Identification of progressive glaucomatous visual field loss

Efficacy of Smoothing Algorithms to Enhance Detection of Visual Field Progression in Glaucoma

Purpose

To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models.

Design

Longitudinal cohort study.

Subjects

7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits.

Methods

Vsual field thresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data.

Main Outcome Measures

The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models.

Results

The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data.

Conclusions

Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting.

Financial Disclosures

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

Utility of targeted mean total deviation trend analysis for detecting progressive visual field changes in early-to-moderate stage glaucoma

OBJECTIVES

To evaluate the clinical utility of trend-based analysis of the targeted mean total deviation (TMTD) by comparing its rates of visual field (VF) change and sensitivities of detecting VF progression with those of the mean total deviation (mTD) in the global and hemifield VF area in early to-moderate glaucoma patients.

METHODS

A single eye from 139 open-angle glaucoma patients with hemifield VF defects and a minimum two year follow-up were retrospectively evaluated. The TMTD was estimated by averaging the total deviation (TD) values after excluding VF points that had a threshold sensitivity of <0 dB in three baseline tests, and the mTD by averaging the entire VF TD values. The study patients were classified as VF progressors vs. non-progressors using both event- and trend-based analysis. The rates of change and ratios of progression detection were compared between TMTD and mTD.

RESULTS

This study included 49 VF progressors and 90 non-progressors. Slopes for the global and VF-affected hemifield TMTD were significantly faster than those for the mTD in each subgroup and in the entire cohort (P < 0.001). Trend-based TMTD analysis detected VF progression in greater proportion than either trend-based mTD or event-based analysis (38.1% vs. 30.2% vs. 27.3%, respectively: VF affected hemifields).

CONCLUSIONS

The rates of change in the TMTD are significantly faster than those for the mTD globally and in the VF-affected hemifields. Trend-based TMTD analysis shows greater sensitivity for detecting VF progression than trend-based mTD or event-based analysis in early-to-moderate glaucoma patients with hemifield VF loss.

Validation of Rates of Mean Deviation Change as Clinically Relevant End Points for Glaucoma Progression

PURPOSE

To investigate whether rates of standard automated perimetry (SAP) mean deviation (MD) over an initial 2-year follow-up period were predictive of events of visual field progression over an extended follow-up.

DESIGN

Longitudinal, prospective, observational study.

PARTICIPANTS

Two hundred forty-six eyes of 168 patients with glaucoma followed up every 6 months for up to 5 years.

METHODS

Patients were required to have a minimum of 5 reliable SAP tests during the first 2 years of follow-up. Events of progression were evaluated using 2 methods: Guided Progression Analysis (GPA; Carl Zeiss Meditec, Inc) and a United States Food and Drug Administration (FDA)-suggested end point. The date of the first test showing progression after the first 2 years was considered to be the event date. Rates of change in SAP MD were calculated for the first 2 years of follow-up, and joint longitudinal survival models were used to assess the risk of faster initial MD loss for subsequent progression based on each event analysis.

MAIN OUTCOME MEASURE

Risk of having an event of progression based on initial rates of SAP MD change.

RESULTS

Fifty-six eye (22.8%) showed an event of progression by the GPA and 51 eyes (20.7%) did so by the FDA end point. Each 0.1-dB/year faster rate of SAP MD loss in the first 2 years was associated with a 26% increase in risk of a GPA progression end point developing (R2 = 76%) and 32% risk of an FDA-based end point developing (R2 = 83%). A reduction of 30% in the rate of MD change in the first 2 years was associated with a 20% reduction in the cumulative probability of a progression event developing over 5 years of follow-up.

CONCLUSIONS

Rates of SAP MD change for eyes with glaucoma calculated over the initial 2 years of follow-up were strongly predictive of events of progression over subsequent follow-up. Our findings give support for the use of slopes of MD change as suitable end points of progression in clinical trials.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

A deep learning model incorporating spatial and temporal information successfully detects visual field worsening using a consensus based approach

Glaucoma is a leading cause of irreversible blindness, and its worsening is most often monitored with visual field (VF) testing. Deep learning models (DLM) may help identify VF worsening consistently and reproducibly. In this study, we developed and investigated the performance of a DLM on a large population of glaucoma patients. We included 5099 patients (8705 eyes) seen at one institute from June 1990 to June 2020 that had VF testing as well as clinician assessment of VF worsening. Since there is no gold standard to identify VF worsening, we used a consensus of six commonly used algorithmic methods which include global regressions as well as point-wise change in the VFs. We used the consensus decision as a reference standard to train/test the DLM and evaluate clinician performance. 80%, 10%, and 10% of patients were included in training, validation, and test sets, respectively. Of the 873 eyes in the test set, 309 [60.6%] were from females and the median age was 62.4; (IQR 54.8-68.9). The DLM achieved an AUC of 0.94 (95% CI 0.93-0.99). Even after removing the 6 most recent VFs, providing fewer data points to the model, the DLM successfully identified worsening with an AUC of 0.78 (95% CI 0.72-0.84). Clinician assessment of worsening (based on documentation from the health record at the time of the final VF in each eye) had an AUC of 0.64 (95% CI 0.63-0.66). Both the DLM and clinician performed worse when the initial disease was more severe. This data shows that a DLM trained on a consensus of methods to define worsening successfully identified VF worsening and could help guide clinicians during routine clinical care.

[Static automated perimetry in the diagnosis of glaucoma. Assessment of disease progression]

There are several ways to assess glaucoma progression using standard automated perimetry. Most often, ophthalmologists evaluate the stability of visual functions manually when comparing several study protocols. The advantages of clinical assessment are ease of implementation and the ability to interpret data from any device. The main disadvantage of this method is its subjectivity. There are many available automated methods for assessing disease progression involving Humphrey Field Analyzer and Octopus perimeters. Event analysis allows determining glaucoma progression at the time of examination, with consideration of the possible physiological fluctuations in light sensitivity. Trend analysis of perimetric indices makes it possible to assess the rate of glaucoma progression and forecast the trend of changes in visual functions over the next five years. All these methods for assessing progression have certain advantages and disadvantages and cannot be considered ideal. Pointwise and cluster trend analysis are more sensitive in early glaucoma and are being actively researched and developed. These methods have great potential, although they are not yet sufficiently available in clinical practice.

Visual Field Endpoints for Neuroprotective Trials: A Case for AI-Driven Patient Enrichment

PURPOSE

To evaluate whether an artificial intelligence (AI) model can better select candidates that would demonstrate visual field (VF) progression, in order to shorten the duration or the number of patients needed for a clinical trial.

DESIGN

Retrospective cohort study.

METHODS

7428 eyes of 3871 patients from the University of Washington Department of Ophthalmology VF Dataset were included. Progression was defined as at least 5 locations with >7 dB of change compared with baseline on 2 consecutive tests. Progression for all patients, a subgroup of the fastest progressing based on survival curves, and patients selected based on an elastic net Cox regression model were compared. The model was trained on pointwise threshold deviation values of the first VF, age, gender, laterality, and the mean total deviation (MD) at baseline.

RESULTS

A total of 13% of all patients met the criteria for progression at 5 years. Differences in survival were observed when stratified by MD and age (P < .0001). Those at risk of progression included patients aged 60 to 80 years with an initial MD < -5.0. This subgroup decreased the sample size required to detect progression compared with the entire cohort. The AI model-selected patients required the lowest number of patients for all effect sizes and trial lengths. For a trial length of 3 years and effect size of 30%, the number of patients required was 1656 (95% CI, 1638-1674), 903 (95% CI, 884-922), and 636 (95% CI, 625-646) for the entire cohort, the subgroup, and the model-selected patients, respectively.

CONCLUSION

An AI model can identify high-risk patients to substantially reduce the number of patients needed or study duration required to meet clinical trial endpoints.

Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Central 10-2 Tests

We investigated the influence of aging on the reliability indices of visual field (VF) testing using a large dataset of central 10-2 program tests, including 6674 VF tests, which consisted of 1782 eyes of 1094 Japanese subjects (the mean age ± standard deviation was 66.6 ± 14.1 years). All of the combinations for each parameter, except for the pairs between age and fixation losses (FLs) or false positives (FPs) and between pattern standard deviation (PSD) and FPs, had significant correlations (p < 0.0001). Among the reliability indices, the false negatives (FNs) had the strongest correlation against age (the correlation coefficient was ρ = 0.21). Each reliability index changes differently with aging. The FLs were the highest in the first 10 s and remained constant after 20 s. The FNs remained constant for 60 s and rose steeply after 70 s. The FPs reached their highest value in 10 s and remained constant after 40 s. In mixed-effect regression analyses in 40-year-old or older subjects, older age was significantly associated with higher FNs (p < 0.0001) but not with FLs (p = 0.9014) and FPs (p = 0.9267). Compared to central 30-2 VF testing, central 10-2 VF tests were associated with smaller FLs (p < 0.0001) and FPs (p < 0.0001). In central 10-2 testing, age-related deterioration was seen in FNs but not in FLs and FPs. Choosing the 10-2 program over the 30-2 program can be effective in reducing the FL, especially in older cases with severe VF loss. This study highlighted the relationships between age and each reliability index in central 10-2 VF testing.

Evaluating Visual Field Progression in Advanced Glaucoma Using Trend Analysis of Targeted Mean Total Deviation

PURPOSE

Trend analysis of visual field (VF) global indices may underestimate the rate of progression in severe glaucoma because of the influence of test points without detectable sensitivity. To test this hypothesis, we compared the rates of change of VF global indices with and without exclusion of undetectable points at various disease stages.

MATERIALS AND METHODS

Six hundred and forty-eight eyes of 366 glaucoma patients with 8 or more reliable 30-2 standard automated perimetry over more than 2 years were enrolled. We calculated targeted mean total deviation (TMTD) by averaging total deviation except points which were consistently undetectable in 3 baseline tests. Eyes were classified as early (≥-6 dB), moderate (-6 dB to -12 dB), advanced (-12 dB to -20 dB), and severe (<-20 dB) based on baseline mean deviation (MD). The rates of change of MD and TMTD in each stage were statistically compared.

RESULTS

Mean age±SD at baseline was 56.9±11.9 years. The MD slope (-0.34 dB/y) in severe glaucoma was significantly slower than TMTD slope (-0.42 dB/y, P=0.028) and was slower than MD slopes in the other stages. Difference between MD slopes and TMTD slopes was most prominent in eyes with MD values less than -25 dB (P=0.002).

CONCLUSIONS

Undetectable locations in eyes with severe glaucoma may underestimate the rates of VF progression. Trend analysis of TMTD rather than global indices offers a practical and simple approach for alleviating underestimation of VF progression in severe glaucoma.

Structure-function analysis of MP3 microperimetry versus Octopus perimetry in central glaucomatous visual field defects

INTRODUCTION

To compare the structure-function relationship with microperimetry and Octopus perimetry in primary open angle glaucoma (POAG) patients with central visual field (VF) defects.

METHODS

40 eyes of 24 patients with POAG were enrolled. Circumpapillary retinal nerve fiber layer (cpRNFL) analysis measured by spectral-domain optical coherence tomography (SD-OCT) of the superotemporal, temporal, and inferotemporal optic nerve head (ONH) sectors were related to corresponding microperimetric and Octopus VF clusters using the G2 grid-pattern with dynamic strategy, respectively. The structure-function relationships of both devices were assessed via a segmented regression, as well as linear regression across overall SD-OCT cpRNFL values and outside normative (<1%) SD-OCT cpRNFL values.

RESULTS

Linear and segmented regression fits were similar with both devices. Across overall cpRNFL sectorial values, structure-function relations for the superotemporal, temporal and inferotemporal sectors were R2=0.176 (p=<0.001), R2=0.008 (p=0.069), and R2=0.294 (p=<0.001) for microperimetry, and R2= 0.189 (p=<0.001), R2= 0.020 (p=0.002), and R2= 0.326 (p=<0.001) for Octopus perimetry. For corresponding values outside normative limits (<1%), the relationships were R2=0.113 (p=<0.001), R2=0.001 (p=0.836), and R2=0.420 (p=<0.001) for microperimetry, and R2= 0.192 (p=<0.001), R2= 0.002, (p=0.336), and R2= 0.366 (p=<0.001) for Octopus perimetry.

DISCUSSION/CONCLUSION

Structure-function analysis was similar for both devices. Fundus-tracking should be further evaluated in a longitudinal setting in patients affected by glaucoma.

Real-World Analysis of the Aging Effects on Visual Field Reliability Indices in Humans

Relationships between age and visual field (VF) reliability indices were investigated using a large real-world dataset (42,421 VF data points from 11,525 eyes of 5930 subjects). All VFs tested and stored at Shimane University Hospital between 1988 and 2019 were exported. Correlations between age, mean deviation (MD), pattern standard deviation (PSD), and reliability indices including fixation losses (FLs), false negatives (FNs), and false positives (FPs) were analyzed. The mean ± standard deviation age was 65.0 ± 15.1 years; MD—−6.9 ± 8.1 decibels (dB); PSD—6.3 ± 4.6 dB; FL—8.6 ± 11.7%; FN—5.3 ± 8.3%; and FP—2.6 ± 5.0%. Univariate analyses showed strong associations between age and FNs (correlation coefficient, ρ = 0.20, p < 0.0001) and MD (ρ = −0.21, p < 0.0001). All FLs, FNs, and FPs were lowest during the third decade (20–29 years) of life. FLs were elevated consistently after that decade, and FNs were elevated sharply after the seventh decade. FPs were relatively stable after the fourth decade (30–39 years). Mixed-effect regression analyses in subjects 40 years and older showed that older age was associated with worse FLs (p < 0.0001) and FNs (p < 0.0001) but not FPs (p = 0.4126). Aging affects FLs and FNs with different modes but had minimal effects on FPs. Decreased VF sensitivity, deteriorated macular function, and technical difficulties with testing may be mechanisms of age-related changes in FLs and FNs.

Macular Pigment Response to Lutein, Zeaxanthin, and Meso-zeaxanthin Supplementation in Open-Angle Glaucoma

Purpose

To evaluate macular pigment response to carotenoid supplementation in glaucomatous eyes.

Design

Double-masked, randomized, placebo-controlled clinical trial, the European Nutrition in Glaucoma Management Study (ClinicalTrials.gov identifier, NCT04460365).

Participants

Sixty-two participants (38 men, 24 women) with a diagnosis of open-angle glaucoma were enrolled. Forty-two were randomized to receive the active supplement, 20 participants were allocated to placebo.

Methods

Macular pigment optical density (MPOD) was measured by autofluorescence using the Heidelberg Spectralis scanning laser ophthalmoscope. Macular pigment optical density volume within the central 6° of retinal eccentricity as well as MPOD at 0.23°, 0.51°, 0.74°, and 1.02° were recorded at baseline and at 6-month intervals over 18 months. Visual function was assessed using visual acuity, mesopic and photopic contrast sensitivity under glare conditions, photo stress recovery time, microperimetry, and Glaucoma Activities Limitation 9 questionnaire. Advanced glaucoma module scans of retinal nerve fiber layer thickness and ganglion cell complex thickness over the central 6° of retinal eccentricity also were completed at each study visit.

Main Outcome Measures

Change in MPOD after supplementation with 10 mg lutein, 2 mg zeaxanthin, and 10 mg meso-zeaxanthin or placebo over 18 months.

Results

A mixed-model repeated measures analysis of variance revealed a statistically significant increase in MPOD volume (significant time effect: F(3,111) = 89.31, mean square error (MSE) = 1656.9; P < 0.01). Post hoc t tests revealed a significant difference in MPOD volume at each study visit for the treatment group (P < 0.01 for all), but no change in the placebo group (P > 0.05 for all). A statistically significant increase in mesopic contrast sensitivity under glare conditions was noted at 18 months in the treatment group, but not placebo. No other structural or functional changes were observed. No serious adverse events were noted during the trial.

Conclusions

Macular pigment can be augmented in glaucomatous eyes by supplementation with a formulation containing the carotenoids lutein, zeaxanthin, and meso-zeaxanthin. The greatest relative benefit was observed in those with the lowest baseline levels, but increases were noted across all participants and each retinal eccentricity. The potential benefits of MP augmentation for macular health in glaucoma merit further long-term evaluation.

Predicting eyes at risk for rapid glaucoma progression based on an initial visual field test using machine learning

OBJECTIVE

To assess whether machine learning algorithms (MLA) can predict eyes that will undergo rapid glaucoma progression based on an initial visual field (VF) test.

DESIGN

Retrospective analysis of longitudinal data.

SUBJECTS

175,786 VFs (22,925 initial VFs) from 14,217 patients who completed ≥5 reliable VFs at academic glaucoma centers were included.

METHODS

Summary measures and reliability metrics from the initial VF and age were used to train MLA designed to predict the likelihood of rapid progression. Additionally, the neural network model was trained with point-wise threshold data in addition to summary measures, reliability metrics and age. 80% of eyes were used for a training set and 20% were used as a test set. MLA test set performance was assessed using the area under the receiver operating curve (AUC). Performance of models trained on initial VF data alone was compared to performance of models trained on data from the first two VFs.

MAIN OUTCOME MEASURES

Accuracy in predicting future rapid progression defined as MD worsening more than 1 dB/year.

RESULTS

1,968 eyes (8.6%) underwent rapid progression. The support vector machine model (AUC 0.72 [95% CI 0.70-0.75]) most accurately predicted rapid progression when trained on initial VF data. Artificial neural network, random forest, logistic regression and naïve Bayes classifiers produced AUC of 0.72, 0.70, 0.69, 0.68 respectively. Models trained on data from the first two VFs performed no better than top models trained on the initial VF alone. Based on the odds ratio (OR) from logistic regression and variable importance plots from the random forest model, older age (OR: 1.41 per 10 year increment [95% CI: 1.34 to 1.08]) and higher pattern standard deviation (OR: 1.31 per 5-dB increment [95% CI: 1.18 to 1.46]) were the variables in the initial VF most strongly associated with rapid progression.

CONCLUSIONS

MLA can be used to predict eyes at risk for rapid progression with modest accuracy based on an initial VF test. Incorporating additional clinical data to the current model may offer opportunities to predict patients most likely to rapidly progress with even greater accuracy.

Recent developments in perimetry: test stimuli and procedures

Automated perimetry has evolved substantially in recent years, in part due to modern computer technology that enables more complex visual stimuli and test procedures to be realised than those incorporated in traditional white-on-white luminance increment perimetry. This paper reviews briefly a number of advances in automated perimetry. The review includes discussion of new test types: frequency doubling technology perimetry, short wavelength automated perimetry, flicker perimetry, high-pass resolution perimetry and rarebit perimetry. Test algorithms applied to perimetry such as zippy estimation of sequential thresholds (ZEST), Swedish interactive thresholding algorithm (SITA), tendency-oriented perimetry (TOP) and multi-sampling supra-threshold perimetry are also discussed.

Investigating the clinical usefulness of definitions of progression with 10-2 visual field

BACKGROUND/AIM

To investigate the clinical validity of the Guided Progression Analysis definition (GPAD) and cluster-based definition (CBD) with the Humphrey Field Analyzer 10-2 test in diagnosing glaucomatous visual field (VF) progression, and to introduce a novel definition with optimised specificity by combining the 'any-location' and 'cluster-based' approaches (hybrid definition).

METHODS

64 400 stable glaucomatous VFs were simulated from 664 pairs of 10-2 tests (10 sets × 10 VF series × 664 eyes; data set 1). Using these simulated VFs, the specificity to detect progression and the effects of changing the parameters (number of test locations or consecutive VF tests, and percentile cut-off values) were investigated. The hybrid definition was designed as the combination where the specificity was closest to 95.0%. Subsequently, another 5000 actual glaucomatous 10-2 tests from 500 eyes (10 VFs each) were collected (data set 2), and their accuracy (sensitivity, specificity and false positive rate) and the time needed to detect VF progression were evaluated.

RESULTS

The specificity values calculated using data set 1 with GPAD and CBD were 99.6% and 99.8%. Using data set 2, the hybrid definition had a higher sensitivity than GPAD and CBD, without detriment to the specificity or false positive rate. The hybrid definition also detected progression significantly earlier than GPAD and CBD (at 3.1 years vs 4.2 years and 4.1 years, respectively).

CONCLUSIONS

GPAD and CBD had specificities of 99.6% and 99.8%, respectively. A novel hybrid definition (with a specificity of 95.5%) had higher sensitivity and enabled earlier detection of progression.

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

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

Detection of Functional Deterioration in Glaucoma by Trend Analysis Using Overlapping Clusters of Locations

Purpose

Cluster trend analysis detects glaucomatous deterioration within predefined subsets (clusters) of visual field locations. However, it may miss small defects straddling boundaries between the clusters. This study assesses whether simultaneously using a second set of clusters, overlapping the first, could improve progression detection.

Methods

Deterioration in eyes with or at risk of glaucomatous visual field loss was "detected" by mean deviation (MD) on the first visit at which the P value from linear regression over time was below the fifth percentile of its permutation distribution. Similarly, P values were calculated for each of 10 predefined nonoverlapping clusters of locations, or 21 overlapping clusters; deterioration was "detected" when the Nth-smallest P value was below the fifth percentile of its permutation distribution, for different N. Times to detect deterioration were compared using survival models.

Results

Biannual series of ≥5 visual fields (mean = 14) were available for 420 eyes of 213 participants. Deterioration of 33% of eyes was detected earliest using N = 1 overlapping cluster in 3.3 years (95% confidence interval 2.7-4.6 years); or N = 2 nonoverlapping clusters in 3.3 years (2.7-5.0) (comparison P = 0.654). There was also no significant difference in the probability that deterioration would be confirmed (92.8% vs. 94.4%, P = 0.289). Both overlapping and nonoverlapping clusters detected deterioration significantly sooner than MD (4.5 years, P ≤ 0.001).

Conclusions

After equalizing specificity, overlapping clusters of locations did not significantly reduce the time to detect deterioration compared with nonoverlapping clusters.

Translational Relevance

Cluster trend analyses detected deterioration sooner than global analyses even when defects straddled cluster borders.

Factors Associated with Midterm Visual Field Variability in Patients with Stable Glaucoma

Purpose

To evaluate factors associated with midterm visual field (VF) variability in stable glaucoma patients in Brazil.

Methods

This retrospective observational study included 59 eyes of 39 stable glaucoma patients. Baseline data assessed were age, gender, educational level, intraocular pressure (IOP), central corneal thickness, best-corrected visual acuity, spherical equivalent, number of hypotensive eye drops, type of glaucoma, number of VFs performed, follow-up in years, lens status, visual field index (VFI) values from the last 5 VF (standard automated perimetry (SAP)) tests, the presence or absence of central scotoma in the VF test, and the level of glaucomatous damage according to the VF mean deviation (MD) index of the last VFs. The 5 latest VFI scores were used to calculate the mean, the standard deviation (SD), and the coefficient of variation (CV). We divided the eyes into 2 groups, being group 1 comprised by the 29 eyes presenting the lowest CV values and group 2 comprised by the 30 eyes presenting the highest CV values. GEE models were used to compare the CV and demographic and clinical parameters of all participants.

Results

Mean age of all subjects was 65.8 ± 10.1 years. 54.0% were women. Average SAP MD values for groups 1 and 2 were −2.8 ± 3.1 dB and −6.2 ± 4.1 dB, respectively (P=0.006). Average SAP VFI values for groups 1 and 2 were 95.6 ± 5.9% and 85.9 ± 11.3%, respectively (P=0.002). There was a statistically significant association between CV and SAP MD values (P=0.006). A worse SAP MD and VFI were associated with a higher CV. In addition, even adjusting for potential confounding factors (age and level of education), the association between CV and the SAP MD and between CV and VFI remained significant (P ≤ 0.010).

Conclusion

Glaucomatous patients with worse VF sensitivity scores (both MD and VFI indices) present higher VF test variability.

Quantification of Visual Field Variability in Glaucoma: Implications for Visual Field Prediction and Modeling

Purpose

To quantify visual field (VF) variability as a function of threshold sensitivity and location, and to compare weighted pointwise linear regression (PLR) with unweighted PLR and pointwise exponential regression (PER) for data fit and prediction ability.

Methods

Two datasets were used for this retrospective study. The first was used to characterize and estimate VF variability, and included a total of 4,747 eyes of 3,095 glaucoma patients with six or more VFs and 3 years or more of follow-up. After performing PER for each series, standard deviation of residuals was quantified for each decibel of sensitivity as a measure of variability. A separate dataset was used to test and compare unweighted PLR, weighted PLR, and PER for data fit and prediction, and included 261 eyes of 176 primary open-angle glaucoma patients with 10 or more VFs and 6 years or more of follow-up.

Results

The degree of variability changed as a function of threshold sensitivity with a zenith and a nadir at 33 and 11 dB, respectively. Variability decreased with eccentricity and was higher in the central 10° (P < 0.001). Differences among the methods for data fit were negligible. PER was the best model to predict future sensitivity values in the mid term and long term.

Conclusions

VF variability increases with the severity of glaucoma damage and decreases with eccentricity. Weighted linear regression neither improves model fit nor prediction. PER exhibited the best prediction ability, which is likely related to the nonlinear nature of long-term glaucomatous perimetric decay.

Translational Relevance

This study suggests that taking into account heteroscedasticity has no advantage in VF modeling.

Investigating the neuroprotective effect of Copolymer-1 in acute primary angle closure - Interim report of a randomized placebo-controlled double-masked clinical trial

PURPOSE

To investigate the neuroprotective effect of Copolymer-1 (Cop-1) in patients with acute primary angle closure (APAC) in a randomized double-masked controlled trial.

METHODS

After initial medical management, APAC patients were randomized to receive either subcutaneous Cop-1 or placebo within 24 hr and at 1 week. After laser peripheral iridotomy (LPI), subjects underwent serial visual field (VF) tests and retinal nerve fibre layer (RNFL) thickness measurements with spectral-domain optical coherence tomography. The primary outcome measure was mean number of progressing points (significant slope of ≥ 1 dB per year sensitivity loss) over 16 weeks based on pointwise linear regression analysis, and the secondary outcome measure was the change in RNFL thickness.

RESULTS

Thirty-eight patients (19 in each group) completed the study. Twenty-five (65.8%) were female, the majority being Chinese (86.8%) with mean age 62.5 years (SD 8.1). Patients in the Cop-1 group were found to have mean of 0.32 (SD 0.95) progressing points compared to 2.74 (SD 5.31) in the placebo group (p = 0.09), while 3/19 (15.8%) of Cop-1 treated patients had 1 or more progressing points compared to 7/19 (36.8%) in the placebo group (p = 0.14). There was no difference in change of RNFL thickness between groups (p = 0.57). We found improvement of mean deviation (MD) at week 16 in the Cop-1 group (p = 0.01) compared to worsening of MD in the placebo group (p = 0.04).

CONCLUSION

After APAC, there was no difference in VF progression (or RNFL thickness change) between Cop-1 and placebo groups. However, there was improvement of MD in Cop-1 treated patients.

Comparison of Methods to Detect and Measure Glaucomatous Visual Field Progression

PURPOSE

To compare methods to assess visual field (VF) progression in glaucoma.

METHODS

4,950 VFs of 253 primary open angle-glaucoma patients were evaluated for progression with the following methods: clinical evaluation, guided progression analysis (GPA), mean deviation (MD), and visual field index (VFI) rates, Advanced Glaucoma Intervention Study (AGIS) and Collaborative Initial Glaucoma Treatment Study (CIGTS) scores, pointwise linear regression (PLR), permutation of PLR (PoPLR), and glaucoma rate index (GRI). A separate simulated series of longitudinal VFs was assessed with all methods except for GPA and clinical evaluation.

RESULTS

The average (±SD) age of the patients at baseline was 65.4 (±11.5) years. The average (±SD) follow-up was 11.8 (±4.6) years, and the mean (±SD) number of VFs was 16.8 (±7.0). Proportion of series detected as progressing was 65% for PoPLR, 58% for GRI, 41% for GPA, 40% for PLR, 36% for CIGTS, 35% for clinicians, 31% for MD rate, 29% for AGIS, and 22% for VFI rate. Median times to detection of progression were 7.3 years for PoPLR, 7.5 years for GRI, 11 years for clinicians, 14 years for GPA, 16 years for PLR, 17 years for CIGTS, 19 years for AGIS, and more than 20 years for MD and VFI rates. In simulated VF series, GRI had the highest partial area under the receiver operator characteristic curve (0.040) to distinguish between glaucoma progression and aging/cataract decay, followed by VFI rate (0.028), MD rate (0.024), and PoPLR (0.006).

CONCLUSIONS

GRI and PoPLR showed the highest proportion of series detected as progressing and shortest times to progression detection. GRI exhibited the best ability to detect progression in the simulated VF series.

TRANSLATIONAL RELEVANCE

Knowledge of the properties of every method would allow tailoring application in both clinical and research settings.

Loss of Foveal Cone Structure Precedes Loss of Visual Acuity in Patients With Rod-Cone Degeneration

Purpose

To assess the relationship between cone spacing and visual acuity in eyes with rod-cone degeneration (RCD) followed longitudinally.

Methods

High-resolution images of the retina were obtained using adaptive optics scanning laser ophthalmoscopy from 13 eyes of nine RCD patients and 13 eyes of eight healthy subjects at two sessions separated by 10 or more months (mean 765 days, range 311-1935 days). Cone spacing Z-score measured as close as possible (average <0.25°) to the preferred retinal locus was compared with visual acuity (letters read on the Early Treatment of Diabetic Retinopathy Study [ETDRS] chart and logMAR) and foveal sensitivity.

Results

Cone spacing was significantly correlated with ETDRS letters read (ρ = -0.47, 95%CI -0.67 to -0.24), logMAR (ρ = 0.46, 95%CI 0.24 to 0.66), and foveal sensitivity (ρ = -0.30, 95%CI -0.52 to -0.018). There was a small but significant increase in mean cone spacing Z-score during follow-up of +0.97 (95%CI 0.57 to 1.4) in RCD patients, but not in healthy eyes, and there was no significant change in any measure of visual acuity.

Conclusions

Cone spacing was correlated with visual acuity and foveal sensitivity. In RCD patients, cone spacing increased during follow-up, while visual acuity did not change significantly. Cone spacing Z-score may be a more sensitive measure of cone loss at the fovea than visual acuity in patients with RCD.

An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis

Purpose

To detect visual field (VF) progression by analyzing spatial pattern changes.

Methods

We selected 12,217 eyes from 7360 patients with at least five reliable 24-2 VFs and 5 years of follow-up with an interval of at least 6 months. VFs were decomposed into 16 archetype patterns previously derived by artificial intelligence techniques. Linear regressions were applied to the 16 archetype weights of VF series over time. We defined progression as the decrease rate of the normal archetype or any increase rate of the 15 VF defect archetypes to be outside normal limits. The archetype method was compared with mean deviation (MD) slope, Advanced Glaucoma Intervention Study (AGIS) scoring, Collaborative Initial Glaucoma Treatment Study (CIGTS) scoring, and the permutation of pointwise linear regression (PoPLR), and was validated by a subset of VFs assessed by three glaucoma specialists.

Results

In the method development cohort of 11,817 eyes, the archetype method agreed more with MD slope (kappa: 0.37) and PoPLR (0.33) than AGIS (0.12) and CIGTS (0.22). The most frequently progressed patterns included decreased normal pattern (63.7%), and increased nasal steps (16.4%), altitudinal loss (15.9%), superior-peripheral defect (12.1%), paracentral/central defects (10.5%), and near total loss (10.4%). In the clinical validation cohort of 397 eyes with 27.5% of confirmed progression, the agreement (kappa) and accuracy (mean of hit rate and correct rejection rate) of the archetype method (0.51 and 0.77) significantly (P < 0.001 for all) outperformed AGIS (0.06 and 0.52), CIGTS (0.24 and 0.59), MD slope (0.21 and 0.59), and PoPLR (0.26 and 0.60).

Conclusions

The archetype method can inform clinicians of VF progression patterns.

Machine Learning in the Detection of the Glaucomatous Disc and Visual Field

Glaucoma is the leading cause of irreversible blindness worldwide. Early detection is of utmost importance as there is abundant evidence that early treatment prevents disease progression, preserves vision, and improves patients' long-term quality of life. The structure and function thresholds that alert to the diagnosis of glaucoma can be obtained entirely via digital means, and as such, screening is well suited to benefit from artificial intelligence and specifically machine learning. This paper reviews the concepts and current literature on the use of machine learning for detection of the glaucomatous disc and visual field.

Combining optical coherence tomography with visual field data to rapidly detect disease progression in glaucoma: a diagnostic accuracy study

BACKGROUND

Progressive optic nerve damage in glaucoma results in vision loss, quantifiable with visual field (VF) testing. VF measurements are, however, highly variable, making identification of worsening vision ('progression') challenging. Glaucomatous optic nerve damage can also be measured with imaging techniques such as optical coherence tomography (OCT).

OBJECTIVE

To compare statistical methods that combine VF and OCT data with VF-only methods to establish whether or not these allow (1) more rapid identification of glaucoma progression and (2) shorter or smaller clinical trials.

DESIGN

Method 'hit rate' (related to sensitivity) was evaluated in subsets of the United Kingdom Glaucoma Treatment Study (UKGTS) and specificity was evaluated in 72 stable glaucoma patients who had 11 VF and OCT tests within 3 months (the RAPID data set). The reference progression detection method was based on Guided Progression Analysis™ (GPA) Software (Carl Zeiss Meditec Inc., Dublin, CA, USA). Index methods were based on previously described approaches [Analysis with Non-Stationary Weibull Error Regression and Spatial enhancement (ANSWERS), Permutation analyses Of Pointwise Linear Regression (PoPLR) and structure-guided ANSWERS (sANSWERS)] or newly developed methods based on Permutation Test (PERM), multivariate hierarchical models with multiple imputation for censored values (MaHMIC) and multivariate generalised estimating equations with multiple imputation for censored values (MaGIC).

SETTING

Ten university and general ophthalmology units (UKGTS) and a single university ophthalmology unit (RAPID).

PARTICIPANTS

UKGTS participants were newly diagnosed glaucoma patients randomised to intraocular pressure-lowering drops or placebo. RAPID participants had glaucomatous VF loss, were on treatment and were clinically stable.

INTERVENTIONS

24-2 VF tests with the Humphrey Field Analyzer and optic nerve imaging with time-domain (TD) Stratus OCT™ (Carl Zeiss Meditec Inc., Dublin, CA, USA).

MAIN OUTCOME MEASURES

Criterion hit rate and specificity, time to progression, future VF prediction error, proportion progressing in UKGTS treatment groups, hazard ratios (HRs) and study sample size.

RESULTS

Criterion specificity was 95% for all tests; the hit rate was 22.2% for GPA, 41.6% for PoPLR, 53.8% for ANSWERS and 61.3% for sANSWERS (all comparisons p ≤ 0.042). Mean survival time (weeks) was 93.6 for GPA, 82.5 for PoPLR, 72.0 for ANSWERS and 69.1 for sANSWERS. The median prediction errors (decibels) when the initial trend was used to predict the final VF were 3.8 (5th to 95th percentile 1.7 to 7.6) for PoPLR, 3.0 (5th to 95th percentile 1.5 to 5.7) for ANSWERS and 2.3 (5th to 95th percentile 1.3 to 4.5) for sANSWERS. HRs were 0.57 [95% confidence interval (CI) 0.34 to 0.90; p = 0.016] for GPA, 0.59 (95% CI 0.42 to 0.83; p = 0.002) for PoPLR, 0.76 (95% CI 0.56 to 1.02; p = 0.065) for ANSWERS and 0.70 (95% CI 0.53 to 0.93; p = 0.012) for sANSWERS. Sample size estimates were not reduced using methods including OCT data. PERM hit rates were between 8.3% and 17.4%. Treatment effects were non-significant in MaHMIC and MaGIC analyses; statistical significance was altered little by incorporating imaging.

LIMITATIONS

TD OCT is less precise than current imaging technology; current OCT technology would likely perform better. The size of the RAPID data set limited the precision of criterion specificity estimates.

CONCLUSIONS

The sANSWERS method combining VF and OCT data had a higher hit rate and identified progression more quickly than the reference and other VF-only methods, and produced more accurate estimates of the progression rate, but did not increase treatment effect statistical significance. Similar studies with current OCT technology need to be undertaken and the statistical methods need refinement.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN96423140.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 22, No. 4. See the NIHR Journals Library website for further project information. Data analysed in the study were from the UKGTS. Funding for the UKGTS was provided through an unrestricted investigator-initiated research grant from Pfizer Inc. (New York, NY, USA), with supplementary funding from the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK. Imaging equipment loans were made by Heidelberg Engineering, Carl Zeiss Meditec and Optovue (Fremont, CA, USA). Pfizer, Heidelberg Engineering, Carl Zeiss Meditec and Optovue had no input into the design, conduct, analysis or reporting of any of the UKGTS findings or this work. The sponsor for both the UKGTS and RAPID data collection was Moorfields Eye Hospital NHS Foundation Trust. David F Garway-Heath, Tuan-Anh Ho and Haogang Zhu are partly funded by the NIHR Biomedical Research Centre based at Moorfields Eye Hospital and UCL Institute of Ophthalmology. David F Garway-Heath's chair at University College London (UCL) is supported by funding from the International Glaucoma Association.

Improved Detection of Visual Field Progression Using a Spatiotemporal Boundary Detection Method

Glaucoma is the leading cause of irreversible blindness worldwide and requires regular monitoring upon diagnosis to ascertain whether the disease is stable or progressing. However, making this determination remains a difficult clinical task. Recently, a novel spatiotemporal boundary detection predictor of glaucomatous visual field (VF) progression (STBound) was developed. In this work, we explore the ability of STBound to differentiate progressing and non-progressing glaucoma patients in comparison to existing methods. STBound, Spatial PROGgression, and traditional trend-based progression methods (global index (GI) regression, mean regression slope, point-wise linear regression, permutation of pointwise linear regression) were applied to longitudinal VF data from 191 eyes of 91 glaucoma patients. The ability of each method to identify progression was compared using Akaike information criterion (AIC), full/partial area under the receiver operating characteristic curve (AUC/pAUC), sensitivity, and specificity. STBound offered improved diagnostic ability (AIC: 197.77 vs. 204.11-217.55; AUC: 0.74 vs. 0.63-0.70) and showed no correlation (r: -0.01-0.11; p-values: 0.11-0.93) with the competing methods. STBound combined with GI (the top performing competitor) provided improved performance over all individual metrics and compared to all metrics combined with GI (all p-values < 0.05). STBound may be a valuable diagnostic tool and can be used in conjunction with existing methods.

Development and validation of a new glaucoma screening test using temporally modulated flicker

PURPOSE

Describing the psychometric characteristics and diagnostic accuracy of the Accelerator 4-Alternative Forced-Choice Flicker Test prototype (A4FTp) for detecting chronic open angle glaucoma (COAG).

METHODS

A4FTp measures temporally-modulated flicker thresholds in regions of the visual field with high susceptibility to glaucomatous loss. We initially evaluated its psychometric properties on 20 normals (aged 33.8 ± 8.5 years) who were tested multiple times over a period of 3 months. All subjects underwent four repetitions for shorter (T8) and longer (T12) staircase termination criteria, to determine the most suitable threshold criterion. Four randomly selected subjects underwent a total of 10 repetitions to study test-retest repeatability and learning effects. To determine its diagnostic accuracy, one eye of 40 participants with COAG and 38 normal controls were tested with the A4FTp in comparison with the Frequency Doubling Technology (FDT; C20-5 programme) and iVue Spectral Domain Optical Coherence Tomography (SD-OCT). Tests were conducted in a random order with results masked to the clinician conducting the reference ophthalmic examination. The accuracy of each test was determined by analysis of the area under the receiver operator characteristic curve (AUROC).

RESULTS

A4FTp flicker thresholds were stable, with standard deviations of only 0.52 decilog (dL) for T8, increasing to 1.32 dL for T12, and no significant flicker sensitivity threshold improvement over the 10 repeat runs. T8 was superior to T12 on several other measures, so it was used for the remaining comparisons. In terms of diagnostic accuracy, the mean AUROC for the three tests were A4FTp [T8 criterion; 0.82, 95% confidence interval (0.73-0.92)]; SD-OCT [any RNFL parameter p < 1% level; 0.90 (0.83-0.97)]; and FDT [one or more locations missed at p < 5% level; 0.91 (0.82-0.96)]. There was no statistical difference in AUROC between A4FTp and SD-OCT (p = 0.18) or FDT (p = 0.12). The A4FTp test duration averaged just over 2 min per eye, taking approximately one-third of the time for completion of the HFA SITA 24-2 algorithm (conducted as part of the reference examination) and twice the time for the suprathreshold FDT.

CONCLUSION

Test accuracy for the A4FTp was comparable to those of the FDT and SD-OCT for the detection of COAG. Time taken to complete the A4FTp was relatively short and initial results are promising. With further refinement, the A4FTp could have a future role in glaucoma detection.

Desenvolvimento de Equipamento para Exame de Campo Visual

O exame de campo visual (campimetria) é utilizado como procedimento médico principalmente para o diagnóstico e seguimento de pacientes com glaucoma, doenças da retina e em neuro-oftalmologia. As diferentes formas de glaucoma constituem a principal causa de cegueira nos países industrializados ou em desenvolvimento. O diagnóstico precoce do glaucoma e o controle de sua evolução são fundamentais para evitar a cegueira. Assim, o desenvolvimento de um equipamento de menor custo torna possível a realização do exame de campo visual por uma parcela maior da população. Este projeto contempla o desenvolvimento de um equipamento para o exame de campo visual, que consiste em um monitor de vídeo do tipo LCD controlado por computador, no qual são plotados focos de luz de intensidade ajustável em coordenadas pré-determinadas, simulando um ponto no espaço dentro de um campo de visão.

Nutritional supplementation in the treatment of glaucoma: A systematic review

Current treatment strategies for glaucoma are limited to halting disease progression and do not restore lost visual function. Intraocular pressure is the main risk factor for glaucoma, and intraocular pressure-lowering treatment remains the mainstay of glaucoma treatment, but even successful intraocular pressure reduction does not stop the progression of glaucoma in all patients. We review the literature to determine whether nutritional interventions intended to prevent or delay the progression of glaucoma could prove to be a valuable addition to the mainstay of glaucoma therapy. A total of 33 intervention trials were included in this review, including 21 randomized controlled trials. These suggest that flavonoids exert a beneficial effect in glaucoma, particularly in terms of improving ocular blood flow and potentially slowing progression of visual field loss. In addition, supplements containing forskolin have consistently demonstrated the capacity to reduce intraocular pressure beyond the levels achieved with traditional therapy alone; however, despite the strong theoretical rationale and initial clinical evidence for the beneficial effect of dietary supplementation as an adjunct therapy for glaucoma, the evidence is not conclusive. More and better quality research is required to evaluate the role of nutritional supplementation in glaucoma.

Reducing Spatial Uncertainty Through Attentional Cueing Improves Contrast Sensitivity in Regions of the Visual Field With Glaucomatous Defects

Purpose

Current clinical perimetric test paradigms present stimuli randomly to various locations across the visual field (VF), inherently introducing spatial uncertainty, which reduces contrast sensitivity. In the present study, we determined the extent to which spatial uncertainty affects contrast sensitivity in glaucoma patients by minimizing spatial uncertainty through attentional cueing.

Methods

Six patients with open-angle glaucoma and six healthy subjects underwent laboratory-based psychophysical testing to measure contrast sensitivity at preselected locations at two eccentricities (9.5° and 17.5°) with two stimulus sizes (Goldmann sizes III and V) under different cueing conditions: 1, 2, 4, or 8 points verbally cued. Method of Constant Stimuli and a single-interval forced-choice procedure were used to generate frequency of seeing (FOS) curves at locations with and without VF defects.

Results

At locations with VF defects, cueing minimizes spatial uncertainty and improves sensitivity under all conditions. The effect of cueing was maximal when one point was cued, and rapidly diminished when more points were cued (no change to baseline with 8 points cued). The slope of the FOS curve steepened with reduced spatial uncertainty. Locations with normal sensitivity in glaucomatous eyes had similar performance to that of healthy subjects. There was a systematic increase in uncertainty with the depth of VF loss.

Conclusions

Sensitivity measurements across the VF are negatively affected by spatial uncertainty, which increases with greater VF loss. Minimizing uncertainty can improve sensitivity at locations of deficit.

Translational Relevance

Current perimetric techniques introduce spatial uncertainty and may therefore underestimate sensitivity in regions of VF loss.

Visual Subfield Progression in Glaucoma Subtypes

Purpose

To investigate visual field progression pattern and factors associated with progression in patients with primary open-angle glaucoma (POAG), normal-tension glaucoma (NTG), and chronic angle-closure glaucoma (CACG).

Methods

The raw data of the 30-2 Humphrey Field Analyzer from glaucoma patients with definite visual field progression were processed with pointwise linear regression (PLR) analysis. The rate of change of retinal threshold sensitivity in the ten glaucoma hemifield test (GHT) zones, the upper and the lower hemifields, and the whole field was evaluated and was correlated with patients' basic demographic data.

Results

An average follow-up of 6.94 ± 2.69 years that showed the rate of change of visual field threshold sensitivity was correlated with the peak posttreatment intraocular pressure (IOP) and the long-term IOP fluctuations in all GHT zones except in the inferior arcuate area. The baseline IOP, the trough posttreatment IOP, the refractive status, and the CCT were not correlated with VF progression.

Conclusion

The rate of visual field progression was correlated with the peak posttreatment IOP and the long-term IOP fluctuation but with subfield differences.

Measuring Rates of Visual Field Progression in Linear Versus Nonlinear Scales: Implications for Understanding the Relationship Between Baseline Damage and Target Rates of Glaucoma Progression

PURPOSE

The purpose of this study is to test the hypothesis that the relationship between baseline visual field damage and the rate of progression depends upon the use of logarithmic (dB) versus linear (1/Lambert) scale.

METHODS

A total of 60 eyes (60 patients) with treated, established glaucoma and at least 5 reliable 24-2 visual fields were included. Baseline visual field mean deviation (MD) in dB was transformed to 1/Lambert using standard equation. Mixed effects linear regression was used to calculate the slopes (MD rates of progression over time) with linear and nonlinear scales. We tested the relationship between baseline MD and MD slopes for each scale of measure.

RESULTS

In dB scale, worse baseline visual field loss was associated with faster MD slopes (P=0.037), whereas the opposite effect was seen in 1/Lambert (P=0.001). For a similar rate of progression in dB/y, eyes with mild visual field damage lost more linear sensitivity over a given period of time than those with more severe baseline damage.

CONCLUSIONS

There is a significant relationship between baseline visual field severity and rates of MD progression, although the direction of this association depends on the scale sensitivity is measured. The definition of fast versus slow visual field progression should be revised and take into account that sensitivity in linear scales show a better correlation with structural loss than when conventionally measured in nonlinear scale.

Applying "Lasso" Regression to Predict Future Glaucomatous Visual Field Progression in the Central 10 Degrees

PURPOSE OF THE STUDY

We recently reported that it is beneficial to apply least absolute shrinkage and selection operator (Lasso) regression to predict future 24-2 visual field (VF) progression. The purpose of the current study was to investigate the usefulness of Lasso regression to predict VF progression in the central 10 degrees (10-2) in glaucoma patients.

METHODS

Series of 10 VFs (Humphrey Field Analyzer 10-2 SITA-standard) from each of 149 eyes in 110 open angle glaucoma patients, obtained over 5.7±1.4 years (mean±SD) were investigated. Mean deviation values of the 10th VF were predicted using varying numbers of VFs (ranging from the first to third VFs to the first to ninth VFs), applying ordinary least square regression (OLSLR) and Lasso regression. Absolute prediction errors were then compared.

RESULTS

With OLSLR, prediction error varied between 5.4±5.0 (using first to third VFs) and 1.1±1.6 dB (using first to ninth VFs). Significantly smaller prediction errors were obtained with Lasso regression, in particular with small numbers of VFs (from 2.1±2.8: first to third VFs, to 1.0±1.6 dB: first to ninth VFs). A large λ value, which is an index showing the degree of penalty in Lasso regression, was observed when a small number of VFs were used for prediction.

CONCLUSION

Mean deviation prediction using OLSLR with a small number of VFs resulted in large prediction errors. It was useful to apply Lasso regression when predicting future progression of the central 10 degrees, compared to OLSLR.

Risk Factors for Rapid Glaucoma Disease Progression

PURPOSE

To determine the intraocular and systemic risk factor differences between a cohort of rapid glaucoma disease progressors and nonrapid disease progressors.

DESIGN

Retrospective case-control study.

METHODS

Setting: Five private ophthalmology clinics.

STUDY POPULATION

Forty-eight rapidly progressing eyes (progression ≥1 dB mean deviation [MD]/year) and 486 non-rapidly progressing eyes (progression <1 dB MD/year). Patients were eligible if they had a diagnosis of glaucoma from their ophthalmologist and if they had greater than or equal to 5 Humphrey visual fields (24-2) conducted. Patients were excluded if their sequential visual fields showed an improvement in MD or if they had greater than 5 dB MD variation in between visits. Patients with obvious neurologic fields were excluded.

OBSERVATION PROCEDURE

Clinical and demographic data (age, sex, central corneal thickness [CCT], intraocular pressure [IOP], refraction, medications), as well as medical, surgical, and ocular histories, were collected.

MAIN OUTCOME MEASURES

Risk factor differences between the cohorts were measured using the independent t test, Wald χ², and binomial regression analysis.

RESULTS

Rapid progressors were older, had significantly lower CCT and baseline IOPs, and were more likely to have pseudoexfoliation, disc haemorrhages, ocular medication changes, and IOP-lowering surgery. They also had significantly higher rates of cardiovascular disease and hypotension. Subjects with cardiovascular disease were 2.33 times more likely to develop rapidly progressive glaucoma disease despite significantly lower mean and baseline IOPs.

CONCLUSION

Cardiovascular disease is an important risk factor for rapid glaucoma disease progression irrespective of IOP control.

Impact of intraocular pressure reduction on visual field progression in normal-tension glaucoma followed up over 15 years

PURPOSE

To investigate the impact of surgical or medical reduction of intraocular pressure (IOP) on progressive normal-tension glaucoma followed up over 15 years.

METHODS

Sixty eyes of 60 patients were divided into 3 intervention groups: group 1 (trabeculectomy, n = 17); group 2 (IOP reduction rate ≥15% with prostaglandin analogs, n = 24); and group 3 (IOP reduction rate <15% with prostaglandin analogs, n = 19). The preintervention and postintervention mean deviation (MD) slopes and IOP were compared. Factors associated with the rate of visual field progression were identified by multiple regression analysis.

RESULTS

The mean follow-up was 19.8 years. In group 1, the preintervention and postintervention IOPs were 14.7 ± 1.3 and 9.1 ± 2.0 mmHg, respectively (P < .001, 38% reduction). The MD slope decreased significantly after trabeculectomy (-0.86 ± 0.51 versus -0.19 ± 0.20 dB/y; P < .001). In group 2, the preintervention and postintervention IOPs were 14.7 ± 1.5 and 11.7 ± 1.2 mmHg, respectively (P < 0.001, 20% reduction), with significant differences in the MD slope (-0.52 ± 0.37 versus -0.31 ± 0.30 dB/y; P = .019). In group 3, the preintervention and postintervention IOPs were 14.4 ± 1.8 and 13.2 ± 1.6 mmHg, respectively (P < 0.001, 8% reduction), with no differences in the MD slope (-0.40 ± 0.27 versus -0.50 ± 0.65 dB/y; P > .05). Multiple regression analysis showed that the average IOP, IOP reduction rate, and preintervention MD slope were related to the extent of the postintervention reduction in the MD slope. The difference in the preintervention and postintervention MD slopes significantly correlated with the rate of IOP reduction (r = 0.559, P < .001).

CONCLUSIONS

A pressure-dependent maintenance effect of the visual field was confirmed in progressive normal-tension glaucoma.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma

BACKGROUND/AIMS

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma.

METHODS

Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis.

RESULT

Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters.

CONCLUSION

Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity.

Detection and measurement of clinically meaningful visual field progression in clinical trials for glaucoma

Glaucomatous visual field progression has both personal and societal costs and therefore has a serious impact on quality of life. At the present time, intraocular pressure (IOP) is considered to be the most important modifiable risk factor for glaucoma onset and progression. Reduction of IOP has been repeatedly demonstrated to be an effective intervention across the spectrum of glaucoma, regardless of subtype or disease stage. In the setting of approval of IOP-lowering therapies, it is expected that effects on IOP will translate into benefits in long-term patient-reported outcomes. Nonetheless, the effect of these medications on IOP and their associated risks can be consistently and objectively measured. This helps to explain why regulatory approval of new therapies in glaucoma has historically used IOP as the outcome variable. Although all approved treatments for glaucoma involve IOP reduction, patients frequently continue to progress despite treatment. It would therefore be beneficial to develop treatments that preserve visual function through mechanisms other than lowering IOP. The United States Food and Drug Administration (FDA) has stated that they will accept a clinically meaningful definition of visual field progression using Glaucoma Change Probability criteria. Nonetheless, these criteria do not take into account the time (and hence, the speed) needed to reach significant change. In this paper we provide an analysis based on the existing literature to support the hypothesis that decreasing the rate of visual field progression by 30% in a trial lasting 12-18 months is clinically meaningful. We demonstrate that a 30% decrease in rate of visual field progression can be reliably projected to have a significant effect on health-related quality of life, as defined by validated instruments designed to measure that endpoint.

Predicting Clinical Binary Outcome Using Multivariate Longitudinal Data: Application to Patients with Newly Diagnosed Primary Open-Angle Glaucoma

Primary open angle glaucoma (POAG) is a chronic, progressive, irreversible, and potentially blinding optic neuropathy. The risk of blindness due to progressive visual field (VF) loss varies substantially from patient to patient. Early identification of those patients destined to rapid progressive visual loss is crucial to prevent further damage. In this article, a latent class growth model (LCGM) was developed to predict the binary outcome of VF progression using longitudinal mean deviation (MD) and pattern standard deviation (PSD). Specifically, the trajectories of MD and PSD were summarized by a functional principal component (FPC) analysis, and the estimated FPC scores were used to identify subgroups (latent classes) of individuals with distinct patterns of MD and PSD trajectories. Probability of VF progression for an individual was then estimated as weighted average across latent classes, weighted by posterior probability of class membership given baseline covariates and longitudinal MD/PSD series. The model was applied to the participants with newly diagnosed POAG from the Ocular Hypertension Treatment Study (OHTS), and the OHTS data was best fit by a model with 4 latent classes. Using the resultant optimal LCGM, the OHTS participants with and without VF progression could be accurately differentiated by incorporating longitudinal MD and PSD.

Relationship between consecutive deterioration of mean deviation value and progression of visual field defect in open-angle glaucoma

Purpose

To analyze the relationship between consecutive deterioration of mean deviation (MD) value and glaucomatous visual field (VF) progression in open-angle glaucoma (OAG), including primary OAG and normal tension glaucoma.

Patients and methods

The subjects of the study were patients undergoing treatment for OAG who had performed VF tests at least 10 times with a Humphrey field analyzer (SITA standard, C30-2 program). The VF progression was defined by a significantly negative MD slope (MD slope worsening) at the final VF test during the follow-up period. The relationship between the MD slope worsening and the consecutive deterioration of MD value were retrospectively analyzed.

Results

A total of 165 eyes of 165 patients were included in the analysis. Significant progression of VF defects was observed in 72 eyes of 72 patients (43.6%), while no significant progression was evident in 93 eyes of 93 patients (56.4%). There was significant relationship between the frequency of consecutive deterioration of MD value and MD slope worsening (P<0.0001, Cochran–Armitage trend test). A significant association was observed for MD slope worsening in the eyes with three (odds ratio: 2.1, P=0.0224) and four (odds ratio: 3.6, P=0.0008) consecutive deterioration of MD value in multiple logistic regression analysis, but no significant association in the eyes with two consecutive deterioration (odds ratio: 1.1, P=0.8282). The eyes with VF progression had significantly lower intraocular pressure reduction rate (P<0.01).

Conclusion

This retrospective study has shown that three or more consecutive deterioration of MD value might be a predictor to future significant MD slope worsening in OAG.

Perimetric progression using the Visual Field Index and the Advanced Glaucoma Intervention Study score and its clinical correlations

PURPOSE

To evaluate the association between clinical parameters and the diagnosis of progression using VFI (Visual Field Index) and AGIS (Advanced Glaucoma Intervention Study) score in primary open angle glaucoma.

METHODS

Retrospective study of 517 visual fields of 78 eyes with primary open angle glaucoma analyzed with VFI and AGIS score. Clinical data registered included: age, sphere, pachimetry, basal intraocular pressure (IOP), and IOP during the follow up.

RESULTS

Only the AGIS score diagnosis of progression was associated with the clinical parameters registered. Among the analyzed data, the mean IOP during follow up (p = 0.0005) and IOP at the third month of follow up (p = 0.004) were statistically associated with progression using the AGIS criteria.

CONCLUSION

The diagnosis of perimetric progression using the AGIS score in the current study was closer to the real functional progression than the diagnosis using the VFI, as the former was associated with known risk factors for progression in glaucoma.

Reducing variability in visual field assessment for glaucoma through filtering that combines structural and functional information

PURPOSE

To reduce variability and improve measurements of true change signal in visual field (VF) assessments through the use of filters that combine functional and structural test results.

METHODS

Humphrey VF data (Swedish Interactive Thresholding Algorithm [SITA] Standard, 24-2) and confocal scanning laser ophthalmoscopy (Heidelberg Retina Tomograph [HRT]) data from 1057 eyes of 637 participants were used to derive a filter. Another dataset, consisting of VF and HRT data from 112 eyes of 62 participants each with ≥5 visits, was used to test the filter. At each VF location per eye, the trend over time was modeled by a linear model (LM), and a nonlinear model (NLM), using filtered or unfiltered data, but with the last visit excluded. The SD of residuals from the trends, and prediction errors (PE) for the last visit were compared between filtered and unfiltered data. The filter was reconstructed and analyses were repeated after truncating VF data so that thresholds < 19 dB were replaced by 19 dB to reduce noise.

RESULTS

The SD of the residuals at all 52 VF locations for all analyses was reduced by filtering (P < 0.001). The PE was reduced by filtering at 43 and 47 VF locations (P < 0.05) for LM analyses on observed and truncated data, and all 52 VF locations (P < 0.05) for both NLM analyses. Truncating data before filtering reduced variability (P < 0.01) at 41 and 40 VF locations for LM and NLM analyses.

CONCLUSIONS

Filtering can reduce variability about trends in longitudinal sequences of VF data, and improves the accuracy of predicting the next test result.

The relationship between the mean deviation slope and follow-up intraocular pressure in open-angle glaucoma patients

PURPOSE

The purpose of this study was to analyze the relationship between the mean deviation (MD) slope as the progressive rate of visual field defects and the follow-up intraocular pressure (IOP) in open-angle glaucoma (OAG) patients.

METHODS

This study was a retrospective, nonrandomized comparative study. A total of 287 eyes from 287 Japanese OAG patients were examined. The MD slope of the Humphrey Field Analyzer was calculated and compared with the follow-up IOP. OAG was classified into the high-tension group (>21 mm Hg) and the normal-tension group (≤ 21 mm Hg) on the basis of the highest recorded IOP without treatment, and then the 2 groups were compared. After setting a threshold for the progression rate at -0.3 dB/y, related factors were compared between the fast-progression and slow-progression eyes in each group.

RESULTS

The correlation line between the follow-up IOP and the MD slope was statistically significant in the high-tension group but not in the normal-tension group. Compared with eyes with slow progression, eyes with fast progression in the high-tension group were older and had a higher mean IOP, greater highest and lowest IOPs, and a smaller mean IOP reduction ratio, whereas eyes with fast progression in the normal-tension group had a greater SD of the mean IOP, a larger IOP range, and a greater highest IOP.

CONCLUSIONS

Eyes with a faster visual field progression tended to have a higher follow-up IOP in the high-tension group and larger IOP fluctuations in the normal-tension group of OAG patients. We should monitor both the follow-up IOP and fluctuations in IOP to provide a safer and more reliable visual field prognosis for OAG.

Psychophysical factors that have been applied to clinical perimetry

Perimetry is the most common clinical diagnostic test procedure for evaluating the status of peripheral visual function in the management of ocular and neurologic diseases. This procedure has an extended history, and its design, implementation and interpretation is dependent on many principles that have been developed through visual psychophysical studies of target size, target duration, background adaptation level, chromatic characteristics and other stimulus properties (see Greve, 1973; Johnson, 1994, chap. 17, 1996, 2008, 2010, chap. 23; Johnson & Keltner, 1998, chap. 7; Johnson & Sample, 2002, chap. 22; Johnson & Wall, 2011, chap. 35; Wall & Johnson, 2005, chap. 2 for reviews). This paper will provide a general overview of the history of perimetry, selection of stimulus parameters, development of test strategies, clinical testing conditions, new procedures and approaches to perimetry, experimental design, analysis and interpretation methods, hypothesis testing, prediction and forecasting procedures, and other related topics. It is somewhat paradoxical that although there have been major advances in all of these areas that have significantly enhanced the utility and value of this clinical diagnostic test, the fundamental methodology has remained mostly unchanged for thousands of years. It is hoped that this overview will be of assistance to investigators and clinicians who wish to use or modify this diagnostic procedure for their ongoing career activities.

Changes in the circadian rhythm in patients with primary glaucoma

Purpose

The current study was undertaken to investigate whether glaucoma affects the sleep quality and whether there is any difference between patients with primary glaucoma (primary open angle glaucoma, POAG and primary angle-closure glaucoma, PACG) and healthy subjects, using a validated self-rated questionnaire, the Pittsburgh Sleep Quality Index (PSQI).

Methods

The sleep quality of patients with POAG and PACG was tested against normal controls. Subjects were divided into three sub-groups according to age. Differences in the frequency of sleep disturbances (PSQI score >7) were assessed. The differences of sleep quality within the three groups and within the POAG group depending on the patients’ intraocular pressure (IOP) and impairment of visual field (VF) were also studied.

Results

92 POAG patients, 48 PACG patients and 199 controls were included. Sleep quality declined with age in control and POAG group (tendency chi-square, P<0.05). The prevalence of sleep disturbances was higher in POAG and PACG group than in the control group, the differences were statistically significant. The prevalence of sleep disturbances was higher in patients with PACG, compared to POAG patients in the age interval of 61–80. In POAG group, the ratio of patients with sleep disorders increased with augmented impairment of VF, but the differences were not statistically significant (χ²-test, P>0.05). No significant differences were found in POAG group between patients with a highest IOP in daytime and at nighttime (χ²-test, P>0.05).

Conclusions

The prevalence of sleep disorders was higher in patients with POAG and PACG than in controls. PACG patients seemed to have a more serious problem of sleep disorders than POAG patients between 61 to 80 years old. No correlation was found between the prevalence of sleep disorders and impairment of VF or the time when POAG patients showed a highest IOP.

Novel fractal feature-based multiclass glaucoma detection and progression prediction

We investigate the use of fractal analysis (FA) as the basis of a system for multiclass prediction of the progression of glaucoma. FA is applied to pseudo two-dimensional images converted from one-dimensional retinal nerve fiber layer (RNFL) data obtained from the eyes of normal subjects, and from subjects with progressive and non-progressive glaucoma. FA features are obtained using a box-counting method and a multi-fractional Brownian motion method that incorporates texture and multiresolution analyses. Both features are used for Gaussian kernel-based multiclass classification. Sensitivity, specificity, and area under receiver operating characteristic curve (AUROC) are computed for the FA features and for metrics obtained using wavelet-Fourier analysis (WFA) and fast-Fourier analysis (FFA). The AUROCs that predict progressors from non-progressors based on classifiers trained using a dataset comprised of non-progressors and ocular normal subjects are 0.70, 0.71 and 0.82 for WFA, FFA, and FA, respectively. The correct multiclass classification rates among progressors, non-progressors, and ocular normal subjects are 0.82, 0.86 and 0.88 for WFA, FFA, and FA, respectively. Simultaneous multiclass classification among progressors, non-progressors, and ocular normal subjects has not been previously described. The novel FA-based features achieve better performance with fewer features and less computational complexity than WFA and FFA.