Hazard Detection During Simulated Driving in Glaucoma Patients.

PRCIS: In this cross-sectional study, glaucoma patients showed slower reaction times (RTs) to hazardous situations when compared with control subjects during simulated driving. Worse RTs were associated with a greater magnitude of visual field loss. PURPOSE: The purpose of this study was to evaluate the impact of different hazardous traffic conditions on driving performance in glaucoma patients using a high-fidelity driving simulator. METHODS: The cross-sectional study was performed with 52 glaucoma patients and 15 control subjects. A series of hazard scenarios were presented, such as pedestrians crossing the street unexpectedly or vehicles suddenly pulling into the driver's lane. RTs in seconds (s) from first the evidence of a hazard to the time it took the driver to take the foot off the gas pedal ("Gas Off") and the time it took to depress the brake pedal ("Brake On") were compared between groups. RESULTS: Overall, mean RTs were statistically significantly slower in glaucoma patients (3.39±3.88 s) compared with controls (2.39±1.99 s; P =0.005) for the "Brake On" task but not for the "Gas Off" task (2.74±3.42 vs. 2.13±1.91 s, respectively; P =0.120). For subjects with glaucoma, multivariable models adjusted for age, gender, race, and visual acuity demonstrated significantly slower RTs for worse values of binocular mean sensitivity for both "Gas Off" and "Brake On" tasks (1.12 and 1.14 s slower per 10 dB worse; P =0.009 and P <0.001, respectively). Subjects with glaucoma took significantly longer times to brake for smaller (low saliency) hazards compared with larger (high saliency) hazards ( P =0.027). CONCLUSIONS: RTs in response to hazardous driving situations were slower for glaucoma patients compared with controls. Individualized assessment of driving fitness using hazardous scenarios in driving simulators could be helpful in providing an assessment of driving risk in glaucoma patients.

Deep Learning-Assisted Detection of Glaucoma Progression in Spectral-Domain OCT.

PURPOSE: To develop and validate a deep learning (DL) model for detection of glaucoma progression using spectral-domain (SD)-OCT measurements of retinal nerve fiber layer (RNFL) thickness. DESIGN: Retrospective cohort study. PARTICIPANTS: A total of 14 034 SD-OCT scans from 816 eyes from 462 individuals. METHODS: A DL convolutional neural network was trained to assess SD-OCT RNFL thickness measurements of 2 visits (a baseline and a follow-up visit) along with time between visits to predict the probability of glaucoma progression. The ground truth was defined by consensus from subjective grading by glaucoma specialists. Diagnostic performance was summarized by the area under the receiver operator characteristic curve (AUC), sensitivity, and specificity, and was compared with conventional trend-based analyses of change. Interval likelihood ratios were calculated to determine the impact of DL model results in changing the post-test probability of progression. MAIN OUTCOME MEASURES: The AUC, sensitivity, and specificity of the DL model. RESULTS: The DL model had an AUC of 0.938 (95% confidence interval [CI], 0.921-0.955), with sensitivity of 87.3% (95% CI, 83.6%-91.6%) and specificity of 86.4% (95% CI, 79.9%-89.6%). When matched for the same specificity, the DL model significantly outperformed trend-based analyses. Likelihood ratios for the DL model were associated with large changes in the probability of progression in the vast majority of SD-OCT tests. CONCLUSIONS: A DL model was able to assess the probability of glaucomatous structural progression from SD-OCT RNFL thickness measurements. The model agreed well with expert judgments and outperformed conventional trend-based analyses of change, while also providing indication of the likely locations of change. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Diagnostic Performance of Optical Coherence Tomography and Nonspecialist Gonioscopy to Detect Angle Closure.

Aim: To compare the usefulness of gonioscopy performed by general ophthalmologists (GO) and anterior segment optical coherence tomography (AS-OCT) in detecting angle closure in patients with a shallow anterior chamber. Methods: Forty-four patients with a shallow anterior chamber (defined by a ratio of peripheral anterior chamber depth to peripheral corneal thickness lower than 1/2) were included in this cross-sectional study. Gonioscopy was performed in all subjects by two glaucoma experts (GE1 and GE2) and one GO. Anterior segment imaging was performed using Visante® OCT (Carl Zeiss Meditec Inc.). Agreement between examiners was assessed with first-order agreement coefficients (AC1). Diagnostic accuracies of GO gonioscopy and AS-OCT were evaluated using sensitivity, specificity, and area under the receiver operating characteristic (AROC) curves. Results: For static gonioscopy, the agreement between GE1 and GE2 was substantial (AC1 = 0.65), and that between GE1 and GO was moderate (AC1 = 0.50). For indentation gonioscopy, the agreement between GE1 and GE2 was slightly lower (AC1 = 0.55); however, the agreement between GE1 and GO showed a larger reduction (AC1 = 0.12). GO's gonioscopy presented a low specificity (25%) and the AROC to angle closure detection was lower than AS-OCT (0.56-0.73). Combined information of GO gonioscopy and AS-OCT improved specificity (85.7%) and AROC (0.77) of angle closure evaluation. Conclusion: Agreement between GO and glaucoma experts was moderate for static gonioscopy and slight for indentation gonioscopy. AS-OCT performed better than GO gonioscopy in detecting angle closure in patients with a shallow anterior chamber. The addition of AS-OCT to clinical information in patients with GO positive gonioscopy improved the specificity and AROC of gonioscopy test. How to cite this article: Esporcatte BLB, Vessani RM, Melo Jr LAS, et al. Diagnostic Performance of Optical Coherence Tomography and Nonspecialist Gonioscopy to Detect Angle Closure. J Curr Glaucoma Pract 2022;16(1):53-58.

An objective structural and functional reference standard in glaucoma.

The current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using clearly defined parameters from optical coherence tomography and standard automated perimetry. We then use the proposed objective definition as reference standard to develop a DL algorithm to detect GON on fundus photos. A DL algorithm was trained to detect GON on fundus photos, using the proposed objective definition as reference standard. The performance was evaluated on an independent test sample with sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and likelihood ratios (LR). The test sample had 2118 fundus photos from 585 eyes of 405 individuals. The AUC to discriminate between GON and normal was 0.92 with sensitivity of 77% at 95% specificity. LRs indicated that the DL algorithm provided large changes in the post-test probability of disease for the majority of eyes. A DL algorithm to evaluate fundus photos had high performance to discriminate GON from normal. The newly proposed objective definition of GON used as reference standard may increase the comparability of diagnostic studies of glaucoma across devices and populations.

Artificial Intelligence Mapping of Structure to Function in Glaucoma.

Purpose: To develop an artificial intelligence (AI)-based structure-function (SF) map relating retinal nerve fiber layer (RNFL) damage on spectral domain optical coherence tomography (SDOCT) to functional loss on standard automated perimetry (SAP). Methods: The study included 26,499 pairs of SAP and SDOCT from 15,173 eyes of 8878 patients with glaucoma or suspected of having the disease extracted from the Duke Glaucoma Registry. The data set was randomly divided at the patient level in training and test sets. A convolutional neural network (CNN) was initially trained and validated to predict the 52 sensitivity threshold points of the 24-2 SAP from the 768 RNFL thickness points of the SDOCT peripapillary scan. Simulated localized RNFL defects of varied locations and depths were created by modifying the normal average peripapillary RNFL profile. The simulated profiles were then fed to the previously trained CNN, and the topographic SF relationships between structural defects and SAP functional losses were investigated. Results: The CNN predictions had an average correlation coefficient of 0.60 (P < 0.001) with the measured values from SAP and a mean absolute error of 4.25 dB. Simulated RNFL defects led to well-defined arcuate or paracentral visual field losses in the opposite hemifield, which varied according to the location and depth of the simulations. Conclusions: A CNN was capable of predicting SAP sensitivity thresholds from SDOCT RNFL thickness measurements and generate an SF map from simulated defects. Translational Relevance: AI-based SF map improves the understanding of how SDOCT losses translate into detectable SAP damage.

The Estimates of Retinal Ganglion Cell Counts Performed Better than Isolated Structure and Functional Tests for Glaucoma Diagnosis.

PURPOSE: To evaluate the diagnostic accuracy of retinal ganglion cell (RGC) counts as estimated by combining data from standard automated perimetry (SAP) and spectral domain optical coherence tomography (SD-OCT). METHODS: Healthy individuals and glaucoma patients were included in this cross-sectional study. All eyes underwent 24-2 SITA SAP and structural imaging tests. RGC count estimates were obtained using a previously described algorithm, which combines estimates of RGC numbers from SAP sensitivity thresholds and SD-OCT retinal nerve fiber layer (RNFL) average thickness. RESULTS: A total of 119 eyes were evaluated, including 75 eyes of 48 healthy individuals and 44 eyes of 29 glaucoma patients. RGC count estimates performed better than data derived from SD-OCT RNFL average thickness or SAP mean deviation alone (area under ROC curves: 0.98, 0.92, and 0.79; P < 0.001) for discriminating healthy from glaucomatous eyes, even in a subgroup of eyes with mild disease (0.97, 0.88, and 0.75; P < 0.001). There was a strong and significant correlation between estimates of RGC numbers derived from SAP and SD-OCT (R2 = 0.74; P < 0.001). CONCLUSION: RGC count estimates obtained by combined structural and functional data showed excellent diagnostic accuracy for discriminating the healthy from the glaucomatous eyes and performed better than isolated structural and functional parameters.

Agreement on the evaluation of glaucomatous optic nerve head findings by ophthalmology residents and a glaucoma specialist.

OBJECTIVES: To assess agreement among ophthalmology residents and a glaucoma expert in the evaluation of cross-sectional glaucomatous optic nerve head characteristics using stereoscopic photographs. METHODS: Twenty stereo photographs were analyzed by ophthalmology residents just after completion of their first (First-Year Group) or third (Third-Year Group) year of residency and by a glaucoma expert. The agreement was assessed using the kappa statistic (κ) and limits of agreement. RESULTS: Agreement among resident groups and the expert ranged from poor to moderate. Agreement between Third Years and the expert seems to be better than that between First Years and the expert, especially in the evaluation of "nasal cupping", "barring circumlinear vessel," "notching", and "retinal nerve fiber layer defect" criteria. However, no improvement was seen in the agreement with the expert regarding glaucomatous optic neuropathy, which was 64% (κ=0.19) for First Years and 63% (κ=0.20) for Third Years. CONCLUSION: Agreement between residents and the expert was poor to moderate and similar when comparing both groups. This may suggest that the residents learn how to identify glaucoma signals during the first year of training, and the results of this study may facilitate the creation of targeted teaching tools in residency training.

Genotype-Phenotype Correlations in CYP1B1-Associated Primary Congenital Glaucoma Patients Representing Two Large Cohorts from India and Brazil.

BACKGROUND: Primary congenital glaucoma (PCG), occurs due to the developmental defects in the trabecular meshwork and anterior chamber angle in children. PCG exhibits genetic heterogeneity and the CYP1B1 gene has been widely implicated worldwide. Despite the diverse mutation spectra, the clinical implications of these mutations are yet unclear. The present study attempted to delineate the clinical profile of PCG in the background of CYP1B1 mutations from a large cohort of 901 subjects from India (n=601) and Brazil (n=300). METHODS: Genotype-phenotype correlations was undertaken on clinically well characterized PCG cases from India (n=301) and Brazil (n=150) to assess the contributions of CYP1B1 mutation on a set of demographic and clinical parameters. The demographic (gender, and history of consanguinity) and quantitative clinical (presenting intraocular pressure [IOP] and corneal diameter [CD]) parameters were considered as binary and continuous variables, respectively, for PCG patients in the background of the overall mutation spectra and also with respect to the prevalent mutations in India (R368H) and Brazil (4340delG). All these variables were fitted in a multivariate logistic regression model using the Akaike Information Criterion (AIC) to estimate the adjusted odds ratio (OR) using the R software (version 2.14.1). RESULTS: The overall mutation spectrum were similar across the Indian and Brazilian PCG cases, despite significantly higher number of homozygous mutations in the former (p=0.024) and compound heterozygous mutations in the later (p=0.012). A wide allelic heterogeneity was observed and only 6 mutations were infrequently shared between these two populations. The adjusted ORs for the binary (demographic) and continuous (clinical) variables did not indicate any susceptibility to the observed mutations (p>0.05). CONCLUSIONS: The present study demonstrated a lack of genotype-phenotype correlation of the demographic and clinical traits to CYP1B1 mutations in PCG at presentation. However, the susceptibility of these mutations to the long-term progression of these traits are yet to be deciphered.

The retinal nerve fiber layer of patients with neuromyelitis optica and chronic relapsing optic neuritis is more severely damaged than patients with multiple sclerosis.

BACKGROUND: To compare the retinal nerve fiber layer (RNFL) in eyes of patients with relapsing remitting multiple sclerosis (RRMS), neuromyelitis optica (NMO) and chronic relapsing inflammatory optic neuritis (CRION). METHODS: Evaluation of 62 patients with RRMS, NMO, and CRION in a cross-sectional study with spectral domain optical coherence tomography. RESULTS: A total of 124 eyes were evaluated (96 RRMS, 18 NMO, and 10 CRION). Frequency of optic neuritis for each disease was: 34% for RRMS, 84% for NMO, and 100% for CRION. Visual acuity and RNFL thickness were significantly worse in NMO and CRION eyes than in RRMS, but there were no differences between NMO and CRION eyes. A RNFL of 41 µm was 100% specific for optic neuritis associated with NMO and CRION when compared to RRMS. CONCLUSION: This study established RNFL values to differentiate optic neuritis of RRMS from NMO and CRION. Although similarities observed between NMO and CRION eyes might suggest that they are within the same disease spectrum, it is still recommended that these 2 conditions be differentiated on clinical grounds. Optical coherence tomography serves as an additional diagnostic tool and can be used to monitor disease progression.

Relationship between retinal nerve fiber layer and visual field function in human immunodeficiency virus-infected patients without retinitis.

PURPOSE: To evaluate the spatial association between visual field (VF) sensitivity loss and retinal nerve fiber layer (RNFL) thinning in patients infected by the human immunodeficiency virus. METHODS: Fifty-one eyes of 51 human immunodeficiency virus-infected patients and 22 eyes of 22 control subjects were enrolled. Patients were evaluated using the Fast RNFL scan strategy on Stratus OCT and the 24-2 full-threshold program on the Humphrey Matrix frequency doubling technology (FDT) perimeter. Associations between RNFL thickness and VF sensitivity were evaluated globally, in 12 clock-hour optical coherence tomography sectors and in 21 VF zones; linear and quadratic regression models were used in the statistical analysis. RESULTS: The linear and quadratic regression associations between the FDT Matrix pattern standard deviation and the average RNFL thickness in human immunodeficiency virus-infected patients were r2 = 0.185 and r2 = 0.218 (P < 0.05), respectively. The correlation between the FDT Matrix mean deviation and the average RNFL thickness was not significant (P > 0.05). Stronger associations were found when regional RNFL thinning was compared with locally measured FDT Matrix pattern deviation, especially between nasal RNFL measurements and temporal VF zones, and between superior RNFL measurements and inferior VF zones. CONCLUSION: Retinal nerve fiber layer thinning was related to VF sensitivity loss in human immunodeficiency virus-infected patients and regional associations between optical coherence tomography and FDT Matrix sectors were stronger than the associations between global measurements.

Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes.

PURPOSE: To determine whether combining structural (optical coherence tomography, OCT) and functional (standard automated perimetry, SAP) measurements as input for machine learning classifiers (MLCs; relevance vector machine, RVM; and subspace mixture of Gaussians, SSMoG) improves diagnostic accuracy for detecting glaucomatous eyes compared with using each measurement method alone. METHODS: Sixty-nine eyes of 69 healthy control subjects (average age, 62.0, SD 9.7 years; visual field mean deviation [MD], -0.70, SD 1.41 dB) and 156 eyes of 156 patients with glaucoma (average age, 66.4, SD 10.2 years; visual field MD, -3.12, SD 3.43 dB) were imaged with OCT (Stratus OCT, Carl Zeiss Meditec, Inc., Dublin, CA) and tested with SAP (Humphrey Field Analyzer II with Swedish Interactive Thresholding Algorithm, SITA; Carl Zeiss Meditec, Inc.) within 3 months of each other. RVM and SSMoG MLCs were trained and tested on OCT-determined RNFL thickness measurements from 32 sectors ( approximately 11.25 degrees each) obtained in the circumpapillary area under the instrument-defined measurement ellipse and SAP pattern deviation values from 52 points from the 24-2 grid, independently and in combination. Tenfold cross-validation was used to train and test classifiers on unique subsets of the full 225-eye data set, and areas under the receiver operating characteristic curve (AUROC) for the classification of eyes in the test set were generated. AUROC results from classifiers trained on OCT and SAP alone and those trained on OCT and SAP in combination were compared. In addition, these results were compared to currently available OCT measurements (mean retinal nerve fiber layer [RNFL] thickness, inferior RNFL thickness, and superior RNFL thickness) and SAP indices (MD and pattern standard deviation [PSD]). RESULTS: The AUROCs for RVM trained on OCT parameters alone, SAP parameters alone and OCT and SAP parameters combined were 0.809, 0.815, and 0.845, respectively. The AUROCs for SSMoG trained on OCT parameters alone, SAP parameters alone, and OCT and SAP parameters combined were 0.817, 0.841, and 0.869, respectively. Combining techniques using both RVM and SSMoG significantly improved on MLC analysis of OCT, but not SAP, measurements alone. Classification performance using RVM and SSMoG was statistically similar. CONCLUSIONS: RVM and SSMoG Bayesian MLCs trained on OCT and SAP data can successfully discriminate between healthy and early glaucomatous eyes. Combining OCT and SAP measurements using RVM and SSMoG increased diagnostic performance marginally compared with MLC analysis of data obtained using each technology alone.

Spatial characteristics of visual field progression determined by Monte Carlo simulation: diagnostic innovations in glaucoma study.

PURPOSE: To determine the spatial characteristics of glaucomatous visual field progression in persons with glaucomatous-appearing optic neuropathy (GON) from the Diagnostic Innovations in Glaucoma Study (DIGS). METHODS: Changes in pattern deviation (PD) plot values from the average of two baseline examinations to two follow-up examinations were evaluated in test locations. All were eligible, full threshold, pattern 24-2, standard automated perimetry (SAP) examinations (Humphrey Field Analyzer II; Carl Zeiss Meditec, Inc., Dublin, CA) in visual field series from 200 patients with GON confirmed on two occasions by stereophoto review. The proportion of patients exhibiting PD plot progression was determined at each of 52 locations for patients with a baseline abnormal result (P < 5% or worse) in one or more of 52 PD locations in either the first or second baseline test for a total of 2704 location pairings for each possible level of negative PD change from -1 to -50 dB. Progression was defined as any worsening of PD plot value in the follow-up test relative to the average PD plot value in the baseline tests. Monte Carlo simulation was used to determine the significance of the observed patterns of PD plot progression. RESULTS: Changes in PDs were dependent on their location relative to abnormal PD locations in the first test. Of those patients with an abnormality at a location at baseline (mean, 0.23 +/- 0.07), the proportion of patients changing by -2 dB or more ranged between 0.09 and 0.55 (mean, 0.29 +/- 0.06) across locations. For changes of -6 dB or more, the proportions ranged between 0.00 and 0.26 (mean, 0.08 +/- 0.04) of patients. These proportions and the proportional probabilities for each of 2704 location pairings are reported for selected levels of change. The proportional probabilities are consistent with a map of the retinal nerve fiber layer bundles. CONCLUSIONS: Visual field progression occurs in retinotopically constrained patterns consistent with changes along the nerve fiber bundle.

Retinal nerve fiber layer thickness and visual sensitivity using scanning laser polarimetry with variable and enhanced corneal compensation.

PURPOSE: To compare the strength of the structure-function association between scanning laser polarimetry-measured retinal nerve fiber layer (RNFL) thickness and visual sensitivity. Two methods of corneal compensation were evaluated, variable corneal compensation (VCC) and enhanced corneal compensation (ECC). DESIGN: Observational case series. PARTICIPANTS: One hundred twenty-seven glaucoma (repeatable abnormal visual fields [VF] by pattern standard deviation and/or glaucoma hemifield test) or glaucoma suspect (glaucomatous-appearing discs by photograph assessment without field defects) participants in the University of California, San Diego Diagnostic Innovations in Glaucoma Study. METHODS: One eye of each participant was imaged using GDx VCC and GDx ECC on the same day. Visual fields tested using the Humphrey Field Analyzer (with Swedish interactive threshold algorithm) were obtained within 6 months of imaging. MAIN OUTCOME MEASURE: The associations (R2) using linear and logarithmic regression between RNFL thicknesses measured in 6 sectors (inferior, inferotemporal, temporal, superotemporal, superior, nasal) with VCC and ECC and VF sensitivities (decibel threshold measurements) measured in 6 corresponding sectors were compared. Comparisons were made using paired t tests on the log-transformed absolute values of regression residuals. RESULTS: Using GDx VCC, 32 scans had a typical scan score (TSS) < or = 78 (lowest quartile) and no ECC scans had TSS<86. Most RNFL thickness measurements obtained using GDx VCC were significantly greater than those measured using GDx ECC. Regional structure-function associations (R2) ranged from 0.03 (temporal RNFL) to 0.22 (superotemporal RNFL) for VCC and from 0.01 (temporal RNFL) to 0.26 (superotemporal RNFL) for ECC. Associations generally were slightly stronger for ECC than for VCC, although these differences were only significant for inferotemporal RNFL (R2 = 0.19 and 0.11, for ECC and VCC, respectively). CONCLUSION: The RNFL thickness associations with VF sensitivity are stronger using ECC compared with VCC, suggesting that ECC provides a better cross-sectional representation of visual function than VCC.

Inconsistency of the published definition of ocular hypertension.

PURPOSE: To examine the variability and to evaluate the influence of the Ocular Hypertension Treatment Study (OHTS) on the criteria for published definition of ocular hypertension (OH). DESIGN: Systematic literature review. METHODS: All articles about OH published between January 1995 and July 2005 from the 3 clinical journals of ophthalmology were identified by a literature search. They were reviewed to determine the criteria used to define OH, including intraocular pressure and central corneal thickness, visual field and optic disc assessment. RESULTS: There were 133 studies published on OH during the period under study. As a goal of the current study was to evaluate the influence of the publication of the OHTS results on the definition of OH used in the literature, all reports from the OHTS and its ancillary studies (n = 11) were excluded from the main analysis. After the exclusion of the OHTS reports, a total of 122 studies were used in the analysis. The intraocular pressure cut-off level used for OH diagnosis ranged from 18 to 26 mm Hg, with a mode of 22 mm Hg (49.2%). Only 13.1% of the articles reported central corneal thickness, and these were distributed evenly during the 10-year period under study. Visual field assessment was reported by most of the studies (110; 90.2%), but only 45% of them defined the criteria to classify a field as normal or glaucomatous. Further, only 37 of the 57 articles that reported the method of optic disc assessment described the criteria used to classify optic discs. CONCLUSIONS: The criteria used to define OH during the past 10 years have been highly variable. This wide variation suggests the important need for a standardized definition of OH.

Baseline optical coherence tomography predicts the development of glaucomatous change in glaucoma suspects.

PURPOSE: To assess whether baseline retinal nerve fiber layer (RNFL) measurements obtained with optical coherence tomography (OCT2; Carl Zeiss Meditec, Dublin, California, USA) are predictive of the development of glaucomatous change. DESIGN: Cohort study. METHODS: Participants were recruited from the University of California, San Diego (UCSD) longitudinal Diagnostic Innovations in Glaucoma Study (DIGS). One eye was studied from each of 114 glaucoma suspects with normal standard automated perimetry (SAP) and OCT RNFL imaging at baseline. The cohort was divided into two groups based on the development of glaucomatous change (repeatable abnormal visual fields and/or a change in the stereophotographic appearance of the optic disk). Cox proportional hazards models were used to determine the predictive ability of OCT RNFL thickness measurements. RESULTS: Over a 4.2-year average follow-up period, 23 eyes (20%) developed glaucomatous changes and 91 (80%) did not. At baseline, thinner RNFL measurements, higher SAP pattern standard deviation (PSD), "glaucoma" stereophotograph assessment, and thinner central corneal thickness (CCT) were associated with the study endpoints in univariate analysis. After adjusting for age, intraocular pressure (IOP), CCT, and PSD in multivariate models, a 10 mum thinner average, superior and inferior RNFL at baseline was predictive of glaucomatous change [hazard ratio (95% CI); 1.51 (1.11 to 2.12), 1.57 (1.17 to 2.18), and 1.49, (1.19 to 1.91), respectively]. Results were consistent when stereophotographic assessment was included in multivariate analysis. CONCLUSIONS: Thinner OCT RNFL measurements at baseline were associated with development of glaucomatous change in glaucoma suspect eyes. RNFL thinning was an independent predictor of the glaucomatous change, even when adjusting for stereophotograph assessment, age, IOP, CCT, and PSD.

Structure-function relationships using confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry.

PURPOSE: To assess the strength of the association between retinal nerve fiber layer (RNFL) thickness and optic disc topography measured with confocal retinal tomography (HRT II; Heidelberg Engineering, Dossenheim, Germany), optical coherence tomography (StratusOCT; Carl Zeiss Meditec, Inc., Dublin, CA), and scanning laser polarimetry (GDx with variable corneal compensator, VCC; Carl Zeiss Meditec, Inc.), and visual field (VF) sensitivity and to determine whether this association is better expressed as a linear or nonlinear function. METHODS: One hundred twenty-seven patients with glaucoma or suspected glaucoma and 127 healthy eyes from enrollees in the Diagnostic Innovations in Glaucoma Study (DIGS) were tested on HRT II, StratusOCT, GDx VCC, and standard automated perimetry (SAP, with the Swedish Interactive Thresholding Algorithm [SITA]) within 3 months of each other. Linear and logarithmic associations between RNFL thickness (HRT II, StratusOCT, and GDx VCC) and neuroretinal rim area (HRT II) and SAP sensitivity expressed in decibels were determined globally and for six RNFL/optic disc regions (inferonasal, inferotemporal, temporal, superotemporal, superonasal, and nasal) and six corresponding VF regions (superior, superonasal, nasal, inferonasal, inferior, and temporal). RESULTS: The associations (R2) between global and regional RNFL/optic disc measurements and VF sensitivity ranged from <0.01 (temporal RNFL, nasal VF, and nasal RNFL, temporal VF; linear and logarithmic associations) to 0.26 (inferotemporal RNFL, superonasal VF; logarithmic association) for HRT II; from 0.02 (temporal RNFL, nasal VF; linear association) to 0.38 (inferotemporal RNFL, superonasal VF; logarithmic association) for OCT; and from 0.03 (temporal RNFL, nasal VF; linear association) to 0.21 (inferotemporal RNFL, superonasal VF; logarithmic association) for GDx. Structure-function relationships generally were strongest between the inferotemporal RNFL-optic disc sector and the superonasal visual field and were significantly stronger for StratusOCT RNFL thickness than for other instruments in this region. Global associations (linear and logarithmic) were significantly stronger using OCT compared with HRT. In most cases, logarithmic fits were not significantly better than linear fits when visual sensitivity was expressed in log units (i.e., decibels). CONCLUSIONS: These results suggest that structure-function associations are strongest with StratusOCT measurements and are similar between HRT II and GDx VCC and these associations are generally no better expressed logarithmically than linearly when healthy, suspect, and glaucomatous eyes are considered.