A comparison of false positives in retinal nerve fiber layer, optic nerve head and macular ganglion cell-inner plexiform layer from two spectral-domain optical coherence tomography devices

作者：Leal Fonseca Marina^*; Rebolleda Gema; Oblanca Noelia; Moreno Montanes Javier; Munoz Negrete Francisco J

来源：Graefes Archive for Clinical and Experimental Ophthalmology, 2014, 252(2): 321-330.

DOI：10.1007/s00417-013-2529-7

• OCT
• RNFL
• GCIPL
• ONH
• False positive

Background The incidence of false positive (FP) results of optic coherence tomography (OCT) retinal nerve fiber layer (RNFL) color code in healthy subjects can be very high with Cirrus OCT. Recent evidence has shown that OCT parameters derived from macular ganglion cell-inner plexiform layer (GCIPL) have excellent ability to discriminate between normal eyes and eyes with early glaucoma. %26lt;br%26gt;This was a prospective, cross-sectional study. One hundred eyes from 50 healthy volunteers underwent circumpapillary scanning by Cirrus and Spectralis OCT and macular scanning using Cirrus OCT. FP rates for each of the OCT parameters, using predefined criteria for an abnormal test were calculated. Comparative analysis was performed using the McNemar test. A generalized estimating equations model (GEE) was used to compare demographic and clinical factors between the eyes with normal findings and eyes with abnormal results. %26lt;br%26gt;The overall RNFL color-code FP rate was significantly higher for Cirrus (39 %) than for Spectralis (18 %) (P = 0.000). The Spectralis RNFL FP rate showed no significant difference when compared to the FP rate by Cirrus GCIPL (13 %) and ONH (11 %) analysis. Axial length, mean spherical equivalent, presence of peripapillary atrophy, and tilted disc were significantly related to the RNFL FP occurrence displayed by both devices. %26lt;br%26gt;Spectralis might be more specific than Cirrus when evaluating the RNFL thickness for Caucasians and moderate myopic population. GCIPL and ONH analysis might be more useful than RNFL thickness to evaluate this population using Cirrus OCT.

• 出版日期2014-2