Artificial Intelligence-assisted Colonoscopy for Detection of Colon Polyps

NCT04126265 | Unknown

• 1 other identifier: NCT201908-K5-01
• Study Type: interventional
• Target: 560
• Locations: 1 country
• Sites: 1

Brief Summary

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

Conditions

Artificial Intelligence; Colonoscopy

Outcome Measures

Primary Outcomes (1)

• 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 Outcomes (3)

• Number of polyps detected

  6 months

• Polyp size

  6 months

• Polyp morphology

  6 months

Study Arms (2)

Routine colonoscopy group

NO INTERVENTION

The patient underwent routine colonoscopy.

Artificial intelligence assisted colonoscopy group

EXPERIMENTAL

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

Device: Artificial intelligence assisted colonoscopy

Interventions

Artificial intelligence assisted colonoscopy DEVICE

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

Artificial intelligence assisted colonoscopy group

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

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

You may not qualify if:

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

Sponsors & Collaborators

• Side Liu: lead

Study Sites (1)

Nanfang Hospital

Guangzhou, Guangdong, China

RECRUITING

Related Publications (1)

• 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.

  PMID: 32968933 DERIVED

Study Officials

• side liu, doctor degree

  Chief physician

  PRINCIPAL INVESTIGATOR

Central Study Contacts

YI zhang, master degree

CONTACT

+86 13533787871; 13533787871@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: professor

Study Record Dates

• First Submitted: October 11, 2019
• First Posted: October 15, 2019
• Study Start: September 1, 2019
• Primary Completion: April 30, 2020
• Study Completion: August 31, 2020
• Last Updated: January 2, 2020

Record last verified: 2019-12

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)