Comparison of Aurora Fundus Camera With Traditional Camera in Diabetic Retinopathy With Visual Artificial Intelligence

Diabetic Retinopathy Clinical Trial

Official title:

Comparison of Aurora Fundus Camera With Traditional Fundus Camera in Diabetic Retinopathy With Phoebus Visual Artificial Intelligence

Clinical Trial Details — Status: Enrolling by invitation

Administrative data

• NCT number: NCT03903042
• Other study ID #: Shanghai1stAI
• Status: Enrolling by invitation
• Start date: November 1, 2018
• Est. completion date: May 2019

Study information

• Verified date: April 2019
• Source: Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Enrolling by invitation
• Enrollment: 300
• Est. completion date: May 2019
• Est. primary completion date: May 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Participants are more than 18 years of age, male or female Chinese patients;

2. Diagnosed with diabetes;

3. Prior written informed consent should be obtained

Exclusion Criteria:

1. Patients with invisible fundus caused by any cause;

2. Patients or his/her licensor unwill to sign an informed consent or follow this protocol;

3. Pregnant women

Related Conditions & MeSH terms

• Diabetic Retinopathy
• Retinal Diseases

Locations

Country	Name	City	State
China	Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine	Shanghai	Shanghai

Sponsors (1)

Lead Sponsor	Collaborator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine

Country where clinical trial is conducted

China, 

References & Publications (6)

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. — View Citation

Hendrick AM, Gibson MV, Kulshreshtha A. Diabetic Retinopathy. Prim Care. 2015 Sep;42(3):451-64. doi: 10.1016/j.pop.2015.05.005. Review. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Image Quality of Aurora camera	Score of Image Quality	within 3 months
Secondary	Outcome of gold standard	Gold standard: 8 photographs of one patient(4 by Aurora camera, 4 by traditional camera) by ophthalmologist(double blinded)	within 3 months
Secondary	Image of Aurora camera	Images taken by Aurora camera	1 month
Secondary	Image of traditional camera (Center 1: Canon)	Image taken by traditional camera(Center 1: Canon, pupil not dilated)	1 month
Secondary	Image of traditional camera (Center 2: Zeiss)	Image taken by traditional camera(Center 2: Zeiss, pupil dilated)	1 month
Secondary	Image of traditional camera (Center 3: Topcon)	Image taken by traditional camera(Center 3: Topcon, pupil dilated)	1 month
Secondary	Outcome of artificial intelligence algorithm	Outcome of artificial intelligence algorithm(Normal or Referral Required)	3 months