Trials Sponsors Conditions Drugs Pricing

Conditions

Artificial Intelligence Confocal Laser Endomicroscopy Esophageal Neoplasms

Outcome Measures

Primary Outcomes (1)

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 years

Secondary Outcomes (1)

Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists
1 month

Study Arms (1)

esophageal mucosal lesions observed by pCLE

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

Diagnostic Test: The diagnosis of Artificial Intelligence and endoscopist

Interventions

The diagnosis of Artificial Intelligence and endoscopistDiagnostic 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.

esophageal mucosal lesions observed by pCLE

Registry-reported names are shown in full. Names without a link have not yet been matched to a Syfrah profile.

Eligibility Criteria

Age18 Years - 80 Years

Sexall

Healthy VolunteersNo

Age GroupsAdult (18-64), Older Adult (65+)

Sampling MethodNon-Probability Sample

Study Population

Consecutive patients who receive the upper gastrointestinal tract pCLE examination and screened that fulfill the eligibility criteria at Qilu Hospital, Shandong University will be enrolled into the study

You may qualify if:

aged between 18 and 80;

Sponsors & Collaborators

Shandong University
Otherlead

Study Sites (1)

Qilu Hospital, Shandong University

Jinan, Shandong, 250001, China

Biospecimen

Retention: SAMPLES WITH DNA

When suspected lesion is found using white light endoscopy , endoscopist will observe this lesion using pCLE and then take biopsy for histology examination.

MeSH Terms

Conditions

Esophageal Neoplasms

Condition Hierarchy (Ancestors)

Gastrointestinal NeoplasmsDigestive System NeoplasmsNeoplasms by SiteNeoplasmsHead and Neck NeoplasmsDigestive System DiseasesEsophageal DiseasesGastrointestinal Diseases

Study Officials

Yanqing Li
Qilu Hospital of Shandong University
PRINCIPAL INVESTIGATOR

Enrollment

57 participants (actual enrollment reported by the registry).

Study Design

Study Type: observational
Observational Model: COHORT
Time Perspective: OTHER
Sponsor Type: OTHER
Responsible Party: PRINCIPAL INVESTIGATOR
PI Title: Vice president of QiLu Hospital

Study Record Dates

First Submitted

October 20, 2019

First Posted

October 23, 2019

Study Start

August 1, 2019

Actual (reported)

Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI

Brief Summary

Registry Overview

Trial Relationships

Study Timeline

Study Start

First Submitted

First Posted

Primary Completion

Study Completion

Conditions

Outcome Measures

Primary Outcomes (1)

Secondary Outcomes (1)

Study Arms (1)

esophageal mucosal lesions observed by pCLE

Interventions

Eligibility Criteria

You may qualify if:

Sponsors & Collaborators

Study Sites (1)

Biospecimen

MeSH Terms

Conditions

Condition Hierarchy (Ancestors)

Study Officials

Enrollment

Study Design

Study Record Dates

You may not qualify if:

Source record

Locations

Brief Summary

Registry Overview

Trial Relationships

Related Scientific Literature

Study Timeline

Study Start

First Submitted

First Posted

Primary Completion

Study Completion

Conditions

Outcome Measures

Primary Outcomes (1)

Secondary Outcomes (1)

Study Arms (1)

esophageal mucosal lesions observed by pCLE

Interventions

Eligibility Criteria

You may qualify if:

Sponsors & Collaborators

Study Sites (1)

Biospecimen

MeSH Terms

Conditions

Condition Hierarchy (Ancestors)

Study Officials

Enrollment

Study Design

Study Record Dates

You may not qualify if:

Source record

Locations