Artificial Intelligence (AI) Validation Study for Polyp Detection

NCT ID: NCT04378660

Last Updated: 2020-05-07

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 357 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2019-10-30
• Study Completion Date: 2020-04-18

Brief Summary

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

Detailed 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.

Conditions

Polyp of Colon

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: DIAGNOSTIC
• Blinding Strategy: NONE

Study Groups

Intervention arm

Colonoscopy with AI

Group Type: EXPERIMENTAL

Artificial intelligence for polyp detection

Intervention Type: DIAGNOSTIC_TEST

Colonoscopy enriched with artificial intelligence tool developed for polyp detection, implemented as a second observer

Interventions

Artificial intelligence for polyp detection

Colonoscopy enriched with artificial intelligence tool developed for polyp detection, implemented as a second observer

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

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

• Minimum Eligible Age: 16 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Nuovo Regina Margherita Hospital, Rome, Italy

UNKNOWN

Sponsor Role: collaborator

Universitäts Medizin, Mainz, Germany

UNKNOWN

Sponsor Role: collaborator

Universitaire Ziekenhuizen KU Leuven

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Raf Bisschops

Role: PRINCIPAL_INVESTIGATOR

UZ Leuven

Locations

University Hospitals Leuven

Leuven, Vlaams-Brabant, Belgium

Countries

Belgium

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

s59405

Identifier Type: -

Identifier Source: org_study_id