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.

Purpose To evaluate the association between vessel density measurements using optical coherence tomography angiography (OCT-A) and severity of visual field loss in primary open-angle glaucoma (POAG) Design Observational cross-sectional study Participants One hundred and fifty three eyes from 31 healthy, 48 glaucoma suspects, and 74 glaucoma participants enrolled in the Diagnostic Innovations in Glaucoma Study Methods All eyes underwent imaging using an OCT-A (Angiovue, Optovue; Fremont, CA) and a spectral domain OCT (Avanti, Optovue; Fremont, CA), along with standard automated perimetry (SAP). Retinal vasculature information was summarized as vessel density, the percent of area occupied by flowing blood vessels in the selected region. Two measurements from the retinal nerve fiber layer (RNFL) were utilized: circumpapillary vessel density (cpVD) (750-μm-wide elliptical annulus around the optic disc); and whole image vessel density (wiVD) (entire 4.5 × 4.5 mm scan field) Main Outcome Measures Associations between severity of visual field loss, reported as SAP mean deviation (MD) and OCT-A vessel density Results Compared to POAG eyes, normal eyes demonstrated a denser microvascular network within the RNFL. Vessel density was higher in normal eyes followed by glaucoma suspects, mild glaucoma and moderate to severe glaucoma eyes for wiVD (55.5, 51.3, 48.3, 41.7% respectively) and for cpVD (62.8, 61.0, 57.5, 49.6% respectively) (P<0.001 for both). The association between the severity of visual field damage (MD) with cpVD and wiVD was stronger (R2=0.54, and R2=0.51 respectively) than the association between visual field MD and RNFL (R2=0.36) and rim area (R2=0.19) (P<0.05 for all). Multivariate regression analysis, adjusted for confounders, showed that each 1% decrease in cpVD was associated with 0.64 dB loss in MD and each 1% decrease in wiVD, was associated with 0.66 dB loss in MD. In addition, the association between vessel density and the severity of visual field damage was found to be significant even after controlling for the effect of structural loss Conclusions Decreased vessel density was significantly associated with severity of visual field damage independent of the structural loss. OCT-A is a promising technology in glaucoma management, potentially enhancing the understanding of vascular role in the pathophysiology of the disease

Purpose To investigate factors associated with dropout of the deep retinal layer microvasculature within the β-zone parapapillary atrophy (βPPA) assessed by optical coherence tomography angiography (OCT-A) in glaucomatous eyes. Design Cross-sectional study. Participants Seventy-one eyes from 71 primary open angle glaucoma (POAG) patients with βPPA enrolled in the Diagnostic Innovations in Glaucoma Study. Methods βPPA deep layer microvasculature dropout was defined as a complete loss of the microvasculature located within deep retinal layer of the βPPA from OCT-A-derived optic nerve head vessel density maps by standardized qualitative assessment. Circumpapillary vessel density (cpVD) within the retinal nerve fiber layer (RNFL) was also calculated using OCT-A. Choroidal thickness and presence of the focal lamina cribrosa (LC) defect were determined using swept-source OCT. Main Outcome Measures Presence of the βPPA deep layer microvasculature dropout. Parameters including age, systolic and diastolic blood pressure, axial length, intraocular pressure, disc hemorrhage, cpVD, visual field (VF) mean deviation (MD), focal LC defect, βPPA area, and choroidal thickness were analyzed. Results βPPA deep layer microvasculature dropout was detected in 37 eyes (52.1%) of eyes with POAG. Eyes with dropouts had a higher prevalence of LC defect (70.3 vs. 32.4%), lower cpVD (52.7 vs. 58.8%), worse VF MD (-9.06 vs. -3.83dB), thinner total choroidal thickness (126.5 vs. 169.1/μm), longer axial length (24.7 vs. 24.0mm), larger βPPA (1.2 vs. 0.76mm2) and lower diastolic blood pressure (74.7 vs. 81.7mmHg) than those without dropouts (P< 0.05, respectively). In the multivariate logistic regression, higher prevalence of focal LC defect (odds ratio [OR], 6.27; P = 0.012), reduced cpVD (OR, 1.27; P = 0.002), worse VF MD (OR, 1.27; P = 0.001), thinner choroidal thickness (OR, 1.02; P = 0.014), and lower diastolic blood pressure (OR, 1.16; P = 0.003) were significantly associated with the dropout. Conclusions Certain systemic and ocular factors such as focal LC defect, more advanced disease status, reduced RNFL vessel density, thinner choroidal thickness, and lower diastolic blood pressure were factors associated with the βPPA deep layer microvasculature dropout in glaucomatous eyes. Longitudinal studies are required to elucidate the temporal relationship between βPPA deep layer dropout and these factors.

The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus photographs was evaluated. A large database of fundus photographs (n = 14,822) from a racially and ethnically diverse group of individuals (over 33% of African descent) was evaluated by expert reviewers and classified as GON or healthy. Several deep learning architectures and the impact of transfer learning were evaluated. The best performing model achieved an overall area under receiver operating characteristic (AUC) of 0.91 in distinguishing GON eyes from healthy eyes. It also achieved an AUC of 0.97 for identifying GON eyes with moderate-to-severe functional loss and 0.89 for GON eyes with mild functional loss. A sensitivity of 88% at a set 95% specificity was achieved in detecting moderate-to-severe GON. In all cases, transfer improved performance and reduced training time. Model visualizations indicate that these deep learning models relied on, in part, anatomical features in the inferior and superior regions of the optic disc, areas commonly used by clinicians to diagnose GON. The results suggest that deep learning-based assessment of fundus images could be useful in clinical decision support systems and in the automation of large-scale glaucoma detection and screening programs.