A test of a linear model of glaucomatous structure-function loss reveals sources of variability in retinal nerve fiber and visual field measurements

Longitudinal in vivo Ca2+ imaging reveals dynamic activity changes of diseased retinal ganglion cells at the single-cell level

Retinal ganglion cells (RGCs) are heterogeneous projection neurons that convey distinct visual features from the retina to brain. Here, we present a high-throughput in vivo RGC activity assay in response to light stimulation using noninvasive Ca2+ imaging of thousands of RGCs simultaneously in living mice. Population and single-cell analyses of longitudinal RGC Ca2+ imaging reveal distinct functional responses of RGCs and unprecedented individual RGC activity conversions during traumatic and glaucomatous degeneration. This study establishes a foundation for future in vivo RGC function classifications and longitudinal activity evaluations using more advanced imaging techniques and visual stimuli under normal, disease, and neural repair conditions. These analyses can be performed at both the population and single-cell levels using temporal and spatial information, which will be invaluable for understanding RGC pathophysiology and identifying functional biomarkers for diverse optic neuropathies.

Detecting glaucoma from multi-modal data using probabilistic deep learning

Objective

To assess the accuracy of probabilistic deep learning models to discriminate normal eyes and eyes with glaucoma from fundus photographs and visual fields.

Design

Algorithm development for discriminating normal and glaucoma eyes using data from multicenter, cross-sectional, case-control study.

Subjects and participants

Fundus photograph and visual field data from 1,655 eyes of 929 normal and glaucoma subjects to develop and test deep learning models and an independent group of 196 eyes of 98 normal and glaucoma patients to validate deep learning models.

Main outcome measures

Accuracy and area under the receiver-operating characteristic curve (AUC).

Methods

Fundus photographs and OCT images were carefully examined by clinicians to identify glaucomatous optic neuropathy (GON). When GON was detected by the reader, the finding was further evaluated by another clinician. Three probabilistic deep convolutional neural network (CNN) models were developed using 1,655 fundus photographs, 1,655 visual fields, and 1,655 pairs of fundus photographs and visual fields collected from Compass instruments. Deep learning models were trained and tested using 80% of fundus photographs and visual fields for training set and 20% of the data for testing set. Models were further validated using an independent validation dataset. The performance of the probabilistic deep learning model was compared with that of the corresponding deterministic CNN model.

Results

The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and combined modalities using development dataset were 0.90 (95% confidence interval: 0.89-0.92), 0.89 (0.88-0.91), and 0.94 (0.92-0.96), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using the independent validation dataset were 0.94 (0.92-0.95), 0.98 (0.98-0.99), and 0.98 (0.98-0.99), respectively. The AUC of the deep learning model in detecting glaucoma from fundus photographs, visual fields, and both modalities using an early glaucoma subset were 0.90 (0.88,0.91), 0.74 (0.73,0.75), 0.91 (0.89,0.93), respectively. Eyes that were misclassified had significantly higher uncertainty in likelihood of diagnosis compared to eyes that were classified correctly. The uncertainty level of the correctly classified eyes is much lower in the combined model compared to the model based on visual fields only. The AUCs of the deterministic CNN model using fundus images, visual field, and combined modalities based on the development dataset were 0.87 (0.85,0.90), 0.88 (0.84,0.91), and 0.91 (0.89,0.94), and the AUCs based on the independent validation dataset were 0.91 (0.89,0.93), 0.97 (0.95,0.99), and 0.97 (0.96,0.99), respectively, while the AUCs based on an early glaucoma subset were 0.88 (0.86,0.91), 0.75 (0.73,0.77), and 0.92 (0.89,0.95), respectively.

Conclusion and relevance

Probabilistic deep learning models can detect glaucoma from multi-modal data with high accuracy. Our findings suggest that models based on combined visual field and fundus photograph modalities detects glaucoma with higher accuracy. While probabilistic and deterministic CNN models provided similar performance, probabilistic models generate certainty level of the outcome thus providing another level of confidence in decision making.

Comparison of machine learning approaches for structure-function modeling in glaucoma

To evaluate machine learning (ML) approaches for structure-function modeling to estimate visual field (VF) loss in glaucoma, models from different ML approaches were trained on optical coherence tomography thickness measurements to estimate global VF mean deviation (VF MD) and focal VF loss from 24-2 standard automated perimetry. The models were compared using mean absolute errors (MAEs). Baseline MAEs were obtained from the VF values and their means. Data of 832 eyes from 569 participants were included, with 537 Asian eyes for training, and 148 Asian and 111 Caucasian eyes set aside as the respective test sets. All ML models performed significantly better than baseline. Gradient-boosted trees (XGB) achieved the lowest MAE of 3.01 (95% CI: 2.57, 3.48) dB and 3.04 (95% CI: 2.59, 3.99) dB for VF MD estimation in the Asian and Caucasian test sets, although difference between models was not significant. In focal VF estimation, XGB achieved median MAEs of 4.44 [IQR 3.45-5.17] dB and 3.87 [IQR 3.64-4.22] dB across the 24-2 VF for the Asian and Caucasian test sets and was comparable to VF estimates from support vector regression (SVR) models. VF estimates from both XGB and SVR were significantly better than the other models. These results show that XGB and SVR could potentially be used for both global and focal structure-function modeling in 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.

Patient Reported Symptoms Demonstrating an Association with Severity of Visual Field Damage in Glaucoma

OBJECTIVE

To determine which patient reported symptoms best distinguishes patients with and without glaucoma and explains the most variance in visual field (VF) damage, and compare the amount of variance that can be explained by symptoms vs. retinal nerve fiber layer (RNFL) thickness.

DESIGN

Cross-sectional study.

PARTICIPANTS

Adults diagnosed with glaucoma or suspicion of glaucoma (controls).

METHODS

Worse-eye VF damage was defined based on perimetric testing. RNFL thickness was defined by OCT imaging. Patients rated their visual symptoms on questions collated from several published questionnaires, rating the frequency and severity of 28 symptoms on a scale of 1 (never/not at all) to 4 (very often/severe). Multivariable regression models identified patient reported symptoms that contributed the highest variance in VF damage.

MAIN OUTCOME MEASURES

Patient reported symptoms that explained the most variance in VF damage; amount of variance in VF damage explained by patient reported symptoms and RNFL RESULTS: A total of 170 patients (mean age= 64; 58% female; 47% employed) completed testing, including 95 glaucoma suspects and 75 glaucoma patients. In glaucoma patients, median mean deviation of VF damage in the worse eye was -19.3 and ranged from -5.3 to -34.7 dB. Symptoms more common amongst glaucoma patients compared to glaucoma suspects included better vision in one eye, blurry vision, glare, sensitivity to light, cloudy vision, and little peripheral vision. Worse severity ratings for the symptom 'little peripheral vision' explained the most variance in VF damage (43%). A multivariable model including the frequency of cloudy vision, severity of having little peripheral vision, missing patches, one eye having better vision, and vision worsening, plus sociodemographic features explained 62% of the variance in VF damage. Comparatively, a multivariable model of worse-eye RNFL thickness and sociodemographic features explained 42% of the variance in VF damage, while a model including only sociodemographic features explained 8% of the variance in VF damage.

CONCLUSIONS

Five patient reported symptoms explain a significant amount of the variance in VF damage. Asking patients about their symptoms may optimize patient-physician communication and be a useful adjunct to clinical testing in some patients to estimate disease severity.

Optical coherence tomography angiography vessel density parameters in primary open-angle glaucoma

Background

Many studies suggest the existence of an alteration of the retinal hemoperfusion in primary open-angle glaucoma. The OCT-A is a novel technique that allows to provide information on retinal microcirculation in a non-invasive way, thus it represents a possible imaging target for the early diagnosis and follow-up of glaucoma. The aim of our work is to evaluate the contribution of vascular parameters provided by OCT-A and their diagnostic abilities in the different stages of primary open-angle glaucoma.

Method

This is a prospective cross-sectional study involving 200 eyes of control subjects and 250 eyes of glaucomatous subjects divided into early glaucoma, moderate glaucoma and advanced glaucoma subgroups. They were assessed for MD, LV by visual field, RNFL and GCC thickness by SS-OCT papillary and macular vascular densities by SS-OCT A.

Results

OCT-A vessel densities determined in the optic nerve head, in the peripapillary and in the macular regions were significantly lower in glaucomatous eyes. Among the vascular parameters studied the whole image vascular density showed the best diagnostic ability in the discrimination between glaucomatous eyes and healthy eyes with an AUC of 0.949. Nevertheless, the diagnostic ability of vascular parameters remains lower than of the structural parameters RNFL (AUC: 0.981). A significant correlation was found between structural, functional and vascular parameters with r < 0.05. The quadratic non-linear model defines better the relationship between structural, vascular and functional damage in glaucoma.

Conclusion

The OCT-A plays an important role in the early diagnosis and follow-up of PAOG. It also contributes to the understanding of some aspects of the vascular role in glaucoma.

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OCT-A vascular density parameters exploring the macular and papillary regions are decreased in primary open-angle glaucoma.

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Disc and macular vessel density parameters have excellent diagnostic abilities in diagnosing glaucomatous eyes.

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A correlation is shown between functional, structural, and vascular parameters.

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The non-linear quadratic model better describes the relationship between structural, functional, and vascular parameters.

Multimodal Machine Learning Using Visual Fields and Peripapillary Circular OCT Scans in Detection of Glaucomatous Optic Neuropathy

PURPOSE

To develop and validate a multimodal artificial intelligence algorithm, FusionNet, using the pattern deviation probability plots from visual field (VF) reports and circular peripapillary OCT scans to detect glaucomatous optic neuropathy (GON).

DESIGN

Cross-sectional study.

SUBJECTS

Two thousand four hundred sixty-three pairs of VF and OCT images from 1083 patients.

METHODS

FusionNet based on bimodal input of VF and OCT paired data was developed to detect GON. Visual field data were collected using the Humphrey Field Analyzer (HFA). OCT images were collected from 3 types of devices (DRI-OCT, Cirrus OCT, and Spectralis). Two thousand four hundred sixty-three pairs of VF and OCT images were divided into 4 datasets: 1567 for training (HFA and DRI-OCT), 441 for primary validation (HFA and DRI-OCT), 255 for the internal test (HFA and Cirrus OCT), and 200 for the external test set (HFA and Spectralis). GON was defined as retinal nerve fiber layer thinning with corresponding VF defects.

MAIN OUTCOME MEASURES

Diagnostic performance of FusionNet compared with that of VFNet (with VF data as input) and OCTNet (with OCT data as input).

RESULTS

FusionNet achieved an area under the receiver operating characteristic curve (AUC) of 0.950 (0.931-0.968) and outperformed VFNet (AUC, 0.868 [95% confidence interval (CI), 0.834-0.902]), OCTNet (AUC, 0.809 [95% CI, 0.768-0.850]), and 2 glaucomatologists (glaucomatologist 1: AUC, 0.882 [95% CI, 0.847-0.917]; glaucomatologist 2: AUC, 0.883 [95% CI, 0.849-0.918]) in the primary validation set. In the internal and external test sets, the performances of FusionNet were also superior to VFNet and OCTNet (FusionNet vs VFNet vs OCTNet: internal test set 0.917 vs 0.854 vs 0.811; external test set 0.873 vs 0.772 vs 0.785). No significant difference was found between the 2 glaucomatologists and FusionNet in the internal and external test sets, except for glaucomatologist 2 (AUC, 0.858 [95% CI, 0.805-0.912]) in the internal test set.

CONCLUSIONS

FusionNet, developed using paired VF and OCT data, demonstrated superior performance to both VFNet and OCTNet in detecting GON, suggesting that multimodal machine learning models are valuable in detecting GON.

Detecting Progression in Advanced Glaucoma: Are Optical Coherence Tomography Global Metrics Viable Measures?

SIGNIFICANCE

Optical coherence tomography (OCT) summary measures have been suggested as a way to detect progression in eyes with advanced glaucoma. Here, we show that these measures have serious flaws largely due to segmentation errors. However, inspection of the images and thickness maps can be clinically useful.

PURPOSE

This study aimed to test the hypothesis that recently suggested global OCT measures for detecting progression in eyes with advanced progression are seriously affected by segmentation mistakes and other errors that limit their clinical utility.

METHODS

Forty-five eyes of 38 patients with a 24-2 mean deviation worse than -12 dB had at least two spectral domain OCT sessions (0.8 to 4.4 years apart) with 3.5-mm circle scans of the disc and cube scans centered on the fovea. Average (global) circumpapillary retinal nerve fiber layer thickness, GcRNFL, and ganglion cell plus inner plexiform layer thickness, GGCLP, were obtained from the circle and cube scan, respectively. To evaluate progression, ΔGcRNFL was calculated for each eye as the GcRNFL value at time 2 minus the value at time 1, and ΔGGCLP was calculated in a similar manner. The b-scans of the six eyes with the highest and lowest ΔGcRNFL and ΔGGCLP values were examined for progression as well as segmentation, alignment, and centering errors.

RESULTS

Progression was a major factor in only 7 of the 12 eyes with the most negative values of either ΔGcRNFL or ΔGGCLP, whereas segmentation played a role in 8 eyes and was the major factor in all 12 eyes with the largest positive values. In addition, alignment (one eye) and other (three eyes) errors played a secondary role in four of the six eyes with the most negative ΔGcRNFL values.

CONCLUSIONS

For detecting the progression of advanced glaucoma, common summary metrics have serious flaws largely due to segmentation errors, which limit their utility in clinical and research settings.

Association Between Structure-function Characteristics and Visual Field Outcomes in Glaucoma Subjects With Intraocular Pressure Reduction After Trabeculectomy

PRECIS

Improvements in post-trabeculectomy visual field (VF) outcomes were found to be significantly associated with preoperative nerve fiber layer thickness parameters extracted from the sectorized structure-function relationship, baseline VF, and severity of glaucoma.

OBJECTIVE

To determine whether the preoperative structure-function relationship helps to predict visual outcomes at 1-year post-trabeculectomy.

PATIENTS AND METHODS

In total, 91 eyes from 87 participants who successfully underwent trabeculectomy were included in our study. All eyes received optical coherence tomography imaging and VF assessment using 30-2 standard automated perimetry preoperatively at baseline and postoperatively 1 year after trabeculectomy. The linear mixed-model analysis was used to assess the association of structure and function at baseline, and multivariate analysis to investigate factors associated with postoperative VF outcomes.

RESULTS

Results from multivariate and univariate analysis for VF 1 year after trabeculectomy showed that a positive preoperative retinal nerve fiber layer thickness deviation from the structure-function model was found to be significantly associated with improved postoperative VF outcomes [β=0.06 dB/μm; 95% confidence interval (CI), 0.03-0.09]. Other significant factors included baseline VF MD (β=-0.18; 95% CI, -0.23 to -0.13) and the presence of severe glaucoma (β=-1.69; 95% CI, -2.80 to -0.57). Intraocular pressure was positively associated with improved VF outcomes only in univariate analysis (β=0.06; 95% CI, 0.01-0.11).

CONCLUSIONS AND RELEVANCE

Characteristics derived from the baseline structure-function relationship were found to be strongly associated with postoperative VF outcomes. These findings suggest that the structure-function relationship could potentially have a role in predicting VF progression after trabeculectomy.

Review of Longitudinal Glaucoma Progression: 5 Years after the Shaffer Lecture

In 2013, the senior author delivered the American Academy of Ophthalmology Robert N. Shaffer Lecture entitled "Glaucoma Changes-Reality Bites." This talk focused on describing the longitudinal structure-function relationships in glaucoma progression. The study was based on a 10-year longitudinal dataset created by calibrated measurements across multiple OCT generations with corresponding visual fields (VFs). The prior held observation was that functional damage follows structural damage. The lecture posited that structure and function change at similar times, but that current measurement technology limits our ability to detect functional abnormalities and change early in glaucoma, as well as to measure structural change late in the disease. The Shaffer lecture provided evidence that structure and function change concordantly and that any apparent discordance in the relationship was due to technologic limitations to measure glaucomatous change. Furthermore, we observed 5 longitudinal relationships of concordance and discordance that can exist with structure-function interactions. Concordance: (1) structure-structure progression, (2) structure-function tipping point, (3) structural floor tipping point. Discordance: (4) functional progression in a "stable" VF with structure-function correlation, (5) functional progression with "normal" structure. In this review article, we will review longitudinal glaucoma progression studies with long-term follow-up and discuss the clinical relevance of relationships of concordance and discordance that can exist with structure-function interactions.

Factors affecting the diagnostic performance of circumpapillary retinal nerve fibre layer measurement in glaucoma

BACKGROUND/AIMS

To identify factors that influence the diagnostic performance of circumpapillary retinal nerve fibre layer (RNFL) thickness measurements in the detection of primary open-angle glaucoma (POAG).

METHODS

1592 eyes from 1076 healthy controls and 758 eyes from 502 patients with POAG underwent optical coherence tomography (OCT) imaging to assess RNFL parameters. Visual field (VF) mean deviation (MD) from standard automated perimetry was used to indicate severity in subjects with glaucoma.

RESULTS

RNFL thickness significantly decreased with age (ρ=-0.10 to -0.16, p<0.001) and increased with spherical equivalent (SE) refractive error (ρ=0.23-0.29, p<0.001) in healthy and glaucoma groups but showed a significant reduction with SE (ρ=-0.20, p<0.001) in the temporal RNFL of healthy subjects. RNFL measurements significantly decreased with VF MD (ρ=0.08-0.53, p<0.05) in subjects with POAG. When healthy subjects and subjects with glaucoma were matched to subgroups within a factor, significant differences in area under the curve (AUC) between subgroups were only found with SE AUCs increased significantly with disease severity, particularly in the global, inferior and superior measurements (p<0.001). Overall, the diagnostic performance of the inferior and global RNFL measurements were found to be more resilient to different factors.

CONCLUSION

Diagnostic accuracy in glaucoma was influenced by SE but could be mitigated by using controls with similar refractive characteristics. Increasing disease severity led to significantly better diagnostic accuracy. These factors should be considered when using OCT for glaucoma diagnosis in practice.

Defective angles of localized retinal nerve fiber layer reflect the severity of visual field defect- a cross-sectional analysis

Background

In order to detect glaucomatous optic nerve damages early on and evaluate the severity of glaucoma, a previously developed analytic method based on photographic retinal nerve fiber layer (RNFL) angle defect was proposed. However, the correlation between these defective angles and the severity of visual field defect has not been verified. This study aimed to confirm the correlation described above.

Methods

We reviewed a total of 227 glaucomatous eyes (38 enrolled, 189 excluded) during an interval of 5 years. The angles of all eyes were measured on RNFL photograph, of which angle α is the angular width between the macula center and the proximity of RNFL defect, and angle β (+c) is the sum of angular width(s) of localized RNFL defect. The severity of visual field defect was determined by mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI). Correlation analysis was performed on angle α and angle β (+c) with the presence of central scotoma and visual field defect parameters, respectively.

Results

Angle β (+c) showed significant correlation with MD (P = 0.007), PSD (P = 0.02), VFI (P = 0.03), and average RNFL thickness (P = 0.03). No correlation was found between angle α and the presence of central scotoma.

Conclusions

In conclusion, measuring the angular width of localized RNFL defect is a viable method for determining the severity of visual field defect.

Within-subject variability in human retinal nerve fiber bundle width

With the growing availability of high-resolution imaging there has been increased interest in developing new metrics for integrity of the retinal nerve fiber layer. In particular, it has been suggested that measurement of width of retinal nerve fiber bundles (RNFBs) may be useful in glaucoma, due to low between-subject variability in mean RNFB width. However, there have also been reports of substantial within-subject variability in the width of individual RNFBs. To assess within-subject variability as a potential source of selection bias in measurements of RNFB width, we used an adaptive optics scanning laser ophthalmoscope (AOSLO) to measure widths of individual RNFBs in one eye each of 11 young adults in good ocular health. In a pilot study we analyzed a large AOSLO image of RNFL in one participant then, based on those findings, in the main study we used AOSLO to image a smaller region in 10 additional healthy young adults. The pilot study of one eye found RNFB widths ranging from 10 μm to 44 μm. This suggested that biological variability was too high for measuring small changes arising from disease processes. This was confirmed in measurements of 10 eyes in the main study, RNFB widths ranged from 9 μm to 55 μm and every eye had large within-subject variability (exceeding 19 μm in all eyes) in RNFB width for nearby bundles. The within-subject variability in RNFB width, as well as variation in the width of single RNFBs over relatively short distances (<300 um) depending on the precise location of measurement, suggests that bundle width measurements would be highly susceptible to selection bias and therefore of limited clinical use.

Thinning rates of retinal nerve layer and ganglion cell-inner plexiform layer in various stages of normal tension glaucoma

AIMS

To compare the changes in the macular retinal nerve fibre layer (mRNFL), macular ganglion cell layer and inner plexiform layer (mGCIPL), and circumpapillary retinal nerve fibre layer (cpRNFL) in various stages of normal tension glaucoma (NTG) using spectral domain optical coherence tomography.

METHODS

Eyes with NTG (n=218) were assigned into three groups based on initial mean deviation (MD) as follows: mild (MD>-6 dB), moderate (-6 dB≥MD≥-12 dB) and severe (-12 dB>MD>-20 dB). Annual rates of change in mRNFL, mGCIPL and cpRNFL thickness were calculated by linear regression analysis.

RESULTS

Age, gender, spherical equivalent, and average intraocular pressure during follow-up were not significantly different among the three groups. There were significant differences in the mRNFL, mGCIPL and cpRNFL among the three groups at baseline (p<0.0001 in all sectors except for the mRNFL in the superonasal sector). The average thinning rates of the mRNFL, mGCIPL and cpRNFL were -0.38±0.32 µm/year, -0.62±0.46 µm/year and -0.86±0.83 µm/year, respectively. No significant difference in the rates of change in the mRNFL and mGCIPL were found among the groups in any sector. However, there was a significant difference in the rate of change in the cpRNFL among the groups (in all sectors: p<0.0001).

CONCLUSIONS

Changes in the mRNFL and mGCIPL can reflect the progression of NTG even in its advanced stage. However, careful interpretation of changes in the cpRNFL in the advanced stage of glaucoma is warranted due to a potential floor effect.

Significant Relationship of Visual Field Sensitivity in Central 10° to Thickness of Retinal Layers in Retinitis Pigmentosa

Purpose

To determine the relationship between the sensitivity of the retina in the central 10° and the thickness of the retinal layers in patients with retinitis pigmentosa (RP).

Methods

Fifty-two RP patients were studied. All of the patients had been examined by the Humphrey Field Analyzer 10-2 program (HFA10-2) and spectral-domain optical coherence tomography (SD-OCT). The thicknesses of the photoreceptor outer segment (OS), outer nuclear layer (ONL), inner nuclear layer (INL), and the retinal nerve fiber layer (RNFL) were measured at 1°, 3°, 5°, 7°, and 9° from the fovea. The same measurements were made on the SD-OCT images of 40 healthy subjects and used as controls. The relationships between the retinal sensitivities and retinal layer thicknesses were determined.

Results

The thicknesses of the OS and ONL and their product were significantly and positively correlated with the retinal sensitivities. The thickness of the INL was significantly and negatively correlated with the sensitivity. The strongest correlation with the sensitivity was with the OS thickness (marginal R2 [mR2] = 0.525, P < 0.001), followed by the product of the OS and ONL thicknesses (mR2 = 0.420, P < 0.001), ONL thickness (mR2 = 0.416, P < 0.001), and the INL thickness (mR2 = 0.014, P = 0.044). The thickness of the RNFL was not correlated with the sensitivity (mR2 = 0.005, P = 0.331).

Conclusions

In contrast to previous reports, the thickness of the OS reflected the retinal sensitivity better than the product of OS and ONL.

Mapping the Central 10° Visual Field to the Optic Nerve Head Using the Structure-Function Relationship

Purpose

To investigate the structure-function mapping in the central 10° by relating Humphrey field analyzer (HFA) 10-2 visual field (VF) and circumpapillary retinal nerve fiber layer (cpRNFL) thickness from spectral-domain optical coherence tomography (SD-OCT). We also compared the obtained results with a previously reported mapping between 10-2 VF and the optic disc.

Methods

In 151 eyes of 151 POAG patients and 35 eyes from 35 healthy participants, cpRNFL thickness measurements were obtained using SD-OCT and the 10-2 VF was measured with the HFA. The relationship between visual sensitivity and cpRNL thickness values in the temporal 180° was analyzed using least absolute shrinkage and selection operator (LASSO) regression. The optic disc angle corresponding to each VF test point was then derived using the coefficients from the optimal LASSO regression.

Results

The structure-function map obtained was largely consistent with the mapping reported previously; superior central VF test points correspond to a more vulnerable area of the optic disc, more distant toward the inferior pole from the center of the temporal quadrant (9:00 o'clock for the right eye) while inferior VF test points correspond closer to the center of the temporal quadrant. The prediction error tended to be large in the 'more vulnerable area' in the map reported previously.

Conclusions

The structure-function map obtained largely confirms the previously reported map; however, some important differences were observed.

Steeper structure-function relationship in eyes with than without a parapapillary deep-layer microvasculature dropout

The degree of visual field (VF) loss can vary widely at a given level of retinal nerve fiber layer (RNFL) thickness. The cause of this variability is not fully understood. This cross-sectional study investigated whether the presence of choroidal microvasculature dropout (MvD) influences on the structure-function relationship among glaucomatous eyes. Seventy-one primary open-angle glaucoma (POAG) patients with choroidal MvD as determined by optical coherence tomography angiography (MvD+ group), and 71 age- and inferotemporal (IT) RNFL thickness-matched POAG patients without MvD (MvD– group) were included. VF sensitivity within the region corresponding to the IT RNFL sector was averaged using the total and pattern deviation fields. The slope of log-scale RNFL thickness versus VF defect was significantly steeper for the MvD+ than the MvD– group, as determined by both total and pattern deviation maps (P = 0.004 and <0.001, respectively). Both total and pattern VF deviation were significantly worse in the MvD+ than in the MvD– group (P = 0.002 and 0.007, respectively). Same results were obtained in subgroup analyses for eyes with thick and thin RNFL thickness (all P ≤ 0.027). These data suggest that parapapillary MvD is associated with poorer function of the remaining axons in eyes with POAG.

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.

A comparative study of structural, functional and circulatory parameters in glaucoma diagnostics

PURPOSE

To compare the diagnostic accuracy of structural parameters, vessel density (VD) measured by optical coherence tomography angiography (OCTA), and electrophysiological testing in diagnosis of primary open-angle glaucoma (POAG).

METHODS

35 healthy participants and 90 POAG subjects underwent the measurement of whole image en face (wi) VD in the disc/peripapillary region and macula, the retinal nerve fiber layer (RNFL), and the average thickness of ganglion cell complex (GCC), pattern electroretinograms and pattern visual evoked potentials. The area under the receiver operating characteristic curve (AUC) was assessed for each parameter to differentiate early POAG from healthy eyes and between the POAG stages.

RESULTS

To distinguish early POAG from healthy eyes, the parameters with the highest AUC were detected: P50 amplitude of transient pattern electroretinogram, 1° (AUC 0.93, p = 0.002), P1 component of steady-state pattern electroretinogram (AUC 0.92, p = 0.003), P100 amplitude of pattern visual evoked potential, 1° (AUC 0.84, p = 0.013), wiVD macula superficial (AUC 0.80, p = 0.001), wiVD Disc (AUC 0.74, p = 0.016), GCC (AUC 0.74, p = 0.016) and to distinguish early POAG from the moderate to severe POAG: inferotemporal peripapillary VD (AUC 0.94, p < 0.0001) and focal loss volume of GCC (AUC 0.92, p < 0, 001).

CONCLUSIONS

Our results demonstrate the importance of measuring the microcirculation parameters in the macular area along with PERGs and PVEPs for the early detection of glaucoma. VD in the inferotemporal sector of the peripapillary retina and focal loss volume of the GCC are important for monitoring of the disease. The inclusion of OCTA, PERGs and PVEPs in glaucoma diagnostics may improve its early detection and monitoring.

Associations between structure and function are different in healthy and glaucomatous eyes

Purpose

To assess if there are differences in the structure-function associations between healthy and glaucomatous eyes.

Methods

Structure-function associations were assessed in healthy and glaucomatous eyes in three datasets, globally and in the six sectors of the optic nerve head. Structural parameters included rim area (RA) and retinal nerve fiber layer thickness (RNFLT). Functional parameters included unweighted mean of sensitivity thresholds (MS) and unweighted mean of total deviation values (MD), assessed with standard automated perimetry, short-wavelength automated perimetry, frequency-doubling technology perimetry, or contrast sensitivity perimetry. All structural and functional parameters were expressed as percent of mean normal. SF associations were assessed with correlation analyses (Pearson, Spearman and Kendall). We also assessed the SF associations with linear regression analyses: the generalized estimating equation (GEE) was used to adjust for inter-eye correlations and ordinary least squares (OLS) linear models were used when these adjustments were not necessary. We applied Bonferroni corrections to adjust for the impact of multiple comparisons.

Results

Overall, none of the Pearson correlations tested in healthy eyes were significant (correlations ranged from -0.17 to 0.37), whereas 77% of the correlations tested in glaucomatous eyes were significant (correlations ranged from 0.01 to 0.79). Similarly, none of the slopes obtained with GEE and OLS were significant in healthy eyes (slopes ranged from -0.30 to 0.87), whereas 82% of the slopes obtained in glaucomatous eyes were significant (slopes ranged from 0.02 to 1.38).

Conclusions

Significant associations between structure and function were consistently observed in glaucomatous eyes, but not in healthy eyes. These differences in association should be considered in the design of structure-function models for progression.

Deep Defects Seen on Visual Fields Spatially Correspond Well to Loss of Retinal Nerve Fiber Layer Seen on Circumpapillary OCT Scans

Purpose

To examine the structure-function relationship in glaucoma between deep defects on visual fields (VF) and deep losses in the circumpapillary retinal nerve fiber layer (cpRNFL) on optical coherence tomography (OCT) circle scans.

Methods

Thirty two glaucomatous eyes with deep VF defects, as defined by at least one test location worse than ≤ -15 dB on the 10-2 and/or 24-2 VF pattern deviation (PD) plots, were included from 87 eyes with "early" glaucoma (i.e., 24-2 mean deviation better than -6 dB). Using the location of the deep VF points and a schematic model, the location of local damage on an OCT circle scan was predicted. The thinnest location of cpRNFL (i.e., deepest loss) was also determined.

Results

In 19 of 32 eyes, a region of complete or near complete cpRNFL loss was observed. All 19 of these had deep VF defects on the 24-2 and/or 10-2. All of the 32 eyes with deep VF defects had abnormal cpRNFL regions (red, 1%) and all but 2 had a region of cpRNFL thickness <21 μm. The midpoint of the VF defect and the location of deepest cpRNFL had a 95% limit of agreement within approximately two-thirds of a clock-hour (or 30°) sector (between -22.1° to 25.2°). Individual fovea-to-disc angle (FtoDa) adjustment improved agreement in one eye with an extreme FtoDa.

Conclusions

Although studies relating local structural (OCT) and functional (VF) measures typically show poor to moderate correlations, there is good qualitative agreement between the location of deep cpRNFL loss and deep defects on VFs.

Applying a New Automated Perimetry Pattern Based on the Stimulus Distribution of the Multifocal ERG to Improve Structure-Function Investigation in Glaucoma

Purpose

To validate a new automated perimetry pattern (mf103 pattern) for the investigation of retinal structure-function relationships in glaucoma in comparison to the standard G2 pattern and to relate either field's performance to optical coherence tomography (OCT).

Methods

Automated perimetry data from the mfERG103 pattern were compared with the standard G2 pattern in glaucoma patients (18) and controls (15). The results of both (mean defect (MD) and mean sensitivity (MS)) were compared with optical coherence tomography (OCT): retinal nerve fiber layer (RNFL) thickness, macular thickness (mT), and ganglion cell analysis (GCIPL). Nine patients were followed up after one year.

Results

G2 pattern and mf103 pattern did not differ significantly in MD or MS. The mf103 pattern associated significantly with more RNFL sectors in both MD and MS (p < 0.01 and p < 0.05, resp.). GCIPL thickness was not significantly associated with either SAP protocols. Both protocols remained comparable after one-year follow-up.

Conclusions

G2 and mf103 pattern can both differentiate patients from controls with no significant difference in performance. RNFL thickness defects correlated better with mf103 than G2 with POAG. The mfERG-103 perimetry pattern can be used to establish structure-function correlations in glaucoma and may enable a more direct comparison with objective electrophysiological data.

Optical Coherence Tomography Analysis Based Prediction of Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma

Purpose

A pilot study showed that prediction of individual Humphrey 24-2 visual field (HVF 24-2) sensitivity thresholds from optical coherence tomography (OCT) image analysis is possible. We evaluate performance of an improved approach as well as 3 other predictive algorithms on a new, fully independent set of glaucoma subjects.

Methods

Subjects underwent HVF 24-2 and 9-field OCT (Heidelberg Spectralis) testing. Nerve fiber (NFL), and ganglion cell and inner plexiform (GCL+IPL) layers were cosegmented and partitioned into 52 sectors matching HVF 24-2 test locations. The Wilcoxon rank sum test was applied to test correlation R, root mean square error (RMSE), and limits of agreement (LoA) between actual and predicted thresholds for four prediction models. The training data consisted of the 9-field OCT and HVF 24-2 thresholds of 111 glaucoma patients from our pilot study.

Results

We studied 112 subjects (112 eyes) with early, moderate, or advanced primary and secondary open angle glaucoma. Subjects with less than 9 scans (15/112) or insufficient quality segmentations (11/97) were excluded. Retinal ganglion cell axonal complex (RGC-AC) optimized had superior average R = 0.74 (95% confidence interval [CI], 0.67-0.76) and RMSE = 5.42 (95% CI, 5.1-5.7) dB, which was significantly better (P < 0.05/3) than the other three models: Naïve (R = 0.49; 95% CI, 0.44-0.54; RMSE = 7.24 dB; 95% CI, 6.6-7.8 dB), Garway-Heath (R = 0.66; 95% CI, 0.60-0.68; RMSE = 6.07 dB; 95% CI, 5.7-6.5 dB), and Donut (R = 0.67; 95% CI, 0.61-0.69; RMSE = 6.08 dB, 95% CI, 5.8-6.4 dB).

Conclusions

The proposed RGC-AC optimized predictive algorithm based on 9-field OCT image analysis and the RGC-AC concept is superior to previous methods and its performance is close to the reproducibility of HVF 24-2.

Association of Glaucoma-Related, Optical Coherence Tomography-Measured Macular Damage With Vision-Related Quality of Life

Importance

Little is known about the association between structural macular damage and self-reported visual function of people with glaucoma.

Objective

To determine the association between vision-related quality of life among patients with primary open-angle glaucoma with structural macular retinal ganglion cell plus inner plexiform layer (RGC+IPL) loss identified by spectral-domain optical coherence tomography (SD-OCT) machine-generated deviation maps and thickness measurements.

Design, Setting, and Participants

This cross-sectional prospective study was conducted from March 1, 2014, to March 30, 2015, at the Department of Ophthalmology at Columbia University Medical Center. The participants were 107 patients who were enrolled in the study and represented the entire range of glaucomatous damage. All 214 eyes of the 107 participants underwent 10-2 visual field tests and SD-OCT scans, and all participants completed the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25). They also received ophthalmologic examination, including medical history review, best-corrected visual acuity, slitlamp biomicroscopy, intraocular pressure measurement, gonioscopy, dilated ophthalmoscopy, and standard automated perimetry. Macular RGC+IPL loss was determined by diffuse or focal patterns on SD-OCT-generated deviation maps (probability map that compared patients with aged-matched normative database) and thickness measurements.

Main Outcomes and Measures

Regression analyses to assess the association of NEI VFQ-25 scores (score range: 41.9-99.5; higher scores indicate better functioning) with patterns of RGC+IPL loss and with RGC+IPL thickness measurements.

Results

Of the 107 patients, 48 (45%) were men and the mean (SD) age was 65 (11) years. The self-reported race/ethnicity of participants consisted of 45 (46%) black, 47 (48%) white, and 6 (6%) "other" individuals. In the univariable analyses, patients with diffuse macular RGC+IPL loss had mean composite Rasch-calibrated NEI VFQ-25 scores that were 6.15 points lower than the scores of patients with focal damage (β = -6.15; 95% CI, -11.7 to -0.59; P = .03). The effect remained significant even after controlling for mean RGC+IPL thickness (β = -7.64; 95% CI, -14.2 to -1.03; P = .02).

Conclusions and Relevance

Characteristic patterns of glaucoma-related macular RGC+IPL loss appeared to be more important predictors of vision-related quality of life than thickness measures, with diffuse RGC+IPL loss as an indicator for diminished vision-related quality of life.

Detecting Change Using Standard Global Perimetric Indices in Glaucoma

PURPOSE

Various global indices are available to summarize results from standard automated perimetry. This study asks which index can detect significant deterioration earliest, for a fixed specificity.

DESIGN

Comparison of prognostic indices.

METHODS

Two cohorts were tested. A test-retest cohort contained 5 reliable visual fields, within a short interval, from 45 eyes of 23 participants with glaucoma and/or likelihood of developing glaucoma. A separate longitudinal cohort contained 508 eyes from 330 participants, tested on average 13 times. Three global indices were extracted: mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI). For each index we defined a critical P value Crit_Index, such that 5% of test-retest series showed significant deterioration with P < Crit_Index, using artificial "test dates" in random order. Therefore these criteria have 95% specificity over series of 5 tests. The times to detect significant deterioration in the longitudinal cohort were compared using a survival analysis model.

RESULTS

The median time to detect significant deterioration with MD was 7.3 years (95% confidence interval [CI] 6.8-7.9 years). For VFI, the median was 8.5 years (95% CI 7.9-9.0 years); this comparison had P = .088. For PSD, the median was 10.5 years (95% CI 9.3-11.7 years), slower than MD with P < .001. Within the first 5 years of a series, MD detected significant deterioration in 138 eyes, vs 104 for VFI (P = .0013) and 107 for PSD (P = .029).

CONCLUSIONS

MD detected significant deterioration sooner than VFI or PSD. In particular, MD detected more eyes in the first 5 years of their follow-up, which were presumably undergoing more rapid progression.

Improving our understanding, and detection, of glaucomatous damage: An approach based upon optical coherence tomography (OCT)

Although ophthalmologists are becoming increasingly reliant upon optical coherence tomography (OCT), clinicians who care for glaucoma patients are not taking full advantage of the potential of this powerful technology. First, we ask, how would one describe the nature of glaucomatous damage if only OCT scans were available? In particular, a schematic model of glaucomatous damage is developed in section 2, and the nature of glaucomatous damage seen on OCT scans described in the context of this model in section 3. In particular, we illustrate that local thinning of the circumpapillary retinal nerve fiber layer (cpRNFL) around the optic disc can vary in location, depth, and/or width, as well as homogeneity of damage. Second, we seek to better understand the relationship between the thinning of the cpRNFL and the various patterns of sensitivity loss seen on visual fields obtained with standard automated perimetry. In sections 4 and 5, we illustrate why one should expect a wide range of visual field patterns, and iilustrate why they should not be placed into discrete categories. Finally, section 6 describes how the clinician can take better advantage of the information in OCT scans. The approach is summarized in a single-page report, which can be generated from a single wide-field scan. The superiority of this approach, as opposed to the typical reliance on summary metrics, is described.

["Point by point" approach to structure-function correlation of glaucoma on the ganglion cell complex in the posterior pole]

PURPOSE

To try to establish a "point by point" relationship between the local thickness of the retinal ganglion cell complex and its sensitivity.

MATERIALS AND METHODS

In total, 104 glaucomatous eyes of 89 patients with a confirmed 24-2 visual field, were measured by superimposing the visual field, using imaging software, with the Wide 40° by 30° measurements of retinal ganglion cell complex obtained from the Topcon^© 3D 2000 OCT, after upward adjustment, inversion and scaling. Visual fields were classified into two groups according to the extent of the disease: 58 mild to moderate (MD up to -12dB), and 46 severe (MD beyond -12dB). The 6mm by 6mm central region, equipped with a normative database, was studied, corresponding to 16 points in the visual field. These points were individually matched one by one to the local ganglion cell complex, which was classified into 2 groups depending on whether it was greater or less than 70 microns. The normative database confirmed the pathological nature of the thin areas, with a significance of 95 to 99%. Displacement of central retinal ganglion cells was compensated for. Of 1664 points (16 central points for 104 eyes), 283 points were found to be "borderline" and excluded. Of the 1381 analyzed points, 727 points were classified as "over 70 microns" and 654 points "under 70 microns".

RESULTS

(1) For all stages combined, 85.8% of the 727 points which were greater than 70 microns had a deviation between -3 and +3dB: areas above 70 microns had no observable loss of light sensitivity. (2) In total, 92.5% of the 428 points having a gap ranging from -6 to -35dB were located on ganglion cell complex areas below 70 microns: functional visual loss was identified in thin areas, which were less than 70 microns. (3) Areas which were less than 70 microns, that is 654 points, had quite variable sensitivity and can be divided into three groups: the first with preserved sensitivity, another with obliterated sensitivity, and an intermediate group connecting the two previous ones.

DISCUSSION

In pathologically thin areas, the distribution of these three functional groups seems to correspond to the progression of glaucomatous visual degradation, including a period of resistance, a period of rapid decline, finally leading to complete functional loss.

CONCLUSION

In the studied area, the analysis of retinal ganglion cell complex is relevant to identify areas which are still functional when they exceed 70 microns. Scotomas correspond to the thin areas less than 70 microns. The functionality of areas which are pathologically thinned by glaucomatous degeneration is not correlated to their thickness. In the future, the correlation between structure and function, currently "regional" may be realized "point by point" once automation of the visual field superimposition is made available for the ganglion cell complex.

Localized Changes in Retinal Nerve Fiber Layer Thickness as a Predictor of Localized Functional Change in Glaucoma

PURPOSE

To determine how well rates of localized retinal nerve fiber layer thickness (RNFLT) change correlate with rates of sensitivity change at corresponding locations in the visual field in glaucoma.

DESIGN

Retrospective cohort study.

METHODS

Three hundred and sixty-four eyes of 191 participants with suspected or confirmed glaucoma, as judged by experienced clinicians, were tested every 6 months with perimetry and optical coherence tomography (OCT). For each 24-2 visual field location, the corresponding sectoral peripapillary RNFLT was defined using a 30-degree sector, centered on the angle of nerve fiber entry into the optic nerve head. Rates of change of pointwise sensitivity and sectoral RNFLT were calculated over the last 8 visits at which reliable data were obtained. Passing-Bablok regression was used to predict the rate of pointwise sensitivity change from the rate of sectoral RNFLT change, for each location.

RESULTS

Rates of sectoral RNFLT change were significantly predictive of rates of pointwise sensitivity change at all locations in the field. Correlations were modest, averaging 0.15, ranging from 0.03 to 0.25 depending on the location. A 1 μm/y more rapid thinning in corresponding sectors was associated with 0.3 dB/y more rapid loss in the superior visual field but less than 0.1 dB/y more rapid loss at many locations in the inferior visual field.

CONCLUSIONS

Localized RNFL thinning is associated with sensitivity loss at corresponding locations in the visual field, and their rates of change are significantly correlated. Peripapillary RNFLT may be used to monitor localized changes caused by glaucoma that have measurable consequences for a patient's vision.

Between-Subject Variability in Healthy Eyes as a Primary Source of Structural-Functional Discordance in Patients With Glaucoma

Purpose

To test with an independent data set the finding that between-subject variability in healthy eyes is the primary source of structural–functional discordance in patients with glaucoma.

Methods

Neuroretinal rim area, retinal nerve fiber layer thickness, and perimetric data were analyzed for one eye in each of 55 control subjects and for 245 right eyes of patients in the United Kingdom Glaucoma Treatment Study. Data were gathered with the Heidelberg Retina Tomograph (HRT), Stratus Optical Coherence Tomograph (OCT), and Humphrey Field Analyzer (HFA). Discordance was quantified as width of the limits of agreement from a Bland-Altman analysis of depth of defect. The ratio of variances (F test) for the patient and control groups was computed for comparisons of HFA-OCT, HFA-HRT, and OCT-HRT. Bonferroni adjustment required P less than 0.017 for statistical significance. The discordance in the patients was also quantified as the 95% prediction interval computed from the discordance in controls using the Hood-Kardon model for the HFA-OCT comparison.

Results

The F ratio comparing discordance in patients and controls was 0.77, 1.43, and 1.32 for the HFA-OCT, HFA-HRT, and OCT-HRT comparisons with P values 0.88, 0.06, and 0.11, respectively. For the Hood-Kardon model, 4.7% of the patients had discordance outside the 95% prediction interval computed from the discordance in controls. Similar results were obtained when all comparisons were repeated for left eyes of patients.

Conclusions

These results confirm previous findings that between-subject variability in healthy eyes is the primary source of structural–functional discordance in patients with glaucoma, and extends this finding to a structural–structural comparison.

Evaluation of the Structure-Function Relationship in Glaucoma Using a Novel Method for Estimating the Number of Retinal Ganglion Cells in the Human Retina

PURPOSE

We developed a simple method for estimating the number of retinal ganglion cells (RGCs) in the human retina using optical coherence tomography (OCT), compared it to a previous approach, and demonstrated its potential for furthering our understanding of the structure-function relationship in glaucoma.

METHODS

Swept-source (ss) OCT data and 10-2 visual fields (VFs) were obtained from 43 eyes of 36 healthy controls, and 50 eyes of 50 glaucoma patients and suspects. Using estimates of RGC density from the literature and relatively few assumptions, estimates of the number of RGCs in the macula were obtained based on ssOCT-derived RGC layer thickness measurements.

RESULTS

The RGC estimates were in general agreement with previously published values derived from histology, whereas a prior method based on VF sensitivity did not agree as well with histological data and had significantly higher (P = 0.001) and more variable (P < 0.001) RGC estimates than the new method based on ssOCT. However, the RGC estimates of the new approach were not zero for extreme VF losses, suggesting that a residual, non-RGC contribution needs to be added. Finally, the new ssOCT-derived RGC estimates were significantly (P < 0.001 to P = 0.018) related to VF sensitivity (Spearman's ρ = 0.26-0.47), and, in contrast to claims made in prior studies, statistically significant RGC loss did not occur more often than statistically significant visual loss.

CONCLUSIONS

The novel method for estimating RGCs yields values that are closer to histological estimates than prior methods, while relying on considerably fewer assumptions. Although the value added for clinical applications is yet to be determined, this approach is useful for assessing the structure-function relationship in glaucoma.

Evaluation of a Method for Estimating Retinal Ganglion Cell Counts Using Visual Fields and Optical Coherence Tomography

PURPOSE

To evaluate the accuracy and generalizability of a published model that derives estimates of retinal ganglion cell (RGC) counts and relates structural and functional changes due to glaucoma.

METHODS

Both the Harwerth et al. nonlinear model (H-NLM) and the Hood and Kardon linear model (HK-LM) were applied to an independent dataset of frequency-domain optical coherence tomography and visual fields, consisting of 48 eyes of 48 healthy controls, 100 eyes of 77 glaucoma patients and suspects, and 18 eyes of 14 nonarteritic anterior ischemic optic neuropathy (ION) patients with severe vision loss. Using the coefficient of determination R2, the models were compared while keeping constant the topographic maps, specifically a map by Garway-Heath et al. and a separate map by Harwerth et al., which relate sensitivity test stimulus locations to corresponding regions around the optic disc. Additionally, simulations were used to evaluate the assumptions of the H-NLM.

RESULTS

Although the predictions of the HK-LM with the anatomically-derived Garway-Heath et al. map were reasonably good (R2 = 0.31-0.64), the predictions of the H-NLM were poor (R2 < 0) regardless of the map used. Furthermore, simulations of the H-NLM yielded results that differed substantially from RGC estimates based on histology from human subjects. Finally, the value-added of factors increasing the relative complexity of the H-NLM, such as assumptions regarding age- and stage-dependent corrections to structural measures, was unclear.

CONCLUSIONS

Several of the assumptions underlying the H-NLM should be revisited. Studies and models relying on the RGC estimates of the H-NLM should be interpreted with caution.

Enhancing Structure-Function Correlations in Glaucoma with Customized Spatial Mapping

PURPOSE

To determine whether the structure-function relationship in glaucoma can be strengthened by using more precise structural and functional measurements combined with individualized structure-function maps and custom sector selection on the optic nerve head (ONH).

DESIGN

Cross-sectional study.

PARTICIPANTS

One eye of each of 23 participants with glaucoma.

METHODS

Participants were tested twice. Visual fields were collected on a high-resolution 3° × 3° grid (164 locations) using a Zippy Estimation by Sequential Testing test procedure with uniform prior probability to improve the accuracy and precision of scotoma characterization relative to standard methods. Retinal nerve fiber layer (RNFL) thickness was measured using spectral-domain optical coherence tomography (OCT; 4 scans, 2 per visit) with manual removal of blood vessels. Individualized maps, based on biometric data, were used. To customize the areas of the ONH and visual field to correlate, we chose a 30° sector centered on the largest defect shown by OCT and chose visual field locations using the individualized maps. Baseline structure-function correlations were calculated between 24-2 locations (n = 52) of the first tested visual field and RNFL thickness from 1 OCT scan, using the sectors of the Garway-Heath map. We added additional data (averaged visual field and OCT, additional 106 visual field locations and OCT without blood vessels, individualized map, and customized sector) and recomputed the correlations.

MAIN OUTCOME MEASURES

Spearman correlation between structure and function.

RESULTS

The highest baseline correlation was 0.52 (95% confidence interval [CI], 0.13-0.78) in the superior temporal ONH sector. Improved measurements increased the correlation marginally to 0.58 (95% CI, 0.21-0.81). Applying the individualized map to the large, predefined ONH sectors did not improve the correlation; however, using the individualized map with the single 30° ONH sector resulted in a large increase in correlation to 0.77 (95% CI, 0.47-0.92).

CONCLUSIONS

Using more precise visual field and OCT measurements did not improve structure-function correlation in our cohort, but customizing the ONH sector and its associated visual field points substantially improved correlation. We suggest using customized ONH sectors mapped to individually relevant visual field locations to unmask localized structural and functional loss.

Contrast sensitivity perimetry and clinical measures of glaucomatous damage

Purpose

To compare conventional structural and functional measures of glaucomatous damage with a new functional measure—contrast sensitivity perimetry (CSP-2).

Methods

One eye each was tested for 51 patients with glaucoma and 62 age-similar control subjects using CSP-2, size III 24-2 conventional automated perimetry (CAP), 24-2 frequency-doubling perimetry (FDP), and retinal nerve fiber layer (RNFL) thickness. For superior temporal (ST) and inferior temporal (IT) optic disc sectors, defect depth was computed as amount below mean normal, in log units. Bland-Altman analysis was used to assess agreement on defect depth, using limits of agreement and three indices: intercept, slope, and mean difference. A criterion of p < 0.0014 for significance used Bonferroni correction.

Results

Contrast sensitivity perimetry-2 and FDP were in agreement for both sectors. Normal variability was lower for CSP-2 than for CAP and FDP (F > 1.69, p < 0.02), and Bland-Altman limits of agreement for patient data were consistent with variability of control subjects (mean difference, −0.01 log units; SD, 0.11 log units). Intercepts for IT indicated that CSP-2 and FDP were below mean normal when CAP was at mean normal (t > 4, p < 0.0005). Slopes indicated that, as sector damage became more severe, CAP defects for IT and ST deepened more rapidly than CSP-2 defects (t > 4.3, p < 0.0005) and RNFL defects for ST deepened more slowly than for CSP, FDP, and CAP. Mean differences indicated that FDP defects for ST and IT were on average deeper than RNFL defects, as were CSP-2 defects for ST (t > 4.9, p < 0.0001).

Conclusions

Contrast sensitivity perimetry-2 and FDP defects were deeper than CAP defects in optic disc sectors with mild damage and revealed greater residual function in sectors with severe damage. The discordance between different measures of glaucomatous damage can be accounted for by variability in people free of disease.

Morphological features and important parameters of large optic discs for diagnosing glaucoma

Purpose

To compare the optic disc parameters of glaucomatous eyes to those of non-glaucomatous eyes with large discs.

Methods

We studied 225 consecutive eyes with large optic discs (>2.82 mm2): 91 eyes with glaucoma and 134 eyes without glaucoma. An eye was diagnosed with glaucoma when visual field defects were detected by the Humphrey Field Analyzer. All of the Heidelberg Retina Tomograph II (HRT II) parameters were compared between the non-glaucomatous and glaucomatous eyes. A logistic regression analysis of the HRT II parameters was used to establish a new formula for diagnosing glaucoma, and the sensitivity and specificity of the Moorfields Regression Analysis (MRA) was compared to the findings made by our analyses.

Results

The mean disc area was 3.44±0.50 mm2 in the non-glaucomatous group and 3.40±0.52 mm2 in the glaucoma group. The cup area, cup volume, cup-to-disc area ratio, linear cup/disc ratio, mean cup depth, and the maximum cup depth were significantly larger in glaucomatous eyes than in the non-glaucomatous eyes. The rim area, rim volume, cup shape measurement, mean retinal nerve fiber layer (RNFL) thickness, and RFNL cross-sectional area were significantly smaller in glaucomatous eyes than in non-glaucomatous eyes. The cup-to-disc area ratio, the height variation contour (HVC), and the RNFL cross-sectional area were important parameters for diagnosing the early stage glaucoma, and the cup-to-disc area ratio and cup volume were useful for diagnosing advanced stage glaucoma in eyes with a large optic disc. The new formula had higher sensitivity and specificity for diagnosing glaucoma than MRA.

Conclusions

The cup-to-disc area ratio, HVC, RNFL cross-sectional area, and cup volume were important parameters for diagnosing glaucoma in eyes with a large optic disc. The important disc parameters to diagnose glaucoma depend on the stage of glaucoma in patients with large discs.

A perimetric test procedure that uses structural information

PURPOSE

To develop a perimetric test strategy, Structure Estimation of Minimum Uncertainty (SEMU), that uses structural information to drive stimulus choices.

METHODS

Structure Estimation of Minimum Uncertainty uses retinal nerve fiber layer (RNFL) thickness data as measured by optical coherence tomography to predict perimetric sensitivity. This prediction is used to set suprathreshold levels that then alter a prior probability distribution of the final test output. Using computer simulation, we studied SEMU's performance under three different patient error response conditions: No Error, Typical False Positive errors, and Extremely Unreliable patients. In experiment 1, SEMU was compared with an existing suprathreshold cum thresholding combination test procedure, Estimation of Minimum Uncertainty (EMU), on single visual field locations. We used these results to finalize SEMU parameters. In experiment 2, SEMU was compared with full threshold (FT) on 163 glaucomatous visual fields.

RESULTS

On individual locations, SEMU has similar accuracy to EMU, but is, on average, one presentation faster than EMU. For the typical false-positive error condition, SEMU has significantly lower error compared with FT (SEMU average 0.33 dB lower; p < 0.001) and the 90% measured sensitivity range for SEMU is also smaller than that for FT. For unreliable patients, however, FT has lower mean and SD of error. Structure Estimation of Minimum Uncertainty makes significantly fewer presentations than FT (1.08 presentation on average fewer in a typical false-positive condition; p < 0.001). Assuming that a location in the field is marked abnormal if it falls below the 5th percentile of normal, SEMU has a false-positive rate of less than 10% for all error conditions compared with FT's rate of 20% or more.

CONCLUSIONS

On average, simulations show that using RNFL information to guide stimulus placement in a perimetric test procedure maintains accuracy, improves precision, and decreases test duration for patients with less than 15% false-positive rates.

Assessing assumptions of a combined structure-function index

Purpose

Medeiros et al. developed a combined structure-function index for glaucoma by combining two ganglion cell models developed by Harwerth et al. The current study assessed assumptions of the Medeiros combined structure-function index by evaluating whether the two Harwerth models gave similar distributions of ganglion cells in an independent dataset.

Methods

The Harwerth models were applied to our previously published data for retinal nerve fibre layer (RNFL) thickness (Stratus OCT 3.4) and visual field sensitivities (24-2 SITA Standard) from one eye each of 51 patients with glaucoma and 62 age-similar control subjects free of eye disease. RNFL thicknesses and perimetric sensitivities were converted to ganglion cell numbers using the Harwerth model for perimetry and the Harwerth model for RNFL. These two estimates of ganglion cell number were compared for the inferior temporal (IT) and superior temporal (ST) sectors of the optic disc and the corresponding visual field locations. Comparisons were made with 14 visual field locations per sector (including a point in the macula for the inferior temporal sector) and with 13 locations (no point in the macula). Data for controls and patients were analysed separately, comparing mean values for RNFL perimetry models. Bonferroni correction was applied to control for repeated tests of significance. The difference between mean values for the RNFL and perimetry models was quantified by equating the means for controls through reduction of the assumed axon diameter used by the RNFL model.

Results

For the control group, the Harwerth RNFL model yielded smaller mean number of retinal ganglion cells than the Harwerth perimetry model, 23–47% lower (t > 13, p < 0.0001). This corresponded to mean axon diameters from 0.48 to 0.69 μm, with the smallest axons when the 14th location in the macula was included. With these new axon diameters, estimates of ganglion cell numbers for patients were still lower than for the RNFL model, by 19–28% (t > 6.5, p < 0.0001).

Conclusions

The Harwerth RNFL model consistently gave lower ganglion cell numbers than the Harwerth perimetry model, and this discordance persisted in patients even after reducing assumed axon diameter for controls. This finding contradicts the assumptions of the Medeiros structure-function index.

Relationships of retinal structure and humphrey 24-2 visual field thresholds in patients with glaucoma

PURPOSE

To determine relationships between spectral-domain optical coherence tomography (SD-OCT) derived regional damage to the retinal ganglion cell-axonal complex (RGC-AC) and visual thresholds for each location of the Humphrey 24-2 visual field, in all stages of open-angle glaucoma.

METHODS

Patients with early, moderate, and advanced glaucoma were recruited from a tertiary glaucoma clinic. Humphrey 24-2 and 9-field Spectralis SD-OCT were acquired for each subject. Individual OCT volumes were aligned, nerve fiber layer (NFL), ganglion cell and inner plexiform layers (GCL+IPL) cosegmented. These layers were then partitioned into 54 sectors corresponding to the 24-2 grid. A Support Vector Machine was trained independently for each sector to predict the sector threshold, using these structural properties.

RESULTS

One hundred twenty-two consecutive subjects, 43 early, 39 moderate, and 40 advanced, glaucoma were included (122 eyes). Average correlation coefficient (R) was 0.68 (0.47-0.82), and average root mean square error (RMSE) was 6.92 dB (3.93-8.68 dB). Prediction performance averaged over the entire field, superior hemifield, and inferior hemifield had R (RMSE) values of 0.77 (3.76), 0.80 (5.05), and 0.84 (3.80) dB, respectively.

CONCLUSIONS

Predicting individual 24-2 visual field thresholds from structural information derived from nine-field SD-OCT local NFL and GCL+IPL thicknesses using the RGC-AC concept is feasible, showing the potential for the predictive ability of SD-OCT structural information for visual function. Ultimately, it may be feasible to complement and reduce the burden of subjective visual field testing in glaucoma patients with predicted function derived objectively from OCT.

Relationship Between Optic Nerve Appearance and Retinal Nerve Fiber Layer Thickness as Explored with Spectral Domain Optical Coherence Tomography

PURPOSE

To study the relationship between the appearance of the optic nerve and the retinal nerve fiber layer (RNFL) thickness determined by spectral domain optical coherence tomography (OCT).

METHODS

Records from patients with spectral domain-OCT imaging in a neuro-ophthalmology practice were reviewed. Eyes with glaucoma/glaucoma suspicion, macular/optic nerve edema, pseudophakia, and with refractive errors > 6D were excluded. Optic nerve appearance by slit lamp biomicroscopy was related to the RNFL thickness by spectral domain-OCT and to visual field results.

RESULTS

Ninety-one patients (176 eyes; mean age: 49 ± 15 years) were included. Eighty-three eyes (47%) showed optic nerve pallor; 89 eyes (50.6%) showed RNFL thinning (sectoral or average peripapillary). Average peripapillary RNFL thickness in eyes with pallor (mean ± SD = 76 ± 17 μm) was thinner compared to eyes without pallor (91 ± 14 μm, P < 0.001). Optic nerve pallor predicted RNFL thinning with a sensitivity of 69% and a specificity of 75%. Optic nerve appearance predicted RNFL thinning (with a sensitivity and specificity of 81%) when RNFL had thinned by ∼ 40%. Most patients with pallor had RNFL thinning with (66%) or without (25%) visual field loss; the remainder had normal RNFL and fields (5%) or with visual field abnormalities (4%).

CONCLUSIONS

Optic nerve pallor as a predictor of RNFL thinning showed fair sensitivity and specificity, although it is optimally sensitive/specific only when substantial RNFL loss has occurred.

TRANSLATIONAL RELEVANCE

Finding an acceptable relationship between the optic nerve appearance by ophthalmoscopy and spectral domain-OCT RNFL measures will help the clinician's interpretation of the information provided by this technology, which is gaining momentum in neuro-ophthalmic research.

Prediction accuracy of a novel dynamic structure-function model for glaucoma progression

PURPOSE

To assess the prediction accuracy of a novel dynamic structure-function (DSF) model to monitor glaucoma progression.

METHODS

Longitudinal data of paired rim area (RA) and mean sensitivity (MS) from 220 eyes with ocular hypertension or primary open-angle glaucoma enrolled in the Diagnostic Innovations in Glaucoma Study or the African Descent and Glaucoma Evaluation Study were included. Rim area and MS were expressed as percent of mean normal based on an independent dataset of 91 healthy eyes. The DSF model uses centroids as estimates of the current state of the disease and velocity vectors as estimates of direction and rate of change over time. The first three visits were used to predict the fourth visit; the first four visits were used to predict the fifth visit, and so on up to the 11th visit. The prediction error (PE) was compared to that of ordinary least squares linear regression (OLSLR) using Wilcoxon signed-rank test.

RESULTS

For predictions at visit 4 to visit 7, the average PE for the DSF model was significantly lower than OLSLR by 1.19% to 3.42% of mean normal. No significant difference was observed for the predictions at visit 8 to visit 11. The DSF model had lower PE than OLSLR for 70% of eyes in predicting visit 4 and approximately 60% in predicting visits 5, 6, and 7.

CONCLUSIONS

The two models had similar prediction capabilities, and the DSF model performed better in shorter time series. The DSF model could be clinically useful when only limited follow-ups are available. (ClinicalTrials.gov numbers, NCT00221923, NCT00221897.).

Choice of Stimulus Range and Size Can Reduce Test-Retest Variability in Glaucomatous Visual Field Defects

PURPOSE

To develop guidelines for engineering perimetric stimuli to reduce test-retest variability in glaucomatous defects.

METHODS

Perimetric testing was performed on one eye for 62 patients with glaucoma and 41 age-similar controls on size III and frequency-doubling perimetry and three custom tests with Gaussian blob and Gabor sinusoid stimuli. Stimulus range was controlled by values for ceiling (maximum sensitivity) and floor (minimum sensitivity). Bland-Altman analysis was used to derive 95% limits of agreement on test and retest, and bootstrap analysis was used to test the hypotheses about peak variability.

RESULTS

Limits of agreement for the three custom stimuli were similar in width (0.72 to 0.79 log units) and peak variability (0.22 to 0.29 log units) for a stimulus range of 1.7 log units. The width of the limits of agreement for size III decreased from 1.78 to 1.37 to 0.99 log units for stimulus ranges of 3.9, 2.7, and 1.7 log units, respectively (F = 3.23, P < 0.001); peak variability was 0.99, 0.54, and 0.34 log units, respectively (P < 0.01). For a stimulus range of 1.3 log units, limits of agreement were narrowest with Gabor and widest with size III stimuli, and peak variability was lower (P < 0.01) with Gabor (0.18 log units) and frequency-doubling perimetry (0.24 log units) than with size III stimuli (0.38 log units).

CONCLUSIONS

Test-retest variability in glaucomatous visual field defects was substantially reduced by engineering the stimuli.

TRANSLATIONAL RELEVANCE

The guidelines should allow developers to choose from a wide range of stimuli.

Multivariable logistic regression model: a novel mathematical model that predicts visual field sensitivity from macular ganglion cell complex thickness in glaucoma

Purpose

To design a mathematical model that can predict the relationship between the ganglion cell complex (GCC) thickness and visual field sensitivity (VFS) in glaucoma patients.

Design

Retrospective cross-sectional case series.

Method

Within 3 months from VFS measurements by the Humphrey field analyzer 10-2 program, 83 eyes underwent macular GCC thickness measurements by spectral-domain optical coherence tomography (SD-OCT). Data were used to construct a multiple logistic model that depicted the relationship between the explanatory variables (GCC thickness, age, sex, and spherical equivalent of refractive errors) determined by a regression analysis and the mean VFS corresponding to the SD-OCT scanned area. Analyses were performed in half or 8 segmented local areas as well as in whole scanned areas. A simple logistic model that included GCC thickness as the single explanatory variable was also constructed. The ability of the logistic models to depict the real GCC thickness/VFS in SAP distribution was analyzed by the χ² test of goodness-of-fit. The significance of the model effect was analyzed by analysis of variance (ANOVA).

Results

Scatter plots between the GCC thickness and the mean VFS showed sigmoid curves. The χ² test of goodness-of-fit revealed that the multiple logistic models showed a good fit for the real GCC thickness/VFS distribution in all areas except the nasal-inferior-outer area. ANOVA revealed that all of the multiple logistic models significantly predicted the VFS based on the explanatory variables. Although simple logistic models also exhibited significant VFS predictability based on the GCC thickness, the model effect was less than that observed for the multiple logistic models.

Conclusions

The currently proposed logistic models are useful methods for depicting relationships between the explanatory variables, including the GCC thickness, and the mean VFS in glaucoma patients.

On improving the use of OCT imaging for detecting glaucomatous damage

AIMS

To describe two approaches for improving the detection of glaucomatous damage seen with optical coherence tomography (OCT).

METHODS

The two approaches described were: one, a visual analysis of the high-quality OCT circle scans and two, a comparison of local visual field sensitivity loss to local OCT retinal ganglion cell plus inner plexiform (RGC+) and retinal nerve fibre layer (RNFL) thinning. OCT images were obtained from glaucoma patients and suspects using a spectral domain OCT machine and commercially available scanning protocols. A high-quality peripapillary circle scan (average of 50), a three-dimensional (3D) scan of the optic disc, and a 3D scan of the macula were obtained. RGC+ and RNFL thickness and probability plots were generated from the 3D scans.

RESULTS

A close visual analysis of a high-quality circle scan can help avoid both false positive and false negative errors. Similarly, to avoid these errors, the location of abnormal visual field points should be compared to regions of abnormal RGC+ and RNFL thickness.

CONCLUSIONS

To improve the sensitivity and specificity of OCT imaging, high-quality images should be visually scrutinised and topographical information from visual fields and OCT scans combined.

Correlation between early retinal nerve fiber layer loss and visual field loss determined by three different perimetric strategies: white-on-white, frequency-doubling, or flicker-defined form perimetry

PURPOSE

To compare the significance of white-on-white standard automated perimetry (SAP), matrix frequency doubling technology (FDT), and flicker-defined form perimetry (FDF) for early detection of nerve fiber layer loss in early glaucoma patients.

METHODS

Fifty-one healthy controls and 40 patients with early glaucomatous nerve fiber loss were enrolled in this study. Patients had retinal nerve fiber layer (RNFL) imaging and visual field testing by SAP, FDT matrix, and FDF perimetry at the same visit. Visual field defects were confirmed with two or more consecutive examinations by the same types of perimetry. Significant retinal nerve fiber layer loss and thus early glaucoma was defined with the reference to the RNFL thickness deviation map. The sensitivity, specificity, correlation, MD (mean deviation) and PSD (pattern standard deviation) visual field indexes, and area under the receiver operating characteristic curve (AUC) of MD and PSD of the perimetries were compared.

RESULTS

There was a significant difference in nerve fiber layer thickness between healthy patients (97.7 ± 1.34 μm and patients with early glaucoma (84.1 ± 1.58 μm) (p < 0.001). Taking all patients with early glaucoma into consideration, the sensitivity was highest for FDF perimetry (87 %), followed by FDT matrix (62.5 %), and then SAP (40 %). The specificity was 69.2 % for SAP, 62.8 % for FDT matrix, and 38.4 % for FDF perimetry. MD (mean deviation) and PSD (pattern standard deviation) in FDF and FDT matrix were significantly different between patients with RNFL loss and those without (p < 0.05), while no difference could be found in SAP. The AUCs of MD followed a similar pattern, with FDF and FDT matrix perimetry having a suitable AUC of >0.6. AUCs of PSD were not reliable in all of the three VF devices.

CONCLUSIONS

The sensitivity for detection of RNFL loss in early glaucoma seems to be higher in FDF and FDT matrix than SAP perimetry, while specifity was highest in SAP. Thus, simultaneous performance of FDF/FDT matrix and SAP perimetry seems beneficial for the correct diagnosis of early glaucoma in patients.

Ganglion cell layer-inner plexiform layer thickness and vision loss in young children with optic pathway gliomas

PURPOSE

To determine if measures of macular ganglion cell layer-inner plexiform layer (GCL-IPL) thickness can discriminate between children with and without vision loss (visual acuity or field) from their optic pathway glioma (OPG) using spectral-domain optical coherence tomography (SD-OCT).

METHODS

Children with OPGs (sporadic or secondary to neurofibromatosis type 1) enrolled in a prospective study of SD-OCT were included if they were cooperative for vision testing and macular SD-OCT images were acquired. Manual segmentation of the macular GCL-IPL and macular retinal nerve fiber layer (RNFL) was performed using elliptical annuli with diameters of 1.5, 3.0, and 4.5 mm. Logistic regression assessed the ability of GCL-IPL and RNFL thickness measures (micrometers) to differentiate between the normal and abnormal vision groups.

RESULTS

Forty-seven study eyes (normal vision = 31, abnormal vision = 16) from 26 children with OPGs were included. Median age was 5.3 years (range, 2.5-12.8). Thickness of all GCL-IPL and RNFL quadrants differed between the normal and abnormal vision groups (P < 0.01). All GCL-IPL measures demonstrated excellent discrimination between groups (area under the curve [AUC] > 0.90 for all diameters). Using the lower fifth percentile threshold, the number of abnormal GCL-IPL inner macula (3.0 mm) quadrants achieved the highest AUC (0.989) and was greater than the macula RNFL AUCs (P < 0.05).

CONCLUSIONS

Decreased GCL-IPL thickness (<fifth percentile) can discriminate between children with and without vision loss from their OPG. Ganglion cell layer-inner plexiform layer thickness could be used as a surrogate marker of vision in children with OPGs.

A method to estimate the amount of neuroretinal rim tissue in glaucoma: comparison with current methods for measuring rim area

PURPOSE

To test whether the minimum rim area assessed by spectral domain optical coherence tomography (SD-OCT), based on the shortest distance from the Bruch membrane opening (BMO) to the inner limiting membrane, corresponds more closely to retinal nerve fiber layer (RNFL) thickness and visual field mean deviation (MD) than current rim measures in early glaucoma.

DESIGN

Prospective cross-sectional study.

METHODS

We studied 221 participants with non-endstage glaucoma or high-risk ocular hypertension and performed standard automated perimetry. We received SD-OCT and confocal scanning laser ophthalmoscopy (CSLO) scans on the same day. Rim area measured by CSLO was compared with 3 SD-OCT rim measures from radial B-scans: horizontal rim area between BMO and inner limiting membrane within the BMO plane; mean minimum rim width (BMO-MRW); and minimum rim area (BMO-MRA) optimized within sectors and then summed. Correlations between these measures and either MD from perimetry or RNFL thickness from SD-OCT were compared using the Steiger test.

RESULTS

RNFL thickness was better correlated with BMO-MRA (r = 0.676) or BMO-MRW (r = 0.680) than with either CSLO rim area (r = 0.330, P < 0.001) or horizontal rim area (r = 0.482, P < 0.001). MD was better correlated with BMO-MRA (r = 0.534) or BMO-MRW (r = 0.546) than with either CSLO rim area (r = 0.321, P < 0.001) or horizontal rim area (0.403, P < 0.001). The correlation between MD and RNFL thickness was r = 0.646.

CONCLUSIONS

Minimum rim measurements from SD-OCT are significantly better correlated to both RNFL thickness and MD than rim measurements within the BMO plane or based on the clinical disc margin. They provide new structural parameters for both diagnostic and research purposes in glaucoma.