Polyp Histology Prediction by AI

Sponsor

Petz Aladar County Teaching Hospital (Other)

Overall Status

Not yet recruiting

CT.gov ID

NCT05545189

Collaborator

(none)

1,200

Enrollment

Anticipated Duration (Months)

Study Details

Study Description

Brief Summary

We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging(NBI) colonoscopy images to predict the hyperplastic or neoplastic histology of polyps.

We plan to study colonoscopy polyp samples taken by polypectomy from 1200 patients.The documented NBI still images will be analyzed by the AIPHP method and by the NICE classification parallel.Our aim is to analyze the accuracy of AIPHP and NBI classification based histology predictions and also compare the results of the two methods.

Condition or Disease	Intervention/Treatment	Phase
Colorectal Polyp	Diagnostic Test: colonoscopy,polypectomy

Study Design

Study Type:

Observational [Patient Registry]

Anticipated Enrollment :

1200 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

Colorectal Polyp Histology Prediction by Artificial Ingelligence Method Based on NBI Colonoscopy Images.

Anticipated Study Start Date :

Oct 31, 2022

Anticipated Primary Completion Date :

Dec 31, 2023

Anticipated Study Completion Date :

Mar 31, 2024

Arms and Interventions

Arm	Intervention/Treatment
colonoscopy group1	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy
colonoscopy group 2	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy
colonoscopy group 3	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy
colonoscopy group 4	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy
colonoscopy group 5	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy
colonoscopy group 6	Diagnostic Test: colonoscopy,polypectomy polyp removal during colonoscopy

Outcome Measures

Primary Outcome Measures

Polyp histology accuracy by AI method [two weeks]
polyp histology prediction by AI

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 85 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

colorectal polyps removed by polypectomy

Exclusion Criteria:

colorectal polyps with IBD

Contacts and Locations

Locations

No locations specified.

Sponsors and Collaborators

Petz Aladar County Teaching Hospital

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Petz Aladar County Teaching Hospital

ClinicalTrials.gov Identifier:

NCT05545189

Other Study ID Numbers:

PetzACTH2

First Posted:

Sep 19, 2022

Last Update Posted:

Sep 19, 2022

Last Verified:

Sep 1, 2022

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by Petz Aladar County Teaching Hospital

colorectal polyp,histology prediction, artificial intelligence

Additional relevant MeSH terms:

Polyps

Study Results

No Results Posted as of Sep 19, 2022