Automatic Classification of Colorectal Polyps Using Probe-based Endomicroscopy With Artificial Intelligence

Not Applicable

• Conditions: Colorectal Polyps; Artificial Intelligence; Probe-based Confocal Laser Endomicroscopy
• Interventions: Other: AI presentation

• Registration Number: NCT03787784
• Lead Sponsor: Shandong University

Brief Summary

Probe-based confocal laser endomicroscopy (pCLE) is an endoscopic technique that enables real-time histological evaluation of gastrointestinal mucosa during ongoing endoscopy examination. It can predict the classification of Colorectal Polyps accurately. However this requires much experience, which limits the application of pCLE. The investigators designed a computer program using deep neural networks to differentiate hyperplastic from neoplastic polyps automatically in pCLE examination.

Detailed Description

Not available

Study Timeline

• Study Start: 2018-05-01
• Status Verified: 2018-09
• Study First Submitted: 2018-12-21
• Study First Submitted QC: 2018-12-21
• Last Update Submitted: 2018-12-21
• Study First Posted: 2018-12-26
• Last Update Posted: 2018-12-26
• Primary Completion: 2019-01-30
• Study Completion: 2019-03-30

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 200

Inclusion Criteria

aged between 18 and 80; agree to give written informed consent.

Exclusion Criteria

Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium; Inability to provide informed consent

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
AI visible group	AI presentation	-

Primary Outcome Measures

Name	Time	Method
The accuracy of classifying colorectal Polyps using Probe-based endomicroscopy with deep neural networks	4 months	The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing Colorectal Polyps on real-time pCLE examination.

Secondary Outcome Measures

Name	Time	Method
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists	3 month	The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing Colorectal Polyps on real-time pCLE examination) between Artificial Intelligence and endoscopists.

Trial Locations

Locations (1)

Endoscopic unit of Qilu Hospital Shandong University; 🇨🇳 Jinan, Shandong, China