A Computer-aided (CADx）System in Real-time Characterization of Colorectal Ulcerative Diseases

NCT06208982 | Unknown DMC

• 1 other identifier: NFEC-2023-330
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational study is to construct and validate a Computer-aided (CADx）System in Real-time Characterization of Colorectal Ulcrerative Diseases. The main question it aims to answer are to demonstrate whether the newly developed CADx system has a high-level diagnostic accuracy in predicting characterization of colorectal ulcerative diseases. It is a multi-center, retrospective study. The study retrospectively collected colonoscopy images and videos of colorectal ulcers (including colorectal cancer, Crohn's disease, Ulcerative colitis, Intestinal tuberculosis and ischemic enteritis). A training cohort will be developed from majority of the included cases, followed by a validation cohort with the remaining cases. A CADx system in real-time characterization of colonic ulcer diseases was constructed using artificial intelligence to extract endoscopic features from the training set. Subsequently, the performance of the CADx system was preliminarily tested through the validation set.

Conditions

Colorectal Ulcers; Computer-aided System

Outcome Measures

Primary Outcomes (1)

• The diagnostic accuracy

  The diagnostic accuracy (area under receiver operating characteristic curves, AUROC) of newly developed CADx system in prediction of Characterization of Colorectal Ulcerative Diseases.

  From 2023-06 to 2024-06

Secondary Outcomes (2)

• Sensitivity

  From 2023-06 to 2024-06

• Specificity

  From 2023-06 to 2024-06

Study Arms (1)

Colorectal ulcers

Colonoscopy images and videos of colorectal ulcers.

Diagnostic Test: Colonoscopy images and videos

Interventions

Colonoscopy images and videos DIAGNOSTIC_TEST

A CADx system in real-time characterization of colonic ulcer diseases was constructed using artificial intelligence to extract endoscopic features from the training set. Subsequently, the performance of the CADx system was preliminarily tested through the validation set.

Colorectal ulcers

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

They underwent endoscopic examination and are found to have ulcerative lesions in the large intestine.

You may qualify if:

• They underwent endoscopic examination and are found to have ulcerative lesions in the large intestine;
• They have endoscopic images and videos captured and stored during colonoscopy which are available to be retrieved;
• They have the complete medical records and clear diagnosis.

You may not qualify if:

• )Poor quality endoscopic images and videos defined as:
• Incomplete visualization of the colorectal ulcer due to technical reasons (e.g. out-of-focus, motion-blurred or insufficient illumination);
• Artifacts due to mucus, air bubbles, stool, or blood. 2)Obscured view due to poor bowel preparation; 3)Incomplete medical record; 4)Prior history of intestinal resection, fistula, or anastomosis.

Sponsors & Collaborators

• Nanfang Hospital, Southern Medical University: lead
• Prince of Wales Hospital, Shatin, Hong Kong: collaborator
• ZhuHai Hospital: collaborator
• Wuxi People's Hospital: collaborator
• The University of Hong Kong-Shenzhen Hospital: collaborator

Study Sites (1)

Nanfang Hospital, Southern Medical University

Guangzhou, Undefined, undefined, China

RECRUITING

Central Study Contacts

Xiaobei Luo, PhD

CONTACT

17688881428; luoxiaobei63@126.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 7, 2024
• First Posted: January 17, 2024
• Study Start: June 1, 2023
• Primary Completion: June 1, 2024
• Study Completion: June 1, 2024
• Last Updated: January 17, 2024

Record last verified: 2024-01

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)