Abstract
PURPOSE: The purpose of this study was to develop an objective algorithm to discriminate the earliest stages of glaucoma using frequency doubling technology (FDT) Matrix perimetry and spectral domain-optical coherence tomography (OCT) technology to improve primary care detection. MATERIALS AND METHODS: Three hundred six eyes (mean age 58.67±15.12) from 161 patients were included and classified in the following three groups: 101 nonglaucoma (GI-NG), 100 glaucoma suspect (GII-SG), and 105 open-angle glaucoma (GIII-OAG). All participants underwent a visual field exploration using the Humphrey Matrix visual field instrument and retinal nerve fiber layer evaluation using the Topcon 3D OCT-2000. Pattern deviation plot was divided into 19 areas and five aggrupation or quadrants and ranked with a value between 0 and 4 according to its likelihood of normality, and differences among three groups were analyzed. Principal component analysis (PCA) was also used to extract the most notable features of FDT and OCT, and a logistic regression analysis was applied to obtain the classification rules. RESULTS: Only area numbers 7 and 12 and the central zone of FDT Matrix showed statistical differences (P<0.05) between GI-NG and GII-SG. The classification rules were estimated by the four PCA obtained from FDT Matrix and 3D OCT-2000 in a separate and combined use. Area under the receiver operating characteristic curve was 78.88% with FDT-PCA, 82.09% with OCT-PCA, and 94.27% with combined use of FDT and OCT-PCA to discriminate GI-NG and GII-SG. CONCLUSION: The predictive rules based on FDT-PCA or OCT-PCA provide a high sensitivity and specificity to detect the earliest stages of glaucoma and even better in combined use. These predictive rules may help the future development of software for FDT Matrix perimetry and 3D OCT-2000, which will greatly improve their diagnostic ability, making them useful in daily practice in a primary care setting.