Purpose: The aim of this study was to evaluate the diagnostic accuracy of optical coherence tomography (OCT) and retinography in the detection of glaucoma through a telemedicine program. Methods: A population-based sample of 4113 persons was randomly selected. The screening examination included a fundus photograph and OCT images. Images were evaluated on a deferred basis. All participants were then invited to a complete glaucoma examination, including gonioscopy, visual field, and dilated fundus examination. The detection rate, sensitivity, specificity, and positive and negative predictive values were calculated. Results: We screened 1006 persons. Of these, 201 (19.9%) were classified as glaucoma suspects; 20.4% were identified only by retinographs, 11.9% only by OCT images, and 46.3% by both. On ophthalmic examination at the hospital (n = 481), confirmed glaucoma was found in 58 (12.1%), probable glaucoma in 76 (15.8%), and ocular hypertension in 10 (2.1%), and no evidence of glaucoma was found in 337 (70.0%). The detection rate for confirmed or probable glaucoma was 9.2%. Sensitivity ranged from 69.4% to 86.2% and specificity from 82.1% to 97.4%, depending on the definition applied. Conclusions: The combination of OCT images and fundus photographs yielded a detection rate of 9.2% in a population-based screening program with moderate sensitivity, high specificity, and predictive values of 84–96%.

Background/aims To identify objective glaucoma-related structural features based on peripapillary (p) and macular (m) spectral domain optical coherence tomography (SD-OCT) parameters and assess their discriminative ability between healthy and glaucoma patients. Methods Two hundred and sixty eyes (91 controls and 169 glaucoma) were included in this prospective study. After a complete examination, all participants underwent the posterior pole and the peripapillary retinal nerve fibre layer (pRNFL) protocols of the Spectralis SD-OCT. Principal component analysis (PCA), a data reduction method, was applied to identify and characterise the main information provided by the ganglion cell complex (GCC). The discriminative ability between healthy and glaucomatous eyes of the first principal components (PCs) was compared with that of conventional SD-OCT parameters (pRNFL, macular RNFL (mRNFL), macular ganglion cell layer (mGCL)and macular inner plexiform layer (mIPL)) using 10-fold cross-validated areas under the curve (AUC). Results The first PC explained 58% of the total information contained in the GCC and the pRNFL parameters and was the result of a general combination of almost all variables studied (diffuse distribution). Other PCs were driven mainly by pRNFL and mRNFL measurements. PCs and pRNFL had similar AUC (0.95 vs 0.96, p=0.88), and outperformed the other structural measurements: mRNFL (0.91, p=0.002), mGCL (0.92, p=0.02) and mIPL (0.92, p=0.0001). Conclusions PCA identified a diffuse representation of the papillary and macular SD-OCT parameters as the most important PC to summarise structural data in healthy and glaucomatous eyes. PCs and pRNFL parameters showed the greatest discriminative ability between healthy and glaucoma cases.

Glaucoma is the leading cause of irreversible blindness and involves the death of retinal ganglion cells (RGCs). Although biomechanics likely contributes to axonal injury within the optic nerve head (ONH), leading to RGC death, the pathways by which this occurs are not well understood. While rat models of glaucoma are well-suited for mechanistic studies, the anatomy of the rat ONH is different from the human, and the resulting differences in biomechanics have not been characterized. The aim of this study is to describe a methodology for building individual-specific finite element (FE) models of rat ONHs. This method was used to build three rat ONH FE models and compute the biomechanical environment within these ONHs. Initial results show that rat ONH strains are larger and more asymmetric than those seen in human ONH modeling studies. This method provides a framework for building additional models of normotensive and glaucomatous rat ONHs. Comparing model strain patterns with patterns of cellular response seen in studies using rat glaucoma models will help us to learn more about the link between biomechanics and glaucomatous cell death, which in turn may drive the development of novel therapies for glaucoma.

The early failure of glaucoma surgery is mainly caused by over-fibrosis at the subconjunctival space, causing obliteration of the filtration bleb. Because fibrosis has a suspected basis of genetic predisposition, we have undertaken a prospective study to identify upregulated profibrotic genes in a population of glaucoma patients with signs of conjunctival fibrosis and early postoperative surgical failure. Clinical data of re-operated fibrosis patients, hyperfibrosis patients who re-operated more than once in a short time, and control patients with no fibrosis were recorded and analyzed at each follow-up visit. Conjunctival-Tenon surgical specimens were obtained intraoperatively to evaluate the local expression of a panel of genes potentially associated with fibrosis. In order to correlate gene expression signatures with protein levels, we quantified secreted proteins in primary cultures of fibroblasts from patients. Expression of VEGFA, CXCL8, MYC, and CDKN1A was induced in the conjunctiva of hyperfibrosis patients. VEGFA and IL8 protein levels were also increased in fibroblast supernatants. We propose that an increase in these proteins could be useful in detecting conjunctival fibrosis in glaucoma patients undergoing filtering surgery. Molecular markers could be crucial for early detection of patients at high risk of failure of filtration surgery, leading to more optimal and personalized treatments.