Glaucoma Detection with the Heidelberg Retina Tomograph 3

Abstract

To compare the ability of the Heidelberg retina tomograph version 3 (HRT 3) and HRT version 2 (HRT 2) to discriminate between healthy and glaucomatous eyes. Retrospective cross-sectional study. Seventy-one eyes of 71 healthy volunteers and 50 eyes of 50 glaucoma patients were studied. The average visual field mean deviation of the glaucoma group was -6.03+/-5.78 dB. All participants had comprehensive ocular examinations, perimetry, and HRT scanning within 6 months. HRT 2 data were analyzed using HRT 3 software without modifying the disc margin. Discrimination capabilities between healthy and glaucomatous eyes were determined by areas under the receiver operating characteristics (AROCs) curves. Comparisons between corresponding AROCs obtained by HRT 2 and HRT 3 analyses were performed using the nonparametric DeLong method. Agreement between classifications as defined by the different analysis methods was quantified by kappa analysis. The individual stereometric parameters with the best discrimination were linear cup/disc ratio (AROC = 0.897; 95% confidence interval [CI], 0.836-0.958) for standard HRT 3 analysis and horizontal retinal nerve fiber layer curvature (0.905) for HRT 3 glaucoma probability score (GPS) analysis. Areas under the receiver operating characteristics for discrimination between glaucomatous and healthy eyes of the overall classification by HRT 2 Moorfields regression analysis (MRA), HRT 3 MRA, and GPS were 0.927 (95% CI, 0.877-0.977), 0.934 (0.888-0.980), and 0.880 (0.812-0.948), respectively. The difference between the 3 AROCs was not significant (P = 0.44). The agreement between HRT 2 and HRT 3 overall MRA classification was good (kappa = 0.70; CI, 0.59-0.80) with HRT 3 tending to report more abnormalities than HRT 2 analysis. The agreement between overall HRT 3 MRA and overall GPS was kappa = 0.58 (CI, 0.45-0.70). The glaucoma discriminating ability of the new HRT 3 software is similar to that of the previous generation HRT 2. The GPS analysis showed promising results in differentiating between healthy and glaucomatous eyes without the need for subjective operator input.