Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study.

PurposeAlthough recent studies have shown that macular pigment (MP) is significantly lower in glaucoma patients, this relationship merits further investigation.MethodsThis cross-sectional study included 85 glaucoma patients and 22 controls. All subjects had standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) thickness measurements. Intake of lutein (L) and zeaxanthin (Z) was estimated using a novel dietary screener. The Heidelberg Spectralis dual-wavelength autofluorescence (AF) technology was employed to study the relationship between MP and glaucoma. The association between MP volume and glaucoma was investigated using linear regression models accounting for potential confounding factors.ResultsGlaucoma patients had significantly worse SAP mean deviation (MD) and lower RNFL thickness in the study eye compared to control subjects (P < 0.001 for both). MP (volume) was comparable between groups (P = 0.436). In the univariable model, diagnosis of glaucoma was not associated with MP volume (R2 = 1.22%; P = 0.257). Dietary intake of L and Z was positively and significantly related to MP in the univariable (P = 0.022) and multivariable (P = 0.020) models.ConclusionsThese results challenge previous studies that reported that glaucoma is associated with low MP. Dietary habits were found to be the main predictor of MP in this sample. Further research is merited to better understand the relationship between glaucoma, MP, and visual performance in these patients

Detecting retinal nerve fibre layer segmentation errors on spectral domain-optical coherence tomography with a deep learning algorithm

In this study we developed a deep learning (DL) algorithm that detects errors in retinal never fibre layer (RNFL) segmentation on spectral-domain optical coherence tomography (SDOCT) B-scans using human grades as the reference standard. A dataset of 25,250 SDOCT B-scans reviewed for segmentation errors by human graders was randomly divided into validation plus training (50%) and test (50%) sets. The performance of the DL algorithm was evaluated in the test sample by outputting a probability of having a segmentation error for each B-scan. The ability of the algorithm to detect segmentation errors was evaluated with the area under the receiver operating characteristic (ROC) curve. Mean DL probabilities of segmentation error in the test sample were 0.90 +/- 0.17 vs. 0.12 +/- 0.22 (P < 0.001) for scans with and without segmentation errors, respectively. The DL algorithm had an area under the ROC curve of 0.979 (95%CI: 0.974 to 0.984) and an overall accuracy of 92.4%. For the B-scans with severe segmentation errors in the test sample, the DL algorithm was 98.9% sensitive. This algorithm can help clinicians and researchers review images for artifacts in SDOCT tests in a timely manner and avoid inaccurate diagnostic interpretations9COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESSem informaçã

What Is the amount of visual field loss associated with disability in glaucoma?

To propose a new methodology for classifying patient-reported outcomes in glaucoma and for quantifying the amount of visual field damage associated with disability in the disease. DESIGN: Cross-sectional study. METHODS: A total of 263 patients with glaucoma were included. Vision-related disability was assessed by the National Eye Institute Visual Function Questionnaire (NEI VFQ-25). A latent class analysis (LCA) model was applied to analyze NEI VFQ-25 data and patients were divided into mutually exclusive classes according to their responses to the questionnaires. Differences in standard automated perimetry (SAP) mean deviation (MD) and integrated binocular mean sensitivity (MS) values between classes were investigated. The optimal number of classes was defined based on goodness-of-fit criteria, interpretability, and clinical utility. RESULTS: The model with 2 classes, disabled and nondisabled, had the best fit with an entropy of 0.965, indicating excellent separation of classes. The disabled group had 48 (18%) patients, whereas 215 (82%) patients were classified as nondisabled. The average MD of the better eye in the disabled group was -5.98 dB vs -2.51 dB in the nondisabled group (P < .001). For the worse eye, corresponding values were -13.36 dB and -6.05 dB, respectively (P < .001). CONCLUSION: Application of an LCA model allowed categorization of patient-reported outcomes and quantification of visual field levels associated with disability in glaucoma. A damage of approximately-6 dB for SAP MD, indicating relatively early visual field loss, may already be associated with significant disability if occurring in the better eye. (C) 2018 Elsevier Inc. All rights reserved1974552NATIONAL INSTITUTES OF HEALTH/NATIONAL EYE INSTItuteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Eye Institute (NEI) [EY025056, EY021818

Comparison between the nGoggle and Optical Coherence Tomography for Detecting Glaucoma

Univ Calif San Diego, Visual Performance Lab, La Jolla, CA 92093 USAUniv Fed Sao Paulo, Ophthalmol, Sao Paulo, SP, BrazilUniv Calif San Diego, Swartz Ctr Computat Neurosci, San Diego, CA 92103 USANatl Chiao Tung Univ, Dept Comp Sci, Hsinchu, TaiwanUniv Fed Sao Paulo, Ophthalmol, Sao Paulo, SP, BrazilWeb of Scienc

Macular Pigment and Visual Function in Patients With Glaucoma: The San Diego Macular Pigment Study.

PurposeAlthough recent studies have shown that macular pigment (MP) is significantly lower in glaucoma patients, this relationship merits further investigation.MethodsThis cross-sectional study included 85 glaucoma patients and 22 controls. All subjects had standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) thickness measurements. Intake of lutein (L) and zeaxanthin (Z) was estimated using a novel dietary screener. The Heidelberg Spectralis dual-wavelength autofluorescence (AF) technology was employed to study the relationship between MP and glaucoma. The association between MP volume and glaucoma was investigated using linear regression models accounting for potential confounding factors.ResultsGlaucoma patients had significantly worse SAP mean deviation (MD) and lower RNFL thickness in the study eye compared to control subjects (P &lt; 0.001 for both). MP (volume) was comparable between groups (P = 0.436). In the univariable model, diagnosis of glaucoma was not associated with MP volume (R2 = 1.22%; P = 0.257). Dietary intake of L and Z was positively and significantly related to MP in the univariable (P = 0.022) and multivariable (P = 0.020) models.ConclusionsThese results challenge previous studies that reported that glaucoma is associated with low MP. Dietary habits were found to be the main predictor of MP in this sample. Further research is merited to better understand the relationship between glaucoma, MP, and visual performance in these patients