ClinicalTrials.Veeva

Menu

Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps

S

Side Liu

Status

Unknown

Conditions

Artificial Intelligence
Colonoscopy

Treatments

Device: Artificial intelligence assisted colonoscopy

Study type

Interventional

Funder types

Other

Identifiers

NCT04126265
NCT201908-K5-01

Details and patient eligibility

About

All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.

A total of four endoscopists were included in the study, two in each group of senior endoscopists and two in each group of junior endoscopists.

Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed back to back by different endoscopy physicians with the same seniority.

All patients were examined and treated according to routine medical procedures. The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process

Full description

This is a prospective randomized clinical study.This study was conducted in the Endoscopy Center of the Nanfang Hospital, China. Routine bowel preparation consisted of 4 L of polyethylene glycol, given in split doses. Colonoscopies were performed with high definition colonoscopes and high-definition monitors.

All subjects shall sign informed consent before screening, and subjects shall be included according to inclusion and exclusion criteria.

A total of four endoscopists were included in the study, two in each group of senior endoscopists (>1000 colonoscopies) and two in each group of junior endoscopists ( <1000 colonoscopies).

Patients were randomly enrolled into the senior endoscopy group and the junior endoscopy group, and received artificial intelligence assisted colonoscopy and conventional colonoscopy successively. The two colonoscopy methods were performed by different endoscopy physicians back to back with the same seniority.

All patients were examined and treated according to routine medical procedures (outpatient patients and inpatients who did not sign the consent form for polypectomy were not resected for the lesions detected during the examination, while inpatients who signed the consent form for polypectomy were left in the original position after the first colonoscopy and removed at the end of the second examination).

The routine colonoscopy group and the artificial-intelligence-assisted colonoscopy group made detailed records of the patients' withdrawal time, entry time, number of polyps detected, polyp Paris classification, polyp size, polyp shape, polyp location and intestinal preparation during the colonoscopy process.

Enrollment

560 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

Chinese population aged 18-80 years old; Patients voluntarily signed informed consent form; In accordance with the indications of colonoscopy.

Exclusion criteria

(IBD) history of inflammatory bowel disease; History of colorectal surgery; Previous failed colonoscopy; Polyposis syndrome; Highly suspected colorectal cancer (CRC)

Trial design

Primary purpose

Diagnostic

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

560 participants in 2 patient groups

Routine colonoscopy group
No Intervention group
Description:
The patient underwent routine colonoscopy.
Artificial intelligence assisted colonoscopy group
Experimental group
Description:
The real-time automatic polyp detection system was used to assist the endoscopist.
Treatment:
Device: Artificial intelligence assisted colonoscopy

Trial contacts and locations

1

Loading...

Central trial contact

YI zhang, master degree

Data sourced from clinicaltrials.gov

Clinical trials

Find clinical trialsTrials by location
© Copyright 2026 Veeva Systems