Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps

Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps: a Prospective Randomized Cohort Study

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

Study Overview

• Status: Unknown
• Conditions: Artificial Intelligence; Colonoscopy
• Intervention / Treatment: Device: Artificial intelligence assisted colonoscopy

Detailed 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.

• Study Type: Interventional
• Enrollment (Anticipated): 560
• Phase: Not Applicable

Contacts and Locations

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China
      • Recruiting
      • Nanfang Hospital
      • Contact: YI ZHANG, master degree; Phone Number: +86 13533787871

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 80 years (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

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)

Study Plan

How is the study designed?

Design Details

• Primary Purpose: DIAGNOSTIC
• Allocation: RANDOMIZED
• Interventional Model: PARALLEL
• Masking: NONE

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
NO_INTERVENTION: Routine colonoscopy group; The patient underwent routine colonoscopy.
EXPERIMENTAL: Artificial intelligence assisted colonoscopy group; The real-time automatic polyp detection system was used to assist the endoscopist.	Device: Artificial intelligence assisted colonoscopy; The colonoscopy is connected to the real-time polyp detection system. If the polyp is detected by enteroscopy, the alarm will be given.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Detection rate of small polyps (diameter < 6mm)	In each group, the number of patients with small polyps was detected as a percentage of the total number of patients.	6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of polyps detected	Number of polyps found in each group.	6 months
Polyp size	Average size of all polyps detected in each group.	6 months
Polyp morphology	Morphological classification of all polyps detected in each group.	6 months

Collaborators and Investigators

• Sponsor: Side Liu
• Investigators: Principal Investigator: side liu, doctor degree, Chief Physician

Publications and helpful links

General Publications

• Luo Y, Zhang Y, Liu M, Lai Y, Liu P, Wang Z, Xing T, Huang Y, Li Y, Li A, Wang Y, Luo X, Liu S, Han Z. Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study. J Gastrointest Surg. 2021 Aug;25(8):2011-2018. doi: 10.1007/s11605-020-04802-4. Epub 2020 Sep 23.

Study record dates

Study Major Dates

• Study Start (ACTUAL): September 1, 2019
• Primary Completion (ANTICIPATED): April 30, 2020
• Study Completion (ANTICIPATED): August 31, 2020

Study Registration Dates

• First Submitted: October 11, 2019
• First Submitted That Met QC Criteria: October 14, 2019
• First Posted (ACTUAL): October 15, 2019

Study Record Updates

• Last Update Posted (ACTUAL): January 2, 2020
• Last Update Submitted That Met QC Criteria: December 30, 2019
• Last Verified: December 1, 2019

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathological Conditions, Anatomical; Polyps; Intestinal Polyps; Colonic Polyps
• Other Study ID Numbers: NCT201908-K5-01

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No