The relationship between central visual field sensitivity and macular ganglion cell/inner plexiform layer thickness in glaucoma

A Novel Approach To Predict Glaucomatous Impairment in the Central 10° Visual Field, Excluding the Effect of Cataract

Purpose

Our previous study predicted genuine glaucomatous visual field (VF) impairment in the central 10° VF, excluding the effect of cataract, using visual acuity (VA) and global indexes of VF more accurately than pattern deviation (PD). This study aimed to improve the accuracy by using pointwise total deviation (TD) values with the machine-learning method of random forest model (RFM) and to investigate whether incorporating optical coherence tomography-measured ganglion cell-inner plexiform layer (GCIPL) thickness is useful.

Methods

This retrospective study included 89 eyes with open-angle glaucoma that underwent successful cataract surgery (with or without iStent implantation or ab interno trabeculotomy). Postoperative TD in each of the 68 VF points was predicted using preoperative (1) PD, (2) VA and VF with a linear regression model (LM), and (3) VA and VF with RFM, and averaged as predicted mean TD (mTDpost). Further prediction was made by incorporating the preoperative GCIPL into the best model.

Results

The mean absolute error (MAE) between the actual and predicted mTDpost with RFM (1.25 ± 1.03 dB) was significantly smaller than that with PD (3.20 ± 4.06 dB, p < 0.01) and LM (1.42 ± 1.06 dB, p < 0.05). The MAEs with the model incorporating GCIPL into RFM (1.24 ± 1.04 dB) and RFM were not significantly different.

Conclusions

Accurate prediction of genuine glaucomatous VF impairment was achieved using pointwise TD with RFM. No merit was observed by incorporating the GCIPL into this model.

Translational Relevance

This pointwise RFM could clinically reduce cataract effect on VF.

Comparison of the Circumpapillary Structure-Function and Vasculature-Function Relationships at Different Glaucoma Stages Using Longitudinal Data

Purpose

This study investigated the global and regional correlations between longitudinal structure-function (S-F) and vasculature-function (V-F) data using circumpapillary retinal nerve fiber layer thickness (cpRNFLT) measurements from optical coherence tomography (OCT), circumpapillary vessel density (cpVD) from OCT angiography (OCTA), and the corresponding visual field mean sensitivities at different glaucoma stages.

Methods

A total of 107 eyes from 107 glaucoma patients with progressive visual field (VF) changes followed up for an average of 3.33 ± 1.39 years were enrolled, including early-to-moderate (51 eyes) and advanced (56 eyes) stages. The rates of longitudinal change in the VF mean deviation (MD), cpRNFLT, and cpVD were evaluated using linear mixed-effects models and compared between different glaucoma stages. Longitudinal global and regional S-F and V-F relationships were assessed by repeated measures correlation analysis by glaucoma stage.

Results

No significant differences were found in the rates of VF MD and cpVD changes (P > 0.05) between the two glaucoma stage groups. CpRNFLT decreased more rapidly in the early-to-moderate stage group (P < 0.001) in which significant longitudinal global and regional correlations were found in both S-F and V-F relationships (all P < 0.05), except for the nasal sector. Significant global and regional correlations were only found in V-F relationship in advanced stage cases (all P < 0.05).

Conclusions

Significant longitudinal V-F relationships exist globally and regionally regardless of glaucoma stage but no longitudinal S-F relationship is present in advanced glaucoma. Longitudinal follow-up of cpVD parameters may be useful for monitoring glaucomatous VF progression at all disease stages.

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.

Association of macular vessel density and ganglion cell complex thickness with central visual field progression in glaucoma

BACKGROUND/AIMS

To evaluate the association of macular vessel density (VD) and ganglion cell complex (GCC) thickness with 10-2 central visual field (CVF) progression in glaucoma.

METHODS

In this retrospective cohort study, patients with glaucoma from Diagnostic Innovation in Glaucoma Study with≥five 10-2 visual field (VF) tests and 3-year follow-up before optical coherence tomography (OCT) and OCT angiography (OCTA) imaging were included. Whole-image GCC thickness (wiGCC) and superficial VD (wiVD) were obtained from 6*6 macula scans. The association of wiVD and wiGCC with past rate of 10-2 VF mean deviation worsening, and with past CVF progression (defined using clustered linear regression criteria) was evaluated using linear mixed models after adjusting for confounders.

RESULTS

From 238 eyes (141 patients), 25 eyes (11%) of 16 patients were CVF progressors. In the multivariable analysis of the association between OCT/OCTA parameters and past rate of 10-2 CVF worsening, lower wiVD (β=-0.04 (-0.05, -0.02); p<0.001; R2=0.32) and wiGCC (β=-0.01 (-0.01, 0.00); p=0.004; R2=0.21) were significantly associated with faster CVF worsening. For the association between OCT/OCTA parameters and past CVF progression, the multivariable analysis showed that a lower wiVD was significantly associated with increased odds of past CVF progression (OR=1.23 (1.06, 1.44) per 1% lower; p=0.008), while wiGCC did not show correlation.

CONCLUSIONS

Lower macular VD and GCC were associated with faster worsening of CVF, and lower macular VD was associated with increased odds of CVF progression. Assessment of macular OCT and OCTA may help detect glaucoma eyes with CVF progression.

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning

Purpose

Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).

Methods

This study included 1121 OCT volume scans and 10-2 VFs from 289 eyes (257 patients). Macular scans were used to estimate 10-2 VF mean deviation (MD), threshold sensitivities (TS), and total deviation (TD) values at 68 locations. A three-dimensional (3D) convolutional neural network based on the 3D DenseNet121 architecture was used for prediction. We compared DL predictions to those from baseline linear models. We carried out 10-fold stratified cross-validation to optimize generalizability. The performance of the DL and baseline models was compared based on correlations between ground truth and predicted VF measures and mean absolute error (MAE; ground truth - predicted values).

Results

Average (SD) MD was -9.3 (7.7) dB. Average (SD) correlations between predicted and ground truth MD and MD MAE were 0.74 (0.09) and 3.5 (0.4) dB, respectively. Estimation accuracy deteriorated with worsening MD. Average (SD) Pearson correlations between predicted and ground truth TS and MAEs for DL and baseline model were 0.71 (0.05) and 0.52 (0.05) (P < 0.001) and 6.5 (0.6) and 7.5 (0.5) dB (P < 0.001), respectively. For TD, correlation (SD) and MAE (SD) for DL and baseline models were 0.69 (0.02) and 0.48 (0.05) (P < 0.001) and 6.1 (0.5) and 7.8 (0.5) dB (P < 0.001), respectively.

Conclusions

Macular OCT volume scans can be used to predict global central VF parameters with clinically relevant accuracy.

Translational Relevance

Macular OCT imaging may be used to confirm and supplement central VF findings using deep learning.

Relationships of Macular Functional Impairment With Structural and Vascular Changes According to Glaucoma Severity

Purpose

To determine the pointwise relationships of central visual field (VF) defects with macular ganglion cell loss and macular vessel density (VD) loss during various stages of glaucoma.

Methods

Eyes with primary open-angle glaucoma (POAG) were subjected to optical coherence tomography (OCT) and OCT angiography (OCTA) to evaluate macular ganglion cell layer (GCL) thickness and macular VD in the superficial and deep vascular complexes (SVC and DVC). OCT, OCTA, and VF locations were matched after correcting for retinal ganglion cell (RGC) displacement. Pointwise correlations of GCL thickness and VDs of the SVC and DVC with central VF sensitivity (VFS) were evaluated by Pearson's correlation analysis and compared in eyes with early and advanced POAG by Meng's test.

Results

Of the 100 eyes, 52 and 48 were classified as early and advanced POAG. Macular VD showed overall better correlation with central VFS than GCL thickness in both the early and advanced groups. SVC density showed the strongest correlation with central VFS in all groups (R = 0.327 in early group, R = 0.325 in advanced group, all P < 0.001). Although DVC density showed better correlation with VFS (R = 0.311) than GCL thickness (R = 0.212) in the early group (P < 0.001), the correlation was comparable in the advanced group (R = 0.199 and 0.176, respectively, P = 0.254).

Conclusions

After adjustment for RGC displacement, macular SVC density was better correlated with central VFS than macular GCL thickness in both early and advanced POAG. Macular DVC density showed better correlation with VFS than GCL thickness in early but not in advanced POAG, indicating that DVC loss may be involved in early central VF loss.

Relationship between the Macular Microvasculature and Central Visual Field Sensitivity in Patients with Advanced Glaucoma

PURPOSE

To evaluate the relationship between central visual field sensitivity (cVFS) and the structural parameters in patients with advanced glaucoma.

DESIGN

Cross-sectional study.

METHODS

In total, 226 eyes of 226 patients with advanced glaucoma were classified into the "minor central defect" (mean deviation on 10-2 visual field test [MD10] > -10 dB) and "significant central defect" (MD10 ≤ -10 dB) groups. We examined the structural parameters using RTVue OCT and angiography, including the retinal nerve fiber layer, ganglion cell complex, peripapillary vessel density (VD), and superficial and deep macular VD (mVD). The assessment of cVFS included MD10 and the mean deviation of the central 16 points on the 10-2 VF test (MD16). We used Pearson correlation and segmented regression to assess the global and regional relationships between the structural parameters and cVFS.

MAIN OUTCOME MEASURES

Correlation between structural parameters and cVFS.

RESULTS

In the minor central defect group, the best global correlations existed between the superficial macular and parafoveal mVD and MD16 (r = 0.52 and 0.54, P < 0.001). In the significant central defect group, superficial mVD best correlated with MD10 (r = 0.47, P < 0.001). Segmented regression between superficial mVD and cVFS revealed no breakpoint was found as MD10 declined, but a breakpoint was identified at -5.95 dB for MD16, which was statistically significant (P < 0.001). The regional correlations between the grid VD and sectors of the central 16 points were significant (r = 0.20-0.53, P= 0.010 ∼P < 0.001).

CONCLUSIONS

The fair global and regional relationships between mVD and cVFS suggest that mVD may be beneficial for monitoring cVFS in patients with advanced glaucoma.

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Association Between Longitudinal 10-2 Central Visual Field Change and the Risk of Visual Acuity Loss in Mild-to-Moderate Glaucoma

PRCIS

Faster worsening of 10-2 visual field (VF) was associated with the development of visual acuity (VA) loss in mild-to-moderate glaucoma, suggesting longitudinal 10-2 VF change is associated with the risk of VA impairment.

PURPOSE

To examine whether longitudinal 10-2 central VF change is associated with the risk of VA loss in glaucoma.

PATIENTS AND METHODS

Primary open angle glaucoma and glaucoma suspect eyes with ≥3 years and 5 visits of 10-2 VF examinations were included. Cox proportional hazard modeling with shared frailty was used to evaluate the hazard ratio (HR) of 10-2 VF mean deviation (MD), superior hemifield mean sensitivity (hemi-MS), and inferior hemi-MS worsening rates for developing VA loss, defined as a change in logMAR VA ≥95% test-retest variability.

RESULTS

Among the 252 eyes (148 participants, mean follow-up = 5.8 y), 30 eyes (21 participants, mean follow-up = 4.9 y) developed VA loss. There was no difference in baseline VF between eyes with and without VA loss ( P > 0.05). Eyes with VA loss showed faster 10-2 VF MD worsening [-0.39 (95% CI: -0.60, -0.18) dB/y] and hemi-MS decrease (range: -0.42~-0.38 dB/y), as compared with no-VA loss eyes [10-2 VF MD change = -0.11 (-0.16, -0.07) dB/y; hemi-MS change: -0.12~-0.07 dB/y; P < 0.05]. In the multivariable model, faster 10-2 VF MD worsening [HR (95% CI) = 4.05 (1.61, 10.22), per 1 dB/y faster], superior hemi-MS decrease [HR (95% CI) = 7.07 (2.48, 20.14), per 1 dB/y faster], and inferior hemi-MS decrease [HR (95% CI) = 8.32 (1.99, 34.91), per 1 dB/y faster] were all associated with increased risk of developing VA loss ( P < 0.05).

CONCLUSIONS

Faster 10-2 VF MD and hemifield MS worsening are associated with the development of VA loss. Monitoring the longitudinal central 10-degree VF change may suggest that there is impending VA impairment in glaucoma.

Segmentation-Free OCT-Volume-Based Deep Learning Model Improves Pointwise Visual Field Sensitivity Estimation

Purpose

The structural changes measured by optical coherence tomography (OCT) are related to functional changes in visual fields (VFs). This study aims to accurately assess the structure-function relationship and overcome the challenges brought by the minimal measurable level (floor effect) of segmentation-dependent OCT measurements commonly used in prior studies.

Methods

We developed a deep learning model to estimate the functional performance directly from three-dimensional (3D) OCT volumes and compared it to the model trained with segmentation-dependent two-dimensional (2D) OCT thickness maps. Moreover, we proposed a gradient loss to utilize the spatial information of VFs.

Results

Our 3D model was significantly better than the 2D model both globally and pointwise regarding both mean absolute error (MAE = 3.11 + 3.54 vs. 3.47 ± 3.75 dB, P < 0.001) and Pearson's correlation coefficient (0.80 vs. 0.75, P < 0.001). On a subset of test data with floor effects, the 3D model showed less influence from floor effects than the 2D model (MAE = 5.24 ± 3.99 vs. 6.34 ± 4.58 dB, P < 0.001, and correlation 0.83 vs. 0.74, P < 0.001). The gradient loss improved the estimation error for low-sensitivity values. Furthermore, our 3D model outperformed all prior studies.

Conclusions

By providing a better quantitative model to encapsulate the structure-function relationship more accurately, our method may help deriving VF test surrogates.

Translational Relevance

DL-based VF surrogates not only benefit patients by reducing the testing time of VFs but also allow clinicians to make clinical judgments without the inherent limitations of VFs.

Deep learning approaches to predict 10-2 visual field from wide-field swept-source optical coherence tomography en face images in glaucoma

Close monitoring of central visual field (VF) defects with 10-2 VF helps prevent blindness in glaucoma. We aimed to develop a deep learning model to predict 10-2 VF from wide-field swept-source optical coherence tomography (SS-OCT) images. Macular ganglion cell/inner plexiform layer thickness maps with either wide-field en face images (en face model) or retinal nerve fiber layer thickness maps (RNFLT model) were extracted, combined, and preprocessed. Inception-ResNet-V2 was trained to predict 10-2 VF from combined images. Estimation performance was evaluated using mean absolute error (MAE) between actual and predicted threshold values, and the two models were compared with different input data. The training dataset comprised paired 10-2 VF and SS-OCT images of 3,025 eyes of 1,612 participants and the test dataset of 337 eyes of 186 participants. Global prediction errors (MAE_point-wise) were 3.10 and 3.17 dB for the en face and RNFLT models, respectively. The en face model performed better than the RNFLT model in superonasal and inferonasal sectors (P = 0.011 and P = 0.030). Prediction errors were smaller in the inferior versus superior hemifields for both models. The deep learning model effectively predicted 10-2 VF from wide-field SS-OCT images and might help clinicians efficiently individualize the frequency of 10-2 VF in clinical practice.

Macular sector-wise decision tree model for the prediction of parafoveal scotoma not detected by 24-2 visual field test

BACKGROUND

Development of a macular sector-wise decision tree model (DTM) for the prediction of parafoveal scotoma.

METHODS

This prospective study enrolled 126 patients with early-stage open-angle glaucoma (mean deviation ≥-6 decibels) without the signs of parafoveal scotoma on the 24-2 visual field (VF) test (i.e., any abnormalities at the four innermost points). Based on the central 36 points of the 10-2 pattern deviation plot, patients were classified as being with or without 10-2 parafoveal scotoma. For the discrimination of patients from those without 10-2 parafoveal scotoma, a macular ganglion cell-inner plexiform layer (mGCIPL) sector-wise DTM analysis was performed.

RESULTS

Among 126 eyes without 24-2 parafoveal scotoma, 10-2 parafoveal scotoma was detected in 77 (61.1%) eyes. The balanced accuracy of DTM was best in the inferotemporal sector (0.9286; 95% CI, 0.7458-0.9697) and worst in the inferior sector (0.8373; 0.6484-0.9204). DTM revealed that even in the absence of VF abnormalities at the innermost 4 points on the 24-2 test, (1) 10-2 parafoveal scotoma should be strongly suspected when the adjacent 24-2 perifoveal point in the correlated sector is abnormal; (2) if the 24-2 perifoveal point is normal, and if the probability colour codes of the correlated mGCIPL sector are green, the probability of 10-2 parafoveal scotoma is very low.

CONCLUSIONS

In clinical practice, the evaluation of the 24-2 perifoveal test points along with the probability colour codes of mGCIPL can be a useful decision-support tool in determining whether 10-2 tests are needed for a given patient.

Comparison of the Structure-Function Relationship Between Advanced Primary Open Angle Glaucoma and Normal Tension Glaucoma

PURPOSE

The aim was to investigate and compare the characteristics of visual field (VF) defects in primary open angle glaucoma (POAG) and normal-tension glaucoma (NTG) with advanced glaucomatous damage and to determine whether the structure-function relationships found in advanced glaucoma differ based on their glaucoma classification.

PATIENTS AND METHODS

Ninety-seven eyes of 97 patients (59 eyes with POAG and 38 eyes with NTG) with advanced glaucoma were included in this cross-sectional study. Scores at each test point of the 30-2 VF total deviation map were recorded, and average values at each test point were point-wise compared between the groups. Peripapillary retinal nerve fiber layer (RNFL) and macular thickness (total, RNFL, ganglion cell layer, and inner plexiform layer thickness) were measured. The structure-function relationship based on the map of Garway-Heath was determined and compared between the 2 groups.

RESULTS

At advanced stage of glaucoma, POAG eyes demonstrated more diffusely distributed VF defects, whereas NTG eyes had more severe VF defects at the superior nasal quadrant, showing increased asymmetry. Overall, peripapillary RNFL, macular ganglion cell layer, and macular inner plexiform layer thickness showed good relationships with 30-2 VF parameters in both groups. However, in total macula and macular RNFL thickness, the structure-function relationships tended to show different characteristics depending on the glaucoma classification; NTG eyes showed overall better relationships.

CONCLUSIONS

In advanced glaucoma, differences in patterns of VF damage were found between POAG and NTG eyes. Conventional peripapillary RNFL and macular measurements showed generally good performance for estimating functional status, particularly in NTG eyes.

Elucidating macular structure-function correlations in glaucoma

Correlation between structural data from optical coherence tomography and functional data from the visual field may be suboptimal because of poor mapping of OCT measurement locations to VF stimuli. We tested the hypothesis that stronger structure–function correlations in the macula can be achieved with fundus-tracking perimetery, by precisely mapping OCT measurements to VF sensitivity at the same location. The conventional 64 superpixel (3° × 3°) OCT grid was mapped to VF sensitivities averaged in 40 corresponding VF units with standard automated perimetry (conventional mapped approach, CMA) in 38 glaucoma patients and 10 healthy subjects. Similarly, a 144 superpixel (2° × 2°) OCT grid was mapped to each of the 68 locations with fundus-tracking perimetry (localized mapped approach, LMA). For each approach, the correlation between sensitivity at each VF unit and OCT superpixel was computed. Vector maps showing the maximum correlation between each VF unit and OCT pixel was generated. CMA yielded significantly higher structure–function correlations compared to LMA. Only 20% of the vectors with CMA and < 5% with LMA were within corresponding mapped OCT superpixels, while most were directed towards loci with structural damage. Measurement variability and patterns of structural damage more likely impact correlations compared to precise mapping of VF stimuli.

Predicting Visual Fields From Optical Coherence Tomography via an Ensemble of Deep Representation Learners

PURPOSE

To develop and validate a deep learning method of predicting visual function from spectral domain optical coherence tomography (SD-OCT)-derived retinal nerve fiber layer thickness (RNFLT) measurements and corresponding SD-OCT images.

DESIGN

Development and evaluation of diagnostic technology.

METHODS

Two deep learning ensemble models to predict pointwise VF sensitivity from SD-OCT images (model 1: RNFLT profile only; model 2: RNFLT profile plus SD-OCT image) and 2 reference models were developed. All models were tested in an independent test-retest data set comprising 2181 SD-OCT/VF pairs; the median of ∼10 VFs per eye was taken as the best available estimate (BAE) of the true VF. The performance of single VFs predicting the BAE VF was also evaluated. The training data set comprised 954 eyes of 220 healthy and 332 glaucomatous participants, and the test data set, 144 eyes of 72 glaucomatous participants. The main outcome measures included the pointwise prediction mean error (ME), mean absolute error (MAE), and correlation of predictions with the BAE VF sensitivity.

RESULTS

The median mean deviation was -4.17 dB (-14.22 to 0.88). Model 2 had excellent accuracy (ME 0.5 dB, SD 0.8) and overall performance (MAE 2.3 dB, SD 3.1), and significantly (paired t test) outperformed the other methods. For single VFs predicting the BAE VF, the pointwise MAE was 1.5 dB (SD 0.7). The association between SD-OCT and single VF predictions of the BAE pointwise VF sensitivities was R² = 0.78 and R² = 0.88, respectively.

CONCLUSIONS

Our method outperformed standard statistical and deep learning approaches. Predictions of BAEs from OCT images approached the accuracy of single real VF estimates of the BAE.

Identifying the Retinal Layers Linked to Human Contrast Sensitivity Via Deep Learning

Purpose

Luminance contrast is the fundamental building block of human spatial vision. Therefore contrast sensitivity, the reciprocal of contrast threshold required for target detection, has been a barometer of human visual function. Although retinal ganglion cells (RGCs) are known to be involved in contrast coding, it still remains unknown whether the retinal layers containing RGCs are linked to a person's contrast sensitivity (e.g., Pelli-Robson contrast sensitivity) and, if so, to what extent the retinal layers are related to behavioral contrast sensitivity. Thus the current study aims to identify the retinal layers and features critical for predicting a person's contrast sensitivity via deep learning.

Methods

Data were collected from 225 subjects including individuals with either glaucoma, age-related macular degeneration, or normal vision. A deep convolutional neural network trained to predict a person's Pelli-Robson contrast sensitivity from structural retinal images measured with optical coherence tomography was used. Then, activation maps that represent the critical features learned by the network for the output prediction were computed.

Results

The thickness of both ganglion cell and inner plexiform layers, reflecting RGC counts, were found to be significantly correlated with contrast sensitivity (r = 0.26 ∼ 0.58, Ps < 0.001 for different eccentricities). Importantly, the results showed that retinal layers containing RGCs were the critical features the network uses to predict a person's contrast sensitivity (an average R2 = 0.36 ± 0.10).

Conclusions

The findings confirmed the structure and function relationship for contrast sensitivity while highlighting the role of RGC density for human contrast sensitivity.

High-Pass Visual Acuity Loss and Macular Structure-Function Relationship in Patients With Primary Open-Angle Glaucoma

Purpose

The Logarithm of the Minimum Angle of Resolution (logMAR) chart is the most common clinical test for assessing central visual function in glaucoma. However, based on the use of these charts, visual acuity (VA) often remains normal even when severe macular damage exists. Here, we aim to investigate the potential advantages of high-pass VA in detecting glaucoma compared with conventional VA.

Methods

Monocular best-corrected VA measurements were compared for a novel high-pass electronic VA chart (e-chart) and a conventional e-chart in 113 primary open-angle glaucoma (POAG) patients with normal logMAR VA and 65 age-similar healthy controls. One hundred thirty-nine POAG patients underwent spectral-domain optical coherence tomography (SD-OCT) for measurement of macular ganglion cell layer plus inner plexiform layer (GCL+IPL) thickness. Structure-function relationships between OCT measurements and the two VAs were compared. The enrolled eyes were divided into two groups for further analyses according to macular visual field (MVF) defects, specifically two or more adjacent abnormal points within the 12 central sites of 30-2 VF.

Results

The mean deviation (MD) of 30-2 VF test was -12.77 ± 7.47 dB for glaucoma group and -1.70 ± 1.12 dB for control group. The mean difference of the two VAs was slightly larger in glaucoma group (0.29 logMAR) than in control group (0.22 logMAR). The area under the receiver operating characteristic curve of the high-pass e-chart was larger than that of conventional e-chart (0.917 vs. 0.757, P < 0.001). Significant correlations between high-pass VA and GCL+IPL thickness were found only in the MVF-damaged group. Compared with conventional VA, high-pass VA demonstrates stronger correlations with nasal-side macular GCL+IPL thickness (Fisher's Z-test, two-tailed, P2mmin diameter = 0.033 and P3mmin diameter = 0.005).

Conclusions

Compared with conventional VA, high-pass VA displays slightly higher sensitivity to visual loss in glaucoma and has a stronger correlation with the nasal-side macular GCL+IPL thickness.

Translational Relevance

The high-pass acuity test has the potential to be used as an ancillary tool to monitor glaucoma over time.

Estimating Ganglion Cell Complex Rates of Change With Bayesian Hierarchical Models

Purpose

Develop a hierarchical longitudinal regression model for estimating local rates of change of macular ganglion cell complex (GCC) measurements with optical coherence tomography (OCT).

Methods

We enrolled 112 eyes with four or more macular OCT images and ≥2 years of follow-up. GCC thickness measurements within central 6 × 6 superpixels were extracted from macular volume scans. We fit data from each superpixel separately with several hierarchical Bayesian random-effects models. Models were compared with the Watanabe–Akaike information criterion. For our preferred model, we estimated population and individual slopes and intercepts (baseline thickness) and their correlation.

Results

Mean (SD) follow-up time and median (interquartile range) baseline 24-2 visual field mean deviation were 3.6 (0.4) years and −6.8 (−12.2 to −4.3) dB, respectively. The random intercepts and slopes model with random residual variance was the preferred model. While more individual and population negative slopes were observed in the paracentral and papillomacular superpixels, superpixels in the superotemporal and inferior regions displayed the highest correlation between baseline thickness and rates of change (r = –0.43 to –0.50 for the top five correlations).

Conclusions

A Bayesian linear hierarchical model with random intercepts/slopes and random variances is an optimal initial model for estimating GCC slopes at population and individual levels. This novel model is an efficient method for estimating macular rates of change and probability of glaucoma progression locally.

Translational Relevance

The proposed Bayesian hierarchical model can be applied to various macular outcomes from different OCT devices and to superpixels of variable sizes to estimate local rates of change and progression probability.

Higher contrast thresholds for vanishing optotype recognition in macular visual fields among glaucoma patients: a structure-function analysis

BACKGROUND/AIMS

We aimed to explore the impact of glaucomatous macular damage, specifically retinal ganglion cell (RGC) loss, on macular pattern vision measured by the vanishing optotype (VO) recognition contrast threshold.

METHODS

Seventy-two patients (mean age, 33.51±7.05 years) with primary open-angle glaucoma and 36 healthy controls (mean age, 30.25±6.70 years) were enrolled. VO recognition contrast thresholds of each participant were measured at the 16 preset test locations covering the central 5° visual field (VF). Macular sensitivity (MS) was tested by macular threshold test of Humphrey Field Analyzer. Macular RGC plus inner plexiform layer (GCIPL) thickness was also measured by spectral domain optical coherence tomography.

RESULTS

The VO contrast threshold demonstrated weak-to-moderate correlations (rho=-0.275 to -0.653) with MS (p<0.001). There was a significantly higher VO contrast threshold in glaucoma group (p<0.0001). At similar levels of MS, patients with glaucoma with GCIPL damage showed remarkably higher VO contrast thresholds than those with preserved GCIPL (p=0.0079). The structure-function relationships between VO contrast threshold and GCIPL thickness (rho=-0.725 to -0.802) were remarkably stronger than those between MS and GCIPL thickness (rho=0.210 to 0.448). VO contrast threshold showed stronger correlation with average GCIPL thickness (rho=-0.362 to -0.778) than MS (rho=0.238 to 0.398) at multiple test locations in glaucoma group.

CONCLUSIONS

Glaucomatous eyes have higher contrast thresholds for VO recognition in fovea-around VF. Stronger structure-function relationships indicate that VO contrast threshold is more vulnerable to RGC damage.

Characterizing and quantifying the temporal relationship between structural and functional change in glaucoma

PURPOSE

To characterize and quantify the temporal relationship between structural and functional change in glaucoma.

METHODS

120 eyes of 120 patients with ocular hypertension or primary open-angle glaucoma were selected from the Diagnostic Innovations in Glaucoma Study or the African Descent and Glaucoma Evaluation Study. Patients had 11 visits, separated by at least 3 months over 5 to 10 years. Each visit had rim area (RA) and mean sensitivity (MS) measurements taken within a 30-day period. The structure-function (SF) relationship was summarized using conventional and modified cross-correlation functions (CCFs), which identified the strongest absolute and positive correlation, respectively. Patients were categorized in one of the following three groups: RA and MS evolved simultaneously (lag = 0), RA preceded MS (lag<0), and MS preceded RA (lag>0). Lagging regression analysis was used to examine the variations of the SF relationship within groups.

RESULTS

The number of participants, mean visit lag, and mean correlation (standard deviation) were, for the conventional and modified CCFs, respectively: lag = 0 [16, 0, 0.53 (0.10) and 16, 0, 0.46 (0.11)]; lag<0 [50, -2.94, 0.51 (0.11) and 55, -3.45, 0.44 (0.12)], and lag>0 [54, 3.35, 0.53 (0.13) and 49, 3.78, 0.45 (0.12)]. A significant difference of the visit lag relation within groups was identified using lagging regression analysis (p<0.0001).

CONCLUSIONS

The strongest relationship between structure and function was obtained at different visit lags in different patients. This finding also suggests that the SF relationship should be addressed at the subject level when using both measurements jointly to model glaucoma progression.

A Novel Stimulus to Improve Perimetric Sampling within the Macula in Patients with Glaucoma

SIGNIFICANCE

Identifying glaucomatous damage to the macula has become important for diagnosing and managing patients with glaucoma. In this study, we presented an approach that provides better perimetric sampling for the macular region, by testing four locations, with a good structure-function agreement.

PURPOSE

We previously presented a basis for customizing perimetric locations within the macula. In this study, we aimed to improve perimetric sampling within the macula by presenting a stimulus at four locations, with maintaining a good structure-function agreement.

METHODS

We tested one eye each of 30 patients (aged 50 to 88 years). Patients were selected based on observed structural damage to the macula, whereas perimetric defect (using 24-2) did not reflect the locations and extent of this damage. We used en face images to visualize retinal nerve fiber bundle defects. To measure perimetric sensitivities, we used a blob stimulus (standard deviation of 0.25°) at the 10-2 locations. A perimetric defect for a location was defined as any value equal to or deeper than -4, -5, and -6 dB below the mean sensitivity for 37 age-similar controls (aged 47 to 78 years). We also presented an elongated sinusoidal stimulus for 20 patients at four locations within the macula, in which we defined a perimetric defect as any value below the 2.5th percentile from controls.

RESULTS

The -4, -5, and -6 dB criteria identified perimetric defects in 14, 13, and 11 patients, respectively. When testing with the elongated stimulus, 18 patients were identified with perimetric defect. The perimetric defects were consistent with the structural damage.

CONCLUSIONS

The elongated stimulus showed a good structure-function agreement with only four testing locations as compared with 68 locations used with the blob stimulus. This demonstrates a clinical potential for this new stimulus in the next generation of perimetry.

Comparison of the Humphrey Field Analyzer and Photopic Negative Response of Focal Macular Electroretinograms in the Evaluation of the Relationship Between Macula Structure and Function

Purpose: To investigate the association between macular inner retinal layer thickness and macula visual field (VF) mean deviation as measured by the Humphrey Field Analyzer (HFA) or macular function as measured by focal macular electroretinograms (ERGs) in patients with glaucoma.

Methods: The participants in this cross-sectional study were 71 patients with glaucoma and 10 healthy controls. Macular inner retinal layer thickness and function were measured in all participants using optical coherence tomography (OCT) and HFA or focal macular ERGs, respectively. Macular OCT images were segmented into the macular retinal nerve fiber layer (mRNFL), macular ganglion cell layer/inner plexiform layer (GCL/IPL), and ganglion cell complex (GCC). Spearman correlation analysis was used to assess the relationship between macular inner retinal layer thickness and function.

Results: Focal macular ERGs were composed of a negative wave (N1), a positive wave (P1), and a slow negative wave (N2). The N2 response density was significantly reduced in eyes with glaucoma, and was significantly associated with the thickness of the mRNFL (R = 0.317), GCL/IPL (R = 0.372), or GCC (R = 0.367). The observed structure–function relationship was also significantly correlated with the HFA VF mean deviation for each thickness [mRNFL (R = 0.728), GCL/IPL (R = 0.603), or GCC (R = 0.754)].

Conclusions: Although a significant correlation was found between the N2 response density and the thickness of the macular inner layer, the observed structure–function relationship with the mean deviation of the HFA VF was higher than that of the N2 response density.

Macular imaging with optical coherence tomography in glaucoma

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

Comparing Structure-Function Relationships Based on Drasdo's and Sjöstrand's Retinal Ganglion Cell Displacement Models

Purpose

To compare structure-function relationships based on the Drasdo and Sjöstrand retinal ganglion cell displacement models.

Methods

Single eyes from 305 patients with glaucoma and 55 heathy participants were included in this multicenter, cross-sectional study. The ganglion cell and inner plexiform layer (GCIPL) thickness was measured using spectral domain optical coherence tomography. Visual field measurements were performed using the Humphrey 10-2 test. All A-scan pixels (128 × 512 pixels) were allocated to the closest 10-2 location with both displacement models using degree and millimeter scales. Structure-function relationships were investigated between GCIPL thickness and corresponding visual sensitivity in nonlong (160 eyes) and long (200 eyes) axial length (AL) groups.

Results

In both the nonlong and long AL groups, compared with the no-displacement model, both the Drasdo and the Sjöstrand models showed that the structure-function relationship around the fovea improved (P < 0.05). The magnitude of improvement in the area was either comparable between the model or was larger for the Drasdo model than the Sjöstrand model (P < 0.05). Meanwhile, structure-function relationships outside the innermost retinal region that were based on the Drasdo and Sjöstrand models were comparable to or were even worse than (in the case of the Drasdo model) those obtained using the no-displacement model.

Conclusions

Structure-function relationships evaluated based on both the Drasdo and Sjöstrand models significantly improved around the fovea, particularly when using the Drasdo model. This was not the case in other areas.

Associations of Ganglion Cell-Inner Plexiform Layer and Optic Nerve Head Parameters with Visual Field Sensitivity in Advanced Glaucoma

PURPOSE

To evaluate the associations of optical coherence tomography (OCT)-derived macular ganglion cell-inner plexiform layer thickness (mGCIPLT), circumpapillary retinal nerve fiber layer thickness (cpRNFLT), and optic nerve head (ONH) parameters with visual field (VF) sensitivity in advanced glaucoma.

METHODS

In this cross-sectional study, 102 eyes from 102 patients with advanced glaucoma (defined as a 24-2 VF mean deviation (MD) of ≤-12 dB) were included. mGCIPLT, cpRNFLT, and ONH parameters (including the rim area, average cup-to-disc [C:D] ratio, and vertical C:D ratio) were measured using Cirrus high-definition OCT, and 24-2 and 10-2 VF sensitivity tests were performed using standard automated perimetry. Pearson correlations and linear models were used to analyze relationships between OCT-derived parameters and VF parameters.

RESULTS

The mGCIPLT and rim area were significantly positively correlated with the 24-2 VF MD, 24-2 VF pattern standard deviation, 24-2 VF visual field index, and 10-2 VF MD, but cpRNFLT was not significantly correlated with VF parameters. In addition, the average and vertical C:D ratios were significantly negatively correlated with VF parameters. The mGCIPLT and rim area were significantly positively correlated with the 10-2 VF MD (r ranging between 0.542 and 0.621, p < 0.001), while the average and vertical C:D ratios were significantly negatively correlated with the 10-2 VF MD (r = -0.537, p < 0.001, and r = -0.428, p < 0.001, respectively). Each 1-µm change in the average mGCIPLT was associated with an approximately 0.368-dB change in the 24-2 VF MD and 0.677-dB change in the 10-2 VF MD (R2 = 0.268, p < 0.001, and R2 = 0.385, p < 0.001, respectively). The 10-2 VF MD showed a significantly stronger association with inferonasal mGCIPLT than did the 24-2 VF MD in advanced glaucoma (p = 0.007).

CONCLUSIONS

mGCIPLT and ONH parameters were associated with the severity of VF damage and reflected functional damage better than cpRNFLT in advanced glaucoma. Our results suggested that structural measurements of mGCIPLT and ONH parameters and functional measurement of the 10-2 VF may be useful for monitoring progression in advanced glaucoma.

A deep learning approach to predict visual field using optical coherence tomography

We developed a deep learning architecture based on Inception V3 to predict visual field using optical coherence tomography (OCT) imaging and evaluated its performance. Two OCT images, macular ganglion cell-inner plexiform layer (mGCIPL) and peripapillary retinal nerve fibre layer (pRNFL) thicknesses, were acquired and combined. A convolutional neural network architecture was constructed to predict visual field using this combined OCT image. The root mean square error (RMSE) between the actual and predicted visual fields was calculated to evaluate the performance. Globally (the entire visual field area), the RMSE for all patients was 4.79 ± 2.56 dB, with 3.27 dB and 5.27 dB for the normal and glaucoma groups, respectively. The RMSE of the macular region (4.40 dB) was higher than that of the peripheral region (4.29 dB) for all subjects. In normal subjects, the RMSE of the macular region (2.45 dB) was significantly lower than that of the peripheral region (3.11 dB), whereas in glaucoma subjects, the RMSE was higher (5.62 dB versus 5.03 dB, respectively). The deep learning method effectively predicted the visual field 24-2 using the combined OCT image. This method may help clinicians determine visual fields, particularly for patients who are unable to undergo a physical visual field exam.

Comparisons of retinal vessel density and glaucomatous parameters in optical coherence tomography angiography

PURPOSE

To compare the retinal vessel density and glaucomatous parameters in primary angle closure glaucoma (PACG), to evaluate the diagnostic and monitoring abilities of the peripapillary and macular vessel density in the progression of glaucoma.

METHODS

This was a observational, prospective and cross-sectional study. According to Glaucoma Staging System, 218 eyes (116 participants) were divided into 5 groups: no glaucoma, early glaucoma, moderate glaucoma, advance glaucoma, severe glaucoma. All participants underwent a comprehensive ocular examination, which included corrected distance visual acuity measurement, slit-lamp biomicroscopy, intra ocular pressure (IOP), gonioscopy, fundus examination, stereoscopic optic disc photography, Humphrey visual field test(VF), peripapillary and macular optical coherence tomography angiography(OCTA) scan. SPSS software was used to calculate and compare retinal vessel density (peripapillary vessel density, PVD and macular vessel density, MVD) and glaucomatous parameters (mean deviation (MD),pattern standard deviation(PSD), retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer(GCIPL),rim area, average cup/disc(C/D) ratio).

RESULTS

The GCIPL thickness, RNFL thickness, PVD and MVD are significantly reduced in PACG. There were significant differences in all measurements among the groups (P<0.01).Reduced peripapillary and macular vessel density in glaucoma were detected and a statistically significant correlation with glaucoma stages (P<0.01). In addition, the results of retinal vessel density, reduced RNFL thickness and GCIPL thickness were also statistically related to the stage of glaucoma. As expected, the rim area was significantly smaller with higher C/D area ratios in glaucomatous eyes corresponding to the severity of disease.

CONCLUSIONS

The changes of PVD and MVD had strongly positive correlation with GCIPL thickness and RNFL thickness, had negative correlation with the severity of glaucoma, which meant the more severe the glaucoma was, the lower PVD and MVD were. Compared to traditional glaucoma staging system judged by VF, the changes of PVD and MVD obtained by OCTA might be a new method to grade the stage of glaucoma. These findings theorize that the changes of PVD and MVD may be better facilitated for the observation and monitoring of glaucoma progression.

Artificial Intelligence Mapping of Structure to Function in Glaucoma

Purpose

To develop an artificial intelligence (AI)-based structure-function (SF) map relating retinal nerve fiber layer (RNFL) damage on spectral domain optical coherence tomography (SDOCT) to functional loss on standard automated perimetry (SAP).

Methods

The study included 26,499 pairs of SAP and SDOCT from 15,173 eyes of 8878 patients with glaucoma or suspected of having the disease extracted from the Duke Glaucoma Registry. The data set was randomly divided at the patient level in training and test sets. A convolutional neural network (CNN) was initially trained and validated to predict the 52 sensitivity threshold points of the 24-2 SAP from the 768 RNFL thickness points of the SDOCT peripapillary scan. Simulated localized RNFL defects of varied locations and depths were created by modifying the normal average peripapillary RNFL profile. The simulated profiles were then fed to the previously trained CNN, and the topographic SF relationships between structural defects and SAP functional losses were investigated.

Results

The CNN predictions had an average correlation coefficient of 0.60 (P < 0.001) with the measured values from SAP and a mean absolute error of 4.25 dB. Simulated RNFL defects led to well-defined arcuate or paracentral visual field losses in the opposite hemifield, which varied according to the location and depth of the simulations.

Conclusions

A CNN was capable of predicting SAP sensitivity thresholds from SDOCT RNFL thickness measurements and generate an SF map from simulated defects.

Translational Relevance

AI-based SF map improves the understanding of how SDOCT losses translate into detectable SAP damage.

Longitudinal Macular Structure-Function Relationships in Glaucoma

PURPOSE

To investigate the relationship between longitudinal changes in macular thickness measurements from OCT and changes in central visual field (VF) in patients with glaucoma with central or advanced damage at baseline.

DESIGN

Longitudinal cohort study.

PARTICIPANTS

A total of 116 eyes with ≥3 years of follow-up and ≥5 macular OCT images and central 10° VF tests were selected.

METHODS

OCT superpixels and VF locations were matched correcting for retinal ganglion cell (RGC) displacement. Superpixel thickness and VF total deviation (TD) values, in both logarithmic and linear scales, were averaged within 3 eccentricities (3.4°, 5.6°, and 6.8°) and superior and inferior hemiretinas and hemifields. We estimated pointwise TD rates of change and rates of change at superpixels for full macular thickness (FMT), ganglion cell complex (GCC), ganglion cell inner plexiform layer (GCIPL), and ganglion cell layer (GCL). Correlation of structure-function (SF) rates of change was investigated with parametric tests. We compared the proportion of worsening and positive slopes for superpixels and VF test locations (negative vs. positive rates of change with P < 0.05) throughout the follow-up period. Permutation analyses were used to control specificity.

MAIN OUTCOME MEASURES

Magnitude of correlation between structural and functional rates of change and proportion of worsening and positive slopes as a function of follow-up time.

RESULTS

The median (interquartile range) follow-up and number of exams were 4.2 (3.7-4.6) years and 8 (7-9), respectively. The highest correlation of change rates was observed at 3.4° and 5.6° eccentricities (r = 0.24, 0.41, 0.40, and 0.40 for FMT, GCC, GCIPL, and GCL for 3.4° eccentricity and r = 0.28, 0.32, 0.31, and 0.32 for FMT, GCC, GCIPL, and GCL for 5.6° eccentricity, respectively). Although GCC measures demonstrated the highest overall longitudinal SF correlations, the differences were not statistically significant. Significant structural worsening was more frequently detected than functional deterioration at 3- and 5-year time points (P < 0.025). Permutation analyses also confirmed this finding.

CONCLUSIONS

Correlations between central structural and functional rates of change were weak to fair in this cohort. Structural changes were detected more frequently than functional changes. Measurements of both structure and function are required for optimal detection of central progression.

Longitudinal Macular Structure-Function Relationships in Glaucoma and Their Sources of Variability

PURPOSE

To review central structure-function (SF) relationships in glaucoma; to compare contributions of within-session and between-session variability to total variability of macular optical coherence tomography (OCT) thickness measurements; and to test the hypothesis that longitudinal within-eye variability of central SF relationships is smaller than between-individual variability.

METHODS

We reviewed the pertinent literature on central SF relationships in glaucoma. Thirty-eight eyes (20 normal or glaucoma subjects) had ×3 macular images per session over 3 sessions, and superpixels thickness measurements for ganglion cell layer (GCL), ganglion cell/inner plexiform layer (GCIPL), ganglion cell complex (GCC), and full macular thickness (FMT) were exported. Linear mixed models were used for estimating contributions of between- and within-session variability to total thickness variability. One hundred twenty eyes with ≥3 10° visual fields (VFs)/OCT images were enrolled for the longitudinal study. We investigated within-eye longitudinal SF relationships (GCIPL thickness vs VF total deviations) with a change-point regression model and compared within-eye to between-individual variabilities with components-of-variance models.

RESULTS

In the cross-sectional study, the between-session component contributed 8%, 11%, 11%, and 36% of total variability for GCL, GCIPL, GCC, and FMT, respectively. In the longitudinal study, between-individual variability explained 78%, 77%, and 67% of total SF variability at 3.4°, 5.6°, and 6.8° eccentricities, respectively (P < .05). SF relationships remained stable over time within individual eyes.

CONCLUSIONS

Within-session variability accounts for most of macular thickness variability over time. Longitudinal within-eye SF variability is smaller than between-individual variability. Study of within-eye SF relationships could help clinicians better understand SF linking in glaucoma and help refine progression algorithms. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Correlating Structural and Functional Damage in Glaucoma

Structural and functional tests are essential for detecting and monitoring glaucomatous damage. However, the correlations between structural and functional tests in glaucoma are complex and faulty, with the combination of both modalities being recommended for better assessment of glaucoma. The objective of this review is to explore investigations from the last 5 years in the field of structure-function correlation in glaucoma that contributed to increment in the understanding of this correlation and have the potential to improve the diagnosis and detection of glaucoma progression.

The Effect of Gender on Visual Field Sensitivity: The Singapore Chinese Eye Study

PURPOSE

Visual field (VF) sensitivity is known to be age-dependent, but there is a paucity of evidence on whether it is gender-dependent. We therefore investigated the effect of gender on VF sensitivity.

METHODS

An observational study involving 491 adults from the population-based Singapore Chinese Eye Study (SCES). Study participants underwent a comprehensive and standardised ocular examination and VF assessment on the Humphrey Field Analyzer II (Carl Zeiss Meditec, Inc., Dublin, CA, USA). The effect of gender on the mean deviation (MD) and pattern standard deviation (PSD) was analysed with linear regression models.

RESULTS

The mean age was 52.9 ± 5.9 years, and 229 (46.6%) participants were women. A total of 800 reliable VFs from 655 healthy eyes without visual impairment, glaucoma and significant cataract were included. The mean (± standard deviation) MD was -0.45 ± 1.01 dB in men, and -0.84 ± 1.20 dB in women. The MD [95% confidence interval] was 0.28 [-0.44 to -0.12] dB lower in females compared to males (P = 0.001) after adjusting for reliability indices, degree of lens opacity, and other potential confounders. The PSD was not significantly different between the genders.

CONCLUSIONS

In the SCES, the population-average of the central VF sensitivity was significantly lower in women compared to men by a small amount (0.28 dB). This effect was observed in healthy eyes, and was not explained by multiple potential confounders. Hence, this likely represents a physiological gender-based difference that is unaccounted for in standard automated perimetry. Further studies in other populations would be needed to corroborate our findings.

Reduced Macular Vessel Density and Capillary Perfusion in Glaucoma Detected Using OCT Angiography

AIMS

To evaluate retinal vasculature changes in primary open-angle glaucoma (POAG) and whether the functional visual loss correlates with parameters obtained using optical coherence tomography angiography (OCTA).

MATERIALS AND METHODS

OCT and OCTA images were collected from 116 POAG eyes and 40 normal eyes in a prospective, cross-sectional observational study. Glaucomatous eyes were further divided into three groups according to a Glaucoma Staging System. Measurements of macular vessel density, ganglion cell complex (GCC), and disk retinal nerve fiber layer (RNFL) thickness were compared among groups.

RESULTS

The macular vessel density, GCC, and RNFL are significantly reduced in POAG compared to normal eyes that also corresponds to the severity of glaucoma (Kruskal-Wallis test with Dunnett's correction; p < 0.0001). Visual field mean deviation correlates significantly with macular vessel density (p = 0.0028, r = 0.3), GCC (p < 0.0001, r = 0.6), and RNFL (p = 0.008, r = 0.36) in POAG. There are significant correlations between GCC and RNFL (p < 0.0001, r = 0.76) as well as macular vessel density (p < 0.0001, r = 0.48). Increased age also correlates with reduced macular vessel density in both normal (p = 0.0002, r = 0.49) and glaucomatous eyes (p < 0.0001, r = 0.48), but a greater proportionate reduction of vessel density is seen in glaucomatous eyes.

CONCLUSION

Reduced macular vessel density occurs in POAG despite of age-related changes, which also correlates with reductions in RNFL and GCC measurements. OCTA can detect microstructural defects and offers potential to facilitate diagnosis of glaucoma.

The assessment of structural changes on optic nerve head and macula in primary open angle glaucoma and ocular hypertension

AIM

To assess morphological changes in macula, retinal nerve fiber layer (RNFL) and optic nevre head (ONH) of cases with primary open angle glaucoma (POAG) and ocular hypertension (OH) with spectral domain optic coherence tomography (OCT).

METHODS

This study included 109 eyes from 62 POAG patients, 50 eyes from 30 OH patients, and 101 eyes from 53 healthy volunteers. Data gained by OCT were compared with perimetry indexes. ONH, RNFL and macula analysis were performed for all subjects. Rim area, disc area, average cup/disc (C/D) ratio, vertical C/D ratio, cup volume data were recorded during ONH analysis. Average RNFL thickness and the thickness of four quadrants (superior, inferior, nasal and temporal) was established in microns. In total, nine macular quadrants involving the foveal region mentioned in the Early Treatment Diabetic Treatment Study (ETDRS) template were measured, and average macular thickness and macular volume data were recorded during macula analysis. Differences between groups were evaluated with the one-way ANOVA test. Tukey's multiple comparison test was performed to detect difference between groups. Receiver-operating characteristic (ROC) analysis was done for early stage POAG patients to establish sensitivity and specificity of chosen parameters in early stage POAG. Area under the receiver operating characteristic (AUROC) values were calculated to compare ROC areas.

RESULTS

Statistically significant differences were found in all ONH parameters, except optic disc area. Neuroretinal rim area was identified as the parameter with the highest difference between groups (F=21.72, P<0.05). The highest correlation between ONH parameters and perimetry was observed at neuroretinal rim region (r=0.487). Inferior RNFL thickness was established as the parameter with the highest difference between groups among RNFL parameters. In the mean of all glaucoma patients, the highest correlation between data handled with OCT and mean deviation was observed in RNFL thickness. Average macular thickness was detected as the parameter with the highest difference between groups among macular parameters. The highest correlation between macula parameters and perimetry indexes was observed between average macular thickness and perimetry indexes (r=0.514).

CONCLUSION

Although the assessment of ONH and the analysis of macular thickness are important in diagnosis and treatment, RNFL assessment is the most valuable parameter.

Diagnostic Ability of Swept-Source and Spectral-Domain Optical Coherence Tomography for Glaucoma

PURPOSE

To compare the diagnostic abilities of swept-source optical coherence tomography (OCT) [Deep Range Imaging OCT-1 (DRI-OCT)] and spectral-domain OCT (Cirrus HD-OCT) for glaucoma in Korean adults.

MATERIALS AND METHODS

This retrospective study involved measuring peripapillary retinal nerve fiber layer (PP-RNFL) thickness, full macular thickness, and ganglion cell-inner plexiform layer (GC-IPL) thickness on two different OCT systems. We used three-dimensional optic disc scanning of DRI-OCT and included 12 clock-hour sectors for measurement of the PP-RNFL. Areas under receiver operating characteristic curves (AUCs) were calculated and compared to determine how well each system could distinguish control and glaucomatous patients.

RESULTS

Ninety-one healthy and 58 glaucomatous eyes were included. Both systems could clearly distinguish between control eyes and eyes with moderate to severe glaucoma. Among all sectors, the AUC values of areas associated with glaucoma were >0.7 for both OCTs. The PP-RNFL sector of highest AUC value on both OCTs was the inferior sector of the clock-hour map (0.968 and 0.959 in DRI-OCT and Cirrus HD-OCT, respectively). Among macular thickness sectors, AUC values were highest on both OCTs for the outer inferior sector (0.859 and 0.853 in DRI-OCT and Cirrus HD-OCT, respectively). The GC-IPL also provided high diagnostic values (DRI-OCT and Cirrus HD-OCT were the best in the average and inferior sectors, respectively).

CONCLUSION

Although the two OCT systems provided different thickness measurements, DRI-OCT exhibited as good, if not better, diagnostic ability for glaucoma as Cirrus HD-OCT in Korean adults.

Predicting the Integrated Visual Field with Wide-Scan Optical Coherence Tomography in Glaucoma Patients

PURPOSE

This study aimed to calculate a predicted integrated visual field (IVF) based on predicted monocular visual fields (MVFs) derived, with a new method, from wide-scan optical coherence tomography (OCT) data.

MATERIALS AND METHODS

Visual field testing used the central (6 × 4) 24 points of the Humphrey Field Analyzer 24-2 program. OCT scans of a corresponding retinal area, centered on the fovea, were divided into a 6 × 4 grid. The thickness of the macular retinal nerve fiber layer (mRNFL), ganglion cell layer + inner plexiform layer (GCIPL), and mRNFL + GCIPL (GCC) was measured in each grid area. Next, a support vector machine was used to create a MVF prediction model, with training data from 101 eyes of 60 glaucoma patients. Then, the prediction model was validated with data from 108 eyes of 54 glaucoma patients, for MVF and IVF. A simulated IVF was created by merging bilateral simulated MVFs.

RESULTS

The overall average of the median 95% prediction interval length for the MVF prediction model (measured in dB) was 10.0, 18.3, and 11.3 for the mRNFL, GCIPL, and GCC, respectively. In the validation data, the overall average root mean squared error (dB) between actual and predicted sensitivity for the IVF was 9.6, 10.5, and 9.5 for the mRNFL, GCIPL, and GCC, respectively, in the 24 grid areas. The intraclass correlation coefficient between average actual and predicted IVF was 0.61, 0.44, and 0.59 in the mRNFL, GCIPL, and GCC, respectively, in the 24 grid areas.

CONCLUSIONS

We calculated a predicted IVF based on predicted MVFs that were derived, with a new method, from OCT data and validated the accuracy of the calculated IVF. This technique should improve glaucoma management in cases when standard visual field testing is difficult.

A basis for customising perimetric locations within the macula in glaucoma

PURPOSE

It has been recognised that the 24-2 grid used for perimetry may poorly sample the macula, which has been recently identified as a critical region for diagnosing and managing patients with glaucoma. We compared data derived from patients and controls to investigate the efficacy of a basis for customising perimetric locations within the macula, guided by en face images of retinal nerve fibre layer (RNFL) bundles.

METHODS

We used SD-OCT en face montages (www.heidelbergengineering.com) of the RNFL in 10 patients with glaucoma (ages 56-80 years, median 67.5 years) and 30 age-similar controls (ages 47-77, median 58). These patients were selected because of either the absence of perimetric defect while glaucomatous damage to the RNFL bundles was observed, or because of perimetric defect that did not reflect the extent and locations of the glaucomatous damage that appeared in the RNFL images. We used a customised blob stimulus for perimetric testing (a Gaussian blob with 0.25° standard deviation) at 10-2 grid locations, to assess the correspondence between perimetric defects and damaged RNFL bundles observed on en face images and perimetric defects. Data from the age-similar controls were used to compute total deviation (TD) and pattern deviation (PD) values at each location; a perimetric defect for a location was defined as a TD or PD value of -0.5 log unit or deeper. A McNemar's test was used to compare the proportions of locations with perimetric defects that fell outside the damaged RNFL bundles, with and without accounting for displacement of ganglion cell bodies.

RESULTS

All patients but one had perimetric defects that were consistent with the patterns of damaged RNFL bundles observed on the en face images. We found six abnormal perimetric locations of 2040 tested in controls and 132 abnormal perimetric locations of 680 tested in patients. The proportions of abnormal locations that fell outside the damaged RNFL bundles, with and without accounting for displacement of the ganglion cell bodies were 0.08 and 0.07, respectively. The difference between the two proportions did not reach statistical significance (p = 0.5 for a one-tailed test).

CONCLUSIONS

We demonstrated that it is effective to customise perimetric locations within the macula, guided by en face images of the RNFL bundles. The perimetric losses found with a 10-2 grid demonstrated similar patterns as the damaged RNFL bundles observed on the en face images.

Macular imaging by optical coherence tomography in the diagnosis and management of glaucoma

The macular area is important to the detection of glaucomatous retinal ganglion cell (RGC) damage. Macular thickness complementary to peripapillary retinal nerve fibre layer (RNFL) thickness can well reflect glaucomatous damage, given that the macula contains more than 50% of the RGCs in a multilayered pattern and larger RGC bodies compared with their axons. Thus, macular ganglion cell thickness parameters recently have been considered to be an effective glaucoma-diagnostic tool comparable to RNFL thickness parameters. Furthermore, spectral-domain optical coherence tomography ganglion cell-inner plexiform layer thickness and deviation maps can provide additional information essential for distinguishing glaucomatous changes from other, myopia-associated or macular disease-associated changes. Therefore, our aim with this study was to review the clinical application of macular imaging by optical coherence tomography and to provide essential clinical tips for its use in the diagnosis and management of glaucoma.