Changhai Hospital, Naval Medical University, Shanghai 200433, China.

    STUDY CHAIR

Central Study Contacts

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
PARTICIPANT
Masking Details
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.
Purpose
DIAGNOSTIC
Intervention Model
FACTORIAL
Model Details: prospective, multi-endoscopist, single-center or multi- centers
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Director of Gastroenterology Dept and Digestive Endoscopy Center

Study Record Dates

First Submitted

November 26, 2024

First Posted

December 4, 2024

Study Start

December 15, 2024

Primary Completion

April 1, 2025

Study Completion

April 30, 2025

Last Updated

February 19, 2025

Record last verified: 2024-11

Data Sharing

IPD Sharing
Will share

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.

Locations