A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography

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.

Macroglial and retinal changes in hypercholesterolemic rabbits after normalization of cholesterol levels

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.

Macular Thickness as a Potential Biomarker of Mild Alzheimer's Disease

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.