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H. Kobayashi, K. Iwao, T. Hida, S. Sato, R. Iwakiri, K. Kobayashi; Measurement of Retinal Nerve Fiber Layer Thickness in Glaucoma Patients With Myopia . Invest. Ophthalmol. Vis. Sci. 2005;46(13):2507.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: To compare the distribution of retinal nerve fiber layer (RNFL) thickness of eyes with and without severe myopia with Fourier analysis and to evaluate a new Fourier–based analysis method for diagnosing glaucoma in patients with severe myopia. Methods: RNFL thickness estimates were obtained from 20 healthy individuals and 40 glaucoma patients with myopia of –6 diopters and greater and 40 healthy individuals and 40 glaucoma patients without severe myopia. All subjects were imaged using a scanning laser polarimeter with variable corneal compensation (GDx VCC, Laser Diagnostic Technology).The pattern of thickness measurements from SLP in the 32 sectors around the optic disc was analyzed to obtain the Fourier coefficients. The fast Fourier transformation (FFT) was employed to determine the coefficients. The values were entered into linear discriminant analysis. Receiver operating characteristic (ROC) curve were used to compare the performance of the Fourier–based metrics against other commonly used RNFL analytical procedures. Results: Mean RNFL thickness was 55.87 ± 4.87 µm and 48.99 ± 9.81 µm in healthy individuals and glaucoma patients with severe myopia, respectively. In healthy individuals and glaucoma patients with severe myopia, inverse Fourier transform showed the double–hump pattern, and also showed that both peaks were shifted to more temporal compared with those without myopia. The area under the ROC curve using the linear discriminant function based on Fourier analysis was 0.891, and better compared with any other analytical procedures. Conclusions: Fourier analysis showed the difference of the distribution of RNFL thickness between eyes with and without severe myopia. In patients with severe myopia, the discriminant function based on the output from a Fourier analysis of RNFL data resulted in better diagnostic capability compared with other common RNFL analytical procedures.
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