Ignite Creation Date:
2024-05-06 @ 6:54 PM
Last Modification Date:
2024-10-26 @ 2:56 PM
Study NCT ID:
NCT05822895
Status:
RECRUITING
Last Update Posted:
2023-05-08
First Post:
2023-04-10
Brief Title:
Review of the Impact of a Computer-aided Real-time Polyp Detection System on Adult Colonoscopy
Sponsor:
Sengkang General Hospital
Organization:
Sengkang General Hospital
Study Overview
Official Title:
A Comprehensive Review of the Impact of a COmPuter-aIded reaL-time pOlyp deTection System on Adult Colonoscopy COPILOT Study - a Single Institution Adoption Experience
Status:
RECRUITING
Status Verified Date:
2023-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
COPILOT
Brief Summary:
Background
Removal of adenomatous polyps during colonoscopy is associated with long-term prevention of colorectal cancer-related deaths Recently there have been much interest in the use of artificial intelligence AI platforms to augment the routine endoscopic assessment of the colon to enhance adenoma detection rate ADR To date computer assisted detection of polyps CADe have been shown to be safe with a significant increase in ADR without any concomitant increase in post-procedural complications
Aims
The investigators aim to evaluate the use of GI GeniusTM Intelligent Endoscopy Module in a multi-ethnic Asian population Singapore to increase in ADR and adenoma detected per colonoscopy ADPCto justify its effectiveness as an adjunct in polyp detection and training for colonoscopy
Methods
This study will be a single-institution cohort study conducted over a 2-year period Sengkang General Hospital SKH does an estimated 12500 colonoscopies per year with an average of 1040 colonoscopies performed every month Thus given the case volume the investigators expect to detect differences in ADR amongst endoscopists if any during this study period
As part of the subgroup analysis the investigators also aim to compare the ADR rates of trainee endoscopists with and without the GI GeniusTM Intelligent Endoscopy Module to ascertain its utility as an education tooltraining adjunct
Removal of adenomatous polyps during colonoscopy is associated with long-term prevention of colorectal cancer-related deaths Recently there have been much interest in the use of artificial intelligence AI platforms to augment the routine endoscopic assessment of the colon to enhance adenoma detection rate ADR To date computer assisted detection of polyps CADe have been shown to be safe with a significant increase in ADR without any concomitant increase in post-procedural complications
Aims
The investigators aim to evaluate the use of GI GeniusTM Intelligent Endoscopy Module in a multi-ethnic Asian population Singapore to increase in ADR and adenoma detected per colonoscopy ADPCto justify its effectiveness as an adjunct in polyp detection and training for colonoscopy
Methods
This study will be a single-institution cohort study conducted over a 2-year period Sengkang General Hospital SKH does an estimated 12500 colonoscopies per year with an average of 1040 colonoscopies performed every month Thus given the case volume the investigators expect to detect differences in ADR amongst endoscopists if any during this study period
As part of the subgroup analysis the investigators also aim to compare the ADR rates of trainee endoscopists with and without the GI GeniusTM Intelligent Endoscopy Module to ascertain its utility as an education tooltraining adjunct
Detailed Description:
This study will be a single-institution cohort study conducted over a 2-year period The investigators will recruit patients prospectively who would have their colonoscopy performed with AI guidance from the GI Genius which is a standard of care feature in the endoscopy rooms fitted with the GI Genius and compare it against historical data when the AI technology was not available Jan 2018-Jan 2021 This historical data has already been collected as part of a published audit performed for SKHs endoscopy The data collected for this historical cohort are from an anonymised database collected from Operating Theatre Management Unit OTMU who is not involved in the study
For the prospective cohort undergoing AI aided endoscopy 142023 - 3132025
This will include all adult patients going for colonoscopy in the our institution Patients with incomplete or failed colonoscopy flexible sigmoidoscopy colonoscopy done after previous colorectal cancers or previous colonic resections patients with poor bowel preparation when deemed by the endoscopist to have an incomplete assessment of the colon will be excluded from the analysis
patient demographical data procedural related data as well as histology from histological reports from their colonoscopy would be collected by research coordinators in order to ascertain ADR Adenoma Detection Per Colonoscopy ADPC and Polyp Detection Rate PDR
These coordinators are independent of the study team and will not be part of the analysis of the data In order to have an effective barrier for the study team not to be able to identify the patients from the data collected therefore the coordinators act as a trusted independent party who will extractde-identify the data before it is handed to the study team for analysis of the ADR ADPC and PDR The study team will not attempt to re- identify the patients back
Analysis of data
Subsequent analysis will be conducted at every 3 months by reviewing for the absolute ADR and ADPC amongst endoscopists by the study team By comparing these prospectively collected data with the historical cohort data the investigators would be able to evaluate the effectiveness of the GI Genius in improving the ADR PDR and ADPC Cost analysis can also be done to analyse the cost effectiveness of the added AI feature
For the prospective cohort undergoing AI aided endoscopy 142023 - 3132025
This will include all adult patients going for colonoscopy in the our institution Patients with incomplete or failed colonoscopy flexible sigmoidoscopy colonoscopy done after previous colorectal cancers or previous colonic resections patients with poor bowel preparation when deemed by the endoscopist to have an incomplete assessment of the colon will be excluded from the analysis
patient demographical data procedural related data as well as histology from histological reports from their colonoscopy would be collected by research coordinators in order to ascertain ADR Adenoma Detection Per Colonoscopy ADPC and Polyp Detection Rate PDR
These coordinators are independent of the study team and will not be part of the analysis of the data In order to have an effective barrier for the study team not to be able to identify the patients from the data collected therefore the coordinators act as a trusted independent party who will extractde-identify the data before it is handed to the study team for analysis of the ADR ADPC and PDR The study team will not attempt to re- identify the patients back
Analysis of data
Subsequent analysis will be conducted at every 3 months by reviewing for the absolute ADR and ADPC amongst endoscopists by the study team By comparing these prospectively collected data with the historical cohort data the investigators would be able to evaluate the effectiveness of the GI Genius in improving the ADR PDR and ADPC Cost analysis can also be done to analyse the cost effectiveness of the added AI feature
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
True
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
True
Is an FDA AA801 Violation?:
None