Temporal Raphe Sign for Discrimination of Glaucoma from Optic Neuropathy in Eyes with Macular Ganglion Cell-Inner Plexiform Layer Thinning

Case series: Superficial plexus en face may aid distinction of retinal nerve fiber layer loss from diabetic retinal ischemia versus glaucoma

PURPOSE

This study aimed to demonstrate that the pattern and degree of capillary bed dropout in early glaucoma appear different on OCT-A superficial plexus en-face slabs compared with retinal ischemia. RNFL loss associated with retinal ischemia in diabetic patients may be explained and accounted for by overlying the RNFL deviation map on a superficial plexus en-face montage.

CASE REPORTS

Three middle-aged White men with diabetes mellitus showed cup-to-disc ratios of approximately 0.7 and RNFL and ganglion thinning. Each patient had several Cirrus OCT and OCT-A scans taken of the posterior pole. The OCT-A en-face images demonstrated specific patterns of superficial capillary dropout. The appearance of superficial plexus capillary dropout in one case of glaucoma is contrasted against two cases of retinal ischemia.

CONCLUSIONS

Early glaucoma appears to be associated with incomplete capillary bed dropout that extends from macular regions to the disc in a wedge- or arc-shaped pattern. Diabetic retinal ischemia appears to be associated with well-defined patchy and polygonal pockets of complete capillary bed obliteration that may not extend back to the disc. If an RNFL deviation map is superimposed over the superficial plexus en-face montage, areas of RNFL loss may correlate with and thus be well accounted for by areas of retinal ischemia in cases with RNFL thinning likely from ischemia. This approach may supplement inspection of OCT B-scans for focal retinal thinning when trying to differentiate RNFL and ganglion cell loss from retinal ischemia versus glaucoma in patients with diabetes. Formal research studies are needed to validate our observations and proposed use of OCT-A together with OCT in these patients.

Discrimination of glaucomatous from non-glaucomatous optic neuropathy with swept-source optical coherence tomography

OBJECTIVE

To assess the ability of optic nerve head (ONH) parameters, peripapillary retinal nerve fiber layer (pRNFL), and macular ganglion cell layer (GCL) thickness measurements with swept-source optical coherence tomography (SS-OCT), to discriminate between glaucomatous and non-glaucomatous optic neuropathy (GON and NGON).

METHODS

This retrospective cross-sectional study involved 189 eyes of 189 patients, 133 with GON and 56 with NGON. The NGON group included ischemic optic neuropathy, previous optic neuritis, and compressive, toxic-nutritional, and traumatic optic neuropathy. Bivariate analyses of SS-OCT pRNFL and GCL thickness and ONH parameters were performed. Multivariable logistic regression analysis was employed to obtain predictor variables from OCT values, and the area under the receiver operating characteristic curve (AUROC) was calculated to differentiate between NGON and GON.

RESULTS

Bivariate analyses showed that the overall and inferior quadrant of the pNRFL was thinner in the GON group (P=0.044 and P<0.01), while patients with NGON had thinner temporal quadrants (P=0.044). Significant differences between the GON and NGON groups were identified in almost all the ONH topographic parameters. Patients with NGON had thinner superior GCL (P=0.015), but there were no significant differences in GCL overall and inferior thickness. Multivariate logistic regression analysis demonstrated that vertical cup-to-disc ratio (CDR), cup volume, and superior GCL provided independent predictive value for differentiating GON from NGON. The predictive model of these variables along with disc area and age achieved an AUROC=0.944 (95% CI 0.898-0.991).

CONCLUSIONS

SS-OCT is useful in discriminating GON from NGON. Vertical CDR, cup volume, and superior GCL thickness show the highest predictive value.

The Japan Glaucoma Society guidelines for glaucoma 5th edition

We are pleased to bring you the 5th edition of the Glaucoma Clinical Practice Guidelines. Clinical practice guidelines are based on evidence (scientific grounds). It is a document that presents the treatment that is the most appropriate for the patient. "Glaucoma Clinical Guidelines" was first published in 2003. This was the first guideline for glaucoma treatment in Japan. The principle of glaucoma treatment is to lower intraocular pressure. Means for lowering intraocular pressure includes drugs, lasers, and surgery; Glaucoma is a disease that should be considered as a complex syndrome rather than a single condition. Therefore, the actual medical treatment is not as simple as one word. This time we set the Clinical Questionnaire with a focus on glaucoma treatment. We hope that you will take advantage of the 5th edition.

Macular ganglion cell-inner plexiform layer defect patterns in multiple sclerosis patients without optic neuritis: A Spectral-Domain-Optical Coherence Tomography Cross-Sectional, Case-Control, Pilot Study

PURPOSE

Spectral-domain optical coherence tomography (SD-OCT) was used to evaluate, in patients with multiple sclerosis without a history of optic neuritis (MSNON), the proportion of the different macular ganglion cell-inner plexiform layer complex (mGCIP) defect patterns. The results were compared with those of healthy controls (HCs).

METHODS

In this cross-sectional case-control study, 34 eyes of 34 individuals, 17 with MSNON and 17 HCs, were evaluated. All participants underwent mGCIP thickness measurement using SD-OCT (Zeiss Cirrus HD-OCT 4000, macular cube protocol). The mGCIP defect patterns were classified in nine types (minimal, inner, outer, diffuse mild, diffuse severe inferior confined, inferior dominant, superior confined, and superior dominant), according to the shape derived by the deviation map of the instrument, and the proportion of each type was assessed.

RESULTS

A mGCIP defect pattern was detected in 70.5% of MSNON eyes, with an inner type as the most frequent pattern (47%), followed by the outer type (11.7%) and the inferior confined type (11.7%). No defect was found in Hcs.

CONCLUSIONS

A significant thinning of the mGCIP with the frequent presence of an inner defect was seen in MSNON patients. The presence of this defect may serve as a biomarker of subclinical optic nerve involvement in MS patients.

The ICD-10 Glaucoma Severity Score Underestimates the Extent of Glaucomatous Optic Nerve Damage

PURPOSE

To evaluate the International Classification of Disease, Tenth Revision (ICD-10) codes used for glaucoma severity classification, which are based on the location of visual field (VF) defects; given the known poor sensitivity of the 24-2 visual field test to early disease and macular damage, we hypothesized that the ICD-10 codes would not accurately reflect the extent of glaucomatous damage.

DESIGN

Retrospective validity and reliability analysis.

METHODS

We evaluated 80 eyes with glaucomatous optic neuropathy (GON). Masked reviewers assigned an ICD-10 severity grade based on 24-2 VF. Two additional masked examiners determined the presence of optical coherence tomography (OCT) structural damage in each hemifield and/or central 5 degrees to define an OCT-based equivalent ICD-10 classification.

RESULTS

A total of 80 eyes with GON were classified as mild, moderate and advanced in 15, 23, and 42 cases, respectively, based on the 24-2 VF, and in 6, 7, and 67 cases, respectively, based on OCT. The OCT classifications were more severe in 29 of 80 cases (36%). In 33 cases (41.3%), macular damage detected by OCT was missed by the 24-2. In 4 of 80 cases (5%), the VF overestimated the severity, likely due to variability of the 24-2 test.

CONCLUSIONS

The ICD-10 system relies solely on damage seen on the 24-2 and as provides a 24-2 functional score rather than a "glaucoma" severity score. OCT revealed wide variation of damage across grades, with a significant proportion of the eyes showing macular structural damage missed with the 24-2 VF. Adding OCT information to the ICD-10 system would help it to more accurately reflect the extent of glaucomatous damage.

Multivariate Longitudinal Modeling of Macular Ganglion Cell Complex: Spatiotemporal Correlations and Patterns of Longitudinal Change

Purpose

To investigate spatiotemporal correlations among ganglion cell complex (GCC) superpixel thickness measurements and explore underlying patterns of longitudinal change across the macular region.

Design

Longitudinal cohort study.

Subjects

One hundred eleven eyes from 111 subjects from the Advanced Glaucoma Progression Study with ≥ 4 visits and ≥ 2 years of follow-up.

Methods

We further developed our proposed Bayesian hierarchical model for studying longitudinal GCC thickness changes across macular superpixels in a cohort of glaucoma patients. Global priors were introduced for macular superpixel parameters to combine data across superpixels and better estimate population slopes and intercepts.

Main Outcome Measures

Bayesian residual analysis to inspect cross-superpixel correlations for subject random effects and residuals. Principal component analysis (PCA) to explore underlying patterns of longitudinal macular change.

Results

Average (standard deviation [SD]) follow-up and baseline 10-2 visual field mean deviation were 3.6 (0.4) years and -8.9 (5.9) dB, respectively. Superpixel-level random effects and residuals had the greatest correlations with nearest neighbors; correlations were higher in the superior than in the inferior region and strongest among random intercepts, followed by random slopes, residuals, and residual SDs. PCA of random intercepts showed a first large principal component (PC) across superpixels that approximated a global intercept, a second PC that contrasted the superior and inferior macula, and a third PC, contrasting inner and nasal superpixels with temporal and peripheral superpixels. PCs for slopes, residual SDs, and residuals were remarkably similar to those of random intercepts.

Conclusions

Introduction of cross-superpixel random intercepts and slopes is expected to improve estimation of population and subject parameters. Further model enhancement may be possible by including cross-superpixel random effects and correlations to address spatiotemporal relationships in longitudinal data sets.

Detecting glaucoma with only OCT: Implications for the clinic, research, screening, and AI development

A method for detecting glaucoma based only on optical coherence tomography (OCT) is of potential value for routine clinical decisions, for inclusion criteria for research studies and trials, for large-scale clinical screening, as well as for the development of artificial intelligence (AI) decision models. Recent work suggests that the OCT probability (p-) maps, also known as deviation maps, can play a key role in an OCT-based method. However, artifacts seen on the p-maps of healthy control eyes can resemble patterns of damage due to glaucoma. We document in section 2 that these glaucoma-like artifacts are relatively common and are probably due to normal anatomical variations in healthy eyes. We also introduce a simple anatomical artifact model based upon known anatomical variations to help distinguish these artifacts from actual glaucomatous damage. In section 3, we apply this model to an OCT-based method for detecting glaucoma that starts with an examination of the retinal nerve fiber layer (RNFL) p-map. While this method requires a judgment by the clinician, sections 4 and 5 describe automated methods that do not. In section 4, the simple model helps explain the relatively poor performance of commonly employed summary statistics, including circumpapillary RNFL thickness. In section 5, the model helps account for the success of an AI deep learning model, which in turn validates our focus on the RNFL p-map. Finally, in section 6 we consider the implications of OCT-based methods for the clinic, research, screening, and the development of AI models.

Macular Optical Coherence Tomography Imaging in Glaucoma

The advent of spectral-domain optical coherence tomography has played a transformative role in posterior segment imaging of the eye. Traditionally, images of the optic nerve head and the peripapillary area have been used to evaluate the structural changes associated with glaucoma. Recently, there is growing evidence in the literature supporting the use of macular spectral-domain optical coherence tomography as a complementary tool for clinical evaluation and research purposes in glaucoma. Containing more than 50% of retinal ganglion cells in a multilayered pattern, macula is shown to be affected even at the earliest stages of glaucomatous structural damage. Risk assessment for glaucoma progression, earlier detection of glaucomatous structural damage, monitoring of glaucoma especially in advanced cases, and glaucoma evaluation in certain ocular conditions including eyes with high myopia, positive history of disc hemorrhage, and certain optic disc phenotypes are specific domains where macular imaging yields complementary information compared to optic nerve head and peripapillary evaluation using optical coherence tomography. Moreover, the development of artificial intelligence models in data analysis has enabled a tremendous opportunity to create an integrated representation of structural and functional alterations observed in glaucoma. In this study, we aimed at providing a brief review of the main clinical applications and future potential utility of macular spectral-domain optical coherence tomography in glaucoma.

Accuracy and reliability of measurements obtained with a noncontact tono-pachymeter for clinical use in mass screening

We evaluated the reliability and accuracy of the noncontact CT-1P tonopachymeter (Topcon, Japan) in terms of intraocular pressure (IOP) and central corneal thickness (CCT). One hundred sixty-three healthy participants and 33 patients with open angle glaucoma were enrolled. IOPs were measured by CT-1P (T-IOP) and Goldmann applanation tonometer (G-IOP), and CCTs were measured by the CT-1P (T-CCT) and an ultrasound pachymeter (US-CCT). Both CCT instrument-adjusted (T-IOP-C) and unadjusted T-IOPs (T-IOP-NC) were included. Pearson correlation coefficients and biases assessed with Bland-Altman analysis with 95% confidence interval (CI) were calculated for reliability evaluation. Intrasession repeatability was excellent for both T-IOP (intraclass correlation coefficient [ICC] 0.91) and T-CCT (ICC 0.98). Intersession reproducibility was also excellent for T-CCT (ICC 0.94). T-IOP-NC and T-IOP-C both showed significant correlations with G-IOP (r = 0.801, P  <  0.001 and r = 0.658, P  < 0.001, respectively). T-CCT was also strongly correlated with US-CCT (r = 0.958; P  < 0.001). T-IOP-NC and T-IOP-C both showed a positive bias (1.37 mmHg, 95% CI [1.14, 1.61] and 2.77 mmHg, 95% CI [2.49, 3.05], respectively). T-CCT showed a negative bias of - 17.3 µm (95% CI [-18.8, - 15.8]). With cautious interpretation, the CT-1P may offer good feasibility for IOP and CCT measurement in screening centers.

Temporal Raphe Sign in Elderly Patients With Large Optic Disc Cupping: Its Evaluation as a Predictive Factor for Glaucoma Conversion

PURPOSE

To determine baseline clinical features associated with conversion to glaucoma in elderly patients with large optic-disc cupping.

DESIGN

Retrospective cohort study.

METHODS

Seventy-two eyes of 72 untreated elderly (≥65-year-old) patients with large vertical cup-to-disc ratio (CDR ≥0.7) and without any other glaucomatous findings were included. They had undergone a full ophthalmologic examination twice per year for at least 5 years. The optic nerve head (ONH), peripapillary retinal nerve fiber layer (RNFL), and macular ganglion cell-inner plexiform layer (GCIPL) were imaged with Cirrus high-definition optical coherence tomography (OCT). Presence of temporal raphe sign on the OCT's GCIPL thickness map was assessed as one of the morphologic factors. Conversion to normal-tension glaucoma (NTG) was defined as structural or functional deterioration on either red-free RNFL photography or standard automated perimetry, respectively. The utility of the baseline factors associated with conversion to NTG were identified.

RESULTS

During the 5.5-year follow-up, 19 eyes (26.4%) converted to NTG. There were no significant differences in demographics, systemic factors, intraocular pressure factors, or OCT parameters between the nonconverters and converters. Interestingly, the temporal raphe sign was observed in the converters (18/19, 94.7%) much more frequently than in the nonconverters (3/53, 5.7%, P < .001) at baseline. A Cox proportional hazards model indicated the significant influences of temporal raphe sign positivity (hazard ratio 6.823, 95% confidence interval 2.574, 18.088, P < .001) on conversion to NTG.

CONCLUSIONS

In elderly subjects with large CDR, temporal raphe sign positivity on the baseline macular GCIPL thickness map was associated with faster conversion to NTG.

Macular imaging with optical coherence tomography in glaucoma

With the advent of spectral-domain optical coherence tomography, imaging of the posterior segment of the eye can be carried out rapidly at multiple anatomical locations, including the optic nerve head, circumpapillary retinal nerve fiber layer, and macula. There is now ample evidence to support the role of spectral-domain optical coherence tomography imaging of the macula for detection of early glaucoma. Macular spectral-domain optical coherence tomography measurements demonstrate high reproducibility, and evidence on its utility for detection of glaucoma progression is accumulating. We present a comprehensive review of macular spectral-domain optical coherence tomography imaging emerging as an essential diagnostic tool in glaucoma.

Pre-perimetric Open Angle Glaucoma with Young Age of Onset: Natural Clinical Course and Risk Factors for Progression

PURPOSE

To investigate the natural clinical course of more than 5 years and the risk factors of progression in patients with pre-perimetric open angle glaucoma (OAG) of "young age of onset (under age 40)" without treatment.

DESIGN

Retrospective observational case series.

METHODS

Optic disc photography, red-free retinal nerve fiber layer (RNFL) photography, optical coherence tomography, and visual field (VF) examinations were performed every 6 months. Glaucoma progression was defined as structural or functional deterioration. A linear mixed-effects model was used to estimate the rate of structural and functional changes. Kaplan-Meier survival analysis and log-rank testing were used to compare survival experiences, and Cox proportional hazards modeling was performed to identify risk factors for glaucoma progression.

RESULTS

Of the 98 eyes of 98 patients (mean age, 30.6 years old), glaucoma progression was detected in 42 eyes (42.9%). The rate of average RNFL thickness thinning was -0.46 ± 0.50 μm/y, and the mean deviation (MD) change was -0.03 ± 0.13 dB/y. The glaucoma progression probability at 5 years was 39% by structural criteria and 5% by functional criteria. Older age at diagnosis (P = .004), presence of temporal raphe sign (horizontal straight line on macular ganglion cell-inner plexiform layer thickness map) (P = .011), lamina pore visibility (P = .034), and greater pattern standard deviation (P = .005) were significant factors for glaucoma progression.

CONCLUSIONS

In untreated pre-perimetric OAG patients with a "young age of onset" condition, the estimated MD slope for the disease course of more than 5 years was -0.03 dB/y, and the average RNFL thinning rate was -0.46 μm/y. The predictors for progression were structural parameters of temporal raphe sign, lamina pore visibility, and functional parameter of pattern standard deviation.

Focal alteration of the intraretinal layers in neurodegenerative disorders

Focal intraretinal alterations have been studied to advance our understanding of the pathology of neurodegenerative diseases. The current literature involving focal alterations in the intraretinal layers was reviewed through PubMed using the search terms "focal alteration", "region of interest", "optical coherence tomography", "glaucoma", "multiple sclerosis", "Alzheimer's disease", "Parkinson disease", "neurodegenerative diseases" and other related items. It was found that focal alterations of intraretinal layers were different in various neurodegenerative diseases. The typical focal thinning might help differentiate various ocular and cerebral diseases, track disease progression, and evaluate the outcome of clinical trials. Advanced exploration of focal intraretinal alterations will help to further validate their clinical and research utility.

Discriminating glaucomatous and compressive optic neuropathy on spectral-domain optical coherence tomography with deep learning classifier

BACKGROUND/AIMS

To assess the performance of a deep learning classifier for differentiation of glaucomatous optic neuropathy (GON) from compressive optic neuropathy (CON) based on ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fibre layer (RNFL) spectral-domain optical coherence tomography (SD-OCT).

METHODS

Eighty SD-OCT image sets from 80 eyes of 80 patients with GON along with 81 SD-OCT image sets from 54 eyes of 54 patients with CON were compiled for the study. The bottleneck features extracted from the GCIPL thickness map, GCIPL deviation map, RNFL thickness map and RNFL deviation map were used as predictors for the deep learning classifier. The area under the receiver operating characteristic curve (AUC) was calculated to validate the diagnostic performance. The AUC with the deep learning classifier was compared with those for conventional diagnostic parameters including temporal raphe sign, SD-OCT thickness profile and standard automated perimetry.

RESULTS

The deep learning system achieved an AUC of 0.990 (95% CI 0.982 to 0.999) with a sensitivity of 97.9% and a specificity of 92.6% in a fivefold cross-validation testing, which was significantly larger than the AUCs with the other parameters: 0.804 (95% CI 0.737 to 0.872) with temporal raphe sign, 0.815 (95% CI 0.734 to 0.896) with superonasal GCIPL and 0.776 (95% CI 0.691 to 0.860) with superior GCIPL thicknesses (all p<0.001).

CONCLUSION

The deep learning classifier can outperform the conventional diagnostic parameters for discrimination of GON and CON on SD-OCT.

Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model

We developed a hybrid deep learning model (HDLM) algorithm that quantitatively predicts macular ganglion cell-inner plexiform layer (mGCIPL) thickness from red-free retinal nerve fiber layer photographs (RNFLPs). A total of 789 pairs of RNFLPs and spectral domain-optical coherence tomography (SD-OCT) scans for 431 eyes of 259 participants (183 eyes of 114 healthy controls, 68 eyes of 46 glaucoma suspects, and 180 eyes of 99 glaucoma patients) were enrolled. An HDLM was built by combining a pre-trained deep learning network and support vector machine. The correlation coefficient and mean absolute error (MAE) between the predicted and measured mGCIPL thicknesses were calculated. The measured (OCT-based) and predicted (HDLM-based) average mGCIPL thicknesses were 73.96 ± 8.81 µm and 73.92 ± 7.36 µm, respectively (P = 0.844). The predicted mGCIPL thickness showed a strong correlation and good agreement with the measured mGCIPL thickness (Correlation coefficient r = 0.739; P < 0.001; MAE = 4.76 µm). Even when the peripapillary area (diameter: 1.5 disc diameters) was masked, the correlation (r = 0.713; P < 0.001) and agreement (MAE = 4.87 µm) were not changed significantly (P = 0.378 and 0.724, respectively). The trained HDLM algorithm showed a great capability for mGCIPL thickness prediction from RNFLPs.

Focal Thickness Reduction of the Ganglion Cell-Inner Plexiform Layer Best Discriminates Prior Optic Neuritis in Patients With Multiple Sclerosis

Purpose

The goal was to visualize topographic thickness maps of the intraretinal layers and evaluate their discrimination abilities and relationships with clinical manifestations in patients with multiple sclerosis (MS) and a history of optic neuritis (ON).

Methods

Thirty patients with relapsing-remitting MS (34 eyes with a history of ON [MSON] and 26 non-ON fellow eyes [MSFE]) were recruited together with 63 age- and sex-matched controls (HC). Ultrahigh resolution optical coherence tomography was used to image the macula and the volumetric data set was segmented to yield six intraretinal layers. Topographic thickness maps were aligned and averaged for the visualization. The thickness maps were partitioned using the Early Treatment Diabetic Retinopathy Study (ETDRS) and related to Sloan low-contrast letter acuity (LCLA), Expanded Disability Status Scale (EDSS), and disease duration.

Results

Focal thickness reduction occurred in the macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GCIPL), with the most profound reduction occurring in MSON eyes (P < 0.05). A horseshoe-like thickness reduction pattern (U Zone) in the GCIPL appeared in MSON. The thickness of the U Zone had better discrimination power than the ETDRS partitions (area under the curve = 0.97) and differentiated 96% of MSON from HC. The thickness of the U Zone was positively correlated to 2.5% LCLA (r = 0.38, P < 0.05) and 1.25% LCLA (r = 0.57, P < 0.05).

Conclusions

The horseshoe-like thickness reduction of the GCIPL appeared to be an ON-specific focal thickness alteration with the highest discrimination power of prior ON.