4 resultados para RETINAL NERVE FIBER LAYER

em Universidade Complutense de Madrid


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Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

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Although several postmortem findings in the retina of patients with Alzheimer's disease (AD) are available, new biomarkers for early diagnosis and follow-up of AD are still lacking. It has been postulated that the defects in the retinal nerve fiber layer (RNFL) may be the earliest sign of AD, even before damage to the hippocampal region that affects memory. This fact may reflect retinal neuronal-ganglion cell death and axonal loss in the optic nerve in addition to aging.

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Proliferation of microglial cells has been considered a sign of glial activation and a hallmark of ongoing neurodegenerative diseases. Microglia activation is analyzed in animal models of different eye diseases. Numerous retinal samples are required for each of these studies to obtain relevant data of statistical significance. Because manual quantification of microglial cells is time consuming, the aim of this study was develop an algorithm for automatic identification of retinal microglia. Two groups of adult male Swiss mice were used: age-matched controls (naïve, n = 6) and mice subjected to unilateral laser-induced ocular hypertension (lasered; n = 9). In the latter group, both hypertensive eyes and contralateral untreated retinas were analyzed. Retinal whole mounts were immunostained with anti Iba-1 for detecting microglial cell populations. A new algorithm was developed in MATLAB for microglial quantification; it enabled the quantification of microglial cells in the inner and outer plexiform layers and evaluates the area of the retina occupied by Iba-1+ microglia in the nerve fiber-ganglion cell layer. The automatic method was applied to a set of 6,000 images. To validate the algorithm, mouse retinas were evaluated both manually and computationally; the program correctly assessed the number of cells (Pearson correlation R = 0.94 and R = 0.98 for the inner and outer plexiform layers respectively). Statistically significant differences in glial cell number were found between naïve, lasered eyes and contralateral eyes (P<0.05, naïve versus contralateral eyes; P<0.001, naïve versus lasered eyes and contralateral versus lasered eyes). The algorithm developed is a reliable and fast tool that can evaluate the number of microglial cells in naïve mouse retinas and in retinas exhibiting proliferation. The implementation of this new automatic method can enable faster quantification of microglial cells in retinal pathologies.

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This study evaluates hypercholesterolemic rabbits, examining the retinal changes in Müller cells and astrocytes as well as their variations after a period of normal blood-cholesterol values induced by a standard diet. New Zealand rabbits were divided into three groups: G0, fed a standard diet; G1A, fed a 0.5% cholesterol-enriched diet for 8 months; and G1B, fed as G1A followed by standard diet for 6 months. Eyes were processed for transmission electron microscopy and immunohistochemistry (GFAP). While G1B resembled G0 more than did G1A, they shared alterations with G1A: a) as in G1A, Müller cells were GFAP+, filled spaces left by axonal degeneration, formed glial scars and their nuclei were displaced to the nerve-fibre layer. The area occupied by the astrocytes associated with the nerve-fibre bundles (AANFB) and by perivascular astrocytes (PVA) in G1A and G1B was significantly lower than in controls. However, no significant differences in PVA were found between G1A and G1B. In G1B, type I PVA was absent and replaced by hypertrophic type II cells; b) Bruch's membrane (BM) was thinner in G1B than in G1A; c) the retinal pigment epithelium (RPE) cytoplasm contained fewer lipids in G1B than in G1A; d) in G1A and G1B choriocapillaris and retinal vessel showed alterations with respect to G0; e) cell death and axonal degeneration in the retina were similar in G1A and G1B. The substitution of a hyperlipemic diet by a standard one normalizes blood-lipid levels. However, the persistence of damage at retinal vessels and BM-RPE could trigger chronic ischemia.