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Confocal Scanning Laser Ophthalmoscopy Classifiers and Stereophotograph Evaluation for Prediction of Visual Field Abnormalities in Glaucoma-Suspect Eyes

¹From the Hamilton Glaucoma Center of the Department of Ophthalmology, and the ²Institute for Neural Computation, University of California San Diego, La Jolla, California; and the ³Computational Neurobiology Laboratory, The Salk Institute, La Jolla, California.

PURPOSE. To determine whether Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) classification techniques and investigational support vector machine (SVM) analyses can detect optic disc abnormalities in glaucoma-suspect eyes before the development of visual field abnormalities.

METHODS. Glaucoma-suspect eyes (n = 226) were classified as converts or nonconverts based on the development of repeatable (either two or three consecutive) standard automated perimetry (SAP)–detected abnormalities over the course of the study (mean follow-up, 4.5 years). Hazard ratios for development of SAP abnormalities were calculated based on baseline classification results, follow-up time, and end point status (convert, nonconvert). Classification techniques applied were HRT classification (HRTC), Moorfields Regression Analysis, forward-selection optimized SVM (SVM fwd) and backward elimination–optimized SVM (SVM back) analysis of HRT data, and stereophotograph assessment.

RESULTS. Univariate analyses indicated that all classification techniques were predictors of the development of two repeatable abnormal SAP results, with hazards ratios (95% confidence interval [CI]) ranging from 1.32 (1.00–1.75) for HRTC to 2.0 (1.48–2.76) for stereophotograph assessment (all P 0.05). Only SVM (SVM fwd and SVM back) analysis of HRT data and stereophotograph assessment were univariate predictors of the development of three repeatable abnormal SAP results, with hazard ratios (95% CI) ranging from 1.73 (1.16–2.82) for SVM fwd to 1.82 (1.19–3.12) for SVM back (both P < 0.007). Multivariate analyses including each classification technique individually in a model with age, baseline SAP pattern standard deviation [PSD], and baseline IOP indicated that all classification techniques except HRTC (P = 0.06) were predictors of the development of two repeatable abnormal SAP results with hazards ratios ranging from 1.30 (0.99, 1.73) for HRTC to 1.90 (1.37, 2.69) for stereophotograph assessment. Only SVM (SVM fwd and SVM back) analysis of HRT data and stereophotograph assessment were significant predictors of the development of three repeatable abnormal SAP results in multivariate analyses; hazard ratios of 1.57 (1.03, 2.59) and 1.70 (1.18, 2.51), respectively. SAP PSD was a significant predictor of two repeatable abnormal SAP results in multivariate models with all classification techniques, with hazard ratios ranging from 3.31 (1.39, 7.89) to 4.70 (2.02, 10.93) per 1-dB increase.

CONCLUSIONS. HRT classifications techniques and stereophotograph assessment can detect optic disc topography abnormalities in glaucoma-suspect eyes before the development of SAP abnormalities. These data support strongly the importance of optic disc examination for early glaucoma diagnosis.

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