Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

560 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-09-01

Study Completion Date

2020-08-31

Brief Summary

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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

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Detailed Description

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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.

Conditions

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Artificial Intelligence Colonoscopy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Routine colonoscopy group

The patient underwent routine colonoscopy.

Group Type NO_INTERVENTION

No interventions assigned to this group

Artificial intelligence assisted colonoscopy group

The real-time automatic polyp detection system was used to assist the endoscopist.

Group Type EXPERIMENTAL

Artificial intelligence assisted colonoscopy

Intervention Type DEVICE

The colonoscopy is connected to the real-time polyp detection system. If the polyp is detected by enteroscopy, the alarm will be given.

Interventions

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