Digital Retinal Images and Teleophthalmology for Detecting and Grading Diabetic Retinopathy

Author:

Gómez-Ulla Francisco1,Fernandez Maria I.1,Gonzalez Francisco12,Rey Pablo3,Rodriguez Marta4,Rodriguez-Cid Maria J.1,Casanueva Felipe F.5,Tome Maria A.5,Garcia-Tobio Javier3,Gude Francisco6

Affiliation:

1. Ocular Diabetes and Medical Retina Unit, Division of Ophthalmology, Department of Surgery, School of Medicine, University of Santiago de Compostela and Complejo Hospitalario, Universitario de Santiago de Compostela, Santiago de Compostela, Spain

2. Department of Physiology, School of Medicine, University of Santiago de Compostela and Complejo Hospitalario, Universitario de Santiago de Compostela, Santiago de Compostela, Spain

3. Supercomputation Center of Galicia (CESGA), Santiago de Compostela, Spain

4. Department of Ophthalmology, Hospital Meixoeiro, Vigo, Spain

5. Division of Endocrinology, Department of Medicine, School of Medicine, University of Santiago de Compostela and Complejo Hospitalario, Universitario de Santiago de Compostela, Santiago de Compostela, Spain

6. Clinical Epidemiology Unit, School of Medicine, University of Santiago de Compostela and Complejo Hospitalario, Universitario de Santiago de Compostela, Santiago de Compostela, Spain

Abstract

OBJECTIVE—Detecting and grading of diabetic retinopathy (DR) by means of digital retinal images sent via the Internet. RESEARCH DESIGN AND METHODS—Four nonstereoscopic digital retinal images (45° field each) of 126 eye fundus images from 70 diabetic patients were obtained with a nonmydriatic camera at two peripheral units. The images were sent via the Internet using a web-based system to a reference center, where they were diagnosed and graded by one ophthalmologist. These results were compared with those obtained by two other ophthalmologists, one at each peripheral unit, after direct examination of the patients. A modified severity scale of Airlie House was used for grading DR in all cases. Agreement between observers was assessed using unweighted κ for categorical data and the intraclass correlation coefficient (ICC) for continuous data. RESULTS—Presence of DR was detected in 69 eyes (55%). All eyes with DR (69 of 69, 100%) were correctly identified (κ = 1) by inspecting the digital images. In 118 eyes (118 of 126, 94%), 57 with no DR and 61 with DR, there was an agreement between the gradation made after the direct examination and the gradation made after the inspection of the images (ICC = 0.92). In eight eyes with DR (8 of 126, 6%), there was disagreement in the grading made with both techniques. CONCLUSIONS—Inspection of digital retinal images sent via the Internet allowed diagnosis and grading of DR. The presence or absence of DR was correctly assessed by inspection of the images in all instances. We also found agreement, in most cases, between retinopathy gradation made from the images and the gradation made by direct examination of the eyes. These findings suggest that this technique is suitable for screening procedures.

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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