A Multi-center Study on the Artificial Intelligence Enabled Diabetic Retinopathy Screening Based on Fundus Images
A Prospective, Multi-center Clinical Study on the Application of An Artificial Intelligence Enabled Disease Detection Software to Diabetic Retinopathy Screening Based on Fundus Images
1 other identifier
observational
1,000
1 country
3
Brief Summary
Early detection and intervention of diabetic retinopathy (DR) is critical in preventing DR-related vision loss among type 1 (T1DM) and type 2 diabetic mellitus (T2DM) patients, currently estimated at over 100 million in China alone. Yet the healthcare resources, particularly retinal specialists, are in short supply and unevenly distributed. In order to help address this enormous mismatch and implement population-based screening, an artificial intelligence (AI) enabled, cloud based software is developed by training a custom-built convolutional neural network. This study is designed to evaluate the safety and efficacy of such device in detecting referable diabetic retinopathy (moderate non-proliferative DR or worse).
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jul 2018
3 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
July 5, 2018
CompletedFirst Submitted
Initial submission to the registry
July 17, 2018
CompletedFirst Posted
Study publicly available on registry
July 27, 2018
CompletedPrimary Completion
Last participant's last visit for primary outcome
November 30, 2018
CompletedStudy Completion
Last participant's last visit for all outcomes
August 31, 2019
CompletedMay 20, 2019
May 1, 2019
5 months
July 17, 2018
May 17, 2019
Conditions
Outcome Measures
Primary Outcomes (1)
Sensitivity and specificity
To evaluate the sensitivity and specificity of the device in detecting referable DR (more than mild NPDR)
No more than 1 day for each subject
Interventions
Color fundus images of both eyes are captured on site before being uploaded to and analyzed by the cloud-based Artificial Intelligence software
Eligibility Criteria
Patients with T1DM and T2DM under clinical setting. Invitation to volunteer
You may qualify if:
- Subject must understand the study, has chosen to participate voluntarily, and has signed informed consent
- Age 18 or older, no limitations on gender identity
- Type 1 Diabetes Mellitus and Type 2 Diabetes Mellitus
You may not qualify if:
- As it is difficult to obtain fundus images of satisfactory quality with small pupils, mydriasis is advisable under certain circumstances except if:
- the subject is allergic to mydriatic drugs;
- the subject's intraocular pressure (IOP) ≥ 22 mmHg;
- the subject is prone to post-dilation angle closure, pupillary block, etc.;
- The subject has refractive media opacity and/or pupil abnormalities that affect fundus examination and imaging;
- The subject has severe vitreous hemorrhage;
- The subject has received fundus laser treatment;
- The subject is participating in other ophthalmic clinical trials;
- In cases when the researchers believe the subject is not suitable for taking fundus photograph, including but not limited to:
- The subject had nystagmus and could not obtain a gradable fundus photograph;
- other disqualifying condition deemed by the researcher.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Shenzhen SiBright Co., Ltd.lead
- Zhongshan Ophthalmic Center, Sun Yat-sen Universitycollaborator
- Peking University People's Hospitalcollaborator
- The Eye Hospital of Wenzhou Medical Universitycollaborator
Study Sites (3)
Peking University People's Hospital
Beijing, Beijing Municipality, China
Zhongshan Ophthalmic Center
Guangzhou, Guangdong, China
The Eye Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Xiaofeng Lin, M.D.
Zhongshan Ophthalmic Center, Sun Yat-sen University
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
July 17, 2018
First Posted
July 27, 2018
Study Start
July 5, 2018
Primary Completion
November 30, 2018
Study Completion
August 31, 2019
Last Updated
May 20, 2019
Record last verified: 2019-05