Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI

Artificial Intelligence Clinical Trial

Official title:

Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04136236
• Other study ID #: 2019SDU-QILU-66
• Status: Recruiting
• Start date: August 1, 2019
• Est. completion date: December 1, 2019

Study information

• Verified date: October 2019
• Source: Shandong University
• Contact: Yanqing Li
• Phone: 053182169385
• Email: liyanqing[@]sdu.edu.cn
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 60
• Est. completion date: December 1, 2019
• Est. primary completion date: December 1, 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

• aged between 18 and 80; agree to give written informed consent; suspected esophageal mucosal lesion was found by white light endoscopy.

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

Related Conditions & MeSH terms

• Artificial Intelligence
• Confocal Laser Endomicroscopy
• Esophageal Neoplasms

Intervention

Diagnostic Test:
• The diagnosis of Artificial Intelligence and endoscopist
When suspected esophageal mucosal lesion is observed using pCLE, endoscopist and AI will make a diagnosis independently. In addition, the endoscopist can not see the diagnosis of AI.

Locations

Country	Name	City	State
China	Qilu Hospital, Shandong University	Jinan	Shandong

Sponsors (1)

Lead Sponsor	Collaborator
Shandong University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	The diagnosis efficiency of Artificial Intelligence	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.	3 month
Secondary	Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists	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.	1 month