An automated microaneurysm detector as a tool for identification of diabetic retinopathy in rural optometric practice

Background: With the increase in the prevalence of diabetes, rural optometric clinics stand to increase their patient load and assessment of diabetic eye disease. This study aimed to assess whether automated identification of diabetic retinopathy based on the presence of microaneurysms is an effective tool in clinical practice. Methods: We analysed 758 fundal images of 385 patients with diabetes attending the clinic obtained using a Canon CR5 with an EOS10 digital camera through a dilated pupil. Five optometrists employed in the clinic assessed the diabetic retinopathy using binocular indirect ophthalmoscopy. The sensitivity and specificity of the automated system used to analyse the retinal fundal images was determined by comparison with optometric and ophthalmologic assessment. Results: The optometrists achieved 97 per cent sensitivity at 88 per cent specificity with respect to the ophthalmic classification for detecting retinopathy. The automated retinopathy detector achieved 85 per cent sensitivity at 90 per cent specificity at detecting retinopathy. Conclusion: The automated microaneurysm detector has a lower sensitivity compared to the optometrists but meets NHMRC guidelines. It may impact on the efficiency of rural optometric practices by early identification of diabetic retinopathy. Automated assessment can save time and be cost-effective, and provide a history of changes in the retinal fundus and the opportunity for instant patient education using the digital images.