The COMBO CAD Study

Completed

• Conditions: Artificial Intelligence
• Interventions: Device: Artificial Intelligence

• Registration Number: NCT05141409
• Lead Sponsor: Istituto Clinico Humanitas

Brief Summary

Implementation of clinical strategies based on optical diagnosis of \<5 mm colorectal polyps may lead to a substantial saving of economic and financial resources. Despite this, 84.2% of European endoscopists reported not to use such strategies - also named as leave-in situ and resect- and-discard - in their practice due to the fear of an incorrect optical diagnosis.

Indeed, accuracy of optical diagnosis is operator-dependent, and values reported in the community setting are below the safety thresholds proposed for its incorporation in clinical practice.

Artificial intelligence (AI) is being increasingly explored in different domains of medicine, particularly those entailing image analysis. As optical diagnosis involves subitaneous processing of multiple images, searching for specific visual clues, and recognizing well-defined visual patterns, AI systems has the potential to help endoscopists in distinguish neoplastic from non-neoplastic polyps, making the characterization process more reliable and objective. Computer-Aided-Diagnosis systems aiming at characterization are called CADx.

Preliminary data on CADx showed a high feasibility and accuracy of AI for optical diagnosis of colorectal polyp, and initial experiences in clinical practice confirmed preliminary results.

To assess the potential benefit and risk of AI-assisted optical diagnosis with standard colonoscopy, we exploited two new Computer-Aided-Diagnosis systems (CAD-EYE® Fujifilm Co., and GI-Genius® Medtronic) that provide the endoscopist with a real-time polyp characterization without the need of optical magnification.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2021-11-19
• Study First Submitted QC: 2021-11-19
• Study First Posted: 2021-12-02
• Study Start: 2022-01-26
• Primary Completion: 2022-09-30
• Study Completion: 2022-09-30
• Status Verified: 2022-12
• Last Update Submitted: 2022-12-28
• Last Update Posted: 2022-12-29

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 500

Inclusion Criteria

• All patients aged 40 or older undergoing a colonoscopy for gastrointestinal symptoms, fecal immunohistochemical test positivity, primary screening or post-polypectomy surveillance

Exclusion Criteria

• subjects with personal history of CRC, or IBD.
• Subjects affected with Lynch syndrome or Familiar Adenomatous Polyposis.
• patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale < 2 in any colonic segment).
• patients with previous colonic resection.
• patients on antithrombotic therapy, precluding polyp resection.
• patients who were not able or refused to give informed written consent.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
CAD-A	Artificial Intelligence	-
CAD-B	Artificial Intelligence	-

Primary Outcome Measures

Name	Time	Method
AI-assisted optical diagnosis performance	6 Months	AI-assisted optical diagnosis performance

Secondary Outcome Measures

Name	Time	Method
AI alone optical diagnosis performance	6 Months	AI alone optical diagnosis performance

Trial Locations

Locations (1)

Department of Gastroenterology, Humanitas Research Hospital; 🇮🇹 Rozzano, Milano, Italy