Artificial Intelligence for Early Diagnosis of Esophageal Squamous Cell Carcinoma

April 25, 2020 updated by: Yanqing Li, Shandong University

Application of Artificial Intelligence for Early Diagnosis of Esophageal Squamous Cell Carcinoma During Optical Enhancement Magnifying Endoscopy

Esophageal squamous cell carcinoma is one of the most common malignant tumor of upper digestive tract. However, the detection rate and diagnosis accuracy of early esophageal squamous cell cancer is low. The aim of this study is to develop a computer-assisted diagnosis tool combining with optical magnifying endoscopy for early detection and accurate diagnosis of it.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Actual)

119

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

  • China
    • Shandong
      • Jinan, Shandong, China, 250012
        • Department of Gastroenterology, Qilu Hospital, Shandong University

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 and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Consecutive patients who came to Qilu Hospital of Shandong University and received optical magnifying OE endoscopy examination

Description

Inclusion Criteria:

  • high risk patients for esophageal cancer aged 18 years or older;
  • Histologically verified early esophageal squamous cell cancer.

Exclusion Criteria:

  • patients whose images of esophagus not suitable for the training, validation and testing the computer-assist diagnosis tool.

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
AI visible group
the endoscopic novices analyzing the images can see the automatic diagnosis of AI during the process
Other: AI presentation
AI presentation means the automatic diagnosis information of AI and AI presentation means it is visible in the group.
AI invisible group
the endoscopic novice analyzing the images can not see the automatic diagnosis of AI during the process
Other: no AI presentation
AI presentation means the automatic diagnosis information of AI and no AI presentation means it is invisible in the group.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
the diagnosis efficiency of the AI model
Time Frame: 12 months
the sensitivity, specificity and accuracy of the AI model
12 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shandong University

Investigators

  • Principal Investigator: Yanqing Li, PHD, Qilu Hospital, Shandong University

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)

December 1, 2018

Primary Completion (Actual)

March 1, 2020

Study Completion (Actual)

April 1, 2020

Study Registration Dates

First Submitted

November 28, 2018

First Submitted That Met QC Criteria

November 28, 2018

First Posted (Actual)

November 30, 2018

Study Record Updates

Last Update Posted (Actual)

April 28, 2020

Last Update Submitted That Met QC Criteria

April 25, 2020

Last Verified

April 1, 2020

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2018SDU-QILU-2

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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