Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Purpose:To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progression. Methods:Wide-angle SS-OCT, OCT circumpapillary retinal nerve fiber layer (cpRNFL) circle scans spectral-domain (SD)-OCT, standard automated perimetry (SAP), and frequency doubling technology (FDT) visual field tests were completed every 3 months for 2 years from a cohort of 28 healthy participants (56 eyes) and 93 glaucoma participants (179 eyes). RNFL thickness maps were extracted from segmented SS-OCT images and an unsupervised machine learning approach based on principal component analysis (PCA) was used to identify novel structural features. Area under the receiver operating characteristic curve (AUC) was used to assess diagnostic accuracy of RNFL PCA for detecting glaucoma and progression compared to SAP, FDT, and cpRNFL measures. Results:The RNFL PCA features were significantly associated with mean deviation (MD) in both SAP (R2 = 0.49, P < 0.0001) and FDT visual field testing (R2 = 0.48, P < 0.0001), and with mean circumpapillary RNFL thickness (cpRNFLt) from SD-OCT (R2 = 0.58, P < 0.0001). The identified features outperformed each of these measures in detecting glaucoma with an AUC of 0.95 for RNFL PCA compared to an 0.90 for mean cpRNFLt (P = 0.09), 0.86 for SAP MD (P = 0.034), and 0.83 for FDT MD (P = 0.021). Accuracy in predicting progression was also significantly higher for RNFL PCA compared to SAP MD, FDT MD, and mean cpRNFLt (P = 0.046, P = 0.007, and P = 0.044, respectively). Conclusions:A computational approach can identify structural features that improve glaucoma detection and progression prediction

The Relative Odds of Progressing by Structural and Functional Tests in Glaucoma.

PurposeThe purpose of this study was to evaluate the effect of disease severity and number of tests acquired during follow-up on the relative odds of identifying progression by structural or functional tests in glaucoma.MethodsThis was an observational cohort study involving 462 eyes of 305 patients with glaucoma and 62 eyes of 49 healthy subjects. Glaucoma patients and healthy subjects were followed for an average of 3.6 ± 0.9 and 3.8 ± 0.9 years, with a median (interquantile range) of 8 (6-9) and 7 (6-8) visits, respectively. At each visit, subjects underwent visual field assessment with standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) evaluation by spectral-domain optical coherence tomography (SD-OCT). Slopes of change in SAP mean sensitivity and OCT RNFL thickness over time were estimated by linear regression using progressively cumulative visits over time. Cutoff values for age-related expected rates of change for each test were obtained from the healthy group. Progression by SD-OCT and/or SAP was determined if the slope of change was statistically significant and also lower (faster) than the fifth percentile cutoff calculated from the healthy group. A generalized estimating equation logistic regression model was used to evaluate the relative odds of progressing by OCT versus SAP in glaucoma eyes.ResultsEyes with less severe disease at baseline had a higher chance of being detected as progressing by SD-OCT but not by SAP, whereas an increase in disease severity at baseline increased the chance that the eye would be detected as progressing by SAP but not SD-OCT. Each 1 dB higher MD was associated with a 5% increase in the odds of detecting progression by SD-OCT versus SAP (odds ratio = 1.05 per 1 dB; 95% confidence interval: 1.01-1.09; P = 0.005).ConclusionsThe ability to detect glaucoma progression by SAP versus SD-OCT is significantly influenced by the stage of disease. Our results may provide useful information for guiding clinicians on the relative utility of these tests for detecting change throughout the disease continuum

Validating Variational Bayes Linear Regression Method With Multi-Central Datasets.

PurposeTo validate the prediction accuracy of variational Bayes linear regression (VBLR) with two datasets external to the training dataset.MethodThe training dataset consisted of 7268 eyes of 4278 subjects from the University of Tokyo Hospital. The Japanese Archive of Multicentral Databases in Glaucoma (JAMDIG) dataset consisted of 271 eyes of 177 patients, and the Diagnostic Innovations in Glaucoma Study (DIGS) dataset includes 248 eyes of 173 patients, which were used for validation. Prediction accuracy was compared between the VBLR and ordinary least squared linear regression (OLSLR). First, OLSLR and VBLR were carried out using total deviation (TD) values at each of the 52 test points from the second to fourth visual fields (VFs) (VF2-4) to 2nd to 10th VF (VF2-10) of each patient in JAMDIG and DIGS datasets, and the TD values of the 11th VF test were predicted every time. The predictive accuracy of each method was compared through the root mean squared error (RMSE) statistic.ResultsOLSLR RMSEs with the JAMDIG and DIGS datasets were between 31 and 4.3 dB, and between 19.5 and 3.9 dB. On the other hand, VBLR RMSEs with JAMDIG and DIGS datasets were between 5.0 and 3.7, and between 4.6 and 3.6 dB. There was statistically significant difference between VBLR and OLSLR for both datasets at every series (VF2-4 to VF2-10) (P < 0.01 for all tests). However, there was no statistically significant difference in VBLR RMSEs between JAMDIG and DIGS datasets at any series of VFs (VF2-2 to VF2-10) (P > 0.05).ConclusionsVBLR outperformed OLSLR to predict future VF progression, and the VBLR has a potential to be a helpful tool at clinical settings

Estimated Rates of Retinal Ganglion Cell Loss in Glaucomatous Eyes with and without Optic Disc Hemorrhages

Purpose: To evaluate whether optic disc hemorrhages are associated with faster rates of estimated retinal ganglion cell (RGC) loss in glaucoma.Methods: A longitudinal observational cohort study of 222 eyes of 122 patients with glaucoma recruited from the Diagnostic Innovations Glaucoma Study (DIGS) followed for an average of 3.74 +/- 0.85 years. All subjects had optical coherence tomography and standard automated perimetry during follow up. Optic disc hemorrhages were detected by masked evaluation of stereophotographs. Rates of change in estimated numbers of RGCs were determined using a previously described method. A random coefficients model was used to investigate the relationship between disc hemorrhages and rates of change in estimated RGC counts over time.Results: 19 eyes of 18 subjects had at least one disc hemorrhage during follow up. At baseline, average estimated RGC counts in eyes with and without disc hemorrhages were 677,994 cells and 682,021 cells, respectively (P = 0.929). Eyes with optic disc hemorrhages during follow-up had significantly faster rates of estimated RGC loss than eyes without disc hemorrhages (22,233 cells/year versus 10,704 cells/year, P = 0.020). the effect of disc hemorrhages on the rates of estimated RGC loss remained significant after adjusting for confounding variables.Conclusion: Eyes with disc hemorrhages showed faster rates of RGC loss compared to eyes without disc hemorrhages. These results provide further evidence that disc hemorrhages should be considered as an indicator of increased risk for faster neural loss in glaucoma.National Institutes of Health/National Eye InstituteResearch to Prevent Blindness (New York, N.Y.)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)AlconAllerganPfizerMerckSantenUniv Calif San Diego, Hamilton Glaucoma Ctr, San Diego, CA 92103 USAUniv Calif San Diego, Dept Ophthalmol, San Diego, CA 92103 USAUniversidade Federal de São Paulo, Dept Ophthalmol, São Paulo, BrazilUniv Edinburgh, Princess Alexandra Eye Pavil, Edinburgh, Midlothian, ScotlandUniv Edinburgh, Dept Ophthalmol, Edinburgh, Midlothian, ScotlandUniversidade Federal de São Paulo, Dept Ophthalmol, São Paulo, BrazilNational Institutes of Health/National Eye Institute: EY021818National Institutes of Health/National Eye Institute: EY11008National Institutes of Health/National Eye Institute: EY14267National Institutes of Health/National Eye Institute: EY019869National Institutes of Health/National Eye Institute: P30EY022589CAPES: 12309-13-3Web of Scienc

Optical Coherence Tomography Angiography Vessel Density in Healthy, Glaucoma Suspect, and Glaucoma Eyes.

PurposeThe purpose of this study was to compare retinal nerve fiber layer (RNFL) thickness and optical coherence tomography angiography (OCT-A) retinal vasculature measurements in healthy, glaucoma suspect, and glaucoma patients.MethodsTwo hundred sixty-one eyes of 164 healthy, glaucoma suspect, and open-angle glaucoma (OAG) participants from the Diagnostic Innovations in Glaucoma Study with good quality OCT-A images were included. Retinal vasculature information was summarized as a vessel density map and as vessel density (%), which is the proportion of flowing vessel area over the total area evaluated. Two vessel density measurements extracted from the RNFL were analyzed: (1) circumpapillary vessel density (cpVD) measured in a 750-μm-wide elliptical annulus around the disc and (2) whole image vessel density (wiVD) measured over the entire image. Areas under the receiver operating characteristic curves (AUROC) were used to evaluate diagnostic accuracy.ResultsAge-adjusted mean vessel density was significantly lower in OAG eyes compared with glaucoma suspects and healthy eyes. (cpVD: 55.1 ± 7%, 60.3 ± 5%, and 64.2 ± 3%, respectively; P < 0.001; and wiVD: 46.2 ± 6%, 51.3 ± 5%, and 56.6 ± 3%, respectively; P < 0.001). For differentiating between glaucoma and healthy eyes, the age-adjusted AUROC was highest for wiVD (0.94), followed by RNFL thickness (0.92) and cpVD (0.83). The AUROCs for differentiating between healthy and glaucoma suspect eyes were highest for wiVD (0.70), followed by cpVD (0.65) and RNFL thickness (0.65).ConclusionsOptical coherence tomography angiography vessel density had similar diagnostic accuracy to RNFL thickness measurements for differentiating between healthy and glaucoma eyes. These results suggest that OCT-A measurements reflect damage to tissues relevant to the pathophysiology of OAG

Association of severity of primary open-angle glaucoma with serum vitamin D levels in patients of African descent.

PurposeTo study the relationship between primary open-angle glaucoma (POAG) in a cohort of patients of African descent (AD) and serum vitamin D levels.MethodsA subset of the AD and glaucoma evaluation study III (ADAGES III) cohort, consisting of 357 patients with a diagnosis of POAG and 178 normal controls of self-reported AD, were included in this analysis. Demographic information, family history, and blood samples were collected from all the participants. All the subjects underwent clinical evaluation, including visual field (VF) mean deviation (MD), central cornea thickness (CCT), intraocular pressure (IOP), and height and weight measurements. POAG patients were classified into early and advanced phenotypes based on the severity of their visual field damage, and they were matched for age, gender, and history of hypertension and diabetes. Serum 25-Hydroxy (25-OH) vitamin D levels were measured by enzyme-linked immunosorbent assay (ELISA). The association of serum vitamin D levels with the development and severity of POAG was tested by analysis of variance (ANOVA) and the paired t-test.ResultsThe 178 early POAG subjects had a visual field MD of better than -4.0 dB, and the 179 advanced glaucoma subjects had a visual field MD of worse than -10 dB. The mean (95% confidence interval [CI]) levels of vitamin D of the subjects in the control (8.02 ± 6.19 pg/ml) and early phenotype (7.56 ± 5.74 pg/ml) groups were significantly or marginally significantly different from the levels observed in subjects with the advanced phenotype (6.35 ± 4.76 pg/ml; p = 0.0117 and 0.0543, respectively). In contrast, the mean serum vitamin D level in controls was not significantly different from that of the subjects with the early glaucoma phenotype (p = 0.8508).ConclusionsIn this AD cohort, patients with advanced glaucoma had lower serum levels of vitamin D compared with early glaucoma and normal subjects

Macular Ganglion Cell Inner Plexiform Layer Thickness in Glaucomatous Eyes with Localized Retinal Nerve Fiber Layer Defects

Purpose: To investigate macular ganglion cell–inner plexiform layer (mGCIPL) thickness in glaucomatous eyes with visible localized retinal nerve fiber layer (RNFL) defects on stereophotographs. Methods: 112 healthy and 149 glaucomatous eyes from the Diagnostic Innovations in Glaucoma Study (DIGS) and the African Descent and Glaucoma Evaluation Study (ADAGES) subjects had standard automated perimetry (SAP), optical coherence tomography (OCT) imaging of the macula and optic nerve head, and stereoscopic optic disc photography. Masked observers identified localized RNFL defects by grading of stereophotographs. Result: 47 eyes had visible localized RNFL defects on stereophotographs. Eyes with visible localized RNFL defects had significantly thinner mGCIPL thickness compared to healthy eyes (68.3 ± 11.4 μm versus 79.2 ± 6.6 μm respectively, P<0.001) and similar mGCIPL thickness to glaucomatous eyes without localized RNFL defects (68.6 ± 11.2 μm, P = 1.000). The average mGCIPL thickness in eyes with RNFL defects was 14% less than similarly aged healthy controls. For 29 eyes with a visible RNFL defect in just one hemiretina (superior or inferior) mGCIPL was thinnest in the same hemiretina in 26 eyes (90%). Eyes with inferior-temporal RNFL defects also had significantly thinner inferior-temporal mGCIPL (P<0.001) and inferior mGCIPL (P = 0.030) compared to glaucomatous eyes without a visible RNFL defect. Conclusion: The current study indicates that presence of a localized RNFL defect is likely to indicate significant macular damage, particularly in the region of the macular that topographically corresponds to the location of the RNFL defect

Glaucomatous Patterns in Frequency Doubling Technology (FDT) Perimetry Data Identified by Unsupervised Machine Learning Classifiers

Purpose: The variational Bayesian independent component analysis-mixture model (VIM), an unsupervised machine-learning classifier, was used to automatically separate Matrix Frequency Doubling Technology (FDT) perimetry data into clusters of healthy and glaucomatous eyes, and to identify axes representing statistically independent patterns of defect in the glaucoma clusters. Methods: FDT measurements were obtained from 1,190 eyes with normal FDT results and 786 eyes with abnormal FDT results from the UCSD-based Diagnostic Innovations in Glaucoma Study (DIGS) and African Descent and Glaucoma Evaluation Study (ADAGES). For all eyes, VIM input was 52 threshold test points from the 24-2 test pattern, plus age. Results: FDT mean deviation was -1.00 dB (S.D. = 2.80 dB) and -5.57 dB (S.D. = 5.09 dB) in FDT-normal eyes and FDT-abnormal eyes, respectively (p&lt;0.001). VIM identified meaningful clusters of FDT data and positioned a set of statistically independent axes through the mean of each cluster. The optimal VIM model separated the FDT fields into 3 clusters. Cluster N contained primarily normal fields (1109/1190, specificity 93.1%) and clusters G(1) and G(2) combined, contained primarily abnormal fields (651/786, sensitivity 82.8%). For clusters G(1) and G(2) the optimal number of axes were 2 and 5, respectively. Patterns automatically generated along axes within the glaucoma clusters were similar to those known to be indicative of glaucoma. Fields located farther from the normal mean on each glaucoma axis showed increasing field defect severity. Conclusions: VIM successfully separated FDT fields from healthy and glaucoma eyes without a priori information about class membership, and identified familiar glaucomatous patterns of loss.open0