Functional assessment of glaucoma: Uncovering progression

[Visual field prediction based on temporal-spatial feature learning]

Glaucoma stands as the leading irreversible cause of blindness worldwide. Regular visual field examinations play a crucial role in both diagnosing and treating glaucoma. Predicting future visual field changes can assist clinicians in making timely interventions to manage the progression of this disease. To integrate temporal and spatial features from past visual field examination results and enhance visual field prediction, a convolutional long short-term memory (ConvLSTM) network was employed to construct a predictive model. The predictive performance of the ConvLSTM model was validated and compared with other methods using a dataset of perimetry tests from the Humphrey field analyzer at the University of Washington (UWHVF). Compared to traditional methods, the ConvLSTM model demonstrated higher prediction accuracy. Additionally, the relationship between visual field series length and prediction performance was investigated. In predicting the visual field using the previous three visual field results of past 1.5~6.0 years, it was found that the ConvLSTM model performed better, achieving a mean absolute error of 2.255 dB, a root mean squared error of 3.457 dB, and a coefficient of determination of 0.960. The experimental results show that the proposed method effectively utilizes existing visual field examination results to achieve more accurate visual field prediction for the next 0.5~2.0 years. This approach holds promise in assisting clinicians in diagnosing and treating visual field progression in glaucoma patients.

Multiple (frontloaded) visual field tests increase identification of very slow mean deviation progression in glaucoma

OBJECTIVE

To determine the effect of frontloading (multiple) visual field (VF) tests at the same visit for detecting mean deviation (MD) change in slowly progressive glaucoma.

METHODS

This was a computer simulation study. Baseline MD (range, 0 to -12 dB) and progression rate (range, 0 to -0.4 dB/year, non-inclusive) were generated for 10,000 patients. Each patient had 6 simulated "stable" baseline VF tests. Then follow-up VFs (up to 10 years) were generated by incorporating progression rate and within-visit and between-visit variability. The independent variables were number of VF tests per visit (one non-frontloaded or two frontloaded), VF reliability (100%, 85%, or 70%), repeat testing because of unreliable results (yes or no), and follow-up interval (6-monthly or yearly). The outcomes were detection of progression (MD slope that was negative and significant at p < 0.05), MD at detection, and number of years to detection.

RESULTS

Frontloading identified more progressors (62.7%-79.2%) compared with non-frontloading (31.0%-36.7%) at 10 years (p < 0.0001). Six-monthly follow-ups led to greater detection than yearly intervals. Progressors detected by both methods were detected by the non-frontloaded method sooner (up to 0.26 years), but this was small and not clinically significant (MD difference, 0.06 dB). An increase (less severe) in MD, an increase (slower) in progression rate, and an increase in SD of baseline VFs decreased the likelihood of detecting progression.

CONCLUSIONS

Frontloading VF tests at 6-monthly intervals improve detection rates of MD progression in slowly progressive glaucoma patients compared with performing 1 test per visit at yearly intervals.

Contrast Sensitivity Is Impaired in Suspected Primary Open-Angle Glaucoma Patients

PURPOSE

To assess spatial contrast sensitivity (CS) in suspected primary open-angle glaucoma (POAG) patients.

METHODS

CS was measured using sinusoidal gratings of 4 cycles/degree. First, foveal and peripheral CS were assessed in 34 suspected POAG patients and compared with 71 and 28 age-matched healthy individuals for foveal and peripheral conditions, respectively. Second, foveal CS was assessed in 34 early POAG patients age-matched with suspected POAG patients. Analyses were performed considering two age ranges: Under and Over 50 y.o. Correlations were evaluated between CS and clinical parameters. Diagnostic accuracy was also analyzed.

RESULTS

Peripheral CS was lower in older suspected POAG patients (23.4 ± 16.1) than the control group (39.1 ± 28.2) (p = 0.040). Foveal CS was reduced in suspected POAG participants (Under 50: 146.8 ± 63.3; p = 0.004. Over 50: 110.5 ± 65.0; p = 0.044) and in early POAG patients (Under 50: 141.2 ± 72.6; p = 0.002. Over 50: 80.2 ± 54.5 p < 0.001), both compared to the control group (Under 50: 213.5 ± 66.2. Over 50: 138.6 ± 71.7). CS was lower in early POAG than in POAG suspected in older patients (p = 0.042). Foveal CS was correlated with age (Early: p = 0.001. Suspect: p = 0.002) and with the cup-disc ratio only in early POAG patients (p < 0.001). Foveal CS had fair (AUC = 0.74) diagnostic accuracy for early POAG patients.

CONCLUSIONS

CS in suspected POAG patients is lower than in healthy individuals. Our findings evidence the spatial vision loss before the onset of POAG.

Detecting Visual Field Worsening From Optic Nerve Head and Macular Optical Coherence Tomography Thickness Measurements

Purpose

Compare the use of optic disc and macular optical coherence tomography measurements to predict glaucomatous visual field (VF) worsening.

Methods

Machine learning and statistical models were trained on 924 eyes (924 patients) with circumpapillary retinal nerve fiber layer (cp-RNFL) or ganglion cell inner plexiform layer (GC-IPL) thickness measurements. The probability of 24-2 VF worsening was predicted using both trend-based and event-based progression definitions of VF worsening. Additionally, the cp-RNFL and GC-IPL predictions were combined to produce a combined prediction. A held-out test set of 617 eyes was used to calculate the area under the curve (AUC) to compare cp-RNFL, GC-IPL, and combined predictions.

Results

The AUCs for cp-RNFL, GC-IPL, and combined predictions with the statistical and machine learning models were 0.72, 0.69, 0.73, and 0.78, 0.75, 0.81, respectively, when using trend-based analysis as ground truth. The differences in performance between the cp-RNFL, GC-IPL, and combined predictions were not statistically significant. AUCs were highest in glaucoma suspects using cp-RNFL predictions and highest in moderate/advanced glaucoma using GC-IPL predictions. The AUCs for the statistical and machine learning models were 0.63, 0.68, 0.69, and 0.72, 0.69, 0.73, respectively, when using event-based analysis. AUCs decreased with increasing disease severity for all predictions.

Conclusions

cp-RNFL and GC-IPL similarly predicted VF worsening overall, but cp-RNFL performed best in early glaucoma stages and GC-IPL in later stages. Combining both did not enhance detection significantly.

Translational Relevance

cp-RNFL best predicted trend-based 24-2 VF progression in early-stage disease, while GC-IPL best predicted progression in late-stage disease. Combining both features led to minimal improvement in predicting progression.

A multi-label transformer-based deep learning approach to predict focal visual field progression

PURPOSE

Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression, which has not been explored in prior studies.

METHODS

The study included 2430 eyes of 1283 patients with four or more consecutive VF examinations from the baseline. A multi-label transformer-based network (MTN) using longitudinal VF data was developed to predict progression in six VF regions mapped to the optic disc. Progression was defined using the mean deviation (MD) slope and calculated for all six VF regions, referred to as clusters. Separate MTN models, trained for focal progression detection and forecasting on various numbers of VFs as model input, were tested on a held-out test set.

RESULTS

The MTNs overall demonstrated excellent macro-average AUCs above 0.884 in detecting focal VF progression given five or more VFs. With a minimum of 6 VFs, the model demonstrated superior and more stable overall and per-cluster performance, compared to 5 VFs. The MTN given 6 VFs achieved a macro-average AUC of 0.848 for forecasting progression across 8 VF tests. The MTN also achieved excellent performance (AUCs ≥ 0.86, 1.0 sensitivity, and specificity ≥ 0.70) in four out of six clusters for the eyes already with severe VF loss (baseline MD ≤  - 12 dB).

CONCLUSION

The high prediction accuracy suggested that multi-label DL networks trained with longitudinal VF results may assist in identifying and forecasting progression in VF regions.

Frontloading visual field tests detect earlier mean deviation progression when applied to real-world-derived early-stage glaucoma data

PURPOSE

To examine the diagnostic accuracy of performing two (frontloaded) versus one (clinical standard) visual field (VF) test per visit for detecting the progression of early glaucoma in data derived from clinical populations.

METHODS

A computer simulation model was used to follow the VFs of 10,000 glaucoma patients (derived from two cohorts: Heijl et al., Swedish cohort; and Chauhan et al., Canadian Glaucoma Study [CGS]) over a 10-year period to identify patients whose mean deviation (MD) progression was detected. Core data (baseline MD and progression rates) were extracted from two studies in clinical cohorts of glaucoma, which were modulated using SITA-Faster variability characteristics from previous work. Additional variables included follow-up intervals (six-monthly or yearly) and rates of perimetric data loss for any reason (0%, 15% and 30%). The main outcome measures were the proportions of progressors detected.

RESULTS

When the Swedish cohort was reviewed six-monthly, the frontloaded strategy detected more progressors compared to the non-frontloaded method up to years 8, 9 and 10 of follow-up for 0%, 15% and 30% data loss conditions. The time required to detect 50% of cases was 1.0-1.5 years less for frontloading compared to non-frontloading. At 4 years, frontloading increased detection by 26.7%, 28.7% and 32.4% for 0%, 15% and 30% data loss conditions, respectively. Where both techniques detected progression, frontloading detected progressors earlier compared to the non-frontloaded strategy (78.5%-81.5% and by 1.0-1.3 years when reviewed six-monthly; 81%-82.9% and by 1.2-2.1 years when reviewed yearly). Accordingly, these patients had less severe MD scores (six-monthly review: 0.63-1.67 dB 'saved'; yearly review: 1.10-2.87 dB). The differences increased with higher rates of data loss. Similar tendencies were noted when applied to the CGS cohort.

CONCLUSIONS

Frontloaded VFs applied to clinical distributions of MD and progression led to earlier detection of early glaucoma progression.

The application of functional imaging in visual field defects: a brief review

Visual field defects (VFDs) represent a prevalent complication stemming from neurological and ophthalmic conditions. A range of factors, including tumors, brain surgery, glaucoma, and other disorders, can induce varying degrees of VFDs, significantly impacting patients' quality of life. Over recent decades, functional imaging has emerged as a pivotal field, employing imaging technology to illustrate functional changes within tissues and organs. As functional imaging continues to advance, its integration into various clinical aspects of VFDs has substantially enhanced the diagnostic, therapeutic, and management capabilities of healthcare professionals. Notably, prominent imaging techniques such as DTI, OCT, and MRI have garnered widespread adoption, yet they possess unique applications and considerations. This comprehensive review aims to meticulously examine the application and evolution of functional imaging in the context of VFDs. Our objective is to furnish neurologists and ophthalmologists with a systematic and comprehensive comprehension of this critical subject matter.

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.

ISCEV and IPS guideline for the full-field stimulus test (FST)

The full-field stimulus test (FST) is a psychophysical technique designed for the measurement of visual function in low vision. The method involves the use of a ganzfeld stimulator, as used in routine full-field electroretinography, to deliver full-field flashes of light. This guideline was developed jointly by the International Society for Clinical Electrophysiology of Vision (ISCEV) and Imaging and Perimetry Society (IPS) in order to provide technical information, promote consistency of testing and reporting, and encourage convergence of methods for FST. It is intended to aid practitioners and guide the formulation of FST protocols, with a view to future standardisation.

Early diagnostics and interventional glaucoma

The glaucoma treatment paradigm is starting to change from a more reactive approach that relies on topical medications to a more proactive approach that leverages procedural interventions. This evolution toward interventional glaucoma has been enabled by a growing array of lower-risk minimally invasive procedures such as laser trabeculoplasty, minimally invasive glaucoma surgery, and procedural pharmaceuticals. A common feature of these glaucoma interventions-as with all glaucoma interventions-is the need for early, prompt, and accurate diagnosis. The present review summarizes new and upcoming developments in glaucoma diagnostics. These include technologies and techniques for home-based intraocular pressure measurement, novel visual field platforms, photography- and optical coherence tomography-based visualization, and artificial intelligence applications. They also include emerging technologies such as mitochondrial flavoprotein fluorescence imaging, detection of apoptosing retinal cells, collector channel visualization, and genetic testing. These diagnostic modalities have the potential to circumvent the limitations of traditional diagnostic methods. By increasing the frequency and feasibility of obtaining valuable glaucoma data with more rapid detection of disease and progression, these diagnostics may enable an interventional approach to glaucoma treatment for the betterment of patient care.

Revolutionizing Patient Monitoring in Age-Related Macular Degeneration: A Comparative Study on the Necessity and Efficiency of the AMD VIEWER

(1) Background: Age-related Macular Degeneration (AMD) is a critical condition leading to blindness, necessitating lifelong clinic visits for management, albeit with existing challenges in monitoring its long-term progression. This study introduced and assessed an innovative tool, the AMD long-term Information Viewer (AMD VIEWER), designed to offer a comprehensive display of crucial medical data-including visual acuity, central retinal thickness, macular volume, vitreous injection treatment history, and Optical Coherent Tomography (OCT) images-across an individual eye's entire treatment course. (2) Methods: By analyzing visit frequencies of patients with a history of invasive AMD treatment, a comparative examination between a Dropout group and an Active group underscored the clinical importance of regular visits, particularly highlighting better treatment outcomes and maintained visual acuity in the Active group. (3) Results: The efficiency of AMD VIEWER was proven by comparing it to manual data input by optometrists, showing significantly faster data display with no errors, unlike the time-consuming and error-prone manual entries. Furthermore, an elicited Net Promoter Score (NPS) of 70 from 10 ophthalmologists strongly endorsed AMD VIEWER's practical utility. (4) Conclusions: This study underscores the importance of regular clinic visits for AMD patients. It suggests the AMD VIEWER as an effective tool for improving treatment data management and display.

Comparison of the TEMPO binocular perimeter and Humphrey field analyzer

This study compared between TEMPO, a new binocular perimeter, with the Humphrey Field Analyzer (HFA). Patients were tested with both TEMPO 24-2 Ambient Interactive Zippy Estimated by Sequential Testing (AIZE)-Rapid and HFA 24-2 Swedish Interactive Threshold Algorithm (SITA)-Fast in a randomized sequence on the same day. Using a mixed-effects model, visual field (VF) parameters and reliability indices were compared. Retinal nerve fiber layer (RNFL) thickness was measured using Cirrus optical coherence tomography (OCT), and coefficient of determinations for VF and OCT parameters were calculated and compared using Akaike information criteria. 740 eyes (including 68 healthy, 262 glaucoma suspects, and 410 glaucoma) of 370 participants were evaluated. No significant differences were seen in mean deviation and visual field index between the two perimeters (P > 0.05). A stronger association between VF mean sensitivity (dB or 1/L) and circumpapillary RNFL was found for TEMPO (adjusted R2 = 0.25; Akaike information criteria [AIC] = 5235.5 for dB, and adjusted R2 = 0.29; AIC = 5200.8 for 1/L, respectively) compared to HFA (adjusted R2 = 0.22; AIC = 5263.9 for dB, and adjusted R2 = 0.22; AIC = 5262.7 for 1/L, respectively). Measurement time was faster for TEMPO compared to HFA (261 s vs. 429 s, P < 0.001). Further investigations are needed to assess the long-term monitoring potential of this binocular VF test.

[Primary Open Angle Glaucoma]

Primary open angle glaucoma is the most frequent type among the glaucomas. It is characterized by a progressive loss of retinal ganglion cells and a corresponding visual field loss. Risk factors include older age, ethnicity, family history of glaucoma and, most important, an elevated intraocular pressure (IOP). The IOP is the only modifiable risk factor for glaucoma progression. Therapeutic approaches aim to lowering the IOP and incorporate topical pressure lowering medication, laser treatment, and different surgical approaches. Surgery aims to reducing the outflow resistance of the aqueous humor. This may be achieved by surgically opening the trabecular meshwork or Schlemm's canal. Penetrating glaucoma surgery comprises classic trabeculectomy and other draining devices.

Identifying factors associated with fast visual field progression in patients with ocular hypertension based on unsupervised machine learning

Purpose

To identify ocular hypertension (OHT) subtypes with different trends of visual field (VF) progression based on unsupervised machine learning and to discover factors associated with fast VF progression.

Design

Cross-sectional and longitudinal study.

Participants

A total of 3133 eyes of 1568 ocular hypertension treatment study (OHTS) participants with at least five follow-up VF tests were included in the study.

Methods

We used a latent class mixed model (LCMM) to identify OHT subtypes using standard automated perimetry (SAP) mean deviation (MD) trajectories. We characterized the subtypes based on demographic, clinical, ocular, and VF factors at the baseline. We then identified factors driving fast VF progression using generalized estimating equation (GEE) and justified findings qualitatively and quantitatively.

Main Outcome Measure

Rates of SAP mean deviation (MD) change.

Results

The LCMM model discovered four clusters (subtypes) of eyes with different trajectories of MD worsening. The number of eyes in clusters were 794 (25%), 1675 (54%), 531 (17%) and 133 (4%). We labeled the clusters as Improvers, Stables, Slow progressors, and Fast progressors based on their mean of MD decline, which were 0.08, -0.06, -0.21, and -0.45 dB/year, respectively. Eyes with fast VF progression had higher baseline age, intraocular pressure (IOP), pattern standard deviation (PSD) and refractive error (RE), but lower central corneal thickness (CCT). Fast progression was associated with calcium channel blockers, being male, heart disease history, diabetes history, African American race, stroke history, and migraine headaches.

Conclusion

Unsupervised clustering can objectively identify OHT subtypes including those with fast VF worsening without human expert intervention. Fast VF progression was associated with higher history of stroke, heart disease, diabetes, and history of more using calcium channel blockers. Fast progressors were more from African American race and males and had higher incidence of glaucoma conversion. Subtyping can provide guidance for adjusting treatment plans to slow vision loss and improve quality of life of patients with a faster progression course.

Comparison of Perimetric Outcomes from a Tablet Perimeter, Smart Visual Function Analyzer, and Humphrey Field Analyzer

PURPOSE

The tablet-based Melbourne Rapid Fields (MRF) visual field (VF) test and the IMOvifa Smart Visual Function Analyzer (SVFA) are portable perimeters that may allow for at-home monitoring and more frequent testing. We compared tablet and SVFA results with outputs from the Humphrey Field Analyzer (HFA) 24-2 Swedish Interactive Threshold Algorithm Standard program.

DESIGN

Observational cross-sectional study.

SUBJECTS

Adult participants with a diagnosis of glaucoma, suspected glaucoma, or ocular hypertension seen in the Massachusetts Eye and Ear glaucoma clinic were enrolled. All participants were reliable and experienced HFA testers.

METHODS

Participants were tested with the SVFA and HFA. The study staff also trained participants on the MRF tablet with instructions to take weekly tests at home for 3 months. Visual field results from the 3 devices were compared.

MAIN OUTCOME MEASURES

Mean deviation (MD), pattern standard deviation (PSD), reliability parameters, and point sensitivity.

RESULTS

Overall, 79 participants (133 eyes) with a mean age of 61 ± 13 years (range, 26-79 years) were included; 59% of the participants were female, and the mean HFA MD was -2.7 ± 3.9 dB. The global indices of MD and PSD did not significantly vary between HFA and the 2 novel devices, except that the tablet VF reported a 0.6 dB higher PSD compared with HFA. However, tablet and SVFA sensitivities significantly differed from those of the HFA at 36 and 39 locations, respectively, out of 52 locations. Relative to HFA, the tablet overestimated light sensitivity in the nasal field while underestimating the temporal field. The SVFA generally underestimated light sensitivity, but its results were more similar to HFA results compared with the tablet.

CONCLUSIONS

Although average MD values from the 2 novel devices suggest that they provide similar results to the HFA, point-by-point comparisons highlight notable deviations. Differences in specific point sensitivity values were significant, especially between the tablet and the other 2 devices. These differences may in part be explained by differences in the devices' normative databases as well as how MD is calculated. However, the tablet had substantial differences based on location, indicating that the tablet design itself may be responsible for differences in local sensitivities.

FINANCIAL DISCLOSURE(S)

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

Comparison of the TEMPO Binocular Perimeter and Humphrey Field Analyzer

This study compared between TEMPO, a new binocular perimeter, with the Humphrey Field Analyzer (HFA). Patients were tested with both TEMPO 24 - 2 AIZE-Rapid and HFA 24 - 2 SITA-Fast in a randomized sequence on the same day. Using a mixed-effects model, visual field (VF) parameters and reliability indices were compared. Retinal nerve fiber layer (RNFL) thickness was measured using Cirrus OCT, and coefficient of determinations for visual field and OCT parameters were calculated and compared using Akaike information criteria. 740 eyes (including 68 healthy, 262 glaucoma suspects, and 410 glaucoma) of 370 participants were evaluated. No significant differences were seen in mean deviation and visual field index between the two perimeters (P > 0.05). A stronger association between VF mean deviation and circumpapillary RNFL was found for TEMPO (adjusted R2 = 0.28; AIC = 5210.9) compared to HFA (adjusted R2 = 0.26; AIC = 5232.0). TEMPO had better reliability indices (fixation loss, false positive, and false negative) compared to HFA (all P < 0.05). Measurement time was faster for TEMPO compared to HFA (261sec vs. 429sec, P < 0.001). Further investigations are needed to assess the long-term monitoring potential of this binocular VF test.

Premium Intraocular Lenses in Glaucoma-A Systematic Review

The incidence of both cataract and glaucoma is increasing globally. With increasing patient expectation and improved technology, premium intraocular lenses (IOLs), including presbyopia-correcting and toric IOLs, are being increasingly implanted today. However, concerns remain regarding the use of premium IOLs, particularly presbyopia-correcting IOLs, in eyes with glaucoma. This systematic review evaluates the use of premium IOLs in glaucoma. A comprehensive search of the MEDLINE database was performed from inception until 1 June 2023. Initial search yielded 1404 records, of which 12 were included in the final review of post-operative outcomes. Studies demonstrated high spectacle independence for distance and good patient satisfaction in glaucomatous eyes, with positive outcomes also in post-operative visual acuity, residual astigmatism, and contrast sensitivity. Considerations in patient selection include anatomical and functional factors, such as the type and severity of glaucomatous visual field defects, glaucoma subtype, presence of ocular surface disease, ocular changes after glaucoma surgery, and the reliability of disease monitoring, all of which may be affected by, or influence, the outcomes of premium IOL implantation in glaucoma patients. Regular reviews on this topic are needed in order to keep up with the rapid advancements in IOL technology and glaucoma surgical treatments.

Long-Term Effects on Retinal Structure and Function in a Mouse Endothelin-1 Model of Retinal Ganglion Cell Degeneration

Purpose

To study the long-term effects of endothelin-1 (ET-1)-induced retinal pathologies in mouse, using clinically relevant tools.

Methods

Adult C57BL/6 mice (7-9 weeks old) were intravitreally injected with PBS (n = 10) or 0.25 (n = 8), 0.5 (n = 8), or 1 nmol ET-1 (n = 9) and examined using electroretinogram, optical coherence tomography (OCT), and Doppler OCT at baseline and postinjection days 10, 28, and 56. Retinal ganglion cell (RGC) survival in retinal whole mount was quantified at days 28 and 56.

Results

ET-1 induced immediate retinal arterial constriction. The significantly reduced total blood flow and positive scotopic threshold response in the 0.5- and 1-nmol ET-1 groups at day 10 were recovered at day 28. A-wave magnitude was also significantly reduced at days 10 and 28. While a comparable and significant reduction in retinal nerve fiber layer thickness was detected in all ET-1 groups at day 56, the 1-nmol group was the earliest to develop such change at day 28. All ET-1 groups showed a transient inner retinal layer thinning at days 10 and 28 and a plateaued outer layer thickness at days 10 to 56. The 1-nmol group showed a significant RGC loss over all retinal locations examined at day 28 as compared with PBS control. As for the lower-dosage groups, significant RGC density loss at central and midperipheral retina was detected at day 56 when compared with day 28.

Conclusions

ET-1 injection in mice resulted in a transient vascular constriction and reduction in retinal functions, as well as a gradual loss of retinal nerve fiber layer and RGC in a dose-dependent manner.

Short-term Effect of Macular Edema on the Peripapillary Retinal Nerve Fiber Layer in Patients with Wet Age-Related Macular Degeneration and Diabetic Macular Edema: A Comparative Study

BACKGROUND

The combined presence of glaucoma and age-related macular degeneration (ARMD), or glaucoma and diabetes mellitus (DM), occur fairly frequently, especially in elderly patients. This study was intended to compare the effect of resolving macular edema due to DM and wet ARMD on peripapillary retinal nerve fiber layer (RNFL) thickness.

METHODS

This cross-sectional study included 76 patients with macular edema secondary to DM (n = 40, 52.6%) or wet ARMD (n = 36, 47.4%). The control group was comprised of 34 age and sex-matched healthy subjects. All study participants underwent evaluation of central macular thickness (CMT) and the peripapillary RNFL using spectral domain-optical coherence tomography (SD-OCT). Data from eyes that received an anti-VEGF injection were obtained one month after the procedure and were compared with pre-injection data.

RESULTS

The average initial thickness of the global peripapillary RNFL was 98.9 ±16.7 (61-163) µm in the macular edema group and 92.0±16.0 (84-115) µm in the control group (p = 0.045). The post-injection global peripapillary RNFL thickness was 97.3 ±19.0 (61-163) µm in the macular edema group and 92.2±18.0 (81-126) µm in the control group (p = 0.187). In the DM group, the changes in global RNFL thickness, as well as central and temporal quadrant thicknesses, were found to correlate significantly with the change in CMT (r = 0.356, p = 0.024; r = 0.545, p < 0.001, respectively).

CONCLUSIONS

Macular edema in wet ARMD appeared not to affect RNFL thickness. Differences in the etiology of macular edema can have varied effects on peripapillary RNFL. It is recommended that peripapillary RNFL thickness be evaluated cautiously in DM patients receiving intravitreal anti-VEGF therapy.

Use of artificial intelligence in forecasting glaucoma progression

Artificial intelligence (AI) has been widely used in ophthalmology for disease detection and monitoring progression. For glaucoma research, AI has been used to understand progression patterns and forecast disease trajectory based on analysis of clinical and imaging data. Techniques such as machine learning, natural language processing, and deep learning have been employed for this purpose. The results from studies using AI for forecasting glaucoma progression however vary considerably due to dataset constraints, lack of a standard progression definition and differences in methodology and approach. While glaucoma detection and screening have been the focus of most research that has been published in the last few years, in this narrative review we focus on studies that specifically address glaucoma progression. We also summarize the current evidence, highlight studies that have translational potential, and provide suggestions on how future research that addresses glaucoma progression can be improved.

Intereye comparison of visual field progression in eyes with open-angle glaucoma

PURPOSE

To investigate the intereye correlations between and differences in the rates of visual field (VF) progression in eyes with bilateral open-angle glaucoma.

STUDY DESIGN

Retrospective, longitudinal, observational study.

METHODS

Patients with bilateral open-angle glaucoma with 8 or more reliable 30 - 2 standard automated perimetry tests over a period of more than 2 years were enrolled. The rate of change of the MD (MD slope) was used as the indicator for the rates of VF progression. Descriptive statistics of the absolute intereye difference in the MD slope values were computed. Factors associated with a large intereye difference (> 0.42 dB/year) were explored.

RESULTS

One hundred eighty-eight eyes from 94 patients (56 women) were enrolled. A significant intereye correlation of the rates of visual field progression (P = .002) was found. The mean ± standard deviation and median intereye differences of the MD slope values were 0.29 ± 0.31 and 0.18 dB/year (range: 0-1.41), respectively. The 5th, 10th, 25th, 75th, 90th, and 95th percentiles of intereye differences were 0.01, 0.02, 0.08, 0.42, 0.72, and 0.91 dB/year, respectively. Older age and slower progression were significantly associated with large intereye difference.

CONCLUSION

A significant intereye correlation in the rate of VF progression was found in eyes with bilateral open-angle glaucoma. We showed the distributions and associated factors of intereye differences in VF progression. These data may be used for improving the estimation of rates of VF progression.

[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.

The number of examinations required for the accurate prediction of the progression of the central 10-degree visual field test in glaucoma

The purpose of the study was to investigate the number of examinations required to precisely predict the future central 10-degree visual field (VF) test and to evaluate the effect of fitting non-linear models, including quadratic regression, exponential regression, logistic regression, and M-estimator robust regression model, for eyes with glaucoma. 180 eyes from 133 open angle glaucoma patients with a minimum of 13 Humphrey Field Analyzer 10-2 SITA standard VF tests were analyzed in this study. Using trend analysis with ordinary least squares linear regression (OLSLR), the first, second, and third future VFs were predicted in a point-wise (PW) manner using a varied number of prior VF sequences, and mean absolute errors (MAE) were calculated. The number of VFs needed to reach the minimum 95% confidence interval (CI) of the MAE of the OLSLR was investigated. We also examined the effect of applying other non-linear models. When predicting the first, second, and third future VFs using OLSLR, the minimum MAE was obtained using VF1-12 (2.15 ± 0.98 dB), VF1-11 (2.33 ± 1.10 dB), and VF1-10 (2.63 ± 1.36 dB), respectively. To reach the 95% CI of these MAEs, 10, 10, and 8 VFs were needed for the first, second and third future VF predictions, respectively. No improvement was observed by applying non-linear regression models. As a conclusion, approximately 8-10 VFs were needed to achieve an accurate prediction of PW VF sensitivity of the 10-degree central VF.

Glaucoma Progression Diagnosis: The Agreement between Clinical Judgment and Statistical Software

Background: To explore the agreement between clinical judgment and Guided Progression Analysis II (GPAII) in the evaluation of visual fields (VF) progression in patients with glaucoma. Methods: Three glaucoma experts and three general ophthalmologists were asked to rate the VF series by classifying them as progressive through the observation of the overview report. The agreement between clinical judgment and GPAII event analysis (EA) and trend analysis (TA) was assessed by Cohen statistic. The sensitivity and specificity of clinical judgment in detecting the presence of progression was evaluated considering the results of GPAII as the reference standard. Results: 66 VF series were included in the study. Glaucoma experts, general ophthalmologists, GPAII EA, and GPAII TA found progression in 39%, 38%, 15%, and 21% of the VF series (p < 0.05). The clinical judgment of glaucoma experts and general ophthalmologists was discordant with GPAII EA in 27.2% and 28.7% (k = 0.35, 95% CI 0.15−0.56 and k = 0.30, 95% CI 0.09−0.52) and with GPAII TA in 21.2% and 25.7% of the VF series examined (k = 0.51, 95% CI 0.31−0.72 and k = 0.41, 95% CI 0.18−0.62). Considering the GPAII EA and TA as reference standard, glaucoma experts showed a sensitivity of 90% and 92.8% and a specificity of 69.6% and 75%, while general ophthalmologists showed a sensitivity of 80% and 78.5% and a specificity of 69.6% and 73%. Conclusions: The agreement between clinical judgment and GPAII ranges from fair to moderate. Glaucoma experts showed better ability than general ophthalmologists in detecting VF progression.

Pointwise and Region-Wise Course of Visual Field Loss in Patients With Glaucoma

Purpose

Accurate assessment of visual field (VF) trend may help clinicians devise the optimum treatment regimen. This study was conducted to investigate the behavior of VF sequences using pointwise and region-wise linear, exponential, and sigmoid regression models.

Materials and Methods

In a retrospective cohort study, 277 eyes of 139 patients with glaucoma who had been followed for at least 7 years were investigated. Linear, exponential, and sigmoid regression models were fitted for each VF test location and Glaucoma Hemifield Test (GHT) region to model the trend of VF loss. The model with the lowest root mean square error (RMSE) was selected as the best fit.

Results

The mean age (standard deviation [SD]) of the patients was 59.9 years (9.8) with a mean follow-up time of 9.3 (0.7) years. The exponential regression had the best fit based on pointwise and region-wise approaches in 39.3% and 38.1% of eyes, respectively. The results showed a better performance based on sigmoid regression in patients with initial VF sensitivity threshold greater than 22 dB (71.6% in pointwise and 62.2% in region-wise approaches). The overall RMSE of the region-wise regression model was lower than the overall RMSE of the pointwise model.

Conclusions

In the current study, nonlinear regression models showed a better fit compared to the linear regression models in tracking VF loss behavior. Moreover, findings suggest region-wise analysis may provide a more appropriate approach for assessing VF deterioration.

Translational Relevance

Findings may confirm a nonlinear progression of VF deterioration in patients with glaucoma.

Home-Based Perimetry for Glaucoma: Where Are We Now?

PURPOSE

To systematically summarize the current literature on home-based perimeters for glaucoma.

METHODS

A systematic review was conducted in accordance with the PRISMA-DTA checklist. Studies reporting portable perimeters designed for home use were retrieved from electronic databases and handsearching of reference lists of relevant publications. Studies reporting diagnostic accuracy data were evaluated with the QUADAS-2 tool and using standard automated perimetry as the reference standard. Other aspects of the technology such as detection of disease progression and patient acceptability were also included. Data were reported in a narrative and tabular format.

RESULTS

Of 18 included studies, 10 evaluated tablet-based perimeters, 4 evaluated web-based perimeters, and 4 evaluated head-mounted displays. Most studies used a clinic or laboratory setting. All studies reporting diagnostic accuracy data had high risk of bias in at least one domain. Across studies, sensitivity ranged from 54% in detecting mild to 91% in detecting moderate/severe glaucoma patients from controls, while specificity was between 50% and 100% for any form of glaucoma. The reported acceptability was high but had high risk of bias.

CONCLUSION

Several promising technologies designed for home-based perimetry have been reported. Current studies used a controlled setting in highly selected populations. There is uncertainty on the performance and value of home-based perimetry for glaucoma. Additional efforts are required to elucidate the ability of the home-based perimeters to detect glaucoma and disease progression in real life situations.

A deep-learning system predicts glaucoma incidence and progression using retinal photographs

BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for predicting and stratifying the risk of glaucoma onset and progression based on color fundus photographs (CFPs), with clinical validation of performance in external population cohorts.MethodsWe established data sets of CFPs and visual fields collected from longitudinal cohorts. The mean follow-up duration was 3 to 5 years across the data sets. Artificial intelligence (AI) models were developed to predict future glaucoma incidence and progression based on the CFPs of 17,497 eyes in 9346 patients. The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of the AI models were calculated with reference to the labels provided by experienced ophthalmologists. Incidence and progression of glaucoma were determined based on longitudinal CFP images or visual fields, respectively.ResultsThe AI model to predict glaucoma incidence achieved an AUROC of 0.90 (0.81-0.99) in the validation set and demonstrated good generalizability, with AUROCs of 0.89 (0.83-0.95) and 0.88 (0.79-0.97) in external test sets 1 and 2, respectively. The AI model to predict glaucoma progression achieved an AUROC of 0.91 (0.88-0.94) in the validation set, and also demonstrated outstanding predictive performance with AUROCs of 0.87 (0.81-0.92) and 0.88 (0.83-0.94) in external test sets 1 and 2, respectively.ConclusionOur study demonstrates the feasibility of deep-learning algorithms in the early detection and prediction of glaucoma progression.FUNDINGNational Natural Science Foundation of China (NSFC); the High-level Hospital Construction Project, Zhongshan Ophthalmic Center, Sun Yat-sen University; the Science and Technology Program of Guangzhou, China (2021), the Science and Technology Development Fund (FDCT) of Macau, and FDCT-NSFC.

The Usefulness of Assessing Glaucoma Progression With Postprocessed Visual Field Data

Purpose

Data postprocessing with statistical techniques that are less sensitive to noise can be used to reduce variability in visual field (VF) series. We evaluated the detection of glaucoma progression with postprocessed VF data generated with the dynamic structure–function (DSF) model and MM-estimation robust regression (MRR).

Method

The study included 118 glaucoma eyes with at least 15 visits selected from the Rotterdam dataset. The DSF and MRR models were each applied to observed mean deviation (MD) values from the first three visits (V_1–3) to predict the MD at V_4. MD at V₅ was predicted with data from V_1–4 and so on until the MD at V₉ was predicted, creating two additional datasets: DSF-predicted and MRR-predicted. Simple linear regression was performed to assess progression at the ninth visit. Sensitivity was evaluated by adjusting for false-positive rates estimated from patients with stable glaucoma and by using longer follow-up series (12th and 15th visits) as a surrogate for progression.

Results

For specificities of 80% to 100%, the DSF-predicted dataset had greater sensitivity than the observed and MRR-predicted dataset when positive rates were normalized with corresponding false-positive estimates. The DSF-predicted and observed datasets had similar sensitivity when the surrogate reference standard was applied.

Conclusions

Without compromising specificity, the use of DSF-predicted measurements to identify progression resulted in a better or similar sensitivity compared to using existing VF data.

Translational Relevance

The DSF model could be applied to postprocess existing visual field data, which could then be evaluated to identify patients at risk of progression.

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.

Detecting Progression in Patients With Different Clinical Presentations of Primary Open-angle Glaucoma

PRCIS

Glaucoma progression was more frequently identified by assessing retinal fiber layer thickness than by monitoring visual field (VF) loss for different baseline classifications in primary open-angle glaucoma.

PURPOSE

The aim was to compare the detection of glaucoma progression by retinal nerve fiber layer thickness (RNFLT) and VF assessments for different baseline classifications of primary open-angle glaucoma.

METHODS

This study included 194 eyes from 194 patients with a minimum of 9 follow-up visits selected from the Diagnostic Innovation in Glaucoma Study (DIGS) and the African Descent and Glaucoma Evaluation Study (ADAGES). Each eye was classified according to baseline clinical signs: ocular hypertension (n=39), glaucomatous optic neuropathy only (n=60), glaucomatous visual field loss only (GVF, n=39) and definite glaucoma (concurrent optic disc and VF defect, n=56). We assessed progression by performing simple linear regression on global and sectorial mean deviations values generated for RNFLT (RNFLT-MD) and VF data (VF-MD). The proportion of eyes identified as progressing (positive rate) by RNFLT-MD and by VF-MD were compared within each classification.

RESULTS

Whereas both parameters performed similarly among glaucomatous optic neuropathy only and definite glaucoma eyes, the positive rate obtained with global RNFLT-MD was significantly greater compared with global VF-MD by 33.3% and 30.8% among ocular hypertension eyes and GVF eyes, respectively. This finding was consistent in the inferotemporal sector; however, similar positive rates were obtained for both parameters in the superotemporal sector.

CONCLUSIONS

While both RNFLT and VF parameters showed comparable abilities to identify progression across the different classifications, RNFLT assessment may be better suited to monitor progression, particularly among patients with elevated intraocular pressure and those who present with only GVF defect at baseline.

Evaluation of the external validity of a joint structure-function model for monitoring glaucoma progression

The dynamic structure–function (DSF) model was previously shown to have better prediction accuracy than ordinary least square linear regression (OLSLR) for short series of visits. The current study assessed the external validity of the DSF model by testing its performance in an independent dataset (Ocular Hypertension Treatment Study–Confocal Scanning Laser Ophthalmoscopy [OHTS–CSLO] ancillary study; N = 178 eyes), and also on different test parameters in a sample selected from the Diagnostic Innovations in Glaucoma Study or the African Descent and Glaucoma Evaluation Study (DIGS/ADAGES). Each model was used to predict structure–function paired data at visits 4–7. The resulting prediction errors for both models were compared using the Wilcoxon signed-rank test. In the independent dataset, the DSF model predicted rim area and mean sensitivity paired measurements more accurately than OLSLR by 1.8–5.5% (p ≤ 0.004) from visits 4–6. Using the DIGS/ADAGES dataset, the DSF model predicted retinal nerve fiber layer thickness and mean deviation paired measurements more accurately than OLSLR by 1.2–2.5% (p ≤ 0. 007). These results demonstrate the external validity of the DSF model and provide a strong basis to develop it into a useful clinical tool.

Reasons why OCT Global Circumpapillary Retinal Nerve Fiber Layer Thickness is a Poor Measure of Glaucomatous Progression

Purpose

To assess the effects of local defects, segmentation errors, and improper image alignment on the performance of the commonly used optical coherence tomography (OCT) measure of progression, that is the change in global (average) circumpapillary retinal nerve fiber layer (cpRNFL) thickness (ΔG).

Methods

One hundred fifty eyes suspected of, or with, early glaucoma had OCT circle and cube scans obtained using eye tracking on two occasions at least 1 year apart. Statistical progression was defined by fixed values of ΔG (3-8 um) and quantile regression. For a reference standard, four authors identified 30 eyes as "likely progressed," and 61 eyes that "likely had not progressed" based on OCT reports from both baseline and follow-up tests.

Results

A ΔG criterion of 4 um had the best accuracy: 77%, with 5 false positive (8.2%) and 16 false negative (53%). A post hoc analysis of circular b-scans and OCT probability maps of these eyes indicated that segmentation errors and local progression accounted for most of these mistakes. Segmentation errors, although less common, were also present in true positives and true negatives.

Conclusions

Local defects and segmentation errors are the primary reasons for the poor performance of cpRNFL thickness G metric. Because these problems are difficult, if not impossible, to eliminate, the G metric should not be relied on in isolation for detecting glaucomatous progression.

Translational Relevance

Local defects and segmentation errors are easily identified by viewing OCT circumpapillary images, which should be part of the standard protocol for detecting glaucomatous progression.