Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI

Shandong University

Status: Completed

Conditions: Artificial Intelligence; Confocal Laser Endomicroscopy; Esophageal Neoplasms

Treatments: Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist

Study type: Observational

Funder types: Other

Identifiers

NCT04136236

2019SDU-QILU-66

Details and patient eligibility

About

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.

Enrollment: 57 patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

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.

Trial design

57 participants in 1 patient group

esophageal mucosal lesions observed by pCLE

Description:

pCLE is used to distinguish the suspected lesions detected by white light endoscopy or IEE.

Treatment:

Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist