Real-Time CAD for Colonic Neoplasia: A RCT

Not Applicable

Completed

• Conditions: Colorectal Cancer; Colorectal Neoplasms

• Registration Number: NCT05963724
• Lead Sponsor: Riverside University Health System Medical Center

Brief Summary

This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.

Detailed Description

Failure in polyp detection leads to colon cancer after colonoscopy. Artificial intelligence systems allow real-time computer-aided detection of polyps with high-accuracy. This study will compare GI-Genius, a real-time CAD system to standard colonoscopy in terms of how many colonoscopies detect an adenoma.

Study Timeline

• Study Start: 2022-09-01
• Primary Completion: 2023-03-31
• Study Completion: 2023-05-27
• Status Verified: 2023-07
• Study First Submitted: 2023-07-19
• Study First Submitted QC: 2023-07-19
• Last Update Submitted: 2023-07-19
• Study First Posted: 2023-07-27
• Last Update Posted: 2023-07-27

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 1100

Inclusion Criteria

• Undergoing colonoscopy at RUHS
• Age > 45 years
• No contraindications to colonoscopy

Exclusion Criteria

• Prior history of subtotal colectomy

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Adenoma Detection Rate	1 year

Secondary Outcome Measures

Name	Time	Method
False Neoplasia Rate	1 year
Withdrawal Time	1 year
Adenomas Per Colon	1 year
Sessile Serrated Lesions Per Colon	1 year
Sessile Serrated Lesion Detection Rate	1 year

Trial Locations

Locations (1)

Riverside University Health System; 🇺🇸 Moreno Valley, California, United States