Real-Time Artificial Intelligence Assissted Colonoscopy to Identify and Classify Polyps

Central South University

Status: Completed

Conditions: Quality Control; Artificial Intelligence; Colonoscopy

Treatments: Diagnostic Test: Classified DeFrame; Diagnostic Test: DeFrame; Diagnostic Test: conventional colonoscopy

Study type: Interventional

Funder types: Other

Identifiers

NCT05718193

202112254

Details and patient eligibility

About

To investigate the degree of the real-time detection and classification system for increasing the adenoma detection rate during colonoscopy.

Enrollment: 2,868 patients

Sex: All

Ages: 18 to 85 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

Aged 18 to 85 years old. Colonoscopies for primary CRC screening of the subjects are required.

Exclusion criteria

History of CRC,inflammatory bowel disease, previous colonic resection, antithrombotic therapy precluding polyp resection.

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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2,868 participants in 3 patient groups

The DeFrame Group

Experimental group

Description:

Subjects in the DeFrame group were treated with a real-time computer-aided polyp detection system named DeFrame during colonoscopy.

Treatment:

Diagnostic Test: DeFrame

The Classified DeFrame Group

Experimental group

Description:

Subjects in the Classified DeFrame group were treated with a real-time computer-aided polyp detection and classification system named Classified DeFrame during colonoscopy.

Treatment:

Diagnostic Test: Classified DeFrame

The Control Group

Experimental group

Description:

Subjects in the control group underwent standard colonoscopy.

Treatment:

Diagnostic Test: conventional colonoscopy