PURPOSE: To report retinal nerve fiber layer (RNFL) defect identification and quantification in RNFL thickness maps according to the structural RNFL loss, and to evaluate diffuse RNFL defects. METHODS: A total of 170 patients with glaucoma and 186 normal subjects were consecutively enrolled. We defined RNFL defects in an RNFL thickness map by the degree of RNFL loss. The reference level for RNFL defect determination was set as a 20% to 70% degree of RNFL loss with a 1% interval. To identify RNFL defects, each individual RNFL thickness map was compared to the normative database map by using MATLAB software, and the region below the reference level was detected. The area, volume, location, and angular width of each RNFL defect were measured. Diffuse RNFL defects were defined as having an angular width > 30°. RESULTS: The optimal reference level for glaucomatous RNFL defects identification was 42% loss of RNFL. Retinal nerve fiber layer defects were identified in all (100%) of the 170 glaucoma patients and false-positive RNFL defects were detected in 16 (8.16%) cases among the 186 normal subjects. In all, 64.1% of glaucoma patients had diffuse RNFL defects, and 47.7% of diffuse RNFL defects were associated with mild glaucoma patients. The volume of diffuse RNFL defects was significantly associated with the severity of glaucomatous damage (P = 0.009). Diffuse RNFL defects were located closer to the center of the optic disc than localized RNFL defects (P < 0.001). CONCLUSIONS: Retinal nerve fiber layer thickness map analysis is an effective method for analyzing RNFL defects. Quantitative measurements (area, volume, location, and width) were useful to understanding diffuse RNFL defects. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.
PURPOSE: To report retinal nerve fiber layer (RNFL) defect identification and quantification in RNFL thickness maps according to the structural RNFL loss, and to evaluate diffuse RNFL defects. METHODS: A total of 170 patients with glaucoma and 186 normal subjects were consecutively enrolled. We defined RNFL defects in an RNFL thickness map by the degree of RNFL loss. The reference level for RNFL defect determination was set as a 20% to 70% degree of RNFL loss with a 1% interval. To identify RNFL defects, each individual RNFL thickness map was compared to the normative database map by using MATLAB software, and the region below the reference level was detected. The area, volume, location, and angular width of each RNFL defect were measured. Diffuse RNFL defects were defined as having an angular width > 30°. RESULTS: The optimal reference level for glaucomatous RNFL defects identification was 42% loss of RNFL. Retinal nerve fiber layer defects were identified in all (100%) of the 170 glaucomapatients and false-positive RNFL defects were detected in 16 (8.16%) cases among the 186 normal subjects. In all, 64.1% of glaucomapatients had diffuse RNFL defects, and 47.7% of diffuse RNFL defects were associated with mild glaucomapatients. The volume of diffuse RNFL defects was significantly associated with the severity of glaucomatous damage (P = 0.009). Diffuse RNFL defects were located closer to the center of the optic disc than localized RNFL defects (P < 0.001). CONCLUSIONS: Retinal nerve fiber layer thickness map analysis is an effective method for analyzing RNFL defects. Quantitative measurements (area, volume, location, and width) were useful to understanding diffuse RNFL defects. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.
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