Ignite Creation Date:
2024-05-06 @ 12:42 PM
Last Modification Date:
2024-10-26 @ 1:02 PM
Study NCT ID:
NCT03822390
Status:
COMPLETED
Last Update Posted:
2021-12-29
First Post:
2019-01-21
Brief Title:
Diagnostic Performance of a Convolutional Neural Network for Diminutive Colorectal Polyp Recognition
Sponsor:
Academisch Medisch Centrum - Universiteit van Amsterdam AMC-UvA
Organization:
Academisch Medisch Centrum - Universiteit van Amsterdam AMC-UvA
Study Overview
Official Title:
Diagnostic Performance of a Convolutional Neural Network for Diminutive Colorectal Polyp Recognition A Multicentre Prospective Observational Study
Status:
COMPLETED
Status Verified Date:
2021-12
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:
POLAR
Brief Summary:
Rationale Diminutive colorectal polyps 1-5mm in size have a high prevalence and very low risk of harbouring cancer Current practice is to send all these polyps for histopathological assessment by the pathologist If an endoscopist would be able to correctly predict the histology of these diminutive polyps during colonoscopy histopathological examination could be omitted and practise could become more time- and cost-effective Studies have shown that prediction of histology by the endoscopist remains dependent on training and experience and varies greatly between endoscopists even after systematic training Computer aided diagnosis CAD based on convolutional neural networks CNN may facilitate endoscopists in diminutive polyp differentiation Up to date studies comparing the diagnostic performance of CAD-CNN to a group of endoscopists performing optical diagnosis during real-time colonoscopy are lacking
Objective To develop a CAD-CNN system that is able to differentiate diminutive polyps during colonoscopy with high accuracy and to compare the performance of this system to a group of endoscopist performing optical diagnosis with the histopathology as the gold standard
Study design Multicentre prospective observational trial Study population Consecutive patients who undergo screening colonoscopy phase 2
Main study parametersendpoints The accuracy of optical diagnosis of diminutive colorectal polyps 1-5mm by CAD-CNN system compared with the accuracy of the endoscopists Histopathology is used as the gold standard
Objective To develop a CAD-CNN system that is able to differentiate diminutive polyps during colonoscopy with high accuracy and to compare the performance of this system to a group of endoscopist performing optical diagnosis with the histopathology as the gold standard
Study design Multicentre prospective observational trial Study population Consecutive patients who undergo screening colonoscopy phase 2
Main study parametersendpoints The accuracy of optical diagnosis of diminutive colorectal polyps 1-5mm by CAD-CNN system compared with the accuracy of the endoscopists Histopathology is used as the gold standard
Detailed Description:
None
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None