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Abstract #50513 Published in IGR 14-2
Frequency-doubling technology and retinal measurements with spectral-domain optical coherence tomography in preperimetric glaucoma
Hirashima T; Hangai M; Nukada M; Nakano N; Morooka S; Akagi T; Nonaka A; Yoshimura NGraefe's Archive for Clinical and Experimental Ophthalmology 2013; 251: 129-137
BACKGROUND: To determine the relationship between visual fields and retinal structures measured with spectral-domain optical coherence tomography in preperimetric glaucoma (PPG). METHODS: Twenty-six eyes of 26 patients with PPG and 20 healthy eyes of 20 volunteers were included. All patients underwent Heidelberg retina tomography-2 (HRT2), standard automated perimetry (SAP), frequency-doubling technology (FDT) perimetry, and RTVue-100. SAP and FDT indices, HRT parameters, and circumpapillary retinal nerve fiber layer (cpRNFL) and macular ganglion cell complex (mGCC) thicknesses were correlated using Pearson's test. Areas under the receiver operating characteristic curves (AUROCs) and sensitivity/specificity based on each parameter's definition of abnormalities were compared between parameters. RESULTS: Significant differences were found in FDT-MD, FDT-PSD, SAP-PSD, cpRNFL, and mGCC parameters (p < 0.001-0.015), but not in SAP-MD or HRT parameters, between PPG and control groups. Significant correlations were not found between visual field indices and structural parameters, except between FDT-MD and HRT rim area (r = 0.450, p = 0.021) and between FDT-PSD and temporal cpRNFL thickness (r = 0.402, p = 0.021). AUROCs for cpRNFL (p = 0.0047-0.033) and mGCC (p = 0.0082-0.049) parameters were significantly better than those of HRT parameters, whereas significant differences were not found between FDT indices and cpRNFL or mGCC parameters or between cpRNFL and mGCC parameters. Adding average cpRNFL or mGCC thickness to FDT-MD significantly increased sensitivity compared to single parameters (p = 0.016-0.031). CONCLUSIONS: Structural and functional parameters were poorly correlated but complementary for glaucoma detection in PPG. Combining these parameters may improve PPG diagnosis.
Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan.
Full articleClassification:
6.6.3 Special methods (e.g. color, contrast, SWAP etc.) (Part of: 6 Clinical examination methods > 6.6 Visual field examination and other visual function tests)
6.9.2.2 Posterior (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis > 6.9.2 Optical coherence tomography)
