Colonic NeoplasmsGENIAL-CONCT04441580
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in a Screening Setting
A study testing CADe colonoscopy using GI Genius device in people with Colonic Neoplasms and Colonic Adenocarcinoma, run by Fondazione Poliambulanza Istituto Ospedaliero at 1 site in Italy.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 50 to 69 years
- Conditions the study is for
- Colonic Neoplasms, Colonic Adenocarcinoma, Polyps of Colon
- What is being tested?
- CADe colonoscopy using GI Genius device
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 900 participants
- Where
- 1 siteItaly
- Study dates
- 4 May 2020to 31 Dec 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 50 to 69 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- Patients unwilling or unable to give informed consent.
- Patients reporting use of anti-platelet agents or anticoagulants precluding removal of polyps.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: 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).
Read the 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.
- Conditions
- Colonic Neoplasms, Colonic Adenocarcinoma, Polyps of Colon, Rectal Neoplasms, Rectal Adenocarcinoma
- Being tested
- CADe colonoscopy using GI Genius device
- Keywords
- artificial intelligence, colonoscopy, colonic polyps
- Medical subject headings
- Colonic Neoplasms, Colonic Polyps, Rectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CADe colonoscopy using GI Genius deviceDevice
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.
| Study group | Role | What they receive |
|---|---|---|
| Artificial intelligence arm | Experimental | Patients undergoing colonoscopy with artificial intelligence. Receives: Device: CADe colonoscopy using GI Genius device |
| standard colonoscopy arm | Active comparator | Patients undergoing colonoscopy with standard colonscopy Receives: Device: CADe colonoscopy using GI Genius device |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: When available the histological report of polyps removed (up to 3 weeks).
Secondary outcomes (9)
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: Immediately after the procedure.
Learning curve.
The above-mentioned outcomes will be calculated for each endoscopist at 3, 6, 9 and 12 months.
Measured: 3, 6, 9 and 12 months.
Patient experience
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.
Measured: Immediately after the procedure.
Specific contribution of AI
Proportion of patients diagnosed with polyps which were detected only by Artificial intelligence
Measured: Immediately after the procedure.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jun 2020
- Study start4 May 2020
- Primary completion31 Oct 2023
- Study completion31 Dec 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Colonic NeoplasmsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 900 participants (actual)
Sponsor and investigators
- Lead sponsor
- Fondazione Poliambulanza Istituto Ospedaliero
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Cristiano Spada, MD, PhD, Principal investigator, Fondazione Poliambulanza Istituto Ospedaliero
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04441580
- Sponsor's protocol ID
- GENIAL-CO 2.0 del 09/01/2020
- Acronym
- GENIAL-CO
- Status last verified
- Dec 2023
- First submitted
- 9 Jun 2020
- Last updated
- 10 Apr 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Spada C, Cesaro P, Fuccio L, Salvi D, Ferrari C, Barbaro F, Bizzotto A, Butitta F, Gerardi V, Lovera M, Milluzzo SM, Minelli Grazioli L, Olivari N, Pecere S, Piccirelli S, Pugliano CL, Pesatori EV, Quadarella A, Tettoni E, Zani C, Ricciardiello L, Costamagna G. Impact of Artificial Intelligence for Detection of Precancerous Colonic Lesions in a Fecal Immunochemical Blood Test-Based Organized Screening Program in Italy: A Randomized Control Trial. United European Gastroenterol J. 2026 Feb;14(1):e70176. doi: 10.1002/ueg2.70176.
PubMed 41563802
Study at a glance
From the registry record, last updated by the sponsor on 10 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Resa Diagnostica Aggiuntiva Dell'Intelligenza Artificiale Nella Colonscopia (GENIAL COLONOSCOPY), Per lo Screening Del Carcinoma Colorettale
- ClinicalTrials.gov ID
- NCT04441580
- Acronym / sponsor ID
- GENIAL-CO / GENIAL-CO 2.0 del 09/01/2020
- Conditions
- Colonic Neoplasms, Colonic Adenocarcinoma, Polyps of Colon, Rectal Neoplasms, Rectal Adenocarcinoma
- Keywords
- artificial intelligence, colonoscopy, colonic polyps
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 900 participants (actual)
- Lead sponsor
- Fondazione Poliambulanza Istituto OspedalieroUniversity, hospital or other
- Study start
- 4 May 2020 (actual)
- Primary completion
- 31 Oct 2023 (actual)
- Study completion
- 31 Dec 2023 (actual)
- First posted
- 22 Jun 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
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 design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Artificial intelligence arm | Experimental | Device: CADe colonoscopy using GI Genius devicePatients undergoing colonoscopy with artificial intelligence. |
| standard colonoscopy arm | Active comparator | Device: CADe colonoscopy using GI Genius devicePatients undergoing colonoscopy with standard colonscopy |
Who may qualify
- Ages
- 50 to 69 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- 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.
Key exclusion criteria (2 listed)
- Patients unwilling or unable to give informed consent.
- Patients reporting use of anti-platelet agents or anticoagulants precluding removal of polyps.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CADe colonoscopy using GI Genius deviceWe 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. | Device | Artificial intelligence arm, standard colonoscopy arm |
Primary outcome
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.
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.
9 secondary outcomes
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).
Size of lesions detected
Time frame: Immediately after the procedure.
Rate of neoplasia by colonic site
Time frame: Immediately after the procedure.
Post-colonoscopy surveilance
Time frame: When available the histological report of polyps removed (up to 3 weeks).
Time of cecal intubation.
Time frame: Immediately after the procedure.
Withdrawal and total procedure time.
Time frame: Immediately after the procedure.
Learning curve.
Time frame: 3, 6, 9 and 12 months.
Patient experience
Time frame: Immediately after the procedure.
Specific contribution of AI
Time frame: Immediately after the procedure.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Apr 2025.
- Derived from this study: PubMed 41563802Spada C, Cesaro P, Fuccio L, Salvi D, Ferrari C, Barbaro F, Bizzotto A, Butitta F, Gerardi V, Lovera M, Milluzzo SM, Minelli Grazioli L, Olivari N, Pecere S, Piccirelli S, Pugliano CL, Pesatori EV, Quadarella A, Tettoni E, Zani C, Ricciardiello L, Costamagna G. Impact of Artificial Intelligence for Detection of Precancerous Colonic Lesions in a Fecal Immunochemical Blood Test-Based Organized Screening Program in Italy: A Randomized Control Trial. United European Gastroenterol J. 2026 Feb;14(1):e70176. doi: 10.1002/ueg2.70176.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Cristiano Spada, MD, PhD principal investigator
Fondazione Poliambulanza Istituto Ospedaliero
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing CADe colonoscopy using GI Genius device in people with Colonic Neoplasms and Colonic Adenocarcinoma, run by Fondazione Poliambulanza Istituto Ospedaliero at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 10 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Rate of advanced adenomas (time frame: When available the histological report of polyps removed (up to 3 weeks).). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04441580, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Apr 2025.