- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04136236
Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using pCLE With AI
October 20, 2019 updated by: Yanqing Li, Shandong University
Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
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.
Study Overview
Status
Unknown
Intervention / Treatment
Study Type
Observational
Enrollment (Anticipated)
60
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
-
-
Shandong
-
Jinan, Shandong, China, 250001
- Recruiting
- Qilu Hospital, Shandong University
-
Contact:
- Yanqing Li, PhD,MD
- Phone Number: 053182169385
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years to 80 years (ADULT, OLDER_ADULT)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Sampling Method
Non-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
Description
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
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
esophageal mucosal lesions observed by pCLE
pCLE is used to distinguish the suspected lesions detected by white light endoscopy.
|
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.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
The diagnosis efficiency of Artificial Intelligence
Time Frame: 3 month
|
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 Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists
Time Frame: 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.
|
1 month
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (ACTUAL)
August 1, 2019
Primary Completion (ANTICIPATED)
December 1, 2019
Study Completion (ANTICIPATED)
December 1, 2019
Study Registration Dates
First Submitted
October 20, 2019
First Submitted That Met QC Criteria
October 20, 2019
First Posted (ACTUAL)
October 23, 2019
Study Record Updates
Last Update Posted (ACTUAL)
October 23, 2019
Last Update Submitted That Met QC Criteria
October 20, 2019
Last Verified
October 1, 2019
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2019SDU-QILU-66
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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