Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in Follow-up Patients in a Screening Setting (GENIAL-CO FU)

The goal of this clinical trial is to evaluate the diagnostic yield of CADe in a consecutive population undergoing colonoscopy. The main question it aims to answer is the Adenoma Detection Rate (ADR). Participants undergoing colonoscopy for follow-up in a screening setting will be randomized in a 1:1 ratio to either receive Computer-Aided Detection (CADe) colonoscopy or a conventional colonoscopy (CC). GI Genius is the AI software that will be used in the present trial and is intended to be used as an adjunct to colonic endoscopy procedures to help endoscopists to detect in real time mucosal lesions (such as polyps and adenomas, including those with flat (non-polypoid) morphology) during standard screening and surveillance endoscopic mucosal evaluations. It is not intended to replace histopathological sampling as a means of diagnosis.Researchers will compare the CADe group and the CC-group to see if CAD-e can increase the ADR significantly.

Study Overview

• Status: Recruiting
• Conditions: Adenoma; Polyp of Colon; Colonic Adenoma
• Intervention / Treatment: Device: CADe colonoscopy using GI Genius device; Device: White light

Detailed Description

en if colonoscopy is considered the reference standard for the detection of colonic neoplasia, polyps are still missed. In large administrative cohort or case-control studies, the risk of early post-colonoscopy cancer appeared to be independently predicted by a relatively low polyp/adenoma detection rate. The adenoma detection rate among different endoscopists has been shown to be strictly related with the risk of post-colonoscopy interval cancer. When considering the very high prevalence of advanced neoplasia in the FIT-positive enriched population, the risk of post-colonoscopy interval cancer due to a suboptimal quality of colonoscopy may be substantial. Available evidence justifies therefore the implementation of efforts aimed at improving adenoma detection rate, based on retraining interventions and on the adoption of innovative technologies, designed to enhance the accuracy of the endoscopic examination.Nowadays, Artificial intelligence (AI) is gaining increased attention and investigation, since it seems to improve the quality of medical diagnosis and treatment. In the field of gastrointestinal endoscopy, two potential roles of AI in colonoscopy have been examined so far: automated polyp detection (CADe) and automated polyp histology characterization (CADx). CADe can minimize the probability of missing a polyp during colonoscopy, thereby improving the adenoma detection rate (ADR) and potentially decreasing the incidence of interval cancer. GI Genius is the AI software that will be used in the present trial. The software is developed by Medtronic Inc. (Dublin, Ireland) and is intended to be used as an adjunct to colonic endoscopy procedures to help endoscopists to detect in real time mucosal lesions (such as polyps and adenomas, including those with flat (non-polypoid) morphology) during standard screening and surveillance endoscopic mucosal evaluations. It is not intended to replace histopathological sampling as a means of diagnosis.

The objective of this study was to compare the diagnostic yield obtained by using CADe colonoscopy to the yield obtained by the standard colonoscopy (SC). As the risk of progression is higher for large than for small adenomas the specific contribution of the new technique in reducing the miss rate of large neoplasms represents an important outcome to be assessed in the study. In addition, given the suggested association of a higher miss-rate of serrated and flat lesions with an increased risk of early post-colonoscopy CRC, the benefit of the new technique in reducing the miss rate of these lesions will be assessed.

• Study Type: Interventional
• Enrollment (Estimated): 1160
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: daniele salvi; Phone Number: 0303515373; Email: daniele.salvi@poliambulanza.it
• Study Contact Backup: Name: Paola Cesaro; Phone Number: 0303515373; Email: paola.cesaro@poliambulanza.it

Study Locations

• Italy
  • Bs
    • Brescia, Bs, Italy, 25124
      • Recruiting
      • Fondazione Poliambulanza
      • Contact: daniele salvi; Phone Number: 0303515373; Email: daniele.salvi@poliambulanza.it
      • Contact: Paola Cesaro; Phone Number: 0303515373; Email: paola.cesaro@poliambulanza.it

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Patients aged 50 to 74 undergoing colonoscopy examination following a prior colonsocopy were polyps were found (follow-up) performed in the context of a regional mass-screening program.

Exclusion Criteria:

• Patients unwilling or unable to give informed consent.
• Patients reporting use of anti-platelet agents or anticoagulants precluding removal of polyps.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Artificial intelligence arm Patients undergoing colonoscopy with artificial intelligence.; Patients undergoing colonoscopy with artificial intelligence.	Device: CADe colonoscopy using GI Genius device; We wanted to compare the diagnostic yield obtained by using CADe colonoscopy to the yield obtained by the standard colonoscopy (SC) in a follow-up pateints in the screening population.
Active Comparator: Conventional Colonoscopy; Standard Colonoscopy with white light	Device: White light; White light endoscopy

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Rate of advanced adenomas	The percentage of patients with adenomas with high-grade displasia in CADe colonoscopy group will be recorded and compared with the rate of patients with adenomas with high-grade displasia in standard colonoscopy group.	When available the histological report of polyps removed (up to 3 weeks).
Rate of patients detected with 3 or more adenomas.	The percentage of patients with 3 or more adenomas (serrated adenomas will also be considered in the calculation) in CADe colonoscopy group will be compared with the rate of patients with 3 or more adenomas (including serrated adenomas) in standard colonoscopy group.	When available the histological report of polyps removed (up to 3 weeks).

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Overall adenoma and polyp detection rate, flat adenoma and serrated polyps/adenomas.	The percentage of adenomas, polyps (in general), flat adenoma and serrated polyps/adenoma detected will be recorded and compared between the groups.	When available the histological report of polyps removed (up to 3 weeks).
Size of lesions detected	The size of lesion detected will be measured in millimiters and compared between the groups.	Immediately after the procedure.
Rate of neoplasia by colonic site	The percentage of patients with neoplasia of proximal (right colonic segments) or distal (left colonic segments and rectum) site will be assessed and compared between the groups.	Immediately after the procedure.
Post-colonoscopy surveilance	the time interval, expressed in years, to the next suggested follow-up colonoscopy will be assessed and compared between the groups.	When available the histological report of polyps removed (up to 3 weeks).
Time of cecal intubation.	The time to reach the cecum will be measured in minutes, recorded and compared between the groups.	Immediately after the procedure.
Withdrawal and total procedure time.	The time of withdrawal (from cecum to anus) and of the overall colonoscopy (from anus to anus) will be measured in minutes, recorded and compared between the groups.	Immediately after the procedure.
Learning curve.	The above-mentioned outcomes will be calculated for each endoscopist at 3, 6, 9 and 12 months.	3, 6, 9 and 12 months.
Specific contribution of AI	Proportion of patients diagnosed with polyps which were detected only by Artificial intelligence	Immediately after the procedure.

Collaborators and Investigators

• Sponsor: Fondazione Poliambulanza Istituto Ospedaliero
• Investigators: Principal Investigator: Cristiano Spada, Fondazione Poliambulanza

Study record dates

Study Major Dates

• Study Start (Actual): December 16, 2020
• Primary Completion (Estimated): March 1, 2024
• Study Completion (Estimated): May 1, 2024

Study Registration Dates

• First Submitted: November 29, 2023
• First Submitted That Met QC Criteria: November 29, 2023
• First Posted (Actual): December 7, 2023

Study Record Updates

• Last Update Posted (Actual): February 23, 2024
• Last Update Submitted That Met QC Criteria: February 22, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Keywords: Follow-up; ADR; CADe
• Additional Relevant MeSH Terms: Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Pathological Conditions, Anatomical; Polyps; Intestinal Polyps; Adenoma; Colonic Polyps
• Other Study ID Numbers: NP4451

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No