Diagnostic ability of retinal nerve fiber layer maps to detect localized retinal nerve fiber layer defects

Abstract

Purpose To evaluate and compare the diagnostic ability of spectral domain optical coherence tomography (SD-OCT) for detecting localized retinal nerve fiber layer (RNFL) defects in topographic RNFL maps and circumpapillary RNFL (cpRNFL) thickness measurements. Methods Sixty-four eyes with localized RNFL defects in red-free RNFL photographs and 72 healthy eyes were included. All participants were imaged with SD-OCT. The area and angular width of the localized RNFL defects were measured with ImageJ software on RNFL thickness map, significance map (yellow pixels, <5% level), and red-free RNFL photographs. The sensitivity, specificity, and area under the receiver operating characteristic curves (AUCs) were calculated for cpRNFL thickness, macular inner retina thickness, and RNFL maps (thickness, significance) according to the quantitative measurements and a <5% level of classification to distinguish eyes with localized RNFL defects from healthy eyes. Results RNFL thickness map (sensitivity 96.9-98.4%, specificity 86.1-98.6%, and AUCs 0.915-0.992) and significance map (sensitivity 96.9-98.4%, specificity 88.9-95.8%, and AUCs 0.937-0.983) showed superior performance in detecting localized RNFL defects compared with other parameters (P-value 0.001-0.024) except for 36 sector cpRNFL thickness (sensitivity 92.2%, specificity 87.5%, and AUCs 0.898; P-value 0.080-0.545). The sensitivity for detecting RNFL defects was related to the angular width, area, and depth of the RNFL defects in the cpRNFL (4 sector, 12 sector) and macular inner retinal measurements. RNFL thickness and significance maps showed a constant sensitivity regardless of variations in angular width, area, and depth of the RNFL defects. Conclusion RNFL thickness and significance maps could be used to distinguish eyes with localized RNFL defects from healthy eyes more effectively than cpRNFL thickness and macular inner retina thickness measurements.