- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT03903042
Comparison of Aurora Fundus Camera With Traditional Camera in Diabetic Retinopathy With Visual Artificial Intelligence
April 3, 2019 updated by: Fenghua Wang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Comparison of Aurora Fundus Camera With Traditional Fundus Camera in Diabetic Retinopathy With Phoebus Visual Artificial Intelligence
This study aims to compare the effect of Aurora handheld fundus camera with traditional desktop fundus camera in the fundus photography screening of diabetic patients, and to evaluate the effect of artificial intelligence algorithm in the diagnosis of diabetic retinopathy.
Study Overview
Status
Unknown
Conditions
Detailed Description
Aurora handheld fundus cameras are used to take fundus photography on diabetic patients in 3 ophthalmic diabetic retinopathy screening centers in China to compare its effect with the hospital's traditional desktop fundus camera, and evaluate the auxiliary diagnostic effect of Phoebus artificial intelligence algorithm in diabetic retinopathy.
Study Type
Observational
Enrollment (Anticipated)
300
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
-
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Shanghai
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Shanghai, Shanghai, China, 200080
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
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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
Patients who were diagnosed with diabetes, more than 18 years of age, male or female Chinese patients.
Description
Inclusion Criteria:
- Participants are more than 18 years of age, male or female Chinese patients;
- Diagnosed with diabetes;
- Prior written informed consent should be obtained
Exclusion Criteria:
- Patients with invisible fundus caused by any cause;
- Patients or his/her licensor unwill to sign an informed consent or follow this protocol;
- Pregnant women
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 |
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Group 1
Center 1: Traditional camera(Canon) vs Aurora camera
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Group 2
Center 2: Traditional camera(Zeiss) vs Aurora camera
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Group 3
Center 3: Traditional camera(Topcon) vs Aurora camera
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Image Quality of Aurora camera
Time Frame: within 3 months
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Score of Image Quality
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within 3 months
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Outcome of gold standard
Time Frame: within 3 months
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Gold standard: 8 photographs of one patient(4 by Aurora camera, 4 by traditional camera) by ophthalmologist(double blinded)
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within 3 months
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Image of Aurora camera
Time Frame: 1 month
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Images taken by Aurora camera
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1 month
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Image of traditional camera (Center 1: Canon)
Time Frame: 1 month
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Image taken by traditional camera(Center 1: Canon, pupil not dilated)
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1 month
|
Image of traditional camera (Center 2: Zeiss)
Time Frame: 1 month
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Image taken by traditional camera(Center 2: Zeiss, pupil dilated)
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1 month
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Image of traditional camera (Center 3: Topcon)
Time Frame: 1 month
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Image taken by traditional camera(Center 3: Topcon, pupil dilated)
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1 month
|
Outcome of artificial intelligence algorithm
Time Frame: 3 months
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Outcome of artificial intelligence algorithm(Normal or Referral Required)
|
3 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: Fenghua Wang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Jin G, Xiao W, Ding X, Xu X, An L, Congdon N, Zhao J, He M. Prevalence of and Risk Factors for Diabetic Retinopathy in a Rural Chinese Population: The Yangxi Eye Study. Invest Ophthalmol Vis Sci. 2018 Oct 1;59(12):5067-5073. doi: 10.1167/iovs.18-24280.
- Zheng X, Zhang L. A study of retinopathy analysis in type 2 diabetes patients in Chinese population. Pak J Pharm Sci. 2018 Sep;31(5(Supplementary)):2041-2046.
- Hendrick AM, Gibson MV, Kulshreshtha A. Diabetic Retinopathy. Prim Care. 2015 Sep;42(3):451-64. doi: 10.1016/j.pop.2015.05.005.
- Wong TY, Bressler NM. Artificial Intelligence With Deep Learning Technology Looks Into Diabetic Retinopathy Screening. JAMA. 2016 Dec 13;316(22):2366-2367. doi: 10.1001/jama.2016.17563. No abstract available.
- Abramoff MD, Niemeijer M, Russell SR. Automated detection of diabetic retinopathy: barriers to translation into clinical practice. Expert Rev Med Devices. 2010 Mar;7(2):287-96. doi: 10.1586/erd.09.76.
- Li Z, Keel S, Liu C, He Y, Meng W, Scheetz J, Lee PY, Shaw J, Ting D, Wong TY, Taylor H, Chang R, He M. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs. Diabetes Care. 2018 Dec;41(12):2509-2516. doi: 10.2337/dc18-0147. Epub 2018 Oct 1.
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)
November 1, 2018
Primary Completion (Anticipated)
May 1, 2019
Study Completion (Anticipated)
May 1, 2019
Study Registration Dates
First Submitted
April 3, 2019
First Submitted That Met QC Criteria
April 3, 2019
First Posted (Actual)
April 4, 2019
Study Record Updates
Last Update Posted (Actual)
April 4, 2019
Last Update Submitted That Met QC Criteria
April 3, 2019
Last Verified
April 1, 2019
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- Shanghai1stAI
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
YES
IPD Plan Description
Clinical Study Report will be published
IPD Sharing Time Frame
starting 6 months after publication
IPD Sharing Access Criteria
Dr Fenghua Wang will review requests and criteria.
IPD Sharing Supporting Information Type
- CSR
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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