Vascular changes precede tomographic changes in diabetic eyes without retinopathy and improve artificial intelligence diagnostics.J Biophotonics. 2020 09; 13(9):e202000107.JB
The purpose of this study was to evaluate early vascular and tomographic changes in the retina of diabetic patients using artificial intelligence (AI). The study included 74 age-matched normal eyes, 171 diabetic eyes without retinopathy (DWR) eyes and 69 mild non-proliferative diabetic retinopathy (NPDR) eyes. All patients underwent optical coherence tomography angiography (OCTA) imaging. Tomographic features (thickness and volume) were derived from the OCTA B-scans. These features were used in AI models. Both OCT and OCTA features showed significant differences between the groups (P < .05). However, the OCTA features indicated early retinal changes in DWR eyes better than OCT (P < .05). In the AI model using both OCT and OCTA features simultaneously, the best area under the curve of 0.91 ± 0.02 was obtained (P < .05). Thus, the combined use of AI, OCT and OCTA significantly improved the early diagnosis of diabetic changes in the retina.