OBJECTIVETo 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 METHODSClinic 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.
RESULTSA 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.
CONCLUSIONSPoint-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.Patients with diabetes require lifelong ophthalmic care that generally includes an annual retinal evaluation (1). Given the rapidly growing population affected by diabetes, a 20-year estimate of .2.7 million eyes worldwide will need to be evaluated each day just to fulfill these needs (2). This enormous task is unlikely to be accomplished by the current approaches of diabetes eye care programs. Despite more than one decade of research, no real-time, fully automated retinal image analysis system is currently in active clinical use (2). Until such capability exists, other approaches to speed efficiency of current programs without sacrificing accuracy are urgently needed.