Glaucoma versus red disease: imaging and glaucoma diagnosis

Effect of Bergmeister papilla on disc parameters in spectral domain optical coherence tomography

OBJECTIVES

To investigate the morphological characteristics of Bergmeister papilla (BMP), a persistent hyaloid remnant tissue, and its effects on the measurements and repeatability of spectral-domain optical coherence tomography (OCT).

SUBJECTS/METHODS

The subjects of this prospective cross-sectional study including 83 patients with BMP and 76 unaffected individuals, all had open-angle structures. Images, including a 5-line raster and three consecutive optic disc cube scans centred on the optic disc, were acquired using the Cirrus high-definition OCT. BMP's structural characteristics were classified based on the raster scan images, and repeatability of acquiring optic nerve head and retinal nerve fibre layer parameters acquisition was analysed by calculating the test-retest standard deviation (Sw), coefficient of variance (CV), and intraclass correlation coefficient.

RESULTS

BMPs (n = 83) were categorised into lifting edge (LE) type (63.9%, n = 53), which partially covers the edge of the optic nerve head, and covering disc (CD) type (36.1%, n = 30), which completely covers the cupping area like a cap. The average cup-to-disc ratio (0.58 ± 0.21), vertical cup-to-disc ratio (0.55 ± 0.21), and cup volume (0.22 ± 0.22) of the CD type were lower than those of the LE type (0.66 ± 0.13, 0.64 ± 0.13, and 0.4 ± 0.27, respectively; all P < 0.05). Tolerability indices for repeatability of cup volume (Sw = 0.40 and CV = 0.36) and inferonasal (4 o'clock) retinal nerve fibre layer (Sw = 0.27 and CV = 0.25) in LE-type BMPs exceeded the cut-off value (0.22) and demonstrated stronger correlation with BMP location than that of the controls.

CONCLUSION

Caution should be exercised when interpreting OCT findings in eyes with BMP, as BMP can introduce a pitfall in OCT imaging.

The Finnish current care guideline for open-angle glaucoma

This article is an English translation of the 4th Finnish Current Care Guideline for diagnostics, treatment and follow-up of primary open-angle glaucoma, normal-tension glaucoma and pseudoexfoliative glaucoma. This guideline is based on systematic literature reviews and expert opinions with Finland's geographical and operational healthcare environment in mind.

Racial Differences in Diagnostic Accuracy of Retinal Nerve Fiber Layer Thickness in Primary Open-Angle Glaucoma

Purpose

To evaluate the diagnostic accuracy of retinal nerve fiber layer thickness (RNFLT) by spectral-domain optical coherence tomography (OCT) in primary open-angle glaucoma (POAG) in eyes of African (AD) and European descent (ED).

Design

Comparative diagnostic accuracy analysis by race.

Participants

379 healthy eyes (125 AD and 254 ED) and 442 glaucomatous eyes (226 AD and 216 ED) from the Diagnostic Innovations in Glaucoma Study and the African Descent and Glaucoma Evaluation Study.

Methods

Spectralis (Heidelberg Engineering GmbH) and Cirrus (Carl Zeiss Meditec) OCT scans were taken within one year from each other.

Main Outcome Measures

Diagnostic accuracy of RNFLT measurements.

Results

Diagnostic accuracy for Spectralis-RNFLT was significantly lower in eyes of AD compared to those of ED (area under the receiver operating curve [AUROC]: 0.85 and 0.91, respectively, P=0.04). Results for Cirrus-RNFLT were similar but did not reach statistical significance (AUROC: 0.86 and 0.90 in AD and ED, respectively, P =0.33). Adjustments for age, central corneal thickness, axial length, disc area, visual field mean deviation, and intraocular pressure yielded similar results.

Conclusions

OCT-RNFLT has lower diagnostic accuracy in eyes of AD compared to those of ED. This finding was generally robust across two OCT instruments and remained after adjustment for many potential confounders. Further studies are needed to explore the potential sources of this difference.

Retinal OCT biomarkers and their association with cognitive function-clinical and AI approaches

Retinal optical coherence tomography (OCT) biomarkers have the potential to serve as early, noninvasive, and cost-effective markers for identifying individuals at risk for cognitive impairments and neurodegenerative diseases. They may also aid in monitoring disease progression and evaluating the effectiveness of interventions targeting cognitive decline. The association between retinal OCT biomarkers and cognitive performance has been demonstrated in several studies, and their importance in cognitive assessment is increasingly being recognized. Machine learning (ML) is a branch of artificial intelligence (AI) with an exponential number of applications in the medical field, particularly its deep learning (DL) subset, which is widely used for the analysis of medical images. These techniques efficiently deal with novel biomarkers when their outcome for the applications of interest is unclear, e.g., for diagnosis, prognosis prediction, disease staging, or any other relevance to clinical practice. However, using AI-based tools for medical purposes must be approached with caution, despite the many efforts to address the black-box nature of such approaches, especially due to the general underperformance in datasets other than those used for their development. Retinal OCT biomarkers are promising as potential indicators for decline in cognitive function. The underlying mechanisms are currently being explored to gain deeper insights into this relationship linking retinal health and cognitive function. Insights from neurovascular coupling and retinal microvascular changes play an important role. Further research is needed to establish the validity and utility of retinal OCT biomarkers as early indicators of cognitive decline and neurodegenerative diseases in routine clinical practice. Retinal OCT biomarkers could then provide a new avenue for early detection, monitoring and intervention in cognitive impairment with the potential to improve patient care and outcomes.

Glaucoma Detection Using Optical Coherence Tomography: Reviewing the Pitfalls of Comparison to Normative Data

PRCIS

Optical coherence tomography is essential in managing glaucoma. This review describes various artifacts that originate from using a normative database to compare the individual's scans. This is a review paper regarding artifacts in optical coherence tomography imaging for glaucoma arising from using a normative database as a reference for healthy retinal nerve fiber layer and ganglion cell layer.

[Retinal optical coherence tomography biomarkers and their association with cognitive functions : Clinical and artificial intelligence approaches. German version]

Retinal optical coherence tomography (OCT) biomarkers have the potential to serve as early, noninvasive, and cost-effective markers for identifying individuals at risk for cognitive impairments and neurodegenerative diseases. They may also aid in monitoring disease progression and evaluating the effectiveness of interventions targeting cognitive decline. The association between retinal OCT biomarkers and cognitive performance has been demonstrated in several studies, and their importance in cognitive assessment is increasingly being recognized. Machine learning (ML) is a branch of artificial intelligence (AI) with an exponential number of applications in the medical field, particularly its deep learning (DL) subset, which is widely used for the analysis of medical images. These techniques efficiently deal with novel biomarkers when their outcome for the applications of interest are unclear, e.g., for the diagnosis, prognosis prediction and disease staging. However, using AI-based tools for medical purposes must be approached with caution, despite the many efforts to address the black-box nature of such approaches, especially due to the general underperformance in datasets other than those used for their development. Retinal OCT biomarkers are promising as potential indicators for decline in cognitive function. The underlying mechanisms are currently being explored to gain deeper insights into this relationship linking retinal health and cognitive function. Insights from neurovascular coupling and retinal microvascular changes play an important role. Further research is needed to establish the validity and utility of retinal OCT biomarkers as early indicators of cognitive decline and neurodegenerative diseases in routine clinical practice. Retinal OCT biomarkers could then provide a new avenue for early detection, monitoring and intervention in cognitive impairment with the potential to improve patient care and outcomes.

Diagnostic performance of wide-field optical coherence tomography angiography for high myopic glaucoma

Diagnosing and monitoring glaucoma in high myopic (HM) eyes are becoming very important; however, it is challenging to diagnose this condition. This study aimed to evaluate the diagnostic ability of wide-field optical coherence tomography angiography (WF-OCTA) maps for the detection of glaucomatous damage in eyes with HM and to compare the diagnostic ability of WF-OCTA maps with that of conventional imaging approaches, including swept-source optical coherence tomography (SS-OCT) wide-field maps. In this retrospective observational study, a total 62 HM-healthy eyes and 140 HM eyes with open-angle glaucoma were included. Patients underwent a comprehensive ocular examination, including SS-OCT wide-field and 12 × 12 WF-OCTA scans. The WF-OCTA map represents the peripapillary and macular superficial vascular density maps. Glaucoma specialists determined the presence of glaucomatous damage in HM eyes by reading the WF-OCTA map and comparing its sensitivity and specificity with those of conventional SS-OCT images. The sensitivity and specificity of 12 × 12 WF-OCTA scans for HM-glaucoma diagnosis were 87.28% and 86.94%, respectively, while, the sensitivity and specificity of SS-OCT wide-field maps for HM-glaucoma diagnosis were 87.49% and 80.51%, respectively. The specificity of the WF-OCTA map was significantly higher than that of the SS-OCT wide-field map (p < 0.05). The sensitivity of the WF-OCTA map was comparable with that of the SS-OCT wide-field map (p = 0.078). The WF-OCTA map showed good diagnostic ability for discriminating HM-glaucomatous eyes from HM-healthy eyes. As a complementary method to an alternative imaging modality, WF-OCTA mapping can be a useful tool for the detection of HM glaucoma.

Addressing Glaucoma in Myopic Eyes: Diagnostic and Surgical Challenges

Epidemiological and genetic studies provide strong evidence supporting an association between myopia and glaucoma. The accurate detection of glaucoma in myopic eyes, especially those with high myopia, remains clinically challenging due to characteristic morphologic features of the myopic optic nerve in addition to limitations of current optic nerve imaging modalities. Distinguishing glaucoma from myopia is further complicated by overlapping perimetric findings. Therefore, longitudinal follow-up is essential to differentiate progressive structural and functional abnormalities indicative of glaucoma from defects that may result from myopia alone. Highly myopic eyes are at increased risk of complications from traditional incisional glaucoma surgery and may benefit from newer microinvasive glaucoma surgeries in select cases.

A Systematic Review of Glaucoma Diagnosis in Prevalence Studies and Quality of Reporting

PRCIS

This systematic review has revealed that variable definitions of glaucoma continue to be used in prevalence studies, despite the introduction of the International Society of Geographic and Epidemiologic Ophthalmology (ISGEO) criteria.

PURPOSE

To systematically review diagnostic criteria and examinations performed in glaucoma prevalence studies over time and determine the quality of reporting. Accurate estimates of glaucoma prevalence are crucial to inform resource allocation. However, diagnosis of glaucoma comprises inherently subjective examinations and the cross-sectional nature of prevalence studies precludes monitoring for progression.

METHODS

A systematic review of PubMed, Embase, Web of Science, and Scopus was performed to examine diagnostic protocols used by glaucoma prevalence studies and evaluate uptake of the ISGEO criteria, introduced in 2002 to standardize glaucoma diagnosis in prevalence studies. Detection bias and compliance with the Strengthening Reporting of Observational Studies in Epidemiology (STROBE) guidelines were evaluated.

RESULTS

Ten thousand five hundred forty-four articles were identified. After deduplication, 5589 articles were screened, yielding 136 articles pertaining to 123 studies. An absence of data in many countries was identified. Ninety-two percent of studies stated diagnostic criteria, and 62% used the ISGEO criteria since their publication. Weaknesses of the ISGEO criteria were identified. Temporal variations in the performance of various examinations were observed, including heterogeneity in angle assessment. Mean STROBE compliance was 82% (range 59-100%); 72 articles had a low risk of detection bias, 4 had a high risk, and 60 had some concerns.

CONCLUSION

Heterogeneous diagnostic definitions persist in glaucoma prevalence studies, despite introduction of the ISGEO criteria. Standardization of criteria remains imperative and the development of new criteria represent a valuable opportunity to achieve this goal. In addition, methods of determining diagnoses are poorly reported, suggesting a need for improvement in study conduct and reporting. Accordingly, we propose the Reporting of quality Of GlaUcoma Epidemiological Studies (ROGUES) Checklist. We have also identified a need for further prevalence studies in regions with limited data and to update Australian angle closure glaucoma prevalence. Design and reporting of future studies can be informed by this review's insights into diagnostic protocols previously used.

Long-term Impact of Immediate Versus Delayed Treatment of Early Glaucoma: Results From the Early Manifest Glaucoma Trial

PURPOSE

To compare long-term visual outcomes in the 2 arms of the Early Manifest Glaucoma Trial (EMGT) and determine if delayed treatment was associated with a penalty in terms of visual function.

DESIGN

Long-term follow-up of a prospective, randomized controlled clinical trial.

METHODS

EMGT was carried out at 2 centers in Sweden; 255 subjects with newly detected, untreated glaucoma were randomized to immediate treatment with topical betaxolol and argon laser trabeculoplasty or to no initial treatment as long as no progression was detected. Subjects were followed prospectively with standard automated perimetry, visual acuity measurements, and tonometry for up to 21 years. Outcomes included vision impairment (VI), the perimetric mean deviation (MD) index and rate of progression, and visual acuity.

RESULTS

At study end, percentages of eyes with VI or blindness were slightly higher in the treated group than in the untreated control group, 12.1% vs 11.0%, and 9.4.% vs 6.1% respectively, as were subjects with VI in at least one eye, 19.5% vs 18.7%. The differences were not statistically significant, nor were cumulative incidences of VI in at least one eye. The control group had more field loss than the treatment group, with median MD in the worse eye of -14.73 dB vs -12.85 dB, and rate of progression of -0.74 vs -0.60 dB/y, which was not statistically significant. Differences in visual acuity were minimal.

CONCLUSIONS

Delaying treatment did not result in serious penalties. VI occurred at similar proportions in both treatment arms with a slight preponderance in the treatment group, whereas visual field damage was slightly higher in the control group.

Toward a Real-world Optical Coherence Tomography Reference Database: Optometric Practices as a Source of Healthy Eyes

SIGNIFICANCE

The reports from optical coherence tomography (OCT) instruments depend on a reference database (RDB) of healthy eyes. Although these RDBs tend to be relatively small, they are time consuming and expensive to obtain. A larger RDB should improve our ability to screen for diseases such as glaucoma.

PURPOSE

To explore the feasibility of developing a large RDB from OCT scans obtained by optometrists as part of their pre-test gathering of information, we tested the hypothesis that these scans are of sufficient quality for an RDB and contain a relatively low base rate of glaucoma and other pathologies (OPs).

METHODS

Optical coherence tomography widefield (12 × 9 mm) scans from 400 eyes of 400 patients were randomly selected from a data set of more than 49,000 scans obtained from four optometry sites. Based on a commercial OCT report and a previously validated reading center method, two OCT graders categorized eyes as unacceptable to use for RDB, healthy (H), optic neuropathy consistent with glaucoma (ON-G), glaucoma suspect, or OPs.

RESULTS

Overall, 29 (7.25%) of the eyes were graded unacceptable. Of the remaining 371 eyes, 352 (94.9%) were graded H. Although, for one site, 7.4% of the eligible eyes were graded ON-G, the average for the other three sites was 1.4%. Adjustments of the reading center criteria resulted in exclusion of more than half of these ON-G and OP eyes.

CONCLUSIONS

The OCT scans obtained from optometry practices as part of their pre-test regimen are of sufficient quality for an RDB and contain a relatively low base rate of glaucoma and OPs. With the suggested exclusion criteria, the scans from optometry practices that are primarily involved in refraction and medical screening services should yield a large, real-world RDB with improved specificity and a base rate of glaucoma and/or OPs comparable with existing RDB.

Concordance of Objectively Detected Retinal Nerve Fiber Bundle Defects in En Face OCT Images with Conventional Structural and Functional Changes in Glaucoma

PURPOSE

To assess how objectively detected defects in retinal nerve fiber bundle (RNFB) reflectance on en face OCT images relate to circumpapillary retinal nerve fiber layer thickness (cpRNFLT) and visual field defects.

DESIGN

Cross-sectional study.

PARTICIPANTS

Sixteen participants with early glaucoma and 29 age-matched healthy controls, of whom 22 had usable en face images for the establishment of normative levels of RNFB reflectance.

METHODS

All the participants underwent cpRNFLT scans, visual field examination, and wide-field OCT. En face reflectivity was assessed objectively using the Summary of Multiple Anatomically Adjusted Slabs method. En face defects were deemed concordant with cpRNFLT when they had at least 1 cpRNFLT point with P < 0.01, within ± 15° of the predicted insertion on the optic disc. Visual fields were examined using custom suprathreshold perimetry and SITA Standard 24-2. For each visual field location, the corresponding reflectance was deemed abnormal if any en face superpixel within ± 1° was abnormal. The overall, positive, and negative agreements were measured in each participant.

MAIN OUTCOME MEASURES

Proportion of concordant defects between en face reflectance analysis and cpRNFLT (%) as well as overall, positive, and negative agreements between en face reflectance analysis and visual field results.

RESULTS

Most en face abnormalities had concordant cpRNFLT defects in the mapped sector (median proportion concordant, 0.85; interquartile range, 0.74-0.95). In eyes with glaucoma, a median of 8.1% (range, 2.4%-23.7%) and 14.9% (range, 3.5%-29.1%) locations showed corresponding en face and visual field defects using 24-2 and custom perimetry, respectively. Both the perimetric strategies had moderate-to-good raw agreement with en face analysis (0.66-0.68), with stronger agreement on normal findings than on defects (0.77-0.78 and 0.4-0.44).

CONCLUSIONS

Objectively extracted reflectance defects showed strong concordance with conventional cpRNFLT damage and good agreement with perimetry, which could be enhanced by further minimization of image artifacts.

Glaucoma Detection in Myopic Eyes: Structural and Vascular Assessment by Optic Coherence Tomography Methods

PRCIS

Retinal nerve fiber layer (RNFL) thickness is helpful in the diagnosis of glaucoma in myopic eyes but neuroretinal rim (NRR) thickness is the most valuable measure. However, changes in optical coherence tomography angiography (OCT-A) parameters are insufficient for the diagnosis of mild to moderate glaucoma in myopia.

PURPOSE

To detect how a multimodal evaluation, which includes RNFL, NRR thickness, and optic nerve head (ONH) OCT-A, affects glaucoma diagnosis in myopic patients.

MATERIALS AND METHODS

Parameters of healthy myopic and myopic glaucoma eyes with an axial length of ≥24 mm were compared. The ONH structural features and peripapillary RNFL thickness were determined with Cirrus 5000 HD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Dublin, CA). The Cirrus 5000 HD-OCT with AngioPlex was utilized to perform OCT-A imaging. The sensitivity and specificity levels were calculated by the best cut-off values with area under curve (AUC).

RESULTS

One hundred healthy myopic and 54 myopic glaucoma eyes were evaluated. In all areas, myopic glaucoma patients exhibited lower RNFL and NRR thickness than healthy myopic individuals ( P <0.05), with the exception of nasal quadrant RNFL thickness ( P =0.152). The mean entire and 4 quadrants of global radial peripapillary capillary (RPC)-perfusion and global RPC flux index (FI) were significantly lower in the group of myopic glaucoma patients except for the nasal quadrant mean RPC perfusion ( P =0.224). The average RNFL and NRR thickness had a significant difference in AUC for the diagnosis of glaucoma in myopic individuals ( P =0.001, for each). The average NRR showed excellent diagnostic performance, whereas the average RNFL showed good diagnostic performance. Average RPC perfusion and average RPC FI showed poor diagnostic ability. The average NRR AUC was more significant than average RPC perfusion and average RPC FI AUC ( P <0.001).

CONCLUSIONS

Although RNFL thickness was helpful to diagnose glaucoma in patients with myopia, the diagnostic power of NRR thickness performed best. OCT-A parameters showed poor diagnostic accuracy for glaucoma and the observed perfusion decrease in myopic glaucoma eyes was not sufficiently discriminative compared with NRR and RNFL thickness measurements.

Glaucoma Rose Plot Analysis: Detecting Early Structural Progression Using Angular Histograms

PURPOSE

To evaluate the novel Rose Plot Analysis (RPA) in the analysis and presentation of glaucoma structural progression data.

DESIGN

Case-control image analysis study using retrospective retinal imaging series.

SUBJECTS

Subjects with open-angle glaucoma with at least 5 registered spectral-domain OCT scans.

METHODS

Glaucoma RPA was developed, combining a novel application of angular histograms and dynamic cluster analysis of circumpapillary retinal nerve fiber layer (cRNFL) OCT data. Rose Plot Analysis plots were created for each eye and each visit. Significant clusters of progression were indicated in red. Three masked clinicians categorized all RPA plots (progressing, not progressing), in addition to measuring the significant RPA area. A masked OCT series assessment with linear regression of averaged global and sectoral cRNFL thicknesses was conducted as the clinical imaging standard.

MAIN OUTCOME MEASURES

Interobserver agreement was compared between RPA and the clinical imaging standard. Discriminative ability was assessed using receiver-operating characteristic curves. The time to detection of progression was compared using a Kaplan-Meier survival analysis, and the agreement of RPA with the clinical imaging standard was calculated.

RESULTS

Seven hundred fourty-three scans from 98 eyes were included. Interobserver agreement was significantly greater when categorizing RPA (κ, 0.86; 95% confidence interval [CI], 0.81-0.91) compared with OCT image series (κ, 0.66; 95% CI, 0.54-0.77). The discriminative power of RPA to differentiate between eyes that were progressing and not progressing (area under the curve [AUC], 0.97; 95% CI, 0.92-1.00) was greater than that of global cRNFL thickness (AUC, 0.71; 95% CI, 0.59-0.82; P < 0.0001) and equivalent to that of sectoral cRNFL regression (AUC, 0.97; 95% CI, 0.92-1.00). A Kaplan-Meier survival analysis showed that progression was detected 8.7 months sooner by RPA than by global cRNFL linear regression (P < 0.0001) in progressing eyes but was not sooner than with sectoral cRNFL (P = 0.06). Rose Plot Analysis showed substantial agreement with the presence of significant thinning on sectoral cRNFL linear regression (κ, 0.715; 95% CI, 0.578-0.853).

CONCLUSIONS

Rose Plot Analysis has been shown to provide accurate and intuitive, at-a-glance data analysis and presentation that improve interobserver agreement and may aid early diagnosis of glaucomatous disease progression.

Regression-Based Strategies to Reduce Refractive Error-Associated Glaucoma Diagnostic Bias When Using OCT and OCT Angiography

Purpose

The purpose of this study was to correct refractive error-associated bias in optical coherence tomography (OCT) and OCT angiography (OCTA) glaucoma diagnostic parameters.

Methods

OCT and OCTA imaging were obtained from participants in the Hong Kong FAMILY cohort. The Avanti/AngioVue OCT/OCTA system was used to measure the peripapillary nerve fiber layer thickness (NFLT), peripapillary nerve fiber layer plexus capillary density (NFLP-CD), macular ganglion cell complex thickness (GCCT), and macular superficial vascular complex vascular density (SVC-VD). Healthy eyes, including ones with axial ametropia, were enrolled for analysis.

Results

A total of 1346 eyes from 792 participants were divided into 4 subgroups: high myopia (<−6D), low myopia (−6D to −1D), emmetropia (−1D to 1D), and hyperopia (>1D). After accounting for age, sex, and signal strength, multivariable regression showed strong dependence in most models for NFLT, GCCT, and NFLP-CD on axial eye length (AL), spherical equivalent (SE) refraction, and apparent optic disc diameter (DD). Optical analysis indicated that AL-related transverse optical magnification variations predominated over anatomic variations and were responsible for these trends. Compared to the emmetropic group, the false positive rates were significantly (Chi-square test P < 0.003) elevated in both myopia groups for NFLT, NFLP-CD, and GCCT. Regression-based adjustment of these diagnostic parameters with AL or SE significantly (McNemar test P < 0.03) reduced the elevated false positive rates.

Conclusions

Myopic eyes are biased to have lower NFLT, GCCT, and NFLP-CD measurements. AL- and SE-based adjustments were effective in mitigating this bias.

Translational Relevance

Adoption of these adjustments into commercial OCT systems may reduce false positive rates related to refractive error.

Evaluation of University of North Carolina OCT Index for Diagnosis of Early Glaucoma

PURPOSE

To evaluate the diagnostic performance of the University of North Carolina (UNC) OCT Index based on Cirrus high-definition OCT to discriminate early glaucomatous eyes from normal eyes in clinical practice.

DESIGN

Evaluation of diagnostic test or technology.

PARTICIPANTS

Ninety-eight patients with early glaucoma and 98 age-matched normal subjects.

METHODS

Macular ganglion cell-inner plexiform layer (GCIPL) thickness, peripapillary retinal nerve fiber layer (RNFL) thickness, and optic nerve head parameters were measured in each subject. The measurements were run through the UNC OCT algorithm to compare their diagnostic abilities.

MAIN OUTCOME MEASURES

Area under the curve (AUC) of the receiver operating characteristic and sensitivity at 95% specificity.

RESULTS

The AUC of the UNC OCT Index was 0.974. The best AUCs of the single parameters were those of the minimum GCIPL (0.926) of the macular GCIPL, average RNFL (0.916) of the peripapillary RNFL, and rim area (0.964) of the optic nerve head. The AUC of the UNC OCT Index was significantly greater than those of the minimum GCIPL and average RNFL (all P values < 0.05), and also outperformed the rim area. The sensitivity value of the UNC OCT Index (90.8) was greater than that of single OCT parameters (minimum GCIPL, 42.9; average RNFL, 64.3; rim area, 84.7) at 95% specificity.

CONCLUSIONS

The diagnostic performance of the UNC OCT Index in discriminating early glaucomatous eyes from normal eyes is high and exceeds the best optic nerve head, peripapillary RNFL, and macular GCIPL parameters in clinical practice.

Comparison of Diagnostic Ability Between Wide-Field Swept-Source Optical Coherence Tomography Imaging Maps and Heidelberg Retina Tomograph 3 Optic Nerve Head Assessment to Discriminate Glaucomatous and Non-glaucomatous Eyes

Background

In this study, we aimed to determine the diagnostic performance of optic nerve head (ONH), macular, and circumpapillary retinal nerve fiber layer (cpRNFL) thickness measurements of wide-field maps (12 × 9 mm) using swept-source optical coherence tomography (SS-OCT) compared to measurements of the ONH and RNFL parameters measured by Heidelberg Retina Tomograph (HRT3).

Methodology

This case-control study included 39 eyes of 39 glaucoma patients and 36 eyes of 36 normal subjects (control group). All participants underwent standard automated perimetry (SAP) as well as structural measurements by SS-OCT (DRI-OCT, Triton; Topcon Inc., Tokyo, Japan) and HRT3 (Heidelberg Engineering, Heidelberg, Germany). The abilities of the continuous parameters to discriminate between glaucoma and control groups were assessed using areas under the receiver operating characteristic curves (AUCs). To assess the glaucoma diagnostic abilities of each of the categorical variables, sensitivity, specificity, positive predictive value, and negative predictive value were tested.

Results

The highest sensitivities were achieved by the DRI-OCT categorical parameters of Superpixel-200 map and cpRNFL (12 sectors) thickness analysis. The best performing HRT3 continuous parameter was rim volume (AUC = 0.829, 95% confidence interval (CI) = 0.735-0.922), and the best continuous parameter for DRI-OCT wide-field was vertical cdr (AUC = 0.883, 95% CI = 0.805-0.951), followed by total cpRNFL thickness (AUC = 0.862, 95% CI = 0.774-0.951). AUCs for disc area, rim area, linear cdr, and RNFL thickness were not significantly different between the two technologies. Using either the most or the least specific criteria, SuperPixel-200 map always showed the highest sensitivity among the categorical parameters of both technologies (82.1% and 89.7%, respectively). The highest sensitivity among HRT3 classification parameters was shown by MRA and GPS classification algorithms.

Conclusions

Both wide-field DRI-OCT maps and HRT3 showed good diagnostic performance in discriminating glaucoma. Although DRI-OCT thickness values and normative diagnostic classification showed the best performance, more studies are required to determine the clinical role of wide-field DRI-OCT scan in glaucoma diagnosis.

Structural-Functional Glaucoma Progression Trajectory in 2-Dimensional Space

PRCIS

We describe a method that provides rapid visualization of glaucomatous change in a 2-dimensional (2D) structural and functional (S/F) space.

PURPOSE

To describe a method to visualize glaucomatous change in a 2D S/F space.

DESIGN

This was a retrospective longitudinal observational study.

SUBJECTS

Group I included 64 normal and 64 glaucomatous eyes used to develop the structural score. Group II included 957 glaucomatous eyes used to plot the structural-functional progression vectors.

METHODS

Subjects were arranged in 2 groups. Group I was a cross-sectional group used to develop a structural score which were applied to longitudinal measurements of patients in group II for vectoral analysis. Visual field index was used as a functional score. Vectors were created for each eye to define structural (x) and functional (y) progression. The structural and functional components were calculated with linear models of optical coherence tomography scores and visual field index. The resultant vector and its confidence interval were plotted in 2D S/F space.

MAIN OUTCOME MEASURES

Combined structural-functional glaucomatous progression.

RESULTS

Group I included 64 normal and 64 glaucomatous eyes. We calculated 957 vectors (957 eyes of 582 OAG patients) in group II. The mean (±SD) follow-up period was 6.9 (±1.5) years and mean baseline mean deviation (MD) was -4.3 (±5.4). Preperimetric, mild, moderate, and severe groups included 159, 288, 299, and 211 eyes, respectively. Mean baseline MDs in these groups were 0.8, -1.0, -3.7, and -11.2 dB, and mean vector slopes were 0.88, 1.00, 1.98, and 2.69.

CONCLUSION

We present a method that presents glaucoma progression in a 2D S/F space. This approach integrates a large amount of longitudinal numerical data and provides the clinician with a rapid and intuitive summary of the patient's glaucoma trajectory.

The OCT RNFL Probability Map and Artifacts Resembling Glaucomatous Damage

Purpose

The purpose of this study was to improve the diagnostic ability of the optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability (p-) map by understanding the frequency and pattern of artifacts seen on the p-maps of healthy control (HC) eyes resembling glaucomatous damage.

Methods

RNFL p-maps were generated from wide-field OCT cube scans of 2 groups of HC eyes, 200 from a commercial normative group (HC-norm) and 54 from a prospective study group, as well as from 62 patient eyes, which included 32 with early glaucoma (EG). These 32 EG eyes had 24-2 mean deviation (MD) better than -6 dB and perimetric glaucoma as defined by 24-2 and 10-2 criteria. For the HC groups, "glaucoma-like" arcuates were defined as any red region near the temporal half of the disc.

Results

Seven percent of the 200 HC-norm and 11% of the 54 HC RNFL p-maps satisfied the definition of "glaucoma-like," as did all the patients' p-maps. The HC p-maps showed two general patterns of abnormal regions, "arcuate" and "temporal quadrant," and these patterns resembled those seen on some of the RNFL p-maps of the EG eyes. A "vertical midline" rule, which required the abnormal region to cross the vertical midline through the fovea, had a specificity of >99%, and a sensitivity of 75% for EG and 93% for moderate to advanced eyes.

Conclusions

Glaucoma-like artifacts on RNFL p-maps are relatively common and can masquerade as arcuate and/or widespread/temporal damage.

Translational Relevance

A vertical midline rule had excellent specificity. However, other OCT information is necessary to obtain high sensitivity, especially in eyes with early glaucoma.

The use of deep learning technology for the detection of optic neuropathy

The emergence of computer graphics processing units (GPUs), improvements in mathematical models, and the availability of big data, has allowed artificial intelligence (AI) to use machine learning and deep learning (DL) technology to achieve robust performance in various fields of medicine. The DL system provides improved capabilities, especially in image recognition and image processing. Recent progress in the sorting of AI data sets has stimulated great interest in the development of DL algorithms. Compared with subjective evaluation and other traditional methods, DL algorithms can identify diseases faster and more accurately in diagnostic tests. Medical imaging is of great significance in the clinical diagnosis and individualized treatment of ophthalmic diseases. Based on the morphological data sets of millions of data points, various image-related diagnostic techniques can now impart high-resolution information on anatomical and functional changes, thereby providing unprecedented insights in ophthalmic clinical practice. As ophthalmology relies heavily on imaging examinations, it is one of the first medical fields to apply DL algorithms in clinical practice. Such algorithms can assist in the analysis of large amounts of data acquired from the examination of auxiliary images. In recent years, rapid advancements in imaging technology have facilitated the application of DL in the automatic identification and classification of pathologies that are characteristic of ophthalmic diseases, thereby providing high quality diagnostic information. This paper reviews the origins, development, and application of DL technology. The technical and clinical problems associated with building DL systems to meet clinical needs and the potential challenges of clinical application are discussed, especially in relation to the field of optic nerve diseases.

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.

Evaluation of Average Retinal Nerve Fiber Layer Measurement in Eyes with Refractive Errors

SIGNIFICANCE

Optical coherence tomography (OCT) measurements of peripapillary retinal nerve fiber layer (pRNFL) play an important role in the diagnosis of glaucoma and optic atrophy. However, the interpretation of these measurements in patients with refractive errors, especially of a high degree, presents great difficulties. Optical coherence tomography instruments from most manufacturers do not take into account the effect of refractive errors, especially of a high degree, on quantitative measurements of pRNFL.

PURPOSE

The aim of this study was to develop a simple and easy method for evaluation of average pRNFL in eyes with refractive errors.

METHODS

Average pRNFL was measured by Cirrus HD-OCT (Carl Zeiss Meditec Inc., Dublin, CA) in 183 healthy White subjects (183 eyes) older than 40 years, with an axial length of the eye from 22.5 to 24.5 mm and spherical equivalent of refraction from -1.63 to 2.0 D.

RESULTS

For an average pRNFL, normative database of eyes with refraction close to emmetropia was constructed. The calculated first and fifth percentiles for age groups 41 to 50, 51 to 60, 61 to 70, and 71 to 85 years were 81 and 83, 79 and 81, 78 and 80, and 76 and 79 μm, respectively. Littmann-Bennett formula was modified to calculate a table containing first and fifth percentiles for eyes with axial lengths of 19 to 30 mm in the same age groups.

CONCLUSIONS

For the correct interpretation of the measurements of pRNFL in patients with refractive errors, an original table was proposed, which provides a quick assessment of the results obtained on the Cirrus HD-OCT device. The proposed new formulas make it easy to calculate a similar table for any optical coherence tomography device using existing databases or after collecting a normative database of eyes with refraction close to emmetropia.

Optic Nerve Head Hemoglobin Levels in Glaucoma: A Structural and Functional Correlation Study

Purpose

To investigate structural and functional correlations in glaucoma patients using optic nerve head hemoglobin (ONH Hb) measurements as determined by automated colorimetric analysis of conventional retinography.

Methods

We prospectively enrolled healthy participants and glaucomatous patients with a wide range of disease stages. All participants underwent visual field (VF) testing (standard automated perimetry, SAP), color fundus imaging (mydriatic retinography), and peripapillary retinal nerve fiber layer (pRNFL) assessment through spectral-domain optical coherence tomography (SD-OCT). Software Laguna ONhE was used to estimate the amount of ONH Hb and to determine the glaucoma discriminant function (GDF) index. Scatter plots were constructed, and regression analysis was used to investigate the correlations between GDF, average pRNFL thickness, and VF mean deviation (VFMD) index values. A secondary analysis was performed to compare each parameter between three different glaucoma groups divided according to VFMD values (mild, >−6 dB; moderate, −6 to −12 dB; and advanced, <−12 dB).

Results

One hundred ninety-six eyes from 123 participants (69 with glaucoma and 54 controls) were enrolled. Overall, all parameters evaluated differed significantly between glaucomatous and control eyes (p ≤ 0.001). The comparison of each parameter according to groups of disease stages revealed significant differences between controls and each of the glaucomatous groups (p < 0.001). More pronounced changes in GDF values were observed in early disease stages. We found significant nonlinear correlations between GDF and VFMD values (R² = 0.295, p < 0.001) and between pRNFL thickness and VFMD (R² = 0.598, p < 0.001). A linear correlation was found between GDF and pRNFL thickness values (R² = 0.195, p < 0.001).

Conclusion

Our results showed significant associations between ONH Hb values and both structural and functional damage in glaucoma obtained by SD-OCT and SAP, respectively. The nonlinear correlation we found and the GDF behavior along different disease stages suggest that ONH Hb levels' reduction may precede visual function changes in early glaucoma stages.

Artifacts and Anatomic Variations in Optical Coherence Tomography

In recent years, ophthalmologists widely depend on optical coherence tomography (OCT), which is an objective, reliable, and repeatable structural test for both early diagnosis of glaucoma and detecting progression of the disease. Using this technology, it is now possible to take measures of various anatomic structures and layers of the optic nerve head, peripapillary retinal nerve fiber layer, and macular area. Although OCT has these powerful capabilities in general, anatomical variations, artifacts related to the ocular pathologies, and issues with image acquisition can be present in up to one-third of scans. These anatomical variations and artifacts can be misleading to an interpreter and may lead to erroneous conclusions. This review focuses on the realization and prevention of most common anatomical variations and artifacts observed with OCT imaging. The concepts of floor effect and red and green diseases are also investigated.

Agreement Between Trend-Based and Qualitative Analysis of the Retinal Nerve Fiber Layer Thickness for Glaucoma Progression on Spectral-Domain Optical Coherence Tomography

INTRODUCTION

To evaluate the agreement between trend-based analysis and qualitative assessment of the retinal nerve fiber layer (RNFL) thickness for glaucomatous progression on spectral-domain optical coherence tomography (SDOCT).

METHODS

Retrospective review of 190 eyes from 103 patients with glaucoma or suspected glaucoma that underwent SDOCT imaging during four consecutive clinic visits. Trend-based progression was characterized by a significantly negative slope. Progression by qualitative analysis was determined by review of raw SDOCT B-scans.

RESULTS

The slope was significantly greater in those with progression than without progression for both trend-based and qualitative analysis (p < 0.001). However, the qualitative grading classified a significantly greater proportion of eyes as progressing compared to trend-based analysis in both the superotemporal (ST) (23.2% vs. 10.5%, p = 0.001) and inferotemporal (IT) RNFL (27.4% vs 8.4%, p < 0.001). The trend-based and qualitative classifications of progression showed poor agreement in both the ST (kappa = 0.0135) and IT RNFL (kappa = 0.1222). The agreement between trend-based and qualitative analysis was lower for eyes with artifacts (ST = 58.11%; IT = 68.7%) than those without artifacts (ST = 80.2%; IT = 74.8%). Moreover, among eyes with artifacts, there was no significant difference in slope between those qualitatively categorized as progressing versus not progressing (p > 0.05).

CONCLUSIONS

Poor agreement was found between a trend-based and qualitative analysis of change in RNFL on SDOCT. Careful qualitative review of SDOCT imaging may identify specific areas of glaucoma progression not captured by trend-based methods, especially in the presence of artifacts. Such an approach may also prove useful for detecting glaucoma progression in a clinical setting when there are few data points available.

Peripapillary Halo in Inflammatory Papillitis of Birdshot Chorioretinopathy

Purpose

Peripapillary halos (PPH) are peripapillary changes observed surrounding the optic nerve head in normal eyes and eyes with different disorders. Recognizing the microstructure and mechanism of development of these halos will help clinicians understand the different associated retinal and optic nerve head pathologies. We describe the in vivo histological characteristics of PPH in birdshot chorioretinopathy (BSCR).

Patients and Methods

This was a prospective observational case-series in a single tertiary referral center. Six eyes of three patients with PPH associated with BSCR were determined through clinical examination, fundus photography, and fundus autofluorescence (FAF). Patients underwent swept-source optical coherence tomography (SS-OCT) imaging of the optic nerve head and peripapillary region.

Results

In SS-OCT B-scans across the area of PPH, we observed thinning and interruption of retinal pigment epithelium (RPE)-Bruch’s membrane complex. These halos are a circumferential form of alpha zone RPE-associated crescentic peripapillary atrophy (PPA), unlike the PPH observed with myopia and normal aging.

Conclusion

PPH in BSCR patients may be a sign of prior inflammatory optic neuropathy.

A Simple Subjective Evaluation of Enface OCT Reflectance Images Distinguishes Glaucoma From Healthy Eyes

Purpose

We present a subjective approach to detecting glaucomatous defects in enface images and assess its diagnostic performance. We also test the hypothesis that if reflectivity changes precede thickness changes in glaucoma there should be reduced correlation between the modalities in glaucoma compared to controls.

Methods

Twenty glaucoma participants and 20 age-matched controls underwent high-resolution OCT scans of one eye. 4 µm-thick enface slabs were constructed through the retina. Enface indices were depths of first gap in visible retinal nerve fiber bundles (RNFBs) and last visible bundle, subjectively evaluated in six sectors of a 3.5 mm circle around the optic disc. Retinal nerve fiber layer thickness (RNFLT) along the same circle was extracted at angles corresponding to enface indices. Between-group differences were tested by linear mixed models. Diagnostic performance was measured by partial receiver operating characteristic area (pAUC).

Results

First gap and last visible bundle were closer to the inner limiting membrane in glaucoma eyes (both P < 0.0001). Enface indices showed excellent diagnostic performance (pAUCs 0.63-1.00), similar to RNFLT (pAUCs 0.63-0.95). Correlation between enface and RNFLT parameters was strong in healthy (r = 0.81-0.92) and glaucoma eyes (r = 0.73-0.80).

Conclusions

This simple subjective method reliably identifies glaucomatous defects in enface images with diagnostic performance at least as good as existing thickness indices. Thickness and reflectivity were similarly related in healthy and glaucoma eyes, providing no strong evidence of reflectivity loss preceding thinning. Objective analyses may realize further potential of enface OCT images in glaucoma.

Translational Relevance

Novel enface OCT indices may aid glaucoma diagnosis.

The performance and confidence of clinicians in training in the analysis of ophthalmic images within a work-integrated teaching model

PURPOSE

A fundamental clinical skill is the recognition of artefacts within the outputs of advanced imaging modalities. However, current teaching programmes of healthcare practitioners are becoming increasingly challenged to provide practical exposure within an already crowded curriculum. This study evaluates the impact of a novel work-integrated teaching model on the confidence and competence of clinicians in the use of optical coherence tomography (OCT) and the recognition of its artefacts. The outcomes were then used to develop a model to predict performance and guide teaching strategies.

METHODS

We prospectively evaluated a 6-week clinical placement for final year optometry students within a diagnostic eye clinic in 2018-2020. Participants completed a quiz on the identification of common OCT artefacts and rated their confidence levels on key areas of OCT application using a five-point Likert scale. Both were completed before (pre-rotation) and after (post-rotation) the placement. The cohort was divided into two groups; the first group was used to assess the impact of the placement and derive the prediction model for post-placement performance, which was then validated against the second group.

RESULTS

A significant improvement in detecting OCT imaging artefacts was seen upon completion of the placement, which was greater in participants with lower entry level performance. Across all OCT artefact subtypes, there was an improvement in detecting segmentation error, delineation error and media opacities. A model predicting post-placement student performance was developed using entry level knowledge base as the key dependent variable. Self-rated confidence improved across all domains of OCT application but was not found to be a direct predictor of actual performance.

CONCLUSIONS

These results highlight the benefit of a work-integrated learning programme on both academic performance and confidence whilst identifying entry level knowledge base as the key variable predicting improvement. Tailored teaching incorporating entering knowledge is the best predictor of improvement during clinical placements. Integrating clinicians into a work-integrated setting with tailored teaching and comprehensive practical exposure can be an effective method for training future or current healthcare professionals.

Alterations in the Retinal Nerve Fiber Layer Thickness Color Map in Non-Glaucomatous Eyes with Myopia

Objectives

To determine the normal values for retinal nerve fiber layer thickness (RNFLT) in myopic patients without glaucoma and analyze the changes in their color map.

Materials and Methods

A total of 245 eyes without glaucoma were included in the study. According to the degree of myopia, the cases were divided into 4 groups: control group (+1.00/-1.00 D; n=70), Group 1 (-1.00/-3.00 D; n=50), Group 2 (-3.00/-6.00 D; n=75), and Group 3 (>-6.00 D; n=50). Intra-group comparisons were performed in terms of superotemporal, superonasal, nasal, inferonasal, inferotemporal, temporal, and global RNFLT (Heidelberg Spectralis, Optic Coherence Tomography, Germany) and the color coding of these quadrants (green: within normal limits, yellow: borderline, red: outside normal limits).

Results

All groups were similar in age and gender (p>0.05). As the degree of myopia increased, RNFLT became thinner in the upper and lower temporal and upper and lower nasal quadrants (p<0.01). The rate of measurements considered borderline and outside normal limit in at least 1 quadrant was higher in groups with higher myopia for all quadrants (p<0.05). This rate was found to be 8/70 (11.4%) for the control group, 9/50 (18.0%) for Group 1, 21/75 (28.0%) for Group 2, and 33/50 (66.0%) for Group 3 (p<0.01).

Conclusion

The high rate of RNFLT classified as borderline or outside normal limits in myopic patients is a finding to which clinicians should pay attention in order not to make a misdiagnosis, especially in cases of suspected glaucoma.

Optical Coherence Tomography Can Be Used to Assess Glaucomatous Optic Nerve Damage in Most Eyes With High Myopia

PRECIS

It is generally assumed that optical coherence tomography (OCT) cannot be used to diagnose glaucomatous optic neuropathy (GON) in high myopes. However, this study presents evidence that there is sufficient information in OCT scans to allow for accurate diagnosis of GON in most eyes with high myopia.

PURPOSE

The purpose of this study was to test the hypothesis that glaucomatous damage can be accurately diagnosed in most high myopes via an assessment of the OCT results.

PATIENTS AND METHODS

One hundred eyes from 60 glaucoma patients or suspects, referred for OCT scans and evaluation, had corrected spherical refractive errors worse than -6 D and/or axial lengths ≥26.5 mm. An OCT specialist judged whether the eye had GON, based upon OCT circle scans of the disc and cube scans centered on the macula. A glaucoma specialist made the same judgement using all available information (eg, family history, repeat visits, intraocular pressure, 10-2 and 24-2 visual fields, OCT). A reference standard was created based upon the glaucoma specialist's classifications. In addition, the glaucoma specialist judged whether the eyes had peripapillary atrophy (PPA), epiretinal membrane (ERM), tilted disc (TD), and/or a paravascular inner retinal defect (PIRD).

RESULTS

The OCT specialist correctly identified 97 of the 100 eyes using the OCT information. In 63% of the cases, the inner circle scan alone was sufficient. For the rest, additional scans were requested. In addition, 81% of the total eyes had: PPA (79%), ERM (18%), PIRD (26%), and/or TD (48%).

CONCLUSIONS

For most eyes with high myopia, there is sufficient information in OCT scans to allow for accurate diagnosis of GON. However, the optimal use of the OCT will depend upon training to read OCT scans, which includes taking into consideration myopia related OCT artifacts and segmentation errors, as well as PPA, ERM, PIRD, and TD.

Impact of Artifacts From Optical Coherence Tomography Retinal Nerve Fiber Layer and Macula Scans on Detection of Glaucoma Progression

PURPOSE

To determine the prevalence of artifacts on segmented spectral-domain optical coherence tomography (SDOCT) images and assess their impact on the interpretation of glaucomatous progression in the retinal nerve fiber layer (RNFL) profile and macular thickness map.

DESIGN

Retrospective reliability analysis.

METHODS

Retrospective review of glaucoma and glaucoma suspect eyes imaged with SDOCT during a 1-month period. All cases had at least 4 sets of RNFL and macular images at 6-month intervals. SDOCT raw B-scans were examined to determine true progression and whether artifacts impacted the original interpretation of progression based on auto-segmented change maps. The co-prevalence of artifacts in the RNFL and macula was assessed, as well as the association of clinical factors with the likelihood of artifacts.

RESULTS

A total of 190 eyes with 760 sets of OCT RNFL and macular scans were included. Fifty percent (96/190) of eyes had artifacts, either in the circumpapillary RNFL (83/190; 43.68%) or the macula (57/190; 30.0%). Epiretinal membrane and vitreomacular traction were the most common artifacts. True progression was present on 39.5% (75/190) of scans overall. Among scans with artifacts, 23.9% (23/96) of artifacts masked true progression (ie, false-negative), 36.5% (35/96) led to an interpretation of false progression (ie, false-positive), and 39.6% (38/96) had no effect on the interpretation of progression. The presence of true progression on the RNFL scan was significantly associated with the presence of true progression on the macular scan (P < .001). Similarly, the presence of artifacts on the RNFL scan was significantly associated with artifacts on the macular scan (P < .001). In multivariable analysis, severe glaucoma, hypertension, and age were significantly associated with the presence of artifacts on RNFL (P < .05).

CONCLUSIONS

Artifacts are highly prevalent on both circumpapillary RNFL and macular scans on SDOCT images acquired in a glaucoma clinic. Artifacts can lead to false-positive and false-negative interpretation of progression when using only the auto-segmentation change maps. Thus, careful examination of the raw B-scan images of both the RNFL and macula is critical to identify artifacts and true glaucoma progression.

Ethnicity-Specific Database Improves the Diagnostic Ability of Peripapillary Retinal Nerve Fiber Layer Thickness to Detect Glaucoma

PURPOSE

To determine the changes in optical coherence tomography (OCT) color probability codes and diagnostic ability for peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell complex (GCC) analysis after applying Chinese and white subjects normative databases.

DESIGN

Cross-sectional study.

METHODS

This study enrolled 219 healthy eyes (108 white and 111 Chinese patients) to construct an ethnicity-specific normative database for pRNFL and macular GCC thickness, which was tested then in 180 eyes with or without glaucoma (102 white and 78 Chinese patients). The percent of change of color probability codes were evaluated after applying the original built-in and the ethnicity-specific normative databases, respectively. Sensitivity and specificity were calculated to evaluate the change in diagnostic ability to detect glaucoma.

RESULTS

Healthy white subjects had a thinner pRNFL than Chinese subjects in the overall average thickness as well as the superior, inferior, and temporal quadrants (P < .001). Macular GCC did not differ between ethnicities. After applying an ethnicity-specific normative database, the percent of pRNFL abnormal color code labels decreased significantly for the overall average thickness in the white subjects. This resulted in a significant increase in the specificity to detect glaucoma in the white population (P < .001). No significant changes were seen when applying an ethnicity-specific normative database for macular GCC thickness.

CONCLUSIONS

After applying an ethnicity-specific normative database, the percent of pRNFL abnormal color codes decreased significantly, improving the specificity to detect glaucoma in the white population. These findings suggest there may be utility in having ethnicity-specific normative databases for pRNFL thickness.

Applications of deep learning in detection of glaucoma: A systematic review

Glaucoma is the leading cause of irreversible blindness and disability worldwide. Nevertheless, the majority of patients do not know they have the disease and detection of glaucoma progression using standard technology remains a challenge in clinical practice. Artificial intelligence (AI) is an expanding field that offers the potential to improve diagnosis and screening for glaucoma with minimal reliance on human input. Deep learning (DL) algorithms have risen to the forefront of AI by providing nearly human-level performance, at times exceeding the performance of humans for detection of glaucoma on structural and functional tests. A succinct summary of present studies and challenges to be addressed in this field is needed. Following PRISMA guidelines, we conducted a systematic review of studies that applied DL methods for detection of glaucoma using color fundus photographs, optical coherence tomography (OCT), or standard automated perimetry (SAP). In this review article we describe recent advances in DL as applied to the diagnosis of glaucoma and glaucoma progression for application in screening and clinical settings, as well as the challenges that remain when applying this novel technique in glaucoma.

Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans

Importance

Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.

Objective

To develop a segmentation-free deep learning (DL) algorithm for assessment of glaucomatous damage using the entire circle B-scan image from SD-OCT.

Design, Setting, and Participants

This cross-sectional study at a single institution used data from SD-OCT images of eyes with glaucoma (perimetric and preperimetric) and normal eyes. The data set was randomly split at the patient level into a training (50%), validation (20%), and test data set (30%). Data were collected from March 2008 to April 2019, and analysis began April 2018.

Exposures

A convolutional neural network was trained to discriminate glaucomatous from normal eyes using the SD-OCT circle B-scan without segmentation lines.

Main Outcomes and Measures

The ability to discriminate glaucoma from healthy eyes was evaluated by comparing the area under the receiver operating characteristic curve and sensitivity at 80% or 95% specificity for the DL algorithm's predicted probability of glaucoma vs conventional RNFL thickness parameters given by SD-OCT software. The performance was also assessed in preperimetric glaucoma, as well as by visual field severity using Hodapp-Parrish-Anderson criteria.

Results

A total of 20 806 SD-OCT images from 1154 eyes of 635 individuals (612 [53%] with glaucoma and 542 normal eyes [47%]) were included. The mean (SD) age at SD-OCT scan was 70.8 (10.4) years in individuals with glaucoma and 55.8 (14.1) years in controls. There were 187 women (53.3%) in the glaucoma group and 165 (59.8%) in the control group. Of 612 eyes with glaucoma, 432 (70.4%) had perimetric and 180 (29.6%) had preperimetric glaucoma. The DL algorithm had a significantly higher area under the receiver operating characteristic curve than global RNFL thickness (0.96 vs 0.87; difference = 0.08 [95% CI, 0.04-0.12]) and each RNFL thickness sector for discriminating between glaucoma and controls (all P < .001). At 95% specificity, the DL algorithm (81%; 95% CI, 64%-97%) was more sensitive than global RNFL thickness (67%; 95% CI, 58%-76%). The areas under the receiver operating characteristic curve were also significantly greater for the DL algorithm compared with RNFL thickness at each stage of disease, especially preperimetric and mild perimetric glaucoma.

Conclusions and Relevance

A segmentation-free DL algorithm performed better than conventional RNFL thickness parameters for diagnosing glaucomatous damage on OCT scans, especially in early disease. Future studies should investigate how such an approach contributes to diagnostic decisions when combined with other relevant clinical information, such as risk factors and perimetry results.

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression

Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often equal, or sometimes even exceed, those of human subjects on a variety of tasks, especially those related to image classification and pattern recognition. As one of the medical fields that is highly dependent on ancillary imaging tests, ophthalmology has been in a prime position to witness the application of deep learning algorithms that can help analyze the vast amount of data coming from those tests. In particular, glaucoma stands as one of the conditions where application of deep learning algorithms could potentially lead to better use of the vast amount of information coming from structural and functional tests evaluating the optic nerve and macula. The purpose of this article is to critically review recent applications of deep learning models in glaucoma, discussing their advantages but also focusing on the challenges inherent to the development of such models for screening, diagnosis and detection of progression. After a brief general overview of deep learning and how it compares to traditional machine learning classifiers, we discuss issues related to the training and validation of deep learning models and how they specifically apply to glaucoma. We then discuss specific scenarios where deep learning has been proposed for use in glaucoma, such as screening with fundus photography, and diagnosis and detection of glaucoma progression with optical coherence tomography and standard automated perimetry.

Translational Relevance

Deep learning algorithms have the potential to significantly improve diagnostic capabilities in glaucoma, but their application in clinical practice requires careful validation, with consideration of the target population, the reference standards used to build the models, and potential sources of bias.

Using Enhanced Depth Imaging Optical Coherence Tomography-Derived Parameters to Discriminate between Eyes with and without Glaucoma: A Cross-Sectional Comparative Study

INTRODUCTION

New technologies have been developed in order to decrease interpersonal influence and subjectivity during the glaucoma diagnosis process. Enhanced depth imaging spectral-domain OCT (EDI OCT) has turned up as a favorable tool for deep optic nerve head (ONH) structures assessment.

OBJECTIVE

A prospective cross-sectional study was conducted to compare the diagnostic performance of different EDI OCT-derived parameters to discriminate between eyes with and without glaucoma.

MATERIAL AND METHODS

The following ONH parameters were measured: lamina cribrosa (LC) thickness and area; prelaminar neural tissue (PLNT) thickness and area; average Bruch's membrane opening - minimum rim width (BMO-MRW), superior BMO-MRW, and inferior BMO-MRW. Peripapillary retinal nerve fiber layer (pRNFL) thickness was also obtained.

RESULTS

Seventy-three participants were included. There were no significant differences between AUCs for average BMO-MRW (0.995), PLNT area (0.968), and average pRNFL thickness (0.975; p ≥ 0.089). However, AUCs for each of these 3 parameters were significantly larger than LC area AUC (0.701; p ≤ 0.001). Sensitivities at 80% specificity were: PLNT area = 92.3%, average BMO-MRW = 97.4%, and average pRNFL thickness = 94.9%.

CONCLUSIONS

Comparing the diagnostic performance of different EDI OCT ONH parameters to discriminate between eyes with and without glaucoma, we found better results for neural tissue-based indexes (BMO-MRW and PLNT area) compared to laminar parameters. In this specific population, these neural tissue-based parameters (including PLNT area, which was investigated by the first time in the present study) had a diagnostic performance comparable to that of the conventional pRNFL thickness protocol.

Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy, Third Edition

Contributors The following document and appendices represent the third edition of the Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy. These guidelines were developed by the Diabetic Retinopathy Telehealth Practice Guidelines Working Group. This working group consisted of a large number of subject matter experts in clinical applications for telehealth in ophthalmology. The editorial committee consisted of Mark B. Horton, OD, MD, who served as working group chair and Christopher J. Brady, MD, MHS, and Jerry Cavallerano, OD, PhD, who served as cochairs. The writing committees were separated into seven different categories. They are as follows: 1.Clinical/operational: Jerry Cavallerano, OD, PhD (Chair), Gail Barker, PhD, MBA, Christopher J. Brady, MD, MHS, Yao Liu, MD, MS, Siddarth Rathi, MD, MBA, Veeral Sheth, MD, MBA, Paolo Silva, MD, and Ingrid Zimmer-Galler, MD. 2.Equipment: Veeral Sheth, MD (Chair), Mark B. Horton, OD, MD, Siddarth Rathi, MD, MBA, Paolo Silva, MD, and Kristen Stebbins, MSPH. 3.Quality assurance: Mark B. Horton, OD, MD (Chair), Seema Garg, MD, PhD, Yao Liu, MD, MS, and Ingrid Zimmer-Galler, MD. 4.Glaucoma: Yao Liu, MD, MS (Chair) and Siddarth Rathi, MD, MBA. 5.Retinopathy of prematurity: Christopher J. Brady, MD, MHS (Chair) and Ingrid Zimmer-Galler, MD. 6.Age-related macular degeneration: Christopher J. Brady, MD, MHS (Chair) and Ingrid Zimmer-Galler, MD. 7.Autonomous and computer assisted detection, classification and diagnosis of diabetic retinopathy: Michael Abramoff, MD, PhD (Chair), Michael F. Chiang, MD, and Paolo Silva, MD.

Telemedicine for Glaucoma: Guidelines and Recommendations

Background: Glaucoma is the leading cause of irreversible blindness worldwide. Access to glaucoma specialists is challenging and likely to become more difficult as the population ages. Introduction: Using telemedicine for glaucoma (teleglaucoma) has the potential to increase access to glaucoma care by improving efficiency and decreasing the need for long-distance travel for patients. Results: Teleglaucoma programs can be used for screening, diagnostic consultation, and long-term treatment monitoring. Key components of teleglaucoma programs include patient history, equipment, intraocular pressure measurement, pachymetry, anterior chamber imaging/gonioscopy, fundus photography, retinal nerve fiber layer imaging, medical record and imaging software, and skilled personnel. Discussion: Teleglaucoma has tremendous potential to improve patient access to high-quality cost-effective glaucoma care. Conclusions: We have reviewed some special considerations needed to address the complexity of providing guideline-concordant glaucoma care.

A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans

Purpose

The purpose of this study was to develop a 3D deep learning system from spectral domain optical coherence tomography (SD-OCT) macular cubes to differentiate between referable and nonreferable cases for glaucoma applied to real-world datasets to understand how this would affect the performance.

Methods

There were 2805 Cirrus optical coherence tomography (OCT) macula volumes (Macula protocol 512 × 128) of 1095 eyes from 586 patients at a single site that were used to train a fully 3D convolutional neural network (CNN). Referable glaucoma included true glaucoma, pre-perimetric glaucoma, and high-risk suspects, based on qualitative fundus photographs, visual fields, OCT reports, and clinical examinations, including intraocular pressure (IOP) and treatment history as the binary (two class) ground truth. The curated real-world dataset did not include eyes with retinal disease or nonglaucomatous optic neuropathies. The cubes were first homogenized using layer segmentation with the Orion Software (Voxeleron) to achieve standardization. The algorithm was tested on two separate external validation sets from different glaucoma studies, comprised of Cirrus macular cube scans of 505 and 336 eyes, respectively.

Results

The area under the receiver operating characteristic (AUROC) curve for the development dataset for distinguishing referable glaucoma was 0.88 for our CNN using homogenization, 0.82 without homogenization, and 0.81 for a CNN architecture from the existing literature. For the external validation datasets, which had different glaucoma definitions, the AUCs were 0.78 and 0.95, respectively. The performance of the model across myopia severity distribution has been assessed in the dataset from the United States and was found to have an AUC of 0.85, 0.92, and 0.95 in the severe, moderate, and mild myopia, respectively.

Conclusions

A 3D deep learning algorithm trained on macular OCT volumes without retinal disease to detect referable glaucoma performs better with retinal segmentation preprocessing and performs reasonably well across all levels of myopia.

Translational Relevance

Interpretation of OCT macula volumes based on normative data color distributions is highly influenced by population demographics and characteristics, such as refractive error, as well as the size of the normative database. Referable glaucoma, in this study, was chosen to include cases that should be seen by a specialist. This study is unique because it uses multimodal patient data for the glaucoma definition, and includes all severities of myopia as well as validates the algorithm with international data to understand generalizability potential.

Effect of partial posterior vitreous detachment on spectral-domain optical coherence tomography retinal nerve fibre layer thickness measurements

Background/aims

To assess the effect of partial posterior vitreous detachment (pPVD) on spectral-domain optical coherence tomography (OCT) peripapillary retinal nerve fibre layer thickness (RNFL) measurements.

Methods

Spectral-domain OCT RNFL thickness measurements were obtained from 684 consecutive patients who were seen in the Massachusetts Eye and Ear Glaucoma Service. Of these patients, we compared RNFL thickness measurements between 101 eyes of 101 glaucoma suspects who met inclusion criteria (55 eyes with and 46 eyes without pPVD).

Results

Among all 684 patients, 253 (37%) had pPVD in at least one eye. Among a subset of 101 eyes of 101 glaucoma suspects, average RNFL thickness was greater in eyes with compared to eyes without pPVD (p=0.02). Measurements were significantly greater in the inferior (p=0.004) and superior quadrants (p=0.008), but not in the nasal (p=0.10) and temporal quadrants (p=0.25). The difference in average RNFL thickness remained significant (p=0.05) even when corrected for expected age-related decline in RNFL thickness.

Conclusion

Over a third of patients were found on peripapillary spectral-domain OCT to have a pPVD, which was associated with greater RNFL thickness measurements. Judicious clinical interpretation of this finding on spectral-domain OCT RNFL thickness scans should be factored into the assessment of glaucoma suspects.

Separation and thickness measurements of superficial and deep slabs of the retinal nerve fiber layer in healthy and glaucomatous eyes

PURPOSE

Describe a new method to analyze retinal nerve fiber layer (RNFL) thickness maps.

DESIGN

Cross-sectional study.

SUBJECTS

RNFL thickness maps of healthy and glaucomatous eyes.

METHODS

Optical coherence tomography (OCT) RNFL raster scans from 98 healthy and 50 glaucomatous eyes were analyzed. The RNFL thickness maps were separated into superficial (SNFL) and deep (DNFL) slabs through a partial thickness plane set at the modal thickness (mode). Association between mode and OCT signal strength (SS), age, axial length, and visual field mean deviation (VFMD) was tested (Pearson coefficient, r). Thicknesses of inferior and superior SNFL regions (i-,s-SNFL), and inferior, superior, nasal, and temporal DNFL regions (i-,s-,n-,t-DNFL) were calculated. The regions thicknesses were compared between healthy and glaucomatous eyes (t-test) and between glaucomatous eyes with early, moderate, and severe disease (ANOVA and linear regressions of thickness on VFMD). Diagnostic accuracy and correlation with VFMD of RNFL regions thicknesses were calculated as the area under the receiver operating characteristic curve (AUC) and Pearson r, respectively. P<0.05 was considered significant.

MAIN OUTCOME

Thickness of regions in SNFL and DNFL slabs.

RESULTS

The mode was not associated with SS, age, axial length, or VFMD, it circumscribed the thicker RNFL around the optic disc of healthy and glaucomatous eyes, and it was used to separate the SNFL and DNFL slabs of RNFL thickness maps. The thickness of the SNFL slab was less in glaucomatous eyes than in healthy eyes (P<0.001). S-SNFL and i-SNFL thicknesses (respectively) were 86.0±8.2μm and 87.3±9.6μm in healthy eyes vs. 66.1±9.1μm and 63.4±8.2μm in glaucomatous eyes (P<0.001 for both). The thickness of the DNFL slab was similar between groups (P=0.19). T-DNFL thickness was 37.0±5.3μm in healthy eyes vs. 33.9±5.0μm in glaucomatous eyes (P<0.001); thicknesses of all other DNFL regions were similar. The SNFL regions only thinned with progressively worse glaucoma severity, had excellent AUCs (AUC≥0.95, P<0.001), and correlated strongly with VFMD (r≥0.60, P<0.001).

CONCLUSIONS

Glaucomatous RNFL thinning is predominantly detected within a slab with thickness greater than the mode. SNFL thickness has great AUC and correlation with VFMD in glaucomatous eyes. The usefulness for diagnosis and monitoring of glaucoma needs further study.

Using Small Samples to Evaluate Normative Reference Ranges for Retinal Imaging Measures

SIGNIFICANCE

Retinal nerve fiber layer (RNFL) deviation maps often incorrectly score healthy eyes as having wedge defects. This study shows how to identify such problems early in the development of normative databases.

PURPOSE

After reference values are embedded in devices, clinicians and researchers often learn about issues that cause false-positive rates in healthy eyes. Here we show a way to detect and address such issues early on.

METHODS

The thickness of the RNFL was measured for both eyes of 60 healthy younger adults aged 20 to 31 years and one eye each of 30 healthy older adults aged 54 to 82 years. Deviation maps were developed from the left eyes of the first 30 younger adults, and between-subject variability in the shape of the RNFL was assessed. This was repeated in their right eyes, in the second group of younger adults and in the older adults.

RESULTS

For the first group of 30 healthy young adults, between-subject variability in the location of the region of greatest thickness meant that 58% of the pixels below the fifth percentile in the left eyes were from four people whose deviation maps had wedge-shaped patterns, as did the deviation maps for the nine right eyes with 87% of the pixels below the fifth percentile. Wedge patterns were also seen in deviation maps for 8 left eyes and 11 right eyes of the second group of young adults and for 9 eyes of the older adults.

CONCLUSIONS

Evaluation of RNFL thickness maps from 30 young adults was sufficient to determine that between-subject variability in the shape of the RNFL can cause wedge patterns in RNFL deviation maps in many healthy eyes.

Peripapillary Vessel Density In Unilateral Preperimetric Glaucoma

Purpose

To investigate vessel density (VD) of radial peripapillary capillaries (RPC) and structural alterations in patients with unilateral preperimetric glaucoma (PPG) using optical coherence tomography angiography (OCTA).

Methods

This cross-sectional observational study included 13 untreated patients with unilateral PPG. PPG eyes had larger excavation and abnormal thinning of retinal nerve fiber layer (RNFL) and/or ganglion cell complex (GCC) compared with fellow eyes (F). Both RNFL and GCC thickness in F were statistically within normal limits and/or borderline. The RPC VD on optic disc (idVD), of peripapillary (ppVD) and whole image (wiVD) scan area was measured. Twenty healthy eyes (H) served as controls. Structural and vascular parameters obtained by spectral-domain OCT/OCTA (Optovue; Fremont, CA) were compared between PPG, F and H.

Results

Mean RNFL and GCC average thickness in microns differed significantly (p<0.001) between PPG (82.4±7.1, 81.4±5.9), F (91.0±7.1, 88.5±3.8) and H (103.5±6.0, 99.3±5.7). PPG compared with F showed significantly (p<0.001) lower mean ppVD (43.8%±3.0% versus 47.8%±3.2%) and wiVD (45.9%±3.5% versus 50.1%±3.9%). Mean ppVD (49.7%±2.4%) and wiVD (52.6%±3.0%) in H were not significantly higher than in F. Mean idVD showed no significant differences among the 3 groups. Areas under the receiver operating characteristic curves (AUROCs) for RNFL, GCC, ppVD and wiVD between PPG and H were excellent (>0.9). AUROCs between F and H demonstrated an excellent diagnostic ability for structural parameters and a poor one (<0.7) for vascular parameters.

Conclusion

Affected eyes of patients with unilateral PPG demonstrated significant RPC dropout. Clinically unaffected eyes showed thinner structural parameters but no significant microvasculature differences compared with non-glaucomatous eyes. Diagnostic ability of peripapillary vascular parameters was not superior to structural measurements. Microvascular dysfunction seems to be an early but not a primary event in glaucoma continuum at the stage of undetectable visual field loss. OCTA can be useful in early glaucoma diagnosis.

Exploring the gap between diagnostic research outputs and clinical use of OCT for diagnosing glaucoma

AIMS

To explore the gap between diagnostic research outputs and clinical use of optical coherence tomography (OCT) in glaucoma and assess the reliability of a specific reference database when applied to a morphological imaging parameter for diagnostic purposes.

METHODS

Consecutive subjects enrolled in the Multicenter Italian Glaucoma Imaging Study (MIGIS) have been included in this cross-sectional, comparative evaluation of diagnostic tests study. Patients underwent measurement of global and sectorial peripapillary retinal nerve fibre thickness (pRNFL) and minimum rim width (MRW) by OCT. The sensitivity and specificity of reference-database categorical classifications were calculated by means of 2×2 tables and sensitivity was compared with that of the corresponding continuous parameter extracted from the receiver operating characteristic (ROC) curves by matching the specificity.

RESULTS

280 Caucasian subjects have been included. At matched specificities, the sensitivity of pRNFL categorical classifications was statistically similar to that of the corresponding continuous parameters, whereas the sensitivity of the MRW categorical classifications was significantly lower than that of the corresponding continuous parameters.

CONCLUSIONS

The diagnostic accuracy of reference database classifications might be lower than that extrapolated from the ROC curves of continuous parameters used in diagnostic research. The gap between the accuracy of these two approaches may be used to estimate the reliability of a specific reference database when applied to a continuous parameter for diagnostic purposes.

Characteristics of Patients Showing Discrepancy Between Bruch's Membrane Opening-Minimum Rim Width and Peripapillary Retinal Nerve Fiber Layer Thickness

Background: To investigate clinical characteristics of patients showing discrepancy between Bruch’s membrane opening minimum rim width (BMO-MRW) and peripapillary retinal nerve fiber layer (RNFL) thickness. Correlation with the visual field (VF) was also inspected. Methods: In this prospective, cross-sectional study, 106 eyes (106 subjects) showing normal BMO-MRW classification but abnormal RNFL classification were included. All patients underwent confocal scanning laser ophthalmoscopy, spectral-domain optical coherence tomography, and standard automated perimetry. Results: Clinical characteristics were as follows: mean age: 52.79 ± 14.75 years; spherical equivalent (SE), −2.52 ± 3.48 diopter (D); SE < −5.0 D, 34 (32.1%) eyes; large disc (>2.43 mm²), 40.6%; small disc (<1.63 mm²), 12.5%; VF index, 96.72 ± 9.58%; mean deviation, −1.74 ± 3.61 dB; β-peripapillary atrophy (PPA), 96.2%; γ-PPA, 75.5%. Majority (86.1%) of these cases demonstrated normal (71.3%) or borderline (14.9%) on VF. Temporal and nasal RNFL showed significant differences among disc size subgroups (all p < 0.05). Nasal RNFL was significantly thicker in a large disc group than other subgroups. Temporal, superotemporal, inferotemporal, inferonasal RNFL, and superior RNFL peak location showed significant differences (all p < 0.05) among SE subgroups. Temporal RNFL was significantly thicker in the high myopia group than other subgroups. Conclusions: Temporalization of RNFL peaks in myopia and nasalization of RNFL peaks in large disc that display abnormal classifications might show normal classification of BMO-MRW. These findings of discrepancy between classifications should be considered in the diagnosis of early glaucoma.