Polyp Artificial Intelligence Study
Artificial Intelligence Based Colorectal Polyp Histology Prediction by Using Narrow-band Imaging Magnifying Colonoscopy
Background We are developing artificial intelligence based polyp histology prediction (AIPHP) method to automatically classify Narrow Band Imaging (NBI) magnifying colonoscopy images to predict the non-neoplastic or neoplastic histology of polyps.
Aim Our aim was to analyse the accuracy of AIPHP and NICE classification based histology predictions and also to compare the results of the two methods.
Methods We examined colorectal polyps obtained from colonoscopy patients who had polypectomy or endoscopic mucosectomy. Polyps detected by white light colonoscopy were observed then by using NBI at the optical maximum magnificent (60x). The obtained and stored NBI magnifying images were analysed by NICE classification and by AIPHP method parallelly. Pathology examinations were performed blinded to the NICE and AIPHP diagnosis, as well. Our AIPHP software is based on a machine learning method. This program measures five geometrical and colour features on the endoscopic image.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- endoscopic diagnosis of colorectal polyp
Exclusion Criteria:
- colonoscopy result without polyps or IBD diagnosis
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Software accuracy of polyp histology prediction
Time Frame: 2014-2020
|
Artificial intelligence software diagnosis in comparison with the polyp histology
|
2014-2020
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- PetzACTHospital
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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