Projection artifacts (PAs) affect the quantification of vascular parameters in the deep layer optical coherence tomography (OCT) angiography image. This study eliminated PA and quantified its effect on imaging. 53 eyes (30 subjects) of normal Indian subjects and 113 eyes (92 patients) of type 2 diabetes mellitus with retinopathy (DR) underwent imaging with a scan area of 3 mm × 3 mm. In this study, a normalized cross-correlation between superficial and deep layer was used to remove PA in deep layer. Local fractal analysis was done to compute vascular parameters such as foveal avascular zone area (mm ), vessel density (%), spacing between large vessels (%) and spacing between small vessels (%). Before PA removal, vessel density for mild nonproliferative (NPDR), moderate NPDR, severe NPDR and proliferative DR were 42.56 ±1.69%, 40.69 ±0.72%, 37.34 ±0.85% and 35.61 ±1.26%, respectively. After artifact removal, vessel density was 28.9 ±1.22%, 29.9 ±0.56%, 26.19 ±0.59% and 24.02 ±0.94%, respectively. All the vascular parameters were statistically significant (P <.001) between normal and disease eyes, irrespective of superficial and deep retinal layers. Parafoveal sectoral analyses showed that temporal zone had the lowest vessel density and may undergo DR-related changes first. The current approach enabled rapid and accurate quantitative interpretation of DR eyes, without PA.

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.

Post fever retinitis is a heterogenous entity that is seen 2–4 weeks after a systemic febrile illness in an immunocompetent individual. It may occur following bacterial, viruses, or protozoal infection. Optical coherence angiography (OCTA) is a newer non-invasive modality that is an alternative to fundus fluorescein angiography to image the retinal microvasculature. We hereby describe the vascular changes during the acute phase of post fever retinitis on OCTA. Imaging on OCTA was done for all patients with post fever retinitis at presentation with 3 × 3 mm and 8 × 8 mm scans centred on the macula and corresponding enface optical coherence tomography (OCT) scans obtained. A qualitative and quantitative analysis was done for all images. 46 eyes of 33 patients were included in the study. Salient features noted were changes in the superficial (SCP) and deep capillary plexus (DCP) with capillary rarefaction and irregularity of larger vessels in the SCP. The DCP had more capillary rarefaction when compared to the SCP. The foveal avascular zone (FAZ) was altered with an irregular perifoveal network. Our series of post fever retinitis describes the salient vascular features on OCTA. Although the presumed aetiology was different in all our patients, they developed similar changes on OCTA. While OCTA is not useful if there is gross macular oedema, the altered FAZ can be indicative of macular ischemia.