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PURPOSE: To evaluate the pattern of structural damage in the macula and peripapillary retinal nerve fiber layer (RNFL) using optical coherence tomography (OCT) and scanning laser polarimetry (SLP-VCC) in glaucomatous eyes with localized visual field defects. DESIGN: Prospective, cross-sectional analysis. METHODS: Complete examination, automated achromatic perimetry (AAP), Stratus OCT imaging (512 A-scans) of the peripapillary retina and macula, and SLP-VCC imaging of the peripapillary RNFL were performed. Thickness values in the retinal segments associated with the visual field defect (glaucomatous segments) were compared with corresponding segments across the horizontal raphe (nonglaucomatous segments) and age-matched normal controls. RESULTS: Forty eyes of 40 patients (20 normal, 20 glaucomatous) were enrolled (mean age, 71 ± 10 years; range, 50 to 89). Mean RNFL thickness using SLP-VCC and OCT in the nonglaucomatous segments of glaucomatous eyes (54.0 ± 9.7 μm, 64.7 ± 19.0 μm) were significantly (P =.009, <0.0001) reduced compared with the thickness measurements in the corresponding segments of age-matched normal subjects (62.5 ± 9.2 μm, 105.6 ± 19.0 μm) respectively. No significant (P =.4) differences in the macular thickness measurements were observed between nonglaucomatous (239.0 ± 19.4 μm) and normal segments (243.5 ± 15.0 μm). Compared with age-matched controls, RNFL thickness in the nonglaucomatous segment was abnormal in 15 of 20 patients (75%) with SLP-VCC and in 18 of 20 patients (90%) with OCT. Macular thickness in the nonglaucomatous segment was abnormal in 11 of 20 patients (55%). CONCLUSIONS: Diffuse RNFL and retinal ganglion cell loss is present in eyes with localized visual field abnormalities. Detection of localized changes in macular thickness is limited by measurement overlap among normal and glaucomatous eyes.
Department of Ophthalmology, University of Miami School of Medicine, Bascom Palmer Eye Institute, Miami, Florida, USA.
6.9.2 Optical coherence tomography (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)