Valdez CN, Arboleda-Velasquez JF, Amarnani DS, Kim LA, D'Amore PA.
Retinal microangiopathy in a mouse model of inducible mural cell loss. Am J Pathol 2014;184(10):2618-26.
AbstractDiabetes can lead to vision loss because of progressive degeneration of the neurovascular unit in the retina, a condition known as diabetic retinopathy. In its early stages, the pathology is characterized by microangiopathies, including microaneurysms, microhemorrhages, and nerve layer infarcts known as cotton-wool spots. Analyses of postmortem human retinal tissue and retinas from animal models indicate that degeneration of the pericytes, which constitute the outer layer of capillaries, is an early event in diabetic retinopathy; however, the relative contribution of specific cellular components to the pathobiology of diabetic retinopathy remains to be defined. We investigated the phenotypic consequences of pericyte death on retinal microvascular integrity by using nondiabetic mice conditionally expressing a diphtheria toxin receptor in mural cells. Five days after administering diphtheria toxin in these adult mice, changes were observed in the retinal vasculature that were similar to those observed in diabetes, including microaneurysms and increased vascular permeability, suggesting that pericyte cell loss is sufficient to trigger retinal microvascular degeneration. Therapies aimed at preventing or delaying pericyte dropout may avoid or attenuate the retinal microangiopathy associated with diabetes.
Vujosevic S, Fantaguzzi F, Silva PS, Salongcay R, Brambilla M, Torti E, Nucci P, Peto T.
Macula vs periphery in diabetic retinopathy: OCT-angiography and ultrawide field fluorescein angiography imaging of retinal non perfusion. Eye (Lond) 2024;
AbstractOBJECTIVES: To investigate the association between peripheral non-perfusion index (NPI) on ultrawide-field fluorescein angiography (UWF-FA) and quantitative OCT-Angiography (OCT-A) metrics in the macula. METHODS: In total, 48 eyes with UWF-colour fundus photos (CFP), UWF-FA (California, Optos) and OCT-A (Spectralis, Heidelberg) were included. OCT-A (3 × 3 mm) was used to determine foveal avascular zone (FAZ) parameters and vessel density (VD), perfusion density (PD), fractal dimension (FD) on superficial capillary plexus (SCP). NPI's extent and distribution was determined on UWF-FA within fovea centred concentric rings corresponding to posterior pole (<10 mm), mid-periphery (10-15 mm), and far-periphery (>15 mm) and within the total retinal area, the central macular field (6×6 mm), ETDRS fields and within each extended ETDRS field (P3-P7). RESULTS: Macular PD was correlated to NPI in total area of retina (Spearman ρ = 0.69, p < 0.05), posterior pole (ρ = 0.48, p < 0.05), mid-periphery (ρ = 0.65, p < 0.05), far-periphery (ρ = 0.59, p < 0.05), P3-P7 (ρ = 0,55 at least, p < 0.05 for each), central macula (ρ = 0.47, p < 0.05), total area in ETDRS (ρ = 0.55, p < 0.05). Macular VD and FD were correlated to NPI of total area of the retina (ρ = 0.60 and 0.61, p < 0.05), the mid-periphery (ρ = 0.56, p < 0.05) and far-periphery (ρ = 0.60 and ρ = 0.61, p < 0.05), and in P3-P7 (p < 0.05). FAZ perimeter was significantly corelated to NPI at posterior pole and central macular area (ρ = 0.37 and 0.36, p < 0.05), and FAZ area to NPI in central macular area (ρ = 0.36, p < 0.05). CONCLUSIONS: Perfusion macular metrics on OCT-A correlated with UWF-FA's non-perfusion (NP), particularly in the retina's mid and far periphery, suggesting that OCT-A might be a useful non-invasive method to estimate peripheral retinal NP.
Vujosevic S, Aldington SJ, Silva P, Hernández C, Scanlon P, Peto T, Simó R.
Screening for diabetic retinopathy: new perspectives and challenges. Lancet Diabetes Endocrinol 2020;8(4):337-347.
AbstractAlthough the prevalence of all stages of diabetic retinopathy has been declining since 1980 in populations with improved diabetes control, the crude prevalence of visual impairment and blindness caused by diabetic retinopathy worldwide increased between 1990 and 2015, largely because of the increasing prevalence of type 2 diabetes, particularly in low-income and middle-income countries. Screening for diabetic retinopathy is essential to detect referable cases that need timely full ophthalmic examination and treatment to avoid permanent visual loss. In the past few years, personalised screening intervals that take into account several risk factors have been proposed, with good cost-effectiveness ratios. However, resources for nationwide screening programmes are scarce in many countries. New technologies, such as scanning confocal ophthalmology with ultrawide field imaging and handheld mobile devices, teleophthalmology for remote grading, and artificial intelligence for automated detection and classification of diabetic retinopathy, are changing screening strategies and improving cost-effectiveness. Additionally, emerging evidence suggests that retinal imaging could be useful for identifying individuals at risk of cardiovascular disease or cognitive impairment, which could expand the role of diabetic retinopathy screening beyond the prevention of sight-threatening disease.