Real-world Diagnostic Effectiveness of Artificial Intelligence Algorithm in Diabetic Retinopathy Screening

A Prospective Clinical Study on the Real-world Diagnostic Effectiveness of Artificial Intelligence Algorithm in Diabetic Retinopathy Screening

Recently, artificial intelligence algorithm has made great progress in the prediction of diabetic retinopathy based on fundus images，showing very high sensitivity and specificity. However，the real-world diagnosis effectiveness of deep learning model is still unclear.

This study is designed to evaluate the clinical efficacy of such an algorithm in detecting referable diabetic retinopathy.

Study Overview

• Status: Unknown
• Conditions: Diabetic Retinopathy
• Intervention / Treatment: Other: diabetic retinopathy

Detailed Description

This prospective clinical study is designed to evaluate the real-world diagnostic performance of an AI model in detecting referable diabetic retinopathy (RDR, defined as more than mild NPDR), by evaluating its sensitivity and specificity compared to the clinical reference standard- seven-field stereoscopic photography.

The subjects enrolled in this study are patients with T1DM or T2DM. Qualified color fundus images and seven-field stereoscopic photography images of each eyes of the subject are taken. The fundus images are graded for RDR by the algorithm under test, and seven-field stereoscopic photography images of the same eye are graded by ophthalmologist, which serving as the gold standard to compare the algorithm performance against.

The trial plans to enroll 1000 subjects. With a 95% confidence interval, the sensitivity is expected to be at least 87% whereas the specificity at 89% or above.

The quality of fundus images are assessed according to the National DR Screening Imaging and Grading Guideline published by Chinese Ophthalmological Society and Chinese Medical Doctor Association in 2017.

The grading of RDR is based on the National DR Clinical Diagnosis and Treatment Guideline published by Chinese Ophthalmological Society in 2014.

A brief overview of the clinical protocol is as follows:

Candidate recruiting phase: recruiting qualified participants; Clinical phase: imaging and diagnosing by AI and ophthalmologist ; Statistical analysis phase: comparing two outputs; Closing phase: final report and archiving

• Study Type: Observational
• Enrollment (Anticipated): 1000

Contacts and Locations

• Study Contact: Name: Jiying Hu, PhD; Phone Number: +86-1808-6481-821; Email: 18086481821@163.com

Study Locations

• China
  • Guangdong
    • Shenzhen, Guangdong, China, 518000
      • Recruiting
      • Shenzhen second peoples's hospital
      • Contact: Lisha Mou, PhD; Phone Number: +86-1589-9876-015; Email: lishamou@gmail.com

Participation Criteria

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

Diabetic patients who meet the eligibility criteria.

Description

Inclusion Criteria:

1. Subject must understand the study, participate voluntarily, and has signed informed consent
2. Age 18 or older, no limitations on gender identity
3. Patients with type 1 or type 2 diabetes.

Exclusion Criteria:

1. Subjects diagnosed with eye diseases other than diabetic retinopathy
2. Subjects diagnosed with macular edema, severe non-proliferative retinopathy, proliferative retinopathy, radioactive retinopathy or retinal vein obstruction.
3. Pregnant woman, subjects with mydriatic allergy, unclear refractive medium, family history of glaucoma, or diagnosed as narrow angle
4. Subjects with a history of laser therapy, retinal surgery or anti-vascular endothelial growth factor injection
5. Subjects currently participating in another ophthalmic research, receiving ophthalmic research products.
6. Subject who is photo-sensitivity or taking medication that causes photosensitivity
7. Subjects received photodynamic therapy recently

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity and specificity	To evaluate the sensitivity and specificity of the model in detecting referable DR (more than mild NPDR)	No more than 1 day for each subject

Collaborators and Investigators

• Sponsor: Shenzhen Second People's Hospital
• Investigators: Principal Investigator: Lisha Mou, PhD, Shenzhen Second People's Hospital

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2018
• Primary Completion (Anticipated): October 1, 2020
• Study Completion (Anticipated): October 1, 2020

Study Registration Dates

• First Submitted: April 9, 2019
• First Submitted That Met QC Criteria: April 9, 2019
• First Posted (Actual): April 11, 2019

Study Record Updates

• Last Update Posted (Actual): April 11, 2019
• Last Update Submitted That Met QC Criteria: April 9, 2019
• Last Verified: April 1, 2019

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Cardiovascular Diseases; Vascular Diseases; Eye Diseases; Endocrine System Diseases; Diabetic Angiopathies; Diabetes Complications; Diabetes Mellitus; Retinal Diseases; Diabetic Retinopathy
• Other Study ID Numbers: 20190401

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No