- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04441580
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in a Screening Setting (GENIAL-CO)
Resa Diagnostica Aggiuntiva Dell'Intelligenza Artificiale Nella Colonscopia (GENIAL COLONOSCOPY), Per lo Screening Del Carcinoma Colorettale
Even if colonoscopy is considered the reference standard for the detection of colonic neoplasia, polyps are still missed. The risk of early post-colonoscopy cancer appeared to be independently predicted by a relatively low polyp/adenoma detection rate. 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. Artificial intelligence 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 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).
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Even 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
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Sebastian Manuel Milluzzo, MD
- Phone Number: +39 0303515373
- Email: sebastian.m.milluzzo@gmail.com
Study Contact Backup
- Name: Paola Cesaro, MD, PhD
- Phone Number: +39 0303515372
- Email: paola.cesaro@poliambulanza.it
Study Locations
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-
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Brescia, Italy
- Recruiting
- Fondazione Poliambulanza Istituto Ospedaliero
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Contact:
- Sebastian Manuel Milluzzo, MD
- Phone Number: +39 030 3515372
- Email: sebastian.m.milluzzo@gmail.com
-
Contact:
- Paola Cesaro, MD, Phd
- Phone Number: +39 030 3515373
- Email: paola.cesaro@poliambulanza.it
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Patients aged 50 to 69 undergoing colonoscopy examination following a positive fecal immunochemical test (FIT) 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: Screening
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Artificial intelligence arm
Patients undergoing colonoscopy with artificial intelligence.
|
We wanted to compare the diagnostic yield obtained by using CADe colonoscopy to the yield obtained by the standard colonoscopy (SC) in a FIT-positive screening population.
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Active Comparator: standard colonoscopy arm
Patients undergoing colonoscopy with standard colonscopy
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We wanted to compare the diagnostic yield obtained by using CADe colonoscopy to the yield obtained by the standard colonoscopy (SC) in a FIT-positive screening population.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Rate of advanced adenomas
Time Frame: When available the histological report of polyps removed (up to 3 weeks).
|
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.
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When available the histological report of polyps removed (up to 3 weeks).
|
Rate of patients detected with 3 or more adenomas.
Time Frame: When available the histological report of polyps removed (up to 3 weeks).
|
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.
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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.
Time Frame: When available the histological report of polyps removed (up to 3 weeks).
|
The percentage of adenomas, polyps (in general), flat adenoma and serrated polyps/adenoma detected will be recorded and compared between the groups.
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When available the histological report of polyps removed (up to 3 weeks).
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Size of lesions detected
Time Frame: Immediately after the procedure.
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The size of lesion detected will be measured in millimiters and compared between the groups.
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Immediately after the procedure.
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Rate of neoplasia by colonic site
Time Frame: Immediately after the procedure.
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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.
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Immediately after the procedure.
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Post-colonoscopy surveilance
Time Frame: When available the histological report of polyps removed (up to 3 weeks).
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the time interval, expressed in years, to the next suggested follow-up colonoscopy will be assessed and compared between the groups.
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When available the histological report of polyps removed (up to 3 weeks).
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Time of cecal intubation.
Time Frame: Immediately after the procedure.
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The time to reach the cecum will be measured in minutes, recorded and compared between the groups.
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Immediately after the procedure.
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Withdrawal and total procedure time.
Time Frame: Immediately after the procedure.
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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.
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Immediately after the procedure.
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Learning curve.
Time Frame: 3, 6, 9 and 12 months.
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The above-mentioned outcomes will be calculated for each endoscopist at 3, 6, 9 and 12 months.
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3, 6, 9 and 12 months.
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Patient experience
Time Frame: Immediately after the procedure.
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Visual Analogue Scale (VAS) (0 minimum to 10 maximum) will be recorded to assess the pain before and after the colonoscopy and results will be compared between the groups.
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Immediately after the procedure.
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Specific contribution of AI
Time Frame: Immediately after the procedure.
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Proportion of patients diagnosed with polyps which were detected only by Artificial intelligence
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Immediately after the procedure.
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Collaborators and Investigators
Investigators
- Principal Investigator: Cristiano Spada, MD, PhD, Fondazione Poliambulanza Istituto Ospedaliero
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Digestive System Diseases
- Neoplasms by Histologic Type
- Neoplasms by Site
- Carcinoma
- Neoplasms, Glandular and Epithelial
- Gastrointestinal Neoplasms
- Digestive System Neoplasms
- Gastrointestinal Diseases
- Colonic Diseases
- Intestinal Diseases
- Pathological Conditions, Anatomical
- Intestinal Neoplasms
- Rectal Diseases
- Colorectal Neoplasms
- Polyps
- Intestinal Polyps
- Neoplasms
- Adenocarcinoma
- Rectal Neoplasms
- Colonic Polyps
- Colonic Neoplasms
Other Study ID Numbers
- GENIAL-CO 2.0 del 09/01/2020
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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