Visual field progression patterns in the ocular hypertension treatment study correspond to vulnerability regions of the disc.

OBJECTIVES: To determine the locations on the 24-2 visual field (VF) testing grid that are most likely to progress in patients with ocular hypertension (OHTN). Based on a structural model of superior and inferior areas of relative vulnerability at the optic disc, we hypothesized that the nasal and paracentral regions are more prone to show a reduction in sensitivity. METHODS: Posthoc analysis of data collected in phases 1 and 2 of the Ocular Hypertension Treatment Study (OHTS). A pointwise analysis was applied to determine the progression patterns in the early and delayed treatment groups. Each group's progression rate and frequency were calculated for each of the 52 locations corresponding to the 24-2 VF strategy, using trend- and event-based analyses, respectively. RESULTS: For the event-based analysis, the events were most commonly found in the nasal and paracentral regions. The same regions, with some modest variation, were found to have the fastest rates of progression (ROP) measured with trend analysis. A similar pattern of progression was observed in both the early and delayed treatment groups. The difference in event rates and ROP between the early and delayed treatment groups was also greatest in the nasal and paracentral regions. CONCLUSIONS: Development of VF loss in ocular hypertensive eyes appears to be consistent with the vulnerability zones previously described in glaucomatous eyes with established VF loss. Ocular hypotensive treatment likely helps to slow the rate of progression in these regions. This suggests that careful monitoring of these locations may be useful.

Proactive Decision Support for Glaucoma Treatment: Predicting Surgical Interventions with Clinically Available Data.

A longitudinal ophthalmic dataset was used to investigate multi-modal machine learning (ML) models incorporating patient demographics and history, clinical measurements, optical coherence tomography (OCT), and visual field (VF) testing in predicting glaucoma surgical interventions. The cohort included 369 patients who underwent glaucoma surgery and 592 patients who did not undergo surgery. The data types used for prediction included patient demographics, history of systemic conditions, medication history, ophthalmic measurements, 24-2 VF results, and thickness measurements from OCT imaging. The ML models were trained to predict surgical interventions and evaluated on independent data collected at a separate study site. The models were evaluated based on their ability to predict surgeries at varying lengths of time prior to surgical intervention. The highest performing predictions achieved an AUC of 0.93, 0.92, and 0.93 in predicting surgical intervention at 1 year, 2 years, and 3 years, respectively. The models were also able to achieve high sensitivity (0.89, 0.77, 0.86 at 1, 2, and 3 years, respectively) and specificity (0.85, 0.90, and 0.91 at 1, 2, and 3 years, respectively) at an 0.80 level of precision. The multi-modal models trained on a combination of data types predicted surgical interventions with high accuracy up to three years prior to surgery and could provide an important tool to predict the need for glaucoma intervention.

Detecting Established Glaucoma Using OCT Alone: Utilizing an OCT Reading Center in a Real-World Clinical Setting.

Purpose: We evaluated the ability of an optical coherence tomography (OCT)-based reading center for glaucoma (ORG) to detect established glaucoma using OCT alone. Methods: This study included eyes from 70 consecutive patients with established glaucoma (i.e. moderate or severe glaucoma according to the International Classification of Diseases [ICD]-10 guidelines) and 20 consecutive healthy subjects, who had no evidence of glaucomatous optic neuropathy (GON) or visual field (VF) loss in either eye. Using a standardized ORG quality assessment, 33 eyes were excluded due to media opacity (12), poor image quality (13), or epiretinal membrane (8). Of the remaining 147 eyes, 86 had established glaucoma and 36 were from healthy controls (total n = 122). Based on the OCT report alone and applying a previously described evaluation method, the presence of GON in each eye was determined by two masked ORG graders. The main outcome measures were sensitivity and specificity for detection of eyes with established glaucoma. Results: Of the 86 eyes with established glaucoma (average mean deviation [MD] = -10.9 ± 7.7 dB, range = -0.5 to -31.5 dB), only one eye (MD = -0.46) was missed (sensitivity = 98.8%). However, the other eye of this patient was correctly classified as GON. Therefore, at a patient level, sensitivity was 100%. None of the 36 healthy eyes was classified as GON by the ORG (specificity = 100%). Conclusions: An OCT-based reading center is able to identify eyes with established glaucoma using OCT alone with high sensitivity and specificity. Translational Relevance: Our study validates the use of a systematic OCT-based approach for glaucoma detection in a real-world setting.

Identifying Rapid Glaucoma Progression Using Hemifield Rates of Progression.

PRCIS: Hemifield rates of progression are more sensitive to focal progression (or faster progression) than global rates. This can aid in tailoring management and treatment decisions. PURPOSE: To determine if the rate of progression (ROP) of each hemifield of the 24-2 visual field (VF) aids in the detection of rapidly progressing eyes. METHODS: In this retrospective longitudinal study, we evaluated 1658 eyes of 1658 consecutive glaucoma patients with global mean deviation (MD) VF loss between -3 and -15 dB at baseline and ≥8 reliable VF tests (Swedish Interactive Thresholding Algorithm 24-2) with over ≥3 years of follow-up. The ROP (dB/year) based on global MD, superior hemifield MD, and inferior hemifield MD was calculated. The worst hemifield ROP (ROPworst) and hemifield ROP absolute difference (ROPdiff) were determined for each eye. Eyes were categorized based on the ROP from each metric as slow (-0.5 dB/year or better), rapid (worse than -0.5 dB/year), very rapid (worse than -1.0 dB/year), and catastrophic (worse than -2.0 dB/year) progression. The rate of significant asymmetric hemifield progression rate (ROPdiff ≥0.5 dB/year) was also evaluated. RESULTS: On average, ROPworst was faster than ROPglobal by 0.25±0.3 dB/year ( P <0.001). Based on ROPworst, 422 eyes (25%) were classified as progressing more rapidly than the ROPglobal classification. Over 40% (153/339) of the eyes classified as rapid progressors by ROPglobal were classified as very rapid or catastrophic progressors based on ROPworst. Eyes that progressed more rapidly based on ROPworst also had a higher rate of asymmetric progression. CONCLUSION: Hemifield ROPs are more sensitive to focal progression (or faster progression) than global rates and can aid in tailoring management and treatment decisions.

Improving glaucoma staging in clinical practice by combining the ICD-10 glaucoma severity classification system and optical coherence tomography.

OBJECTIVE: The International Classification of Disease, 10th revision (ICD-10) codes used for glaucoma severity classification are based on the 24-2 visual-field (VF) test. This study aim was to assess the added value of providing clinicians with optical coherence tomography (OCT) data, in addition to functional data, for glaucoma staging in clinical practice. EXPOSURE: Disease classification was determined for 54 glaucoma eyes, according to the principles of the ICD-10 guidelines. Eyes were independently graded in a masked fashion using the 24-2 VF test and 10-2 VF test, with and without OCT information. The reference standard (RS) for severity was determined using a previously published automated structure-function topographic agreement for glaucomatous damage using all available information. RESULTS: The RS classified eyes as mild, moderate and advanced in 3, 16 and 35 cases, respectively. Individual and combined 24-2 and 10-2 based gradings were significantly different from the RS (all P < 0.005), with Kappa agreements of 0.26, 0.45 and 0.42 respectively (P < 0.001). Classifications using OCT combined with either of the VF were not-significantly different from the RS (P > 0.3) with Kappa agreements of 0.56 and 0.57 respectively (P < 0.001). Combining 24-2 with OCT had less severity overestimations while 10-2 with OCT had fewer underestimations. CONCLUSION: Combining OCT and VF data provides better staging of glaucoma severity than VF data alone. The 24-2 and OCT combination seems most appropriate given the high concordance with the RS and less overestimation of severity. Incorporating structural information into disease stages allows clinicians to set more appropriate severity-based treatment targets for individual patients.

Glaucoma Detection Using Optical Coherence Tomography: Reviewing the Pitfalls of Comparison to Normative Data.

PRCIS: Optical coherence tomography is essential in managing glaucoma. This review describes various artifacts that originate from using a normative database to compare the individual's scans. This is a review paper regarding artifacts in optical coherence tomography imaging for glaucoma arising from using a normative database as a reference for healthy retinal nerve fiber layer and ganglion cell layer.

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

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

Validating Trend-Based End Points for Neuroprotection Trials in Glaucoma.

Purpose: The purpose of this study was to evaluate the power of trend-based visual field (VF) progression end points against long-term development of event-based end points accepted by the US Food and Drug Administration (FDA). Methods: One eye from 3352 patients with ≥10 24-2 VFs (median = 11 years) follow-up were analyzed. Two FDA-compatible criteria were applied to these series to label "true-progressed" eyes: ≥5 locations changing from baseline by more than 7 dB (FDA-7) or by more than the expected test-retest variability (GPA-like) in 2 consecutive tests. Observed rates of progression (RoP) were used to simulate trial-like series (2 years) randomly assigned (1000 times) to a "placebo" or a "treatment" arm. We simulated neuroprotective "treatment" effects by changing the proportion of "true progressed" eyes in the two arms. Two trend-based methods for mean deviation (MD) were assessed: (1) linear mixed model (LMM), testing average difference in RoP between the two arms, and (2) time-to-progression (TTP), calculated by linear regression as time needed for MD to decline by predefined cutoffs from baseline. Power curves with 95% confidence intervals were calculated for trend and event-based methods on the simulated series. Results: The FDA-7 and GPA-like progression was achieved by 45% and 55% of the eyes in the clinical database. LMM and TTP had similar power, significantly superior to the event-based methods, none of which reached 80% power. All methods had a 5% false-positive rate. Conclusions: The trend-based methods can efficiently detect treatment effects defined by long-term FDA-compatible progression. Translational Relevance: The assessment of the power of trend-based methods to detect clinically relevant progression end points.

Risk Calculation in the Medication Arm of the Ocular Hypertension Treatment Study.

PURPOSE: Risk assessment is integral to the management of individuals with ocular hypertension (OHTN). This study aims to determine the predictive accuracy of the Ocular Hypertension Treatment Study 5-year risk calculator (OHTS calculator) among treated patients with OHTN by applying it to patients randomized to the Ocular Hypertension Treatment Study (OHTS) medication arm. DESIGN: Post hoc secondary analysis of a randomized clinical trial. SUBJECTS: Individuals participating in the OHTS who were randomized to the medication arm. Only participants with complete baseline data in both eyes were included (n = 726). METHODS: The hazard ratios (HRs) of the medication group in OHTS were compared to the HR used for the OHTS calculator using the z-test statistic to establish the OHTS calculator's generalizability to the OHTS medication arm. The performance of the OHTS calculator among the OHTS medication group was evaluated twice, using both untreated baseline intraocular pressure (IOP) and average treated IOP during the first 24 months for the IOP variable. MAIN OUTCOME MEASURES: The performance was determined based on the model's accuracy in estimating the risk of reaching an OHTS primary open-angle glaucoma (POAG) end point using calibration chi-square and discriminating between participants who did or did not develop POAG. RESULTS: The HRs for the OHTS medication arm were not significantly different from those used in the OHTS calculator for untreated OHTN derived from observation arm data (P > 0.1). Based on the calibration chi-square test for the medication group, the OHTS calculator prediction model had good predictive accuracy when using the mean treated IOP and poorer predictive accuracy with the untreated baseline IOP (chi-square 10 and 29, respectively). The model had good discrimination with treated IOP (c-statistic = 0.77), comparable to what has been reported for the OHTS calculator in the OHTS observation group. CONCLUSIONS: The OHTS calculator can be applied to treated patients with OHTN, and repeat risk calculation after initiating IOP reduction may provide useful information that can aid in disease management. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A potential primary endpoint for clinical trials in glaucoma neuroprotection.

The purpose of this retrospective, longitudinal study is to evaluate the relationship between MD slope from visual field tests collected over a short period of time (2 years) and the current United States' Food and Drug Administration (FDA) recommended endpoints for visual field outcomes. If this correlation is strong and highly predictive, clinical trials employing MD slopes as primary endpoints could be employed in neuroprotection clinical trials with shorter duration and help expedite the development of novel IOP-independent therapies. Visual field tests of patients with or suspected glaucoma were selected from an academic institution and evaluated based on two functional progression endpoints: (A) five or more locations worsening by at least 7 dB, and (B) at least five test locations based upon the GCP algorithm. A total of 271 (57.6%) and 278 (59.1%) eyes reached Endpoints A and B, respectively during the follow up period. The median (IQR) MD slope of eyes reaching vs. not reaching Endpoint A and B were -1.19 (-2.00 to -0.41) vs. 0.36 (0.00 to 1.00) dB/year and -1.16 (-1.98 to -0.40) vs. 0.41 (0.02 to 1.03) dB/year, respectively (P < 0.001). It was found that eyes experiencing rapid 24-2 visual field MD slopes over a 2-year period were on average tenfold more likely to reach one of the FDA accepted endpoints during or soon after that period.

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

Purpose: Performance comparison of optical coherence tomography (OCT) and visual field (VF) summary metrics for detecting glaucomatous progression. Methods: Thirty healthy control eyes (mean deviation [MD], -1.25 ± 2.03; pattern standard deviation [PSD] , 1.78 ± 0.77) and 91 patient eyes comprised of 54 glaucoma patients and 37 glaucoma suspects (MD, -1.58 ± 1.96; PSD, 2.82 ± 1.92) with a follow-up of at least 1 year formed a group to evaluate progression with event analyses (P-Event). A subset of eyes with an additional criterion of a minimum of four tests was used for trend analyses (P-Trend) (30 healthy controls and 73 patients). For P-Event analysis, test-retest variability thresholds (lower 5th percentile) were estimated with repeat tests within a 4-month period. A P-Event eye was considered a "progressor" if the difference between follow-up and baseline tests exceeded the variability thresholds. For the P-Trend analysis, rates of change were calculated based on least-squares regression. Negative rates with significant (P < 0.05) values were considered progressing. For a reference standard, 17 patient eyes were classified as definitely progressing based on clear evidence of structural and corresponding functional progression. Results: Isolated OCT and VF summary metrics were either inadequately sensitive or not too specific. Combinations of OCT-OCT and OCT-VF metrics markedly improved specificity to nearly 100%. A novel combination of OCT metrics (circumpapillary retinal nerve fiber layer and ganglion cell layer) showed high precision, with 13 of the 15 statistical progressors confirmed as true positives. Conclusions: Although relying solely on metrics is not recommended for clinical purposes, in situations requiring very high specificity and precision, combinations of OCT-OCT metrics can be used. Translational Relevance: All available OCT and VF metrics can miss eyes with progressive glaucomatous damage and/or can falsely identify progression in stable eyes.

Fast Progressors in Glaucoma: Prevalence Based on Global and Central Visual Field Loss.

PURPOSE: To determine the prevalence of fast global and central visual field (VF) progression in individuals with glaucoma under routine care. DESIGN: Observational study. PARTICIPANTS: Six hundred ninety-three eyes of 461 individuals with glaucoma followed up over a median of 4.5 years. METHODS: This study included (1) patients at a private ophthalmology clinic in Melbourne, Australia, and (2) individuals in 2 prospective longitudinal observational studies across 3 sites in the United States. All individuals had a diagnosis of glaucoma and were under routine care, and had performed 5 or more reliable 24-2 VF tests over a 1- to 5-year period. Ordinary least squares regression analyses were used to calculate the rate of global mean deviation (MD) change over time and the rate of the mean total deviation values of the 12 test locations within the central 10° region (MTD10) for each eye. MAIN OUTCOME MEASURES: Prevalence of progression based on the rate of MD and the MTD10 change across various fixed cutoffs and cutoffs based on the estimated normal distribution (from the positive slopes). RESULTS: Based on the MD and the MTD10, 12.5% and 11.7% of the eyes, respectively, exhibited a rate of change that was less than -1.0 dB/year (being a rate that typically is defined as "fast progression" for MD values), and 29.0% of the eyes showed a change of less than -0.5 dB/year on MTD10. Furthermore, 12.7% and 9.1% of the eyes exhibited a rate of change that exceeded the 1% cutoff of the estimated normal distribution MD and the MTD10 values, respectively. CONCLUSIONS: This study found that approximately 1 in 8 eyes with glaucoma receiving routine care showed fast progression based on global MD values (< -1.0 dB/year) and that nearly 1 in 3 eyes showed a < -0.5 dB/year decline centrally. These findings highlight the clinical importance of assessing progressive central VF loss and reinforce the need for new therapies to prevent functional disability in a notable proportion of individuals who continue to exhibit fast progression. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

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

PURPOSE: To investigate the efficacy of a deep learning regression method to predict macula ganglion cell-inner plexiform layer (GCIPL) and optic nerve head (ONH) retinal nerve fiber layer (RNFL) thickness for use in glaucoma neuroprotection clinical trials. DESIGN: Cross-sectional study. PARTICIPANTS: Glaucoma patients with good quality macula and ONH scans enrolled in 2 longitudinal studies, the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovations in Glaucoma Study. METHODS: Spectralis macula posterior pole scans and ONH circle scans on 3327 pairs of GCIPL/RNFL scans from 1096 eyes (550 patients) were included. Participants were randomly distributed into a training and validation dataset (90%) and a test dataset (10%) by participant. Networks had access to GCIPL and RNFL data from one hemiretina of the probe eye and all data of the fellow eye. The models were then trained to predict the GCIPL or RNFL thickness of the remaining probe eye hemiretina. MAIN OUTCOME MEASURES: Mean absolute error (MAE) and squared Pearson correlation coefficient (r2) were used to evaluate model performance. RESULTS: The deep learning model was able to predict superior and inferior GCIPL thicknesses with a global r2 value of 0.90 and 0.86, r2 of mean of 0.90 and 0.86, and mean MAE of 3.72 µm and 4.2 µm, respectively. For superior and inferior RNFL thickness predictions, model performance was slightly lower, with a global r2 of 0.75 and 0.84, r2 of mean of 0.81 and 0.82, and MAE of 9.31 µm and 8.57 µm, respectively. There was only a modest decrease in model performance when predicting GCIPL and RNFL in more severe disease. Using individualized hemiretinal predictions to account for variability across patients, we estimate that a clinical trial can detect a difference equivalent to a 25% treatment effect over 24 months with an 11-fold reduction in the number of patients compared to a conventional trial. CONCLUSIONS: Our deep learning models were able to accurately estimate both macula GCIPL and ONH RNFL hemiretinal thickness. Using an internal control based on these model predictions may help reduce clinical trial sample size requirements and facilitate investigation of new glaucoma neuroprotection therapies. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Augmenting Kalman Filter Machine Learning Models with Data from OCT to Predict Future Visual Field Loss: An Analysis Using Data from the African Descent and Glaucoma Evaluation Study and the Diagnostic Innovation in Glaucoma Study.

Purpose: To assess whether the predictive accuracy of machine learning algorithms using Kalman filtering for forecasting future values of global indices on perimetry can be enhanced by adding global retinal nerve fiber layer (RNFL) data and whether model performance is influenced by the racial composition of the training and testing sets. Design: Retrospective, longitudinal cohort study. Participants: Patients with open-angle glaucoma (OAG) or glaucoma suspects enrolled in the African Descent and Glaucoma Evaluation Study or Diagnostic Innovation in Glaucoma Study. Methods: We developed a Kalman filter (KF) with tonometry and perimetry data (KF-TP) and another KF with tonometry, perimetry, and global RNFL data (KF-TPO), comparing these models with one another and with 2 linear regression (LR) models for predicting mean deviation (MD) and pattern standard deviation values 36 months into the future for patients with OAG and glaucoma suspects. We also compared KF model performance when trained on individuals of European and African descent and tested on patients of the same versus the other race. Main Outcome Measures: Predictive accuracy (percentage of MD values forecasted within the 95% repeatability interval) differences among the models. Results: Among 362 eligible patients, the mean ± standard deviation age at baseline was 71.3 ± 10.4 years; 196 patients (54.1%) were women; 202 patients (55.8%) were of European descent, and 139 (38.4%) were of African descent. Among patients with OAG (n = 296), the predictive accuracy for 36 months in the future was higher for the KF models (73.5% for KF-TP, 71.2% for KF-TPO) than for the LR models (57.5%, 58.0%). Predictive accuracy did not differ significantly between KF-TP and KF-TPO (P = 0.20). If the races of the training and testing set patients were aligned (versus nonaligned), the mean absolute prediction error of future MD improved 0.39 dB for KF-TP and 0.48 dB for KF-TPO. Conclusions: Adding global RNFL data to existing KFs minimally improved their predictive accuracy. Although KFs attained better predictive accuracy when the races of the training and testing sets were aligned, these improvements were modest. These findings will help to guide implementation of KFs in clinical practice.

The ICD-10 Glaucoma Severity Score Underestimates the Extent of Glaucomatous Optic Nerve Damage.

PURPOSE: To evaluate the International Classification of Disease, Tenth Revision (ICD-10) codes used for glaucoma severity classification, which are based on the location of visual field (VF) defects; given the known poor sensitivity of the 24-2 visual field test to early disease and macular damage, we hypothesized that the ICD-10 codes would not accurately reflect the extent of glaucomatous damage. DESIGN: Retrospective validity and reliability analysis. METHODS: We evaluated 80 eyes with glaucomatous optic neuropathy (GON). Masked reviewers assigned an ICD-10 severity grade based on 24-2 VF. Two additional masked examiners determined the presence of optical coherence tomography (OCT) structural damage in each hemifield and/or central 5 degrees to define an OCT-based equivalent ICD-10 classification. RESULTS: A total of 80 eyes with GON were classified as mild, moderate and advanced in 15, 23, and 42 cases, respectively, based on the 24-2 VF, and in 6, 7, and 67 cases, respectively, based on OCT. The OCT classifications were more severe in 29 of 80 cases (36%). In 33 cases (41.3%), macular damage detected by OCT was missed by the 24-2. In 4 of 80 cases (5%), the VF overestimated the severity, likely due to variability of the 24-2 test. CONCLUSIONS: The ICD-10 system relies solely on damage seen on the 24-2 and as provides a 24-2 functional score rather than a "glaucoma" severity score. OCT revealed wide variation of damage across grades, with a significant proportion of the eyes showing macular structural damage missed with the 24-2 VF. Adding OCT information to the ICD-10 system would help it to more accurately reflect the extent of glaucomatous damage.

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

Purpose: To test a model of retinal nerve fiber bundle trajectories that predicts the arcuate-shaped patterns seen on optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability/deviation maps (p-maps) in glaucomatous eyes. Methods: Thirty-one glaucomatous eyes from a database of 250 eyes had clear arcuate-shaped patterns on RNFL p-maps derived from an OCT cube scan. The borders of the arcuate patterns were extracted from the RNFL p-maps. Next, the trajectories from an arcuate model were compared against these borders via a normalized root-mean-square difference analysis. The model's parameter, ß, was varied, and the best-fitting, initial clock-hour position of the trajectory to the border was found for each ß. Finally, the regions, as determined by the arcuate border's best-fit, initial clock-hour positions, were compared against the abnormal regions on the circumpapillary retinal nerve fiber layer (cpRNFL) profile. Results: The arcuate model's mean ßSup and ßInf parameters minimized large differences between the trajectories and the arcuate borders on the RNFL p-maps. Furthermore, on average, 68% of the cpRNFL regions defined by the arcuate border's best-fit, initial clock-hour positions were abnormal (i.e., below the ≤5% threshold). Conclusions: The arcuate model performed well in predicting the borders of arcuate patterns seen on RNFL p-maps. It also predicted the associated abnormal regions of the cpRNFL thickness plots. Translational Relevance: This model should prove useful in helping clinicians understand topographical comparisons among different OCT representations and should improve structure-structure, as well as structure-function agreement analyses.

Towards detection of biomarkers in the eye using an aptamer-based graphene affinity nanobiosensor.

We present an approach to enable the sensitive and specific detection of biomarkers in undiluted tears in the eye using an aptamer-based graphene affinity nanosensor. The nanosensor is a graphene field-effect transistor, in which a nucleic acid aptamer and a biomolecule-permeable polyethylene glycol (PEG) nanolayer are immobilized on the graphene surface. The aptamer is capable of specifically recognize the target biomarker and induce a change in the carrier concentration of the graphene, which is measured to determine the biomarker concentration. The PEG nanolayer minimizes nonspecific adsorption of background molecules in the sample that would otherwise interfere with the biomarker detection. Experimental results show that tumor necrosis factor alpha (TNF-alpha), an inflammatory cytokine, can be sensitively and specifically detected in undiluted artificial tears with a limit of detection of 0.34 pM. This ability to detect and measure biomarkers in undiluted physiological fluids allows the nanosensor to be potentially used in applications where sample dilutions are not practical, such as wearable measurements of tear-borne biomarkers in the eye.

Blood pressure control and glaucoma risk in postmenopausal women: an analysis from the Women's Health Initiative.

OBJECTIVE: Individuals with elevated systolic blood pressure (BP) or low diastolic BP, whether or not on antihypertensive treatment, may be at higher risk for developing glaucoma. We aimed to investigate BP levels in relation to glaucoma risk in a large cohort of postmenopausal women. METHODS: Prospective follow-up of 101,447 postmenopausal women without prior history of glaucoma enrolled in the Women's Health Initiative Study. BP was measured in-clinic at baseline and after 3 years using standardized procedures. Antihypertensive medication use was determined by drug inventory at baseline and year 3. Women self-reported incident newly diagnosed glaucoma annually. Hazard ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards analyses adjusting for demographic, medical history, and lifestyle covariates. RESULTS: During a mean follow-up of 4.7 years, we documented 7,514 glaucoma cases. Among women not on antihypertensive treatment, those with systolic BP ≥ 140 mm Hg or diastolic BP ≥80 mm Hg were not at higher risk of developing glaucoma (HR 0.97, 95% confidence intervals 0.88-1.08 and HR 1.00 [0.93-1.08], respectively), compared with women with a systolic BP < 120 mm Hg or a diastolic BP 60 to <80 mm Hg. Among women on antihypertensive treatment, neither systolic BP ≥ 140 mm Hg nor diastolic BP ≥80 mm Hg was associated with an increased glaucoma risk (HR 0.89 [0.79-1.00] and HR 0.97 [0.90-1.05], respectively). A diastolic BP <60 mm Hg was not associated with a higher risk compared with a diastolic BP 60 to <80 mm Hg. CONCLUSIONS: BP control is not associated with an increased or decreased glaucoma risk in postmenopausal women.

The OCT RNFL Probability Map and Artifacts Resembling Glaucomatous Damage.

Purpose: The purpose of this study was to improve the diagnostic ability of the optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) probability (p-) map by understanding the frequency and pattern of artifacts seen on the p-maps of healthy control (HC) eyes resembling glaucomatous damage. Methods: RNFL p-maps were generated from wide-field OCT cube scans of 2 groups of HC eyes, 200 from a commercial normative group (HC-norm) and 54 from a prospective study group, as well as from 62 patient eyes, which included 32 with early glaucoma (EG). These 32 EG eyes had 24-2 mean deviation (MD) better than -6 dB and perimetric glaucoma as defined by 24-2 and 10-2 criteria. For the HC groups, "glaucoma-like" arcuates were defined as any red region near the temporal half of the disc. Results: Seven percent of the 200 HC-norm and 11% of the 54 HC RNFL p-maps satisfied the definition of "glaucoma-like," as did all the patients' p-maps. The HC p-maps showed two general patterns of abnormal regions, "arcuate" and "temporal quadrant," and these patterns resembled those seen on some of the RNFL p-maps of the EG eyes. A "vertical midline" rule, which required the abnormal region to cross the vertical midline through the fovea, had a specificity of >99%, and a sensitivity of 75% for EG and 93% for moderate to advanced eyes. Conclusions: Glaucoma-like artifacts on RNFL p-maps are relatively common and can masquerade as arcuate and/or widespread/temporal damage. Translational Relevance: A vertical midline rule had excellent specificity. However, other OCT information is necessary to obtain high sensitivity, especially in eyes with early glaucoma.