Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI

NCT ID: NCT04136236

Last Updated: 2024-11-19

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

57 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-08-01

Study Completion Date

2023-01-31

Brief Summary

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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

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Conditions

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Esophageal Neoplasms Artificial Intelligence Confocal Laser Endomicroscopy

Study Design

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Observational Model Type

COHORT

Study Time Perspective

OTHER

Study Groups

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esophageal mucosal lesions observed by pCLE

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

The diagnosis of Artificial Intelligence and endoscopist

Intervention Type DIAGNOSTIC_TEST

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. After a washout period, nonexpert endoscopists take the second assessment with AI assistance.

Interventions

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The diagnosis of Artificial Intelligence and endoscopist

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. After a washout period, nonexpert endoscopists take the second assessment with AI assistance.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Shandong University

OTHER

Sponsor Role lead

Responsible Party

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Yanqing Li

Vice president of QiLu Hospital

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Yanqing Li

Role: PRINCIPAL_INVESTIGATOR

Qilu Hospital, Shandong University

Locations

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Qilu Hospital, Shandong University

Jinan, Shandong, China

Site Status

Countries

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China

Other Identifiers

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2019SDU-QILU-66

Identifier Type: -

Identifier Source: org_study_id

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