Assessing Intereye Symmetry and Its Implications for Study Design

Rate and Predictors of Misclassification of Active Diabetic Macular Edema as Detected by an Automated Retinal Image Analysis System

INTRODUCTION

The aim of this work is to estimate the sensitivity, specificity, and misclassification rate of an automated retinal image analysis system (ARIAS) in diagnosing active diabetic macular edema (DME) and to identify factors associated with true and false positives.

METHODS

We conducted a cross-sectional study of prospectively enrolled patients with diabetes mellitus (DM) referred to a tertiary medical retina center for screening or management of DME. All patients underwent two-field fundus photography (macula- and disc-centered) with a true-color confocal camera; images were processed by EyeArt V.2.1.0 (Woodland Hills, CA, USA). Active DME was defined as the presence of intraretinal or subretinal fluid on spectral-domain optical coherence tomography (SD-OCT). Sensitivity and specificity and their 95% confidence intervals (CIs) were calculated. Variables associated with true (i.e., DME labeled as present by ARIAS + fluid on SD-OCT) and false positives (i.e., DME labeled as present by ARIAS + no fluid on SD-OCT) of active DME were explored.

RESULTS

A total of 298 eyes were included; 92 eyes (31%) had active DME. ARIAS sensitivity and specificity were 82.61% (95% CI 72.37-89.60) and 84.47% (95% CI 78.34-89.10). The misclassification rate was 16%. Factors associated with true positives included younger age (p = 0.01), shorter DM duration (p = 0.006), presence of hard exudates (p = 0.005), and microaneurysms (p = 0.002). Factors associated with false positives included longer DM duration (p = 0.01), worse diabetic retinopathy severity (p = 0.008), history of inactivated DME (p < 0.001), and presence of hard exudates (p < 0.001), microaneurysms (p < 0.001), or epiretinal membrane (p = 0.06).

CONCLUSIONS

The sensitivity of ARIAS was diminished in older patients and those without DME-related fundus lesions, while the specificity was reduced in cases with a history of inactivated DME. ARIAS performed well in screening for naïve DME but is not effective in surveillance inactivated DME.

Biomechanical Correlations Between the Cornea and the Optic Nerve Head

Purpose

A thin cornea is a potent risk factor for glaucoma. The underlying mechanisms remain unexplained. It has been postulated that central corneal thickness (CCT) may be a surrogate for biomechanical parameters of the posterior eye. In this study, we aimed to explore correlations of biomechanical responses between the cornea and the optic nerve head (ONH) and the peripapillary sclera (PPS) to elevated intraocular pressure (IOP), the primary risk factor of glaucoma.

Methods

Inflation tests were performed in nine pairs of human donor globes. One eye of each pair was randomly assigned for cornea or posterior eye inflation. IOP was raised from 5 to 30 millimeters of mercury (mmHg) at 0.5 mmHg steps in the whole globe and the cornea or the ONH/PPS was imaged using a 50 MHz ultrasound probe. Correlation-based ultrasound speckle tracking was used to calculate tissue displacements and strains. Associations of radial, tangential, and shear strains at 30 mmHg between the cornea and the ONH or PPS were evaluated.

Results

Corneal shear strain was significantly correlated with ONH shear strain (R = 0.857, P = 0.003) and PPS shear strain (R = 0.724, P = 0.028). CCT was not correlated with any strains in the cornea, ONH, or PPS.

Conclusions

Our results suggested that an eye that experiences a larger shear strain in the cornea would likely experience a larger shear strain in its ONH and PPS at IOP elevations. The strong correlation between the cornea's and the ONH's shear response to IOP provides new insights and suggests a plausible explanation of the cornea's connection to glaucoma risk.

Symmetry of Macular Fundus Features in Age-Related Macular Degeneration

PURPOSE

The symmetry of major macular fundus features in both eyes of the same patient with age-related macular degeneration (AMD) was investigated using swept-source(SS)-OCT.

DESIGN

Retrospective review of a prospective study.

PARTICIPANTS

Patients with AMD.

METHODS

Grading was performed on the first SS-OCT images obtained on the patients. Two graders diagnosed the presence of drusen, geographic atrophy (GA), and exudative AMD (eAMD) in each eye. Medical records were reviewed to assess prior exudation. To assess symmetry, 1 eye of each patient was randomly selected as the index eye and compared with the fellow eye. The kappa statistic (κ) was used to assess the symmetry of diagnosis. The intraclass correlation coefficient (ICC) was used to assess the symmetry of drusen area and volume.

MAIN OUTCOME MEASURES

Interocular symmetry of the AMD stages: drusen, GA, and eAMD.

RESULTS

A total of 1310 patients with AMD were included. The average age was 78 years (range, 50-102; 60% women). Of the 1310 subjects, 54% (701) presented with symmetric disease: 20% with bilateral drusen, 11% with bilateral GA, and 22% with bilateral eAMD. Only 0.5% of the subjects had both GA and eAMD in both eyes. Of the randomly selected index eyes, 825 (47%) were right eyes. Overall, limited interocular agreement was observed between the index and fellow eyes (54%; κ = 0.29). Kappa coefficients were poor (< 0.4) for index eyes diagnosed with drusen (κ = 0.27), eAMD (κ = 0.17), and mixed disease (κ = 0.03). There was moderate agreement between the index and fellow eyes for GA (κ = 0.50). Of the 265 patients with bilateral drusen, the symmetry of drusen area measurements had moderate ICC values of 0.70, 0.71, and 0.70 in the 3- and 5-mm diameter foveal-centered circles and in the total scan area, respectively. The ICC values for the drusen volumes were 0.65, 0.66, and 0.64, respectively.

CONCLUSIONS

Interocular symmetry was poor for eyes with drusen, eAMD, and mixed disease, but moderate for GA. Although the diagnosis of drusen was not very symmetric between eyes, when present in both eyes, the drusen area and volume measurements were moderately symmetric.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Intereye Symmetry in Bietti Crystalline Dystrophy

PURPOSE

To evaluate anatomic and functional intereye symmetry among individuals with Bietti crystalline dystrophy (BCD) using clinical and multimodal imaging methods, with a focus on the number, area, and distribution of the characteristic retinal crystalline deposits.

DESIGN

Observational case series with prospective and retrospective data.

METHODS

Setting: Multicenter.

STUDY POPULATION

Thirteen Australian and New Zealand participants (26 eyes) with confirmed biallelic CYP4V2 mutations and a characteristic BCD fundus appearance. Procedures and main outcome measures: Crystals visible on color fundus photography were manually counted. Crystals were superimposed on aligned multimodal fundus images. Spearman's correlation coefficients (ρ), intraclass correlation coefficients (ICCs), and Bland-Altman plots were used to quantify symmetry between eyes.

MAIN OUTCOME MEASURES

Fundus crystal area and count, and absent-autofluorescence (absent-AF) area.

RESULTS

Median participant age was 48 years (interquartile range: 40-60 years). Intereye symmetry was high for fundus crystal area (ρ = 1.00, 95% confidence interval [CI]: 1.00-1.00; ICC = 0.97, 95% CI: 0.88-0.99), fundus crystal count (ρ = 0.98, 95% CI: 0.92-1.00; ICC = 0.97, 95% CI: 0.89-0.99), and absent-AF area (ρ = 0.88, 95% CI: 0.53-0.98; ICC = 0.98, 95% CI: 0.90-0.99). Average foveal volume, foveal crystal count and area, average and central foveal thickness, best corrected visual acuity, and average macular and central foveal sensitivity were not highly correlated between eyes.

CONCLUSIONS

This study demonstrated strong intereye symmetry measured by fundus crystal area, fundus crystal number, and absent-AF area. This may influence the choice of outcome measures for future therapeutic trials for BCD and provides valuable clinical information for ophthalmologists involved in the care and counseling of patients with BCD.

Tutorial on Biostatistics: Receiver-Operating Characteristic (ROC) Analysis for Correlated Eye Data

Purpose: To demonstrate methods for receiver-operating characteristic (ROC) analysis of correlated eye data.Methods: We applied the Obuchowski's nonparametric approach and cluster bootstrap for estimating and comparing the area under ROC curve (AUC) between different sets of predictors to three datasets with varying inter-eye correlation.Results: In an optic neuritis (ON) study of 152 eyes (80 patients), the AUC of optical coherence tomography retinal nerve fiber layer thickness for diagnosing ON (inter-eye kappa = 0.13) was 0.71 [95% confidence interval (95% CI): 0.622, 0.792] from the naïve approach without accounting for inter-eye correlation was narrower than from nonparametric (95% CI: 0.613, 0.801) or cluster bootstrap (95% CI: 0.614, 0.797) approaches. In an analysis of 198 eyes (135 patients), the baseline Age-related Eye disease Study scale predicted 5-year incidence of advanced age-related macular degeneration (inter-eye kappa = 0.23) with AUC of 0.72. The 95% CI from the naïve approach was slightly narrower (0.645, 0.794) than from the nonparametric (0.641, 0.797) or cluster bootstrap (0.641, 0.793) approaches. In an analysis of 1542 eyes (771 infants), birthweight and gestational age predicted treatment-requiring retinopathy of prematurity (inter-eye kappa = 0.98) with AUC of 0.80. Furthermore, the 95% CI from the naïve approach was narrower (0.769, 0.835) than from the nonparametric (0.755, 0.848) or cluster bootstrap (0.755, 0.845) approaches. 95% CIs for AUC differences between different models were narrower in the naïve approach than the nonparametric or cluster bootstrap approaches.Conclusion: In ROC analysis of correlated eye data, ignoring inter-eye correlation leads to narrower 95% CI with underestimation dependent on magnitude of inter-eye correlation. Nonparametric and cluster bootstrap approaches properly account for inter-eye correlation.

Calculating Sensitivity, Specificity, and Predictive Values for Correlated Eye Data

Purpose

To describe and demonstrate appropriate statistical approaches for estimating sensitivity, specificity, predictive values and their 95% confidence intervals (95% CI) for correlated eye data.

Methods

We described generalized estimating equations (GEE) and cluster bootstrap to account for inter-eye correlation and applied them for analyzing the data from a clinical study of telemedicine for the detection of retinopathy of prematurity (ROP).

Results

Among 100 infants (200 eyes) selected for analysis, 20 infants had referral-warranted ROP (RW-ROP) in both eyes and 9 infants with RW-ROP only in one eye based on clinical eye examination. In the per-eye analysis that included both eyes of an infant, the image evaluation for RW-ROP had sensitivity of 83.7% and specificity of 86.8%. The 95% CI's from the naïve approach that ignored the inter-eye correlation were narrower than those of the GEE approach and cluster bootstrap for both sensitivity (width of 95% CI: 22.4% vs. 23.2% vs. 23.9%) and specificity (11.4% vs. 12.5% vs. 11.6%). The 95% CIs for sensitivity and specificity calculated from left eyes and right eyes separately were wider (35.2% and 30.8% respectively for sensitivity, 25.4% and 17.3% respectively for specificity).

Conclusions

When an ocular test is performed in both eyes of some or all of the study subjects, the statistical analyses are best performed at the eye-level and account for the inter-eye correlation by using either the GEE or cluster bootstrap. Ignoring the inter-eye correlation results in 95% CIs that are inappropriately narrow and analyzing data from two eyes separately are not efficient.