Real-Time Ultrawide Field Image Evaluation of Retinopathy in a Diabetes Telemedicine Program.


Silva PS, Cavallerano JD, Tolson AM, Rodriguez J, Rodriguez S, Ajlan R, Tolls D, Patel B, Sehizadeh M, Thakore K, Sun JK, Aiello LP. Real-Time Ultrawide Field Image Evaluation of Retinopathy in a Diabetes Telemedicine Program. Diabetes Care 2015;38(9):1643-9.

Date Published:

2015 Sep


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 referable retinal disease. With immediate image evaluation, <0.1% of patients with referable DR would be missed, reading center image grading burden would be reduced by 60%, and patient feedback would be expedited.

Last updated on 01/25/2016