Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI

Completed

• Conditions: Artificial Intelligence; Confocal Laser Endomicroscopy; Esophageal Neoplasms

• Registration Number: NCT04136236
• Lead Sponsor: Shandong University

Brief Summary

Detection and differentiation of esophageal squamous neoplasia (ESN) are of value in improving patient outcomes. Probe-based confocal laser endomicroscopy (pCLE) can diagnose ESN accurately.However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.

Detailed Description

Not available

Study Timeline

• Study Start: 2019-08-01
• Study First Submitted: 2019-10-20
• Study First Submitted QC: 2019-10-20
• Study First Posted: 2019-10-23
• Primary Completion: 2023-01-31
• Study Completion: 2023-01-31
• Status Verified: 2024-11
• Last Update Submitted: 2024-11-16
• Last Update Posted: 2024-11-19

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 57

Inclusion Criteria

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

Exclusion Criteria

• advanced esophageal squamous cell carcinoma or esophageal stenosis;
• having no suspicious lesion of ESN found by WLE and IEE
• known allergy to fluorescein sodium;
• having coagulopathy or impaired renal function;
• being pregnant or breastfeeding.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The diagnosis efficiency of Artificial Intelligence	3 years	The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing esophageal mucosal disease on real-time pCLE examination.

Secondary Outcome Measures

Name	Time	Method
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists	1 month	The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing esophageal mucosal disease on real-time pCLE examination) between Artificial Intelligence and endoscopists.

Trial Locations

Locations (1)

Qilu Hospital, Shandong University; 🇨🇳 Jinan, Shandong, China