Real-Time Ultrawide Field Image Evaluation of Retinopathy in a Diabetes Telemedicine Program
Abstract
Objective To evaluate the ability of trained nonphysician retinal imagers to perform diabetic retinopathy (DR) evaluation at the time of ultrawide field retinal (UWF) imaging in a teleophthalmology program. Research design and methods Clinic patients with diabetes received Joslin Vision Network protocol retinal imaging as part of their standard medical care. Retinal imagers evaluated UWF images for referable DR at the time of image capture. Training of the imagers included 4 h of standardized didactic lectures and 12 h of guided image review. Real-time evaluations were compared with standard masked gradings performed at a centralized reading center. Results A total of 3,978 eyes of 1,989 consecutive patients were imaged and evaluated. By reading center evaluation, 3,769 eyes (94.7%) were gradable for DR, 1,376 (36.5%) had DR, and 580 (15.3%) had referable DR. Compared with the reading center, real-time image evaluation had a sensitivity and specificity for identifying more than minimal DR of 0.95 (95% CI 0.94-0.97) and 0.84 (0.82-0.85), respectively, and 0.99 (0.97-1.00) and 0.76 (0.75-0.78), respectively, for detecting referable DR. Only three patients with referable DR were not identified by imager evaluation. Conclusions Point-of-care evaluation of UWF images by nonphysician imagers following standardized acquisition and evaluation protocols within an established teleophthalmology program had good sensitivity and specificity for detection of DR and for identification of re…
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Retinal imaging features are critical for diabetic retinopathy.
“Comparative analyses across complications reveal differing key predictors: retinal imaging features are critical for DR [154], renal function indicators are highly specific to DN [155], while hypertension and dyslipidemia serve as strong predictors for CVD [156] but also overlap with DR and DN [157].”
From Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics (2026) · cites this paper as [154]
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- Authors
- Silva, P. S., Cavallerano, J. D., Tolson, A. M., Rodriguez, J., Rodriguez, S., Ajlan, R., Tolls, D., Patel, B., Sehizadeh, M., Thakore, K., Sun, J. K., & Aiello, L. P.
- Affiliations
- Joslin Diabetes Center (US)
- Corresponding author
- Silva, Paolo S.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2015-06-01
- Volume
- 38
- Issue
- 9
- Pages
- 1643-1649
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W1947168587
- Cited by
- 45
- References
- 15
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 3 · 2020: 6 · 2019: 3 · 2018: 6 · 2017: 6 · 2016: 5 · 2015: 2
- FWCI
- 5.39
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Care (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Center of Integration of Medicine and Innovative Technology
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
- Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
- Health Sciences › Medicine › Ophthalmology › Ophthalmology and Visual Health Research
- Keywords
- diabetic retinopathy, teleophthalmology
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Computer Systems, Diabetic Retinopathy, Diagnostic Imaging, Female, Humans, Male, Middle Aged, Retrospective Studies, Sensitivity and Specificity, Telemedicine, Point-of-Care Systems, Young Adult
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