Structure-Function Agreement Is Better Than Commonly Thought in Eyes With Early Glaucoma

Exploring the relationship between 24-2 visual field and widefield optical coherence tomography data across healthy, glaucoma suspect and glaucoma eyes

PURPOSE

To utilise ganglion cell-inner plexiform layer (GCIPL) measurements acquired using widefield optical coherence tomography (OCT) scans spanning 55° × 45° to explore the link between co-localised structural parameters and clinical visual field (VF) data.

METHODS

Widefield OCT scans acquired from 311 healthy, 268 glaucoma suspect and 269 glaucoma eyes were segmented to generate GCIPL thickness measurements. Estimated ganglion cell (GC) counts, calculated from GCIPL measurements, were plotted against 24-2 SITA Faster visual field (VF) thresholds, and regression models were computed with data categorised by diagnosis and VF status. Classification of locations as VF defective or non-defective using GCIPL parameters computed across eccentricity- and hemifield-dependent clusters was assessed by analysing areas under receiver operating characteristic curves (AUROCCs). Sensitivities and specificities were calculated per diagnostic category.

RESULTS

Segmented linear regression models between GC counts and VF thresholds demonstrated higher variability in VF defective locations relative to non-defective locations (mean absolute error 6.10-9.93 dB and 1.43-1.91 dB, respectively). AUROCCs from cluster-wide GCIPL parameters were similar across methods centrally (p = 0.06-0.84) but significantly greater peripherally, especially when considering classification of more central locations (p < 0.0001). Across diagnoses, cluster-wide GCIPL parameters demonstrated variable sensitivities and specificities (0.36-0.93 and 0.65-0.98, respectively), with the highest specificities observed across healthy eyes (0.73-0.98).

CONCLUSIONS

Quantitative prediction of VF thresholds from widefield OCT is affected by high variability at VF defective locations. Prediction of VF status based on cluster-wide GCIPL parameters from widefield OCT could become useful to aid clinical decision-making in appropriately targeting VF assessments.

Retinal Nerve Fiber Layer Optical Texture Analysis and 10-2 Visual Field Assessment in Glaucoma

PURPOSE

To apply retinal nerve fiber layer (RNFL) optical texture analysis (ROTA) to 1) investigate the association between papillomacular and papillofoveal bundle defects with 10-2 visual field (VF) sensitivity abnormalities, and 2) integrate the information from RNFL bundle defect and 24-2 VF central test locations to determine the likelihood of 10-2 VF sensitivity abnormalities.

DESIGN

Cross-sectional.

METHODS

A total of 841 eyes (144 healthy, 317 glaucoma suspect, and 380 glaucoma) of 442 participants were included. Eyes underwent 24-2, and 10-2 VF testing and OCT for ROTA. The borders of RNFL defects were delineated from ROTA, and the involvement of the arcuate, papillomacular, and papillofoveal bundles was determined for each eye. Multilevel logistic regression analysis was applied to evaluate the structure-function association.

RESULTS

Papillomacular (92.1%) and papillofoveal (37.9%) RNFL bundle defects were prevalent in eyes with glaucoma. A 10-2 VF location that was projected onto a papillomacular or a papillofoveal RNFL bundle defect had a significantly increased likelihood of reduced sensitivity (ORs of 18.61 at PDP < 5%, and 20.17 at TDP < 5%, respectively, P < .001 for both). When predicting the likelihood of VF abnormality in a 10-2 test location, noticeably higher odds ratios were observed when overlapping with an RNFL bundle defect, compared to when an abnormal corresponding 24-2 central point was present.

CONCLUSIONS

Papillomacular and papillofoveal RNFL bundle defects are present in a considerable proportion of eyes with glaucoma. When detected, they significantly increase the likelihood of abnormality in the corresponding central VF test locations assessed by the 10-2 test.

Characterisation of the normal human ganglion cell-inner plexiform layer using widefield optical coherence tomography

PURPOSE

To describe variations in ganglion cell-inner plexiform layer (GCIPL) thickness in a healthy cohort from widefield optical coherence tomography (OCT) scans.

METHODS

Widefield OCT scans spanning 55° × 45° were acquired from 470 healthy eyes. The GCIPL was automatically segmented using deep learning methods. Thickness measurements were extracted after correction for warpage and retinal tilt. Multiple linear regression analysis was applied to discern trends between global GCIPL thickness and age, axial length and sex. To further characterise age-related change, hierarchical and two-step cluster algorithms were applied to identify locations sharing similar ageing properties, and rates of change were quantified using regression analyses with data pooled by cluster analysis outcomes.

RESULTS

Declines in widefield GCIPL thickness with age, increasing axial length and female sex were observed (parameter estimates -0.053, -0.436 and -0.464, p-values <0.001, <0.001 and 0.02, respectively). Cluster analyses revealed concentric, slightly nasally displaced, horseshoe patterns of age-related change in the GCIPL, with up to four statistically distinct clusters outside the macula. Linear regression analyses revealed significant ageing decline in GCIPL thickness across all clusters, with faster rates of change observed at central locations when expressed as absolute (slope = -0.19 centrally vs. -0.04 to -0.12 peripherally) and percentage rates of change (slope = -0.001 centrally vs. -0.0005 peripherally).

CONCLUSIONS

Normative variations in GCIPL thickness from widefield OCT with age, axial length and sex were noted, highlighting factors worth considering in further developments. Widefield OCT has promising potential to facilitate quantitative detection of abnormal GCIPL outside standard fields of view.

Macula vessel density and its relationship with the central visual field mean sensitivity across different stages of exfoliation glaucoma

CLINICAL RELEVANCE

Alterations in ocular microvasculature may contribute to pathogenesis of exfoliation glaucoma (XFG) and may improve monitoring this aggressive type of open angle glaucoma.

BACKGROUND

This work aims to compare the macula vessel density and the relationship between macula vessel density and central visual field mean sensitivity between eyes with XFG and eyes with primary open-angle glaucoma (POAG) of different stages.

METHODS

In this cross-sectional observational study, the macula vessel density values were compared among 52 POAG cases (26 early stage, 26 moderate to advanced stage) and 53 XFG cases (27 early stage, 26 moderate to advanced stage). The vessel density values were evaluated with optical coherence tomography angiography. Vasculature-function and structure-function relationships were analysed by comparing macula vessel density, inner macula thickness and visual field mean sensitivity in early and moderate to advanced stages of XFG and POAG eyes separately.

RESULTS

The early stage XFG eyes had a significantly lower global macula vessel density compared with early stage POAG eyes (42.81 ± 3.85% and 46.56 ± 3.90%, respectively; p = 0.02). However, the tendency of XFG eyes for a lower vessel density compared with the POAG eyes did not exhibit any significance in moderate to advanced stages of glaucoma (37.39 ± 5.65% and 38.35 ± 4.67%, respectively; p = 0.9). The macula vessel density (%)-visual field mean sensitivity (1/Lambert) correlation was statistically significant in early stage XFG eyes (r = 0.464 p = 0.01), while no such correlation was notable for the early stage POAG eyes (r = -0.029 p = 0.89).

CONCLUSION

The macula vessel density appears to be more severely affected in early stage XFG than POAG of similar severity, suggesting a relatively greater value of vascular insufficiency in XFG. The significant vasculature-function association in early stage XFG, which was absent in early stage POAG, may infer the importance of macula vessel density in monitoring functional loss in early stages of XFG.

Central Visual Field Testing in Early Glaucoma: A Report by the American Academy of Ophthalmology

PURPOSE

To evaluate the current published literature on the utility of the 10-2 visual field (VF) testing strategy for the evaluation and management of early glaucoma, defined here as mean deviation (MD) better than -6 decibels (dB).

METHODS

A search of the peer-reviewed literature was last conducted in June 2023 in the PubMed database. Abstracts of 986 articles were examined to exclude reviews and non-English-language articles. After inclusion and exclusion criteria were applied, 26 articles were selected, and the panel methodologist rated them for strength of evidence. Thirteen articles were rated level I, and 8 articles were rated level II. The 5 level III articles were excluded. Data from the 21 included articles were abstracted and reviewed.

RESULTS

The central 12 locations on the 24-2 VF test grid lie within the central 10 degrees covered by the 10-2 VF test. In early glaucoma, defects detected within the central 10 degrees generally agree between the 2 tests. Defects within the central 10 degrees of the 24-2 VF test can predict defects on the 10-2 VF test, although the 24-2 may miss defects detected on the 10-2 VF test. In addition, results from the 10-2 VF test show better association with findings from OCT scans of the macular ganglion cell complex. Modifications of the 24-2 test that include extra test locations within the central 10 degrees improve detection of central defects found on 10-2 VF testing.

CONCLUSIONS

Evidence to date does not support routine testing using 10-2 VF for patients with early glaucoma. However, early 10-2 VF testing may provide sufficient additional information for some patients, particularly those with a repeatable defect within the central 12 locations of the standard 24-2 VF test or who have inner retinal layer thinning on OCT scans of the macula.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Deep Learning Estimation of 10-2 Visual Field Map Based on Macular Optical Coherence Tomography Angiography Measurements

PURPOSE

To develop deep learning (DL) models estimating the central visual field (VF) from optical coherence tomography angiography (OCTA) vessel density (VD) measurements.

DESIGN

Development and validation of a deep learning model.

METHODS

A total of 1051 10-2 VF OCTA pairs from healthy, glaucoma suspects, and glaucoma eyes were included. DL models were trained on en face macula VD images from OCTA to estimate 10-2 mean deviation (MD), pattern standard deviation (PSD), 68 total deviation (TD) and pattern deviation (PD) values and compared with a linear regression (LR) model with the same input. Accuracy of the models was evaluated by calculating the average mean absolute error (MAE) and the R2 (squared Pearson correlation coefficients) of the estimated and actual VF values.

RESULTS

DL models predicting 10-2 MD achieved R2 of 0.85 (95% confidence interval [CI], 74-0.92) for 10-2 MD and MAEs of 1.76 dB (95% CI, 1.39-2.17 dB) for MD. This was significantly better than mean linear estimates for 10-2 MD. The DL model outperformed the LR model for the estimation of pointwise TD values with an average MAE of 2.48 dB (95% CI, 1.99-3.02) and R2 of 0.69 (95% CI, 0.57-0.76) over all test points. The DL model outperformed the LR model for the estimation of all sectors.

CONCLUSIONS

DL models enable the estimation of VF loss from OCTA images with high accuracy. Applying DL to the OCTA images may enhance clinical decision making. It also may improve individualized patient care and risk stratification of patients who are at risk for central VF damage.

A Model of Progression to Help Identify Macular Damage Due to Glaucoma

The central macula contains a thick donut shaped region of the ganglion cell layer (GCL) that surrounds the fovea. This region, which is about 12 degrees (3.5 mm) in diameter, is essential for everyday functions such as driving, reading, and face recognition. Here, we describe a model of progression of glaucomatous damage to this GCL donut. This model is based upon assumptions supported by the literature, and it predicts the patterns of glaucomatous damage to the GCL donut, as seen with optical coherence tomography (OCT). After describing the assumptions and predictions of this model, we test the model against data from our laboratory, as well as from the literature. Finally, three uses of the model are illustrated. One, it provides an aid to help clinicians focus on the essential central macula and to alert them to look for other, non-glaucomatous causes, when the GCL damage does not fit the pattern predicted by the model. Second, the patterns of progression predicted by the model suggest alternative end points for clinical trials. Finally, the model provides a heuristic for future research concerning the anatomic basis of glaucomatous damage.

Importance of Pattern Standard Deviation of Humphrey 10-2 Visual Field to Evaluate Central Visual Function in Patients with Early-Stage Glaucoma

To explore various parameters that can evaluate the central visual impairment in patients with early-stage glaucoma, we included patients into a study with central visual impairments with an MD value greater than -6.0 dB on the 24-2 VF test. A possible association between structural parameters acquired by OCT and functional parameters of VF and PERG was determined. A total of 70 eyes of patients with suspected glaucoma or NTG underwent VF, OCT, and PERG examinations. The patients were classified into two groups according to the MD of the 24-2 VF test. We used Pearson correlation analysis to evaluate the relationships between GCIPL thickness/RNFL thickness and visual functional parameters, such as PERG and perimetry. Linear regression analyses were conducted to evaluate the significant factors affecting the PSD of VF 10-2. In the low MD group, the P50 amplitude presented significant correlations (r = 0.346, p = 0.048) with GCIPL thickness. In the correlation analysis of the high MD group, it was found that only the PSD of 10-2 uniquely presented borderline significant correlations with GCIPL thickness (r = -0.327, p = 0.055), and no other functional parameter showed significant correlation. Univariate and multivariate analyses revealed that GCIPL thickness was significantly associated with a PSD of 10-2 VF (p < 0.001 and 0.013, respectively). Among various parameters, the P50 amplitude and 10-2 PSD demonstrated statistically borderline significant structure-function relationships with GCIPL thickness in early-stage glaucoma.

Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina

This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.

Optical Coherence Tomography and Optical Coherence Tomography Angiography: Essential Tools for Detecting Glaucoma and Disease Progression

Early diagnosis and detection of disease progression are critical to successful therapeutic intervention in glaucoma, the leading cause of irreversible blindness worldwide. Optical coherence tomography (OCT) is a non-invasive imaging technique that allows objective quantification in vivo of key glaucomatous structural changes in the retina and the optic nerve head (ONH). Advances in OCT technology have increased the scan speed and enhanced image quality, contributing to early glaucoma diagnosis and monitoring, as well as the visualization of critically important structures deep within the ONH, such as the lamina cribrosa. OCT angiography (OCTA) is a dye-free technique for noninvasively assessing ocular microvasculature, including capillaries within each plexus serving the macula, peripapillary retina and ONH regions, as well as the deeper vessels of the choroid. This layer-specific assessment of the microvasculature has provided evidence that retinal and choroidal vascular impairments can occur during early stages of glaucoma, suggesting that OCTA-derived measurements could be used as biomarkers for enhancing detection of glaucoma and its progression, as well as to reveal novel insights about pathophysiology. Moreover, these innovations have demonstrated that damage to the macula, a critical region for the vision-related quality of life, can be observed in the early stages of glaucomatous eyes, leading to a paradigm shift in glaucoma monitoring. Other advances in software and hardware, such as artificial intelligence-based algorithms, adaptive optics, and visible-light OCT, may further benefit clinical management of glaucoma in the future. This article reviews the utility of OCT and OCTA for glaucoma diagnosis and disease progression detection, emphasizes the importance of detecting macula damage in glaucoma, and highlights the future perspective of OCT and OCTA. We conclude that the OCT and OCTA are essential glaucoma detection and monitoring tools, leading to clinical and economic benefits for patients and society.

The Definition of Glaucomatous Optic Neuropathy in Artificial Intelligence Research and Clinical Applications

OBJECTIVE

Although artificial intelligence (AI) models may offer innovative and powerful ways to use the wealth of data generated by diagnostic tools, there are important challenges related to their development and validation. Most notable is the lack of a perfect reference standard for glaucomatous optic neuropathy (GON). Because AI models are trained to predict presence of glaucoma or its progression, they generally rely on a reference standard that is used to train the model and assess its validity. If an improper reference standard is used, the model may be trained to detect or predict something that has little or no clinical value. This article summarizes the issues and discussions related to the definition of GON in AI applications as presented by the Glaucoma Workgroup from the Collaborative Community for Ophthalmic Imaging (CCOI) US Food and Drug Administration Virtual Workshop, on September 3 and 4, 2020, and on January 28, 2022.

DESIGN

Review and conference proceedings.

SUBJECTS

No human or animal subjects or data therefrom were used in the production of this article.

METHODS

A summary of the Workshop was produced with input and approval from all participants.

MAIN OUTCOME MEASURES

Consensus position of the CCOI Workgroup on the challenges in defining GON and possible solutions.

RESULTS

The Workshop reviewed existing challenges that arise from the use of subjective definitions of GON and highlighted the need for a more objective approach to characterize GON that could facilitate replication and comparability of AI studies and allow for better clinical validation of proposed AI tools. Different tests and combination of parameters for defining a reference standard for GON have been proposed. Different reference standards may need to be considered depending on the scenario in which the AI models are going to be applied, such as community-based or opportunistic screening versus detection or monitoring of glaucoma in tertiary care.

CONCLUSIONS

The development and validation of new AI-based diagnostic tests should be based on rigorous methodology with clear determination of how the reference standards for glaucomatous damage are constructed and the settings where the tests are going to be applied.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Comparing Static Perimetry Protocols of Central Field Testing among Patients with Glaucoma

SIGNIFICANCE

On comparing the Humphrey Field Analyzer (HFA) 24-2C Faster, which tests 10 additional points in the central field, with the 24-2 Swedish Interactive Thresholding Algorithm (SITA) Standard for detecting central field defects, we found that the HFA 24-2C Faster may be used for the initial field evaluation in glaucoma with the advantage of a shorter testing time.

PURPOSE

This study aimed to compare the HFA 24-2C Faster with the 24-2 SITA Standard and 10-2 among patients with glaucoma for the number of defective central points, global indices, and testing time.

METHODS

Sixty eyes of 60 patients with glaucoma and glaucomatous visual field defects on the 24-2 SITA Standard algorithm underwent the 24-2C Faster and 10-2 field tests. The number of central points detected, global indices, and reliability indices were compared between the 24-2C Faster and the 24-2 SITA Standard and 10-2 field tests.

RESULTS

The 24-2C Faster, on average, detected 5.5 defective points more on the total deviation plot and 2 defective points more on the pattern deviation plot than the 24-2 SITA Standard in central 10°. The 10-2 algorithm detected 2.5 times more points on the total deviation plot than the 24-2C Faster. There was excellent consistency by an intraclass correlation coefficient of 0.95 for the mean deviation and 0.93 for the pattern standard deviation between the 24-2C Faster and the 24-2 SITA Standard. There was good consistency by an intraclass correlation coefficient of 0.80 for both mean deviation and pattern standard deviation between the 24-2C Faster and the 10-2. The testing time was significantly lower with the 24-2C Faster compared with the 24-2 SITA Standard and 10-2 test.

CONCLUSIONS

Our study demonstrates that the HFA 24-2C Faster may be used for the initial evaluation of the visual field in glaucoma with the added advantage of a shorter testing time compared with the 24-2 SITA Standard program.

Progression of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry

Purpose

Performance comparison of optical coherence tomography (OCT) and visual field (VF) summary metrics for detecting glaucomatous progression.

Methods

Thirty healthy control eyes (mean deviation [MD], -1.25 ± 2.03; pattern standard deviation [PSD] , 1.78 ± 0.77) and 91 patient eyes comprised of 54 glaucoma patients and 37 glaucoma suspects (MD, -1.58 ± 1.96; PSD, 2.82 ± 1.92) with a follow-up of at least 1 year formed a group to evaluate progression with event analyses (P-Event). A subset of eyes with an additional criterion of a minimum of four tests was used for trend analyses (P-Trend) (30 healthy controls and 73 patients). For P-Event analysis, test-retest variability thresholds (lower 5th percentile) were estimated with repeat tests within a 4-month period. A P-Event eye was considered a "progressor" if the difference between follow-up and baseline tests exceeded the variability thresholds. For the P-Trend analysis, rates of change were calculated based on least-squares regression. Negative rates with significant (P < 0.05) values were considered progressing. For a reference standard, 17 patient eyes were classified as definitely progressing based on clear evidence of structural and corresponding functional progression.

Results

Isolated OCT and VF summary metrics were either inadequately sensitive or not too specific. Combinations of OCT-OCT and OCT-VF metrics markedly improved specificity to nearly 100%. A novel combination of OCT metrics (circumpapillary retinal nerve fiber layer and ganglion cell layer) showed high precision, with 13 of the 15 statistical progressors confirmed as true positives.

Conclusions

Although relying solely on metrics is not recommended for clinical purposes, in situations requiring very high specificity and precision, combinations of OCT-OCT metrics can be used.

Translational Relevance

All available OCT and VF metrics can miss eyes with progressive glaucomatous damage and/or can falsely identify progression in stable eyes.

A Deep Learning Approach to Improve Retinal Structural Predictions and Aid Glaucoma Neuroprotective Clinical Trial Design

PURPOSE

To investigate the efficacy of a deep learning regression method to predict macula ganglion cell-inner plexiform layer (GCIPL) and optic nerve head (ONH) retinal nerve fiber layer (RNFL) thickness for use in glaucoma neuroprotection clinical trials.

DESIGN

Cross-sectional study.

PARTICIPANTS

Glaucoma patients with good quality macula and ONH scans enrolled in 2 longitudinal studies, the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovations in Glaucoma Study.

METHODS

Spectralis macula posterior pole scans and ONH circle scans on 3327 pairs of GCIPL/RNFL scans from 1096 eyes (550 patients) were included. Participants were randomly distributed into a training and validation dataset (90%) and a test dataset (10%) by participant. Networks had access to GCIPL and RNFL data from one hemiretina of the probe eye and all data of the fellow eye. The models were then trained to predict the GCIPL or RNFL thickness of the remaining probe eye hemiretina.

MAIN OUTCOME MEASURES

Mean absolute error (MAE) and squared Pearson correlation coefficient (r²) were used to evaluate model performance.

RESULTS

The deep learning model was able to predict superior and inferior GCIPL thicknesses with a global r² value of 0.90 and 0.86, r² of mean of 0.90 and 0.86, and mean MAE of 3.72 μm and 4.2 μm, respectively. For superior and inferior RNFL thickness predictions, model performance was slightly lower, with a global r² of 0.75 and 0.84, r² of mean of 0.81 and 0.82, and MAE of 9.31 μm and 8.57 μm, respectively. There was only a modest decrease in model performance when predicting GCIPL and RNFL in more severe disease. Using individualized hemiretinal predictions to account for variability across patients, we estimate that a clinical trial can detect a difference equivalent to a 25% treatment effect over 24 months with an 11-fold reduction in the number of patients compared to a conventional trial.

CONCLUSIONS

Our deep learning models were able to accurately estimate both macula GCIPL and ONH RNFL hemiretinal thickness. Using an internal control based on these model predictions may help reduce clinical trial sample size requirements and facilitate investigation of new glaucoma neuroprotection therapies.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Glaucoma progression. Clinical practice guide

OBJECTIVE

To provide general recommendations that serve as a guide for the evaluation and management of glaucomatous progression in daily clinical practice based on the existing quality of clinical evidence.

METHODS

After defining the objectives and scope of the guide, the working group was formed and structured clinical questions were formulated following the PICO (Patient, Intervention, Comparison, Outcomes) format. Once all the existing clinical evidence had been independently evaluated with the AMSTAR 2 (Assessment of Multiple Systematic Reviews) and Cochrane "Risk of bias" tools by at least two reviewers, recommendations were formulated following the Scottish Intercollegiate Guideline network (SIGN) methodology.

RESULTS

Recommendations with their corresponding levels of evidence that may be useful in the interpretation and decision-making related to the different methods for the detection of glaucomatous progression are presented.

CONCLUSIONS

Despite the fact that for many of the questions the level of scientific evidence available is not very high, this clinical practice guideline offers an updated review of the different existing aspects related to the evaluation and management of glaucomatous progression.

High sampling resolution optical coherence tomography reveals potential concurrent reductions in ganglion cell-inner plexiform and inner nuclear layer thickness but not in outer retinal thickness in glaucoma

PURPOSE

To analyse optical coherence tomography (OCT)-derived inner nuclear layer (INL) and outer retinal complex (ORC) measurements relative to ganglion cell-inner plexiform layer (GCIPL) measurements in glaucoma.

METHODS

Glaucoma participants (n = 271) were categorised by 10-2 visual field defect type. Differences in GCIPL, INL and ORC thickness were calculated between glaucoma and matched healthy eyes (n = 548). Hierarchical cluster algorithms were applied to generate topographic patterns of retinal thickness change, with agreement between layers assessed using Cohen's kappa (κ). Differences in GCIPL, INL and ORC thickness within and outside GCIPL regions showing the greatest reductions and Spearman's correlations between layer pairs were compared with 10-2 mean deviation (MD) and pattern standard deviation (PSD) to determine trends with glaucoma severity.

RESULTS

Glaucoma participants with inferior and superior defects presented with concordant GCIPL and INL defects demonstrating mostly fair-to-moderate agreement (κ = 0.145-0.540), which was not observed in eyes with no or ring defects (κ = -0.067-0.230). Correlations (r) with MD and PSD were moderate and weak in GCIPL and INL thickness differences, respectively (GCIPL vs. MD r = 0.479, GCIPL vs. PSD r = -0.583, INL vs. MD r = 0.259, INL vs. PSD r = -0.187, p = <0.0001-0.002), and weak in GCIPL-INL correlations (MD r = 0.175, p = 0.004 and PSD r = 0.154, p = 0.01). No consistent patterns in ORC thickness or correlations were observed.

CONCLUSIONS

In glaucoma, concordant reductions in macular INL and GCIPL thickness can be observed, but reductions in ORC thickness appear unlikely. These findings suggest that trans-synaptic retrograde degeneration may occur in glaucoma and could indicate the usefulness of INL thickness in evaluating glaucomatous damage.

Updates on the Diagnosis and Management of Glaucoma

Glaucoma is the leading cause of blindness throughout the world (after cataracts); therefore, general physicians should be familiar with the diagnosis and management of affected patients. Glaucomas are usually categorized by the anatomy of the anterior chamber angle (open vs narrow/closed), rapidity of onset (acute vs chronic), and major etiology (primary vs secondary). Most glaucomas are primary (ie, without a contributing comorbidity); however, several coexisting ophthalmic conditions may serve as the underlying etiologies of secondary glaucomas. Chronic glaucoma occurs most commonly; thus, regular eye examinations should be performed in at-risk patients to prevent the insidious loss of vision that can develop before diagnosis. Glaucoma damages the optic nerve and retinal nerve fiber layer, leading to peripheral and central visual field defects. Elevated intraocular pressure (IOP), a crucial determinant of disease progression, remains the only modifiable risk factor; thus, all current treatments (medications, lasers, and operations) aim to reduce the IOP. Pharmacotherapy is the usual first-line therapy, but noncompliance, undesirable adverse effects, and cost limit effectiveness. Laser and surgical treatments may lower IOP significantly over long periods and may be more cost effective than pharmacotherapy, but they are plagued by greater procedural risks and frequent treatment failures. Traditional incisional procedures have recently been replaced by several novel, minimally invasive glaucoma surgeries with improved safety profiles and only minimal decreases in efficacy. Minimally invasive glaucoma surgeries have dramatically transformed the surgical management of glaucoma; nevertheless, large, randomized trials are required to assess their long-term efficacy.

Test of a Retinal Nerve Fiber Bundle Trajectory Model Using Eyes With Glaucomatous Optic Neuropathy

Purpose

To test a model of retinal nerve fiber bundle trajectories that predicts the arcuate-shaped patterns seen on optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability/deviation maps (p-maps) in glaucomatous eyes.

Methods

Thirty-one glaucomatous eyes from a database of 250 eyes had clear arcuate-shaped patterns on RNFL p-maps derived from an OCT cube scan. The borders of the arcuate patterns were extracted from the RNFL p-maps. Next, the trajectories from an arcuate model were compared against these borders via a normalized root-mean-square difference analysis. The model's parameter, β, was varied, and the best-fitting, initial clock-hour position of the trajectory to the border was found for each β. Finally, the regions, as determined by the arcuate border's best-fit, initial clock-hour positions, were compared against the abnormal regions on the circumpapillary retinal nerve fiber layer (cpRNFL) profile.

Results

The arcuate model's mean β_Sup and β_Inf parameters minimized large differences between the trajectories and the arcuate borders on the RNFL p-maps. Furthermore, on average, 68% of the cpRNFL regions defined by the arcuate border's best-fit, initial clock-hour positions were abnormal (i.e., below the ≤5% threshold).

Conclusions

The arcuate model performed well in predicting the borders of arcuate patterns seen on RNFL p-maps. It also predicted the associated abnormal regions of the cpRNFL thickness plots.

Translational Relevance

This model should prove useful in helping clinicians understand topographical comparisons among different OCT representations and should improve structure-structure, as well as structure-function agreement analyses.

Distinguishing Healthy From Glaucomatous Eyes With Optical Coherence Tomography Global Circumpapillary Retinal Nerve Fiber Thickness in the Bottom 5th Percentile

PRCIS

Two novel, quantitative metrics, and 1 traditional metric were able to distinguish between many, but not all healthy and glaucomatous eyes in the bottom 5th percentile of global circumpapillary retinal nerve fiber layer (cpRNFL) thickness.

PURPOSE

To test the hypothesis that objective optical coherence tomography measures can distinguish between a healthy control with global cpRNFL thickness within the lower 5% of normal and a glaucoma patient with an equivalent cpRNFL thickness.

PATIENTS AND METHODS

A total of 37 healthy eyes from over 700 normative eyes fell within the bottom 5th percentile in global cpRNFL thickness. The global cpRNFL thickness of 35 glaucomatous eyes from 188 patients fell within the same range. For the traditional methods, the global cpRNFL thickness percentile and the global ganglion cell layer (GCL) thickness percentile for the central ±8 degrees, were calculated for all 72 eyes. For the novel cpRNFL method, the normalized root mean square (RMS) difference between the cpRNFL thickness profile and the global thickness-matched normative thickness profile was calculated. For the superior-inferior (SI) GCL method, the normalized mean difference in superior and inferior GCL thickness was calculated for the central ±8 degrees.

RESULTS

The best quantitative metric, the RMS cpRNFL method, had an accuracy of 90% compared with 81% for the SI GCL and 81% for the global GCL methods. As expected, the global cpRNFL had the worst accuracy, 72%. Similarly, the RMS cpRNFL method had an area under the curve of 0.93 compared with 0.83 and 0.84 for the SI GCL and global GCL methods, respectively. The global cpRNFL method had the worst area under the curve, 0.75.

CONCLUSION

Quantitative metrics can distinguish between most of the healthy and glaucomatous eyes with low global cpRNFL thickness. However, even the most successful metric, RMS cpRNFL, missed some glaucomatous eyes.

Rationale and Development of an OCT-Based Method for Detection of Glaucomatous Optic Neuropathy

A specific, sensitive, and intersubjectively verifiable definition of disease for clinical care and research remains an important unmet need in the field of glaucoma. Using an iterative, consensus-building approach and employing pilot data, an optical coherence tomography (OCT)-based method to aid in the detection of glaucomatous optic neuropathy was sought to address this challenge. To maximize the chance of success, we utilized all available information from the OCT circle and cube scans, applied both quantitative and semiquantitative data analysis methods, and aimed to limit the use of perimetry to cases where it is absolutely necessary. The outcome of this approach was an OCT-based method for the diagnosis of glaucomatous optic neuropathy that did not require the use of perimetry for initial diagnosis. A decision tree was devised for testing and implementation in clinical practice and research that can be used by reading centers, researchers, and clinicians. While initial pilot data were encouraging, future testing and validation will be needed to establish its utility in clinical practice, as well as for research.

Prediction of visual field defects from macular optical coherence tomography in glaucoma using cluster analysis

Purpose

To assess the accuracy of cluster analysis‐based models in predicting visual field (VF) defects from macular ganglion cell‐inner plexiform layer (GCIPL) measurements in glaucomatous and healthy cohorts.

Methods

GCIPL measurements were extracted from posterior pole optical coherence tomography (OCT), from locations corresponding to central VF test grids. Models incorporating cluster analysis methods and corrections for age and fovea to optic disc tilt were developed from 493 healthy participants, and 5th and 1st percentile limits of GCIPL thickness were derived. These limits were compared with pointwise 5th and 1st percentile limits by calculating sensitivities and specificities in an additional 40 normal and 37 glaucomatous participants, as well as applying receiver operating characteristic (ROC) curve analyses to assess the accuracy of predicting VF results from co‐localised GCIPL measurements.

Results

Clustered models demonstrated globally low sensitivity, but high specificity in the glaucoma cohort (0.28–0.53 and 0.77–0.91, respectively), and high specificity in the healthy cohort (0.91–0.98). Clustered models showed similar sensitivities and superior specificities compared with pointwise methods (0.41–0.65 and 0.71–0.98, respectively). There were significant differences in accuracy between clusters, with relatively poor accuracy at peripheral macular locations (p < 0.0001 for all comparisons).

Conclusions

Cluster analysis‐based models incorporating age correction and holistic consideration of fovea to optic disc tilt demonstrated superior performance in predicting VF results to pointwise methods in both glaucomatous and healthy eyes. However, relatively low sensitivity and poorer performance at the peripheral macula indicate that OCT in isolation may be insufficient to predict visual function across the macula accurately. With modifications to criteria for abnormality, the concepts suggested by the described normative models may guide prioritisation of VF assessment requirements, with the potential to limit excessive VF testing.

Clinical Evaluations of Macular Structure-Function Concordance With and Without Drasdo Displacement

Purpose

The purpose of this study was to compare concordance between ganglion cell-inner plexiform layer (GCIPL) data from the Cirrus optical coherence tomographer (OCT) Ganglion Cell Analysis (GCA) and visual fields (VFs), with and without Drasdo displacement.

Methods

From 296 open-angle glaucoma participants, GCIPL deviation and raw thickness data were extracted over locations per the 10-2 VF test grid, with and without application of Drasdo displacement, with global and eccentricity-dependent sensitivities and specificities calculated for both. With OCT and VF data classified as within or outside normative limits, pattern deviation values were compared using paired t-tests and Spearman correlations. Regression models were applied to pattern deviation values as a function of GCIPL thickness, and differences in model performance with and without displacement were compared using extra sums-of-squares F tests.

Results

There were small but significant improvements in global specificity without displacement (0.58-0.59 with displacement and 0.61 without displacement), without notable differences in sensitivity (0.77-0.78 with displacement and 0.76-0.78 without displacement). At abnormal VF locations and without displacement, a higher proportion of correct OCT classifications (P = 0.0008) and significant correlation with worsening pattern deviation values were observed (r = 0.50, P = 0.002). Regression models indicated significantly steeper slopes with Drasdo displacement centrally (P = 0.002-0.04).

Conclusions

With GCA deviation maps, small improvements in structure-function concordance were observed without displacement, which are unlikely to be clinically meaningful. Using GCIPL thickness data, significantly better structure-function concordance was observed centrally with Drasdo displacement.

Translational Relevance

Applying Drasdo displacement on probability-based reports is unlikely to alter clinical impressions of structure-function concordance, but applying displacement with GCIPL thickness data may improve detection of structure-function concordance.

Detection of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry

Purpose

To evaluate the diagnostic performance of optical coherence tomography (OCT) and visual field (VF) summary statistics (metrics) that are available in OCT and VF reports.

Methods

OCT disc and macular scans and 24-2 and 10-2 VFs were obtained from 56 healthy control (HC) eyes/participants and 61 eyes/patients with 24-2 mean deviation of better than –6 dB. All metrics were obtained from OCT radial, circle, and posterior pole cube scans and 24-2 and 10-2 VFs. Their diagnostic performances were evaluated, in isolation and in combinations. For specificity, the 56 HC eyes were used. For sensitivity, 40 of the 61 patient eyes were deemed likely glaucomatous based on an automated topographic method that evaluates structure–function (S–F) agreement. Any 1 of these 40 eyes not judged as abnormal by any given metric was considered a false negative.

Results

All single OCT and VF metrics misclassified HCs as glaucomatous and missed likely glaucomatous eyes. The best performing single metric was the temporal inferior thickness of the 3.5-mm circle scan, with 96% specificity and 83% sensitivity. Combinations of OCT–OCT and OCT–VF metrics markedly improved specificity. A newly proposed metric that evaluates structure–structure (S–S) agreement at a hemifield level had the highest accuracy. This S–S metric had 98% specificity and 80% sensitivity.

Conclusions

OCT and VF metrics, single or in combinations, have only moderate sensitivity for eyes with early glaucoma.

Translational Relevance

OCT and VF metrics combinations evaluating S–S or S–F agreement can be highly specific, which is an important implication for clinical and research purposes.

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.

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.

Visual Field Sensitivity Prediction Using Optical Coherence Tomography Analysis in Hydroxychloroquine Toxicity

Purpose

This study investigates the association between local retina structure and visual function in a cohort with long-term hydroxychloroquine (HCQ) use.

Methods

The study included 84 participants (54 participants without toxicity and 30 participants with toxicity) with history of chronic HCQ use (14.5 ± 7.4 years) who had testing with spectral-domain optical coherence tomography (SD-OCT) imaging and Humphrey 10-2 visual fields. Optical coherence tomography (OCT) metrics (total and outer retina thickness [TRT and ORT], minimum intensity [MinI], and ellipsoid zone [EZ] loss) were sampled in regions corresponding to visual field test locations. Univariate linear correlations were investigated and a multivariate random forest regression using a combination of OCT metrics was used to predict visual field sensitivity by locus using a leave-one-out cross-validation strategy.

Results

In univariate linear regression, EZ loss demonstrated the strongest relationship with visual field sensitivities in the parafoveal ring with R2 = 0.58. TRT and ORT revealed positive correlations with visual field sensitivity (R2 = 0.57 and 0.40, respectively), whereas total and outer retinal MinI yielded negative correlations (R2 = 0.10 and 0.22). The multivariate model improved correlations (R2 = 0.66) yielding a root mean squared error of 3.8 decibel (dB). Feature importance analysis identified EZ loss as the most relevant predictor of function.

Conclusions

Multiple OCT-derived quantitative metrics used in combination can provide information to predict local sensitivities. The results indicate a strong relationship between retinal function and OCT measures, which contribute to the understanding of the retinal toxicity caused by HCQ as well as being applicable to outcome development for other degenerative diseases of the outer retina.

A Case for The Use of Artificial Intelligence in Glaucoma Assessment

We hypothesize that artificial intelligence applied to relevant clinical testing in glaucoma has the potential to enhance the ability to detect glaucoma. This premise was discussed at the recent Collaborative Community for Ophthalmic Imaging meeting, "The Future of Artificial Intelligence-Enabled Ophthalmic Image Interpretation: Accelerating Innovation and Implementation Pathways," held virtually September 3-4, 2020. The Collaborative Community in Ophthalmic Imaging (CCOI) is an independent self-governing consortium of stakeholders with broad international representation from academic institutions, government agencies, and the private sector whose mission is to act as a forum for the purpose of helping speed innovation in healthcare technology. It was one of the first two such organizations officially designated by the FDA in September 2019 in response to their announcement of the collaborative community program as a strategic priority for 2018-2020. Further information on the CCOI can be found online at their website (https://www.cc-oi.org/about). Artificial intelligence for glaucoma diagnosis would have high utility globally, as access to care is limited in many parts of the world and half of all people with glaucoma are unaware of their illness. The application of artificial intelligence technology to glaucoma diagnosis has the potential to broadly increase access to care worldwide, in essence flattening the Earth by providing expert level evaluation to individuals even in the most remote regions of the planet.

Combining OCT and OCTA for Focal Structure-Function Modeling in Early Primary Open-Angle Glaucoma

Purpose

To investigate modeling of the focal visual field (VF) loss by combining structural measurements and vascular measurements in eyes with early primary open-angle glaucoma (POAG).

Methods

In this cross-sectional study, subjects with early glaucoma (VF mean deviation, ≥−6 dB) underwent optical coherence tomography (OCT) imaging, optical coherence tomography angiography (OCTA) imaging, and Humphrey 24-2 VF tests. Capillary perfusion densities (CPDs) were calculated after the removal of large vessels in the OCTA images. Focal associations between VF losses at the individual VF test locations, circumpapillary retinal nerve fiber layer (RNFL) thickness measurements from OCT, and CPDs were determined using nerve fiber trajectory tracings. Linear mixed models were used to model focal VF losses at each VF test location.

Results

Ninety-seven eyes with early POAG (VF mean deviation, −2.47 ± 1.64 dB) of 71 subjects were included. Focal VF modeling using a combined RNFL–CPD approach resulted in a median adjusted R² value of 0.30 (interquartile range [IQR], 0.13–0.55), whereas the RNFL-only and CPD-only approaches resulted in median values of 0.22 (IQR, 0.10–0.51) and 0.26 (IQR, 0.10–0.52), respectively. Seventeen VF locations with the combined approach had an adjusted R² value greater than 0.50. Likelihood testing at each VF test location showed that the combined approach performed significantly better at the superior nasal VF regions of the eyes compared with the univariate approaches.

Conclusions

Modeling of focal VF losses showed improvements when structural thickness and vascular parameters were included in tandem. Evaluation of VF defects in early glaucoma may benefit from considering both RNFL and OCTA characteristics.

Ganglion cell-inner plexiform layer measurements derived from widefield compared to montaged 9-field optical coherence tomography

CLINICAL RELEVANCE

With equivalent inner retinal thickness measurements compared to a more conventional composite optical coherence tomography (OCT) protocol, Widefield optical coherence tomography (WF-OCT) is a clinically viable, time-saving option facilitating detection of ocular pathologies within the central 55° of the retina.

PURPOSE

To compare ganglion cell-inner plexiform layer (GCIPL) thicknesses obtained using a single WF-OCT scan and standard composite OCT scans acquired in 9 fields of gaze (9F-OCT).

METHODS

Thirteen healthy participants underwent WF-OCT and 9F-OCT using the Spectralis OCT. The GCIPL was automatically segmented with a manual review for 9F-OCT and was manually segmented for WF-OCT. After registration, differences in GCIPL thicknesses were compared using 95% confidence intervals computed from one-sample t-tests and Bland-Altman analyses. Location-specific differences in B-scan tilt were analysed using Spearman correlations and linear regression models. To determine whether B-scan tilt influences GCIPL measurements, regression models of tilt versus differences between perpendicular and axial GCIPL thickness were applied.

RESULTS

While scattered locations demonstrated significant GCIPL thickness differences between WF-OCT and 9F-OCT, most differences did not exceed the axial pixel resolution of the instrument of 3.87 µm. Bland-Altman analyses indicated no notable bias using WF-OCT. Moderate correlations indicating significant location-specific differences in B-scan tilt were observed for temporal, central and inferior B-scans (r = -0.62 to 0.72), with linear regression models predicting a maximum difference in the tilt of 4.65°. The quadratic regression model indicated that at tilts greater than 27.3°, perpendicular GCIPL measurements become increasingly thin relative to axial measurements.

CONCLUSIONS

GCIPL thicknesses and B-scan tilts from WF-OCT are comparable to 9F-OCT, indicating that WF-OCT can be applied clinically to obtain valid inner retinal OCT measurements over 55° of the central retina with relative ease. However, for peripheral locations, B-scan tilt may need to be considered when measuring GCIPL thicknesses.

Variability and Power to Detect Progression of Different Visual Field Patterns

PURPOSE

To compare the variability and ability to detect visual field (VF) progression of 24-2, central 12 locations of the 24-2 and 10-2 VF tests in eyes with abnormal VFs.

DESIGN

Retrospective, multisite cohort.

PARTICIPANTS

A total of 52 806 24-2 and 11 966 10-2 VF tests from 7307 eyes from the Glaucoma Research Network database were analyzed. Only eyes with ≥ 5 visits and ≥ 2 years of follow-up were included.

METHODS

Linear regression models were used to calculate the rates of mean deviation (MD) change (slopes), whereas their residuals were used to assess variability across the entire MD range. Computer simulations (n = 10 000) based on real MD residuals of our sample were performed to estimate power to detect significant progression (P < 5%) at various rates of MD change.

MAIN OUTCOME MEASURES

Time required to detect progression.

RESULTS

For all 3 patterns, the MD variability was highest within the -5 to -20 decibel (dB) range and consistently lower with the 10-2 compared with 24-2 or central 24-2. Overall, time to detect confirmed significant progression at 80% power was the lowest with 10-2 VF, with a decrease of 14.6% to 18.5% when compared with 24-2 and a decrease of 22.9% to 26.5% when compared with central 24-2.

CONCLUSIONS

Time to detect central VF progression was reduced with 10-2 MD compared with 24-2 and C24-2 MD in glaucoma eyes in this large dataset, in part because 10-2 tests had lower variability. These findings contribute to current evidence of the potential value of 10-2 testing in the clinical management of patients with glaucoma and in clinical trial design.

Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT

PURPOSE

To develop deep learning (DL) systems estimating visual function from macula-centered spectral-domain (SD) OCT images.

DESIGN

Evaluation of a diagnostic technology.

PARTICIPANTS

A total of 2408 10-2 visual field (VF) SD OCT pairs and 2999 24-2 VF SD OCT pairs collected from 645 healthy and glaucoma subjects (1222 eyes).

METHODS

Deep learning models were trained on thickness maps from Spectralis macula SD OCT to estimate 10-2 and 24-2 VF mean deviation (MD) and pattern standard deviation (PSD). Individual and combined DL models were trained using thickness data from 6 layers (retinal nerve fiber layer [RNFL], ganglion cell layer [GCL], inner plexiform layer [IPL], ganglion cell-IPL [GCIPL], ganglion cell complex [GCC] and retina). Linear regression of mean layer thicknesses were used for comparison.

MAIN OUTCOME MEASURES

Deep learning models were evaluated using R² and mean absolute error (MAE) compared with 10-2 and 24-2 VF measurements.

RESULTS

Combined DL models estimating 10-2 achieved R² of 0.82 (95% confidence interval [CI], 0.68-0.89) for MD and 0.69 (95% CI, 0.55-0.81) for PSD and MAEs of 1.9 dB (95% CI, 1.6-2.4 dB) for MD and 1.5 dB (95% CI, 1.2-1.9 dB) for PSD. This was significantly better than mean thickness estimates for 10-2 MD (0.61 [95% CI, 0.47-0.71] and 3.0 dB [95% CI, 2.5-3.5 dB]) and 10-2 PSD (0.46 [95% CI, 0.31-0.60] and 2.3 dB [95% CI, 1.8-2.7 dB]). Combined DL models estimating 24-2 achieved R² of 0.79 (95% CI, 0.72-0.84) for MD and 0.68 (95% CI, 0.53-0.79) for PSD and MAEs of 2.1 dB (95% CI, 1.8-2.5 dB) for MD and 1.5 dB (95% CI, 1.3-1.9 dB) for PSD. This was significantly better than mean thickness estimates for 24-2 MD (0.41 [95% CI, 0.26-0.57] and 3.4 dB [95% CI, 2.7-4.5 dB]) and 24-2 PSD (0.38 [95% CI, 0.20-0.57] and 2.4 dB [95% CI, 2.0-2.8 dB]). The GCIPL (R² = 0.79) and GCC (R² = 0.75) had the highest performance estimating 10-2 and 24-2 MD, respectively.

CONCLUSIONS

Deep learning models improved estimates of functional loss from SD OCT imaging. Accurate estimates can help clinicians to individualize VF testing to patients.

Combined structure-function analysis in glaucoma screening

AIM

To assess the applicability of a structure-function (S-F) analysis combining spectral-domain optical coherence tomography (SD-OCT) and standard automated perimetry (SAP) in glaucoma screening in a middle-aged population.

METHODS

A randomised sample of 3001 Caucasian participants aged 45-49 years of the Northern Finland Birth Cohort Eye Study was examined. We performed an eye examination, including 24-2 SAP, optic nerve head (ONH) and retinal nerve fibre layer (RNFL) photography and SD-OCT of the peripapillary RNFL. The S-F report was generated by Forum Glaucoma Workplace software. OCT, SAP and the S-F analysis were evaluated against clinical glaucoma diagnosis, that is, the positive '2 out of 3' rule based on the clinician's evaluation of ONH and RNFL photographs and visual fields (VFs).

RESULTS

At a specificity of 97.5%, the sensitivity for glaucomatous damage was 26% for abnormal OCT, 35% for SAP and 44% for S-F analysis. Estimated areas under the curve were 0.74, 0.85 and 0.76, and the corresponding positive predictive values were 8 %, 10% and 12%, respectively. By applying a classification tree approach combining OCT, SAP and defect localisation data, a sensitivity of 77% was achieved at 90% specificity. In a localisation analysis of glaucomatous structural and functional defects, the correlation with glaucoma increased significantly if the abnormal VF test points were located on borderline or abnormal OCT zones.

CONCLUSION

SAP performs slightly better than OCT in glaucoma screening of middle-aged population. However, the diagnostic capability can be improved by S-F analysis.

Prediction of 10-2 Visual Field Loss Using Optical Coherence Tomography and 24-2 Visual Field Data

PRECIS

Using standard glaucoma structural and functional tests, clinicians accurately predicted the presence/absence of 10-2 glaucomatous visual field (VF) loss in 90% of the eyes in this study.

PURPOSE

To investigate how well clinicians with variable experience can predict the presence and location of 10-2 VF loss using structural and functional data that are routinely obtained for glaucoma assessment.

METHODS

Within a test set of 416 eyes (210 subjects) who were diagnosed glaucoma suspect or primary open-angle glaucoma (with most eyes having mild disease), 6 clinicians were asked to predict the presence and hemispheric location of 10-2 VF loss using 24-2 VF and spectral-domain optical coherence tomography structural data. Prediction accuracies were calculated for each clinician and compared using the weighted κ-statistic. Receiver operating characteristic analyses were used to evaluate models for predicting 10-2 VF loss.

RESULTS

Among the 6 clinicians, mean (range) accuracy, false negatives, and false positives for predicting presence/absence of 10-2 VF loss were 90% (87% to 92%), 4.7% (2.4% to 7.0%), and 5.4% (1.7% to 7.5%) respectively. The mean (range) weighted κ-statistic was 0.75 (0.64 to 0.83), suggesting good or very good inter-rater agreement between examiners. Mean accuracy for correctly predicting hemispheric location was 73% (range, 65% to 82%) with the most common error occurring in eyes with both superior and inferior 10-2 VF defects in which one hemisphere was correctly identified but the other missed.

CONCLUSIONS

In this study, the presence/absence of 10-2 glaucomatous VF loss was highly predictable using standard functional and structural clinical metrics. These findings suggest that 10-2 VF testing is not needed to reliably recognize and confirm central VF involvement in most eyes with glaucoma. Whether error related to identifying second hemisphere involvement in 10-2 VF loss is important requires further study.

Interpreting Retinal Nerve Fiber Layer Reflectance Defects Based on Presence of Retinal Nerve Fiber Bundles

SIGNIFICANCE

Adaptive-optics scanning-laser-ophthalmoscopy (AOSLO) retinal imaging of the retinal nerve fiber layer (RNFL) helps predict the severity of perimetric damage based on absence of fibers and projection of the defects in en face images of the RNFL from spectral-domain optical coherence tomography (SD-OCT).

PURPOSE

En face images of the RNFL reveal reflectance defects in patients with glaucoma and predict locations of perimetric defects. These defects could arise from either loss of retinal nerve fiber bundles or reduced bundle reflectance. This study used AOSLO to assess presence of bundles in areas with RNFL reflectance defects on SD-OCT.

METHODS

Adaptive-optics scanning laser ophthalmoscopy was used to image a vertical strip of RNFL measuring approximately 30 × 3° between the optic disc and the fovea. Fifteen patients with glaucoma who had SD-OCT reflectance defects that passed through this region were chosen. Four patients had reflectance defects in both superior and inferior hemifields, so presence of bundles on AOSLO was assessed for 19 hemifields. Where bundles were present, the hemifield was scored for whether bundles seemed unusual (low contrast and/or low density). Perimetric defects were considered deep when sensitivity was below 15 dB.

RESULTS

Ten hemifields had a region with no fibers present on AOSLO; all had a corresponding deep perimetric defect. The other nine hemifields had no region in the AOSLO image without fibers: four with normal fibers and five with unusual fibers. The only one of these nine hemifields with a deep perimetric defect was one with low-contrast fibers and overall thin RNFL.

CONCLUSIONS

Retinal nerve fiber layer reflectance defects, which were associated with deep perimetric defects, usually had a region with absence of fibers on AOSLO images of RNFL. Ability to predict severity of perimetric damage from en face SD-OCT RNFL reflectance images could benefit from quantification that differentiated between absence of fibers and unusual fibers.

Did the OCT Show Progression Since the Last Visit?

Identifying progression is of fundamental importance to the management of glaucoma. It is also a challenge. The most sophisticated, and probably the most useful, commercially available clinical tool for identifying progression is the Guided Progression Analysis (GPA), which was initially developed to identify progression using 24-2 visual field tests. More recently, it has been extended to retinal nerve fiber layer (RNFL) and ganglion cell+inner plexiform layer thicknesses measured with optical coherence tomography (OCT). However, the OCT GPA requires a minimum of 3 tests to determine "possible loss (progression)" and a minimum of 4 tests to determine if the patient shows "likely loss (progression)." Thus, it is not designed to answer a fundamental question asked by both the clinician and the patient, namely: Did damage progress since the last visit? Some clinicians use changes in summary statistics, such as global/average circumpapillary RNFL thickness. However, these statistics have poor sensitivity and specificity due to segmentation and alignment errors. Instead of relying on the GPA analysis or summary statistics, one needs to evaluate RNFL and ganglion cell+inner plexiform layer probability maps and circumpapillary OCT B-scan images. In addition, we argue that the clinician can make a better decision about suspected progression between 2 test days by topographically comparing the changes in the different OCT maps and images, in addition to topographically comparing the changes in the visual field with the changes in OCT probability maps.

An Evaluation of a New 24-2 Metric for Detecting Early Central Glaucomatous Damage

PURPOSE

We sought to test the hypothesis that a recently proposed pattern standard deviation (PSD) metric, based upon the 24-2 visual field (VF) test, as well as the PSD of the 10-2 VF, will miss central glaucomatous damage confirmed with an objective structure-function method.

DESIGN

Cross-sectional study.

METHODS

A glaucoma (G) group (70 eyes/patients) diagnosed with glaucoma and a 24-2 mean deviation better than -6 dB and a healthy (H) group (45 eyes/patients) had 24-2 and 10-2 VFs and optical coherence tomography (OCT) scans twice within 4 weeks. The PSD(C24-2), based upon the central 12 points of the 24-2, was compared with the PSD(10-2). To evaluate central damage (CD) in G eyes with normal PSD(C24-2) values, a post hoc analysis was combined with a CD reference standard (CD-RS), which was based upon an objective, topographic comparison between abnormal points on the 10-2 VF and OCT probability maps.

RESULTS

The 115 PSD(C24-2) and PSD(10-2) values were significantly correlated (Spearman correclation coefficient: rho = 0.55; P < .001) and the number of G eyes (19) identified as abnormal by the PSD(C24-2) was not significantly different from the number (22) identified by the PSD(10-2) (P = .15). However, based upon the CD-RS, 44 of 70 G eyes were classified as abnormal. The PSD(C24-2) missed 27 (61%) of these 44 eyes, and the PSD(10-2) missed 23 (52%) of these eyes. Post hoc analysis revealed clear CD in most of these eyes.

CONCLUSION

Neither the PSD(C24-2) nor the PSD(10-2) metric is good measure of early CD. Instead we recommend a topographic approach based upon OCT probability maps and a 10-2 VF.

Detection of Glaucoma Deterioration in the Macular Region with Optical Coherence Tomography: Challenges and Solutions

PURPOSE

Macular imaging with optical coherence tomography (OCT) measures the most critical retinal ganglion cells (RGCs) in the human eye. The goal of this perspective is to review the challenges to detection of glaucoma progression with macular OCT imaging and propose ways to enhance its performance.

DESIGN

Perspective with review of relevant literature.

METHODS

Review of challenges and issues related to detection of change on macular OCT images in glaucoma eyes. The primary outcome measures were confounding factors affecting the detection of change on macular OCT images.

RESULTS

The main challenges to detection of structural progression in the macula consist of the magnitude of and the variable amount of test-retest variability among patients, the confounding effect of aging, lack of a reliable and easy-to-measure functional outcome or external standard, the confounding effects of concurrent macular conditions including myopia, and the measurement floor of macular structural outcomes. Potential solutions to these challenges include controlling head tilt or torsion during imaging, estimating within-eye variability for individual patients, improved data visualization, the use of artificial intelligence methods, and the implementation of statistical approaches suitable for multidimensional longitudinal data.

CONCLUSIONS

Macular OCT imaging is a crucial structural imaging modality for assessing central RGCs. Addressing the current shortcomings in acquisition and analysis of macular volume scans can enhance its utility for measuring the health of central RGCs and therefore assist clinicians with timely institution of appropriate treatment.

Local Glaucomatous Defects of the Circumpapillary Retinal Nerve Fiber Layer Show a Variety of Patterns of Progression

PRECIS

The region of glaucomatous progression, seen on optical coherence tomography (OCT) images of the circumpapillary retinal nerve fiber layer (cRNFL), increases in width and depth in all eyes, but shows a variety of different patterns of loss across eyes.

PURPOSE

The purpose of this study was to examine the patterns of cRNFL loss secondary to glaucomatous progression in a region associated with the superior hemifield of the 24-2/30-2 visual field (VF).

METHODS

Twenty-four eyes (20 patients) with a diagnosis of glaucoma and evidence of progression on OCT had OCT disc cube scans on at least 3 separate visits (mean follow-up 7.4 y; range: 3.9 to 11.4). Circumpapillary b-scans were derived after enface images were aligned to assure that the study region (ie, 0 to -135 degrees, where 0 degree is 9 o'clock, on a right eye) coincided. Within this region, a region of progression (ROP) was defined based on the loss in cRNFL thickness between the first and subsequent visits. The width of the ROP was determined, along with the locations of its leading (close to fixation) and trailing edges. In addition, for each ROP, the location and depth at the point of maximal loss, total loss, and average remaining retinal nerve fiber layer were measured.

RESULTS

The ROP proceeded both toward and away from fixation. Across eyes, the ROP varied widely in width (32 to 131 degrees, mean 82.7 degrees), location, and loss at point of deepest loss (22 to 99 μm, mean 52.9 μm), as well as total cRNFL loss.

CONCLUSIONS

All eyes showed a widening and deepening of the ROP, but a variety of different patterns of progressive cRNFL loss. Thus, one should expect considerable variation in patterns of VF loss. Furthermore, conventional metrics (global or quadrant cRNFL thickness) do not fully depict the progressive changes that can be appreciated by inspecting OCT images.

Global optical coherence tomography measures for detecting the progression of glaucoma have fundamental flaws

Objective

To understand the problems involved in using global OCT measures for detecting progression in early glaucoma.

Subjects/Methods

Eyes from 76 patients and 28 healthy controls (HC) had a least two OCT scans at least 1 year apart. To determine the 95% confidence intervals (CI), 151 eyes (49 HC and 102 patients) had at least two scans within 6 months. All eyes had 24-2 mean deviation ≥-6dB. The average (global) thicknesses of the circumpapillary retinal nerve fibre layer (cRNFL), G_ONH, and of the retinal ganglion cell layer plus inner plexiform layer (RGCLP), G_mac, were calculated. Using quantile regression, the 95% CI intervals were determined. Eyes outside the CIs were classified as “progressors.” For a reference standard (RS), four experts evaluated OCT and VF information.

Results

Compared to the RS, 31 of the 76 (40.8%) patient eyes were identified as progressors (RS-P), and 45 patient, and all 28 HC, eyes as nonprogressors (RS-NP). The metrics missed (false negative, FN) 15 (48%) (G_ONH) and 9 (29%) (G_mac) of the 31 RS-P. Further, G_ONH and/or G_mac falsely identified (false positive, FP) 10 (22.2%) of 45 patient RS-NP eyes and 7 (25%) of the 28 HC eyes as progressing. Post-hoc analysis identified three reasons (segmentation, centring, and local damage) for these errors.

Conclusions

Global metrics lead to FPs and FNs because of problems inherent in OCT scanning (segmentation and centring), and to FNs because they can miss local damage. These problems are difficult, if not impossible, to correct, and raise concerns about the advisability of using G_ONH and G_mac for detecting progression.

A Topographic Comparison of OCT Minimum Rim Width (BMO-MRW) and Circumpapillary Retinal Nerve Fiber Layer (cRNFL) Thickness Measures in Eyes With or Suspected Glaucoma

PRéCIS:: Bruch's membrane opening-minimum rim width (BMO-MRW) and circumpapillary retinal nerve fiber layer (cRNFL) thickness measures may be improved by comparing probability levels and accounting for blood vessel locations.

PURPOSE

To understand the differences between 2 optical coherence tomography measures of glaucomatous damage: the BMO-MRW and cRNFL thickness.

MATERIALS AND METHODS

Optical coherence tomography circle scans were obtained for an early glaucoma group (EG) of 88 eyes (88 patients) with 24-2 mean deviation better than -6.0 dB, and a broader group (BG) of 188 eyes (110 patients) with 24-2 mean deviation from -0.15 to -27.0 dB. On the basis of a commercial report, the cRNFL and BMO-MRW of each hemidisc was classified as abnormal if either of the 2 superior (inferior) sectors, temporal superior and nasal superior (temporal inferior and nasal inferior), was yellow or red (P<5%); and as normal if both were green (P≥5%). In addition, a post hoc analysis identified the reasons for disagreements on the basis of the presence (or absence) of glaucomatous damage at a hemidisc level (consensus of 4 experts).

RESULTS

The BMO-MRW and cRNFL measures agreed in 81.9% (broader group) and 73.9% (EG) of the hemidiscs. In both groups, an abnormal-BMO-MRW/normal-cRNFL disagreement was as common as a normal-BMO-MRW/abnormal-cRNFL. Of the 46 EG hemidisc disagreements, the number of "mistakes" for BMO-MRW (28) was nonsignificantly higher than for cRNFL (18) (P=0.15). Primary causes for disagreement were as follows: borderline significance level, a local defect, and aberrant blood vessel location.

CONCLUSIONS

Although BMO-MRW and cRNFL measures agreed in the majority of hemidiscs, they still disagreed in over 25% of the EG hemidiscs. These measures may be improved by comparing actual probability levels and accounting for blood vessel locations. However, both can miss information available on retinal ganglion cell/retinal nerve fiber layer probability maps.

Depth-resolved variations in visibility of retinal nerve fibre bundles across the retina in enface OCT images of healthy eyes

PURPOSE

Recent developments in optical coherence tomography (OCT) technology enable direct enface visualisation of retinal nerve fibre bundle (RNFB) loss in glaucoma. However, the optimum depth at which to visualise RNFBs across the retina is unknown. We aimed to evaluate the range of depths and optimum depth at which RNFBs can be visualised across the retina in healthy eyes.

METHODS

The central ± 25° retina of 10 healthy eyes from 10 people aged 57-75 years (median 68.5 years) were imaged with spectral domain OCT. Slab images of maximum axial resolution (4 μm) containing depth-resolved attenuation coefficients were extracted from 0 to 193.5 μm below the inner limiting membrane (ILM). Bundle visibility within 10 regions of a superimposed grid was assessed subjectively by trained optometrists (n = 8), according to written instructions. Anterior and posterior limits of RNFB visibility and depth of best visibility were identified for each grid sector. Effects of retinal location and individual eye on RNFB visibility were explored using linear mixed modelling with likelihood ratio tests. Intraclass correlation coefficient (ICC) was used to measure overall agreement and repeatability of grading. Spearman's correlation was used to measure correlation between depth range of visible RNFBs and retinal nerve fibre layer thickness (RNFLT).

RESULTS

Retinal location and individual eye affected anterior limit of visibility (χ² ₍₉₎  = 58.6 and 60.5, both p < 0.0001), but none of the differences exceeded instrument resolution, making anterior limit consistent across the retina and different eyes. Greater differences were observed in the posterior limit of visibility across retinal areas (χ² ₍₉₎  = 1671.1, p < 0.0001) and different eyes (χ² ₍₉₎  = 88.7, p < 0.0001). Optimal depth for visualisation of RNFBs was around 20 µm below the ILM in most regions. It varied slightly with retinal location (χ² ₍₉₎  = 58.8, p < 0.0001), but it was not affected by individual eye (χ² ₍₉₎  = 10.7, p = 0.29). RNFB visibility showed good agreement between graders (ICC 0.89, 95%CI 0.87-0.91), and excellent repeatability (ICC 0.96-0.99). Depth range of visible RNFBs was highly correlated with RNFLT (ρ = 0.9, 95%CI: 0.86-0.95).

CONCLUSIONS

The range of depths with visible RNFBs varies markedly across the healthy retina, consistently with RNFLT. To extract all RNFB information consistently across the retina, slab properties should account for differences across retinal locations and between individual eyes.

Ability of 24-2C and 24-2 Grids to Identify Central Visual Field Defects and Structure-Function Concordance in Glaucoma and Suspects

PURPOSE

The purpose of this study was to compare the ability of the 24-2 test grid with that of the 24-2C test grid to measure visual field global indices, identify central visual field defects, and facilitate macular structure-function analysis with optical coherence tomography (OCT) scans in glaucoma suspects and glaucoma patients.

DESIGN

Prospective, cross-sectional study.

METHODS

One eye from each of 100 glaucoma suspects and glaucoma patients (60 undergoing SITA-Faster [Zeiss Meditec] testing on 24-2 and 24-2C; 40 undergoing SITA-Standard [Zeiss Meditec] testing on 24-2 and SITA-Faster on 24-2C) were included in the study. Global visual field indices, test duration, and pattern deviation results were extracted. The deviation map from the Cirrus OCT (Carl Zeiss Meditec) Ganglion Cell Analysis (GCA) was extracted, and structure-function relationships were compared after correction of the visual field test stimulus location that stimulated the corresponding retinal ganglion cell.

RESULTS

Global index results of the 24-2 grid were similar to those of the 24-2C grid, and both identified a comparable number of clusters of visual field defects. Centrally, the 24-2C grid identified more clusters of defects than the 24-2 grid, but this was not statistically significant. Although the 24-2C test locations resulted in more instances of structure-function concordance than the 24-2 locations, half the locations in the 24-2C grid fell close to or outside the GCA grid when corrected for ganglion cell displacement.

CONCLUSIONS

The 24-2C returned global visual field indices similar to the 24-2 grid but tended to identify more clusters of central functional defects. Central structure-function concordance was better achieved using the 24-2C grid, but half of the visual field test locations did not coincide with the commonly used macular thickness scan.

Custom extraction of macular ganglion cell-inner plexiform layer thickness more precisely co-localizes structural measurements with visual fields test grids

We aimed to evaluate methods of extracting optical coherence tomography (OCT)-derived macular ganglion cell-inner plexiform layer (GCIPL) thickness measurements over retinal locations corresponding to standard visual field (VF) test grids. A custom algorithm was developed to automatically extract GCIPL thickness measurements from locations corresponding to Humphrey Field Analyser 10-2 and 30-2 test grids over Goldmann II, III and V stimulus sizes from a healthy cohort of 478 participants. Differences between GCIPL thickness measurements based on VF test grids (VF-based paradigms) and the 8 × 8 grid, as per instrument review software, were analyzed, as were impacts of fovea to optic disc tilt and areas over which GCIPL thickness measurements were extracted. Significant differences between the VF-based paradigms and the 8 × 8 grid were observed at up to 55% of locations across the macula, with the greatest deviations at the fovea (median 25.5 μm, 95% CI 25.24–25.72 μm, P < .0001). While significant correlations with fovea to optic disc tilt were noted at up to 33% of locations distributed 6°–8° from the foveal center, there were no marked differences in GCIPL thickness measurements between VF-based paradigms using different stimulus sizes. As such, standard high-density OCT measurement paradigms do not adequately reflect GCIPL measurements at retinal locations tested with standard VF patterns, with the central macular region contributing most to the observed differences and with further correction required for fovea to optic disc tilt. Spatial direction of GCIPL thickness measurements will improve future comparisons of structure and function, thereby improving methods designed to detect pathology affecting the inner retina.

Revisiting the Drasdo Model: Implications for Structure-Function Analysis of the Macular Region

Purpose

To provide a consistent implementation of a retinal ganglion cell (RGC) displacement model proposed by Drasdo et al. for macular structure-function analysis, customizable by axial length (AL).

Methods

The effect of axial length on the shape of the inner retina was measured on 235 optical coherence tomography (OCT) scans from healthy eyes, to provide evidence for geometric scaling of structures with eye size. Following this assumption, we applied the Drasdo model to map perimetric stimuli on the radially displaced RGCs using two different methods: Method 1 only displaced the center of the stimuli; Method 2 applied the displacement to every point on the edge of the stimuli. We compared the accuracy of the two methods by calculating, for each stimulus, the number of expected RGC receptive fields and the number RGCs calculated from the histology map, expected to be equivalent. The same calculation was repeated on RGC density maps derived from 28 OCT scans from 28 young healthy subjects (age < 40 years) to confirm our results on clinically available measurements.

Results

The size of the retinal structures significantly increased with AL (P < 0.001) and was well predicted by geometric scaling. Method 1 systematically underestimated the RGC counts by as much as 60%. No bias was observed with Method 2.

Conclusions

The Drasdo model can effectively account for AL assuming geometric scaling. Method 2 should be used for structure-function analyses.

Translational Relevance

We developed a free web App in Shiny R to make our results available for researchers.

Immediate Impact of Acute Elevation of Intraocular Pressure on Cortical Visual Motion Processing

Purpose

To physiologically examine the impairment of cortical sensitivity to visual motion during acute elevation of intraocular pressure (IOP).

Methods

Motion processing in the cat brain is well characterized, its X and Y cell visual pathways being functionally analogous to parvocellular and magnocellular pathways in primates. Using this model, we performed ocular anterior chamber perfusion to reversibly elevate IOP over a range from 30 to 90 mm Hg while monitoring cortical activity with intrinsic signal optical imaging. Drifting random-dot fields and gratings were used to characterize cortical population responses to motion direction and orientation in early visual areas 17 and 18.

Results

We found that acute IOP elevations at 50 mm Hg and above, which is often observed in acute glaucoma, suppressed cortical motion direction responses. This suppression was more profound in area 17 than in area 18, and more profound in central than peripheral visual field (eccentricities 0°–4° vs. 4°–8°) within area 17. In addition, orientation responses were more suppressed than motion direction responses for the same IOP modulation.

Conclusions

In contrast to human chronic glaucoma that may cause greater dysfunction in large-cell magnocellular than in small-cell parvocellular visual pathways, our direct measurement of cortical processing networks implies that the small X-cell pathway shows greater vulnerability to acute IOP elevation than the large Y-cell pathway in visual motion processing. The results demonstrate that fine discrimination mechanisms for motion in the central visual field are particularly impacted by acute IOP attacks, suggesting a neural basis for immediate visual deficits in the fine motion perception of acute glaucoma patients.

Comparison of Thickness-Function and Vessel Density-Function Relationship in the Superior and Inferior Macula, and in the Superotemporal and Inferotemporal Peripapillary Sectors

PRéCIS:: In primary open-angle glaucoma (POAG), unlogged mean macular hemifield visual field sensitivity correlates significantly better with superficial capillary vessel density (VD) than with ganglion cell complex (GCC) thickness of the opposite macular hemifield.

PURPOSE

The aim of this study was to compare the relationship of the spatially corresponding superficial retinal capillary VD and retinal thickness parameters with the corresponding visual field sensitivity, for the superior and inferior macula, and the superotemporal and inferotemporal peripapillary sectors, respectively.

PATIENTS AND METHODS

One eye of 27 POAG, 14 ocular hypertensive, and 9 healthy participants were subjected to optical coherence tomography angiography imaging with the Angiovue optical coherence tomography and Octopus G2 perimetry on the same day. Superior and inferior unlogged hemifield average macular sensitivity was correlated with the opposite macular hemifield VD and GCC thickness, respectively. Correlation of visual field cluster unlogged average sensitivity with the spatially corresponding sector VD and sector retinal nerve fiber layer thickness were compared for the superotemporal and inferotemporal peripapillary sector, respectively.

RESULTS

For all participants and the glaucoma population, the correlations for macular hemifield GCC were strong or very strong (r: 0.554 to 0.737, P<0.01). In these groups, the correlations for macular hemifield VD were all very strong (r: 0.823 to 0.838, P<0.0001) and significantly higher than the corresponding correlations for hemifield GCC (P≤0.050). No significant difference between the corresponding correlations was found in the combined normal and ocular hypertensive group for the macular hemifields, or in either population for the peripapillary sectors.

CONCLUSION

Our results suggest that, in contrast to superotemporal and inferotemporal peripapillary sectors in which the thickness-function and VD-function relationships are similar, in POAG, for the macular hemifields, the VD-function relationship is stronger than the thickness-function relationship.

Artificial intelligence and deep learning in glaucoma: Current state and future prospects

Over the past few years, there has been an unprecedented and tremendous excitement for artificial intelligence (AI) research in the field of Ophthalmology; this has naturally been translated to glaucoma-a progressive optic neuropathy characterized by retinal ganglion cell axon loss and associated visual field defects. In this review, we aim to discuss how AI may have a unique opportunity to tackle the many challenges faced in the glaucoma clinic. This is because glaucoma remains poorly understood with difficulties in providing early diagnosis and prognosis accurately and in a timely fashion. In the short term, AI could also become a game changer by paving the way for the first cost-effective glaucoma screening campaigns. While there are undeniable technical and clinical challenges ahead, and more so than for other ophthalmic disorders whereby AI is already booming, we strongly believe that glaucoma specialists should embrace AI as a companion to their practice. Finally, this review will also remind ourselves that glaucoma is a complex group of disorders with a multitude of physiological manifestations that cannot yet be observed clinically. AI in glaucoma is here to stay, but it will not be the only tool to solve glaucoma.

Improving the Detection of Glaucoma and Its Progression: A Topographical Approach

Glaucoma is typically defined as a progressive optic neuropathy characterized by a specific (arcuate) pattern of visual field (VF) and anatomic changes. Therefore, we should be comparing arcuate patterns of damage seen on VFs with those seen on optical coherence tomography (OCT) maps. Instead, clinicians often use summary metrics such as VF pattern standard deviation, OCT retinal nerve fiber (RNF) global thickness, etc. There are 2 major impediments to topographically comparing patterns of damage on VF and OCT maps. First, until recently, it was not easy to make these comparisons with commercial reports. While recent reports do make it easier to compare VF and OCT maps, they have shortcomings. In particular, the 24-2 VF covers a larger retinal region than the commercial OCT scans, and, further, it is not easy to understand the topographical relationship among the different maps/plots within the current OCT reports. Here we show how a model of RNF bundles can overcome these problems. The second major impediment is the lack of a quantitative, and automated, method for comparing patterns of damage seen on VF and OCT maps. However, it is now possible to objectively and automatically quantify this agreement. Together, the RNF bundle model and the automated structure-function method should improve the power of topographical methods for detecting glaucoma and its progression. This should prove useful in clinical studies and trials, as well as for training and validating artificial intelligence/deep learning approaches for these purposes.

Defining glaucomatous optic neuropathy using objective criteria from structural and functional testing

BACKGROUND/AIMS

To identify objective criteria from optical coherence tomography (OCT) and perimetry that denote a useful, specific definition of glaucomatous optic neuropathy (GON) in eyes with open-angle glaucoma for comparisons among glaucoma research studies.

METHODS

A cross-sectional study of adult patients with glaucoma from nine centres on five continents evaluated de-identified physician diagnosis, OCT and perimetry results for 2580 eyes (1531 patients) in an online database. Each eye was graded by their glaucoma specialist as either definite, probable or not GON. Objective measures from OCT and perimetry, derived from an online consensus panel comprising 176 glaucoma specialists globally, were compared against the three diagnostic levels.

RESULTS

Diagnoses were 54% 'definite', 22% 'probable' and 24% 'not GON'. Using only OCT data or only field data had inadequate specificity (<90%). The best definitional choice for data from either the most recent or the preceding OCT/field pair had 77% sensitivity at 98% specificity and consisted of abnormal OCT superior or inferior nerve fibre layer quadrant with matching, opposite, abnormal Glaucoma Hemifield Test.

CONCLUSIONS

Objective criteria to define GON are practical and may be useful for comparisons among clinical studies to supplement subjective clinical assessment.

An Automated Method for Assessing Topographical Structure-Function Agreement in Abnormal Glaucomatous Regions

Purpose

To develop an automated/objective method for topographically comparing abnormal regions on optical coherence tomography (OCT) and visual field (VF) tests of eyes with early glaucoma.

Methods

A custom R program was developed that allows for both visualization and automatic assessment of the topographical agreement between functional (24-2 and/or 10-2 VF) and structural (widefield OCT retinal nerve fiber layer and/or retinal ganglion cell layer) deviation/probability maps. It was optimized using information from 98 eyes: 53 diagnosed as "definitely glaucoma" (DG) and 45 recruited as healthy (H) controls. Different pairs of abnormal VF (P <1%, <2%, <5%) and abnormal OCT (P <5%, <10%, <15%) criteria were evaluated. The percentages of abnormal structure-abnormal function (aS-aF) agreement found in DG eyes and nonagreement found in H eyes were used to define the optimal criteria and number of aS-aF locations for the detection of aS-aF agreement.

Results

A criterion of two aS-aF locations with "OCT <10% and VF <5%" on VF pattern deviation (PD) probability and OCT deviation/probability maps yielded high overall agreement (92%) with high aS-aF agreement for the DG eyes (89%) and high aS-aF nonagreement for the H eyes (95%). Total deviation probability maps achieved slightly lower performance than PD maps.

Conclusions

The method described here can automatically and objectively evaluate aS-aF agreement with a direct comparison of abnormal regions of function and structure.

Translational Relevance

As glaucoma diagnosis often involves assessing structure-function agreement, this technique can overcome subjectivity in this assessment.