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

Primary Purpose

Colonic Neoplasms, Colonic Adenocarcinoma, Polyps of Colon

Status
Unknown status
Phase
Not Applicable
Locations
Italy
Study Type
Interventional
Intervention
CADe colonoscopy using GI Genius device
Sponsored by
Fondazione Poliambulanza Istituto Ospedaliero
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional screening trial for Colonic Neoplasms focused on measuring artificial intelligence, colonoscopy, colonic polyps

Eligibility Criteria

50 Years - 69 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

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.

Sites / Locations

  • Fondazione Poliambulanza Istituto OspedalieroRecruiting

Arms of the Study

Arm 1

Arm 2

Arm Type

Experimental

Active Comparator

Arm Label

Artificial intelligence arm

standard colonoscopy arm

Arm Description

Patients undergoing colonoscopy with artificial intelligence.

Patients undergoing colonoscopy with standard colonscopy

Outcomes

Primary Outcome Measures

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.
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.

Secondary Outcome Measures

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.
Size of lesions detected
The size of lesion detected will be measured in millimiters and compared between the groups.
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.
Post-colonoscopy surveilance
the time interval, expressed in years, to the next suggested follow-up colonoscopy will be assessed and compared between the groups.
Time of cecal intubation.
The time to reach the cecum will be measured in minutes, recorded and compared between the groups.
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.
Learning curve.
The above-mentioned outcomes will be calculated for each endoscopist at 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.
Specific contribution of AI
Proportion of patients diagnosed with polyps which were detected only by Artificial intelligence

Full Information

First Posted
June 9, 2020
Last Updated
September 22, 2021
Sponsor
Fondazione Poliambulanza Istituto Ospedaliero
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1. Study Identification

Unique Protocol Identification Number
NCT04441580
Brief Title
Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in a Screening Setting
Acronym
GENIAL-CO
Official Title
Resa Diagnostica Aggiuntiva Dell'Intelligenza Artificiale Nella Colonscopia (GENIAL COLONOSCOPY), Per lo Screening Del Carcinoma Colorettale
Study Type
Interventional

2. Study Status

Record Verification Date
September 2021
Overall Recruitment Status
Unknown status
Study Start Date
May 4, 2020 (Actual)
Primary Completion Date
August 1, 2022 (Anticipated)
Study Completion Date
August 31, 2022 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Fondazione Poliambulanza Istituto Ospedaliero

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No

5. Study Description

Brief 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. 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colonic Neoplasms, Colonic Adenocarcinoma, Polyps of Colon, Rectal Neoplasms, Rectal Adenocarcinoma
Keywords
artificial intelligence, colonoscopy, colonic polyps

7. Study Design

Primary Purpose
Screening
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
600 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Artificial intelligence arm
Arm Type
Experimental
Arm Description
Patients undergoing colonoscopy with artificial intelligence.
Arm Title
standard colonoscopy arm
Arm Type
Active Comparator
Arm Description
Patients undergoing colonoscopy with standard colonscopy
Intervention Type
Device
Intervention Name(s)
CADe colonoscopy using GI Genius device
Intervention Description
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.
Primary Outcome Measure Information:
Title
Rate of advanced adenomas
Description
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.
Time Frame
When available the histological report of polyps removed (up to 3 weeks).
Title
Rate of patients detected with 3 or more adenomas.
Description
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.
Time Frame
When available the histological report of polyps removed (up to 3 weeks).
Secondary Outcome Measure Information:
Title
Overall adenoma and polyp detection rate, flat adenoma and serrated polyps/adenomas.
Description
The percentage of adenomas, polyps (in general), flat adenoma and serrated polyps/adenoma detected will be recorded and compared between the groups.
Time Frame
When available the histological report of polyps removed (up to 3 weeks).
Title
Size of lesions detected
Description
The size of lesion detected will be measured in millimiters and compared between the groups.
Time Frame
Immediately after the procedure.
Title
Rate of neoplasia by colonic site
Description
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.
Time Frame
Immediately after the procedure.
Title
Post-colonoscopy surveilance
Description
the time interval, expressed in years, to the next suggested follow-up colonoscopy will be assessed and compared between the groups.
Time Frame
When available the histological report of polyps removed (up to 3 weeks).
Title
Time of cecal intubation.
Description
The time to reach the cecum will be measured in minutes, recorded and compared between the groups.
Time Frame
Immediately after the procedure.
Title
Withdrawal and total procedure time.
Description
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.
Time Frame
Immediately after the procedure.
Title
Learning curve.
Description
The above-mentioned outcomes will be calculated for each endoscopist at 3, 6, 9 and 12 months.
Time Frame
3, 6, 9 and 12 months.
Title
Patient experience
Description
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.
Time Frame
Immediately after the procedure.
Title
Specific contribution of AI
Description
Proportion of patients diagnosed with polyps which were detected only by Artificial intelligence
Time Frame
Immediately after the procedure.

10. Eligibility

Sex
All
Minimum Age & Unit of Time
50 Years
Maximum Age & Unit of Time
69 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
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.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Sebastian Manuel Milluzzo, MD
Phone
+39 0303515373
Email
sebastian.m.milluzzo@gmail.com
First Name & Middle Initial & Last Name or Official Title & Degree
Paola Cesaro, MD, PhD
Phone
+39 0303515372
Email
paola.cesaro@poliambulanza.it
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Cristiano Spada, MD, PhD
Organizational Affiliation
Fondazione Poliambulanza Istituto Ospedaliero
Official's Role
Principal Investigator
Facility Information:
Facility Name
Fondazione Poliambulanza Istituto Ospedaliero
City
Brescia
Country
Italy
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Sebastian Manuel Milluzzo, MD
Phone
+39 030 3515372
Email
sebastian.m.milluzzo@gmail.com
First Name & Middle Initial & Last Name & Degree
Paola Cesaro, MD, Phd
Phone
+39 030 3515373
Email
paola.cesaro@poliambulanza.it

12. IPD Sharing Statement

Learn more about this trial

Assessing the Additional Neoplasia Yield of Computer-aided Colonoscopy in a Screening Setting

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