Artificial Intelligence (AI) Validation Study for Polyp Detection

Universitaire Ziekenhuizen KU Leuven

Status: Completed

Conditions: Polyp of Colon

Treatments: Diagnostic Test: Artificial intelligence for polyp detection

Study type: Interventional

Funder types: Other

Identifiers

NCT04378660

s59405

Details and patient eligibility

About

Interventional prospective multicenter study: Polyp detection by an automated endoscopic tool as second observer during routine diagnostic colonoscopy

Full description

This is an investigator-initiated multicentre non-randomized prospective interventional trial to validate the performance of a novel state-of-the-art computer-aided diagnostic (CAD) tool in polyp detection implemented as second observer during routine diagnostic colonoscopy and to evaluate its feasibility in daily endoscopy. Patients referred for a screening surveillance or therapeutic colonoscopy will undergo a colonoscopy performed by an endoscopist with moderate to high adenoma detection rate (ADR > 20% and < 50%) while a second observer will follow the procedure on a bedside AI-tool to count the number of detections made by the AI system and categorize the results into positive or negative results as follows (1) true positive, (2) false negative, (3) other positive and (4) obvious false positive. When a doubtful detection is made by the AI-system, the second observer will ask to re-evaluate the indicated region. When the detection is clear, the endoscopist and second observer do not communicate. The entire procedure is recorded.

Enrollment: 357 patients

Sex: All

Ages: 16+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• > 18 years
• Diagnostic or screening colonoscopy
• Therapeutic colonoscopy

Exclusion criteria

• Inability to give informed consent by the patient or legal representative
• < 18 years old
• Any contraindication for colonoscopy or biopsies of the colon
• Uncontrolled coagulopathy
• Confirmed diagnosis of inflammatory bowel disease
• Short bowel or ileostomy
• Pregnancy

Trial design

Primary purpose: Diagnostic

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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357 participants in 1 patient group

Intervention arm

Experimental group

Description:

Colonoscopy with AI

Treatment:

Diagnostic Test: Artificial intelligence for polyp detection