Fourier analysis of circumpapillary retinal nerve fiber layer thickness in optical coherence tomography for differentiating myopia and glaucoma

Abstract

Differentiating glaucoma from myopic eye is a challenge to ophthalmologists. We try to develop a new discrete Fourier transform (DFT) model for analyzing optical coherence tomography data for the circumpapillary retinal nerve fiber layer (cpRNFL), and investigate DFT as a new diagnostic tool for glaucomatous myopic eyes. The thicknesses of 12 equidistant cpRNFL points were transformed into 6 signals in the frequency domain, ranging from 1 to 6 Hz. In all 232 eyes, generalized linear model showed that 1 Hz, 2 Hz, and 4 Hz were associated with glaucoma, high myopia, and the interaction between glaucoma and high myopia. The 3 Hz signal was associated with glaucoma and high myopia exclusively. A receiver operating characteristic curve analysis of the 3 Hz signals showed areas under the curves of 0.93 (95% CI 0.90–0.96) and 0.93 (95% CI 0.88–0.98), for diagnosing glaucoma in all subjects and in the highly myopic group, respectively. The DFT model is useful to differentiate glaucoma from non-glaucomatous change and showed potential as a diagnostic tool for glaucomatous myopic eyes.