The Relationship Between Parameters Measured by Optical Coherence Tomography and Visual Field Indices.
10.3341/jkos.2008.49.5.771
- Author:
Min Cheol SEONG
1
;
Jae Wan CHOI
;
Joo Eun LEE
;
Soo Hyun KIM
;
Chang Hwan LEE
;
Michael S KOOK
Author Information
1. Department of Ophthalmology, Hanyang University College of Medicine, Guri Hospital, Gyeonggi, Korea.
- Publication Type:Original Article
- Keywords:
Fast optic disc algorithm;
Optical coherence tomography;
Retinal nerve fiber layer;
Structurefunction association
- MeSH:
Cross-Sectional Studies;
Eye;
Glaucoma;
Nerve Fibers;
Retinaldehyde;
Retrospective Studies;
ROC Curve;
Tomography, Optical Coherence;
Visual Fields
- From:Journal of the Korean Ophthalmological Society
2008;49(5):771-777
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
PURPOSE: To evaluate the diagnostic ability of optic disc topographic parameters and the retinal nerve fiber layer (RNFL) thickness parameter measured by optical coherence tomography (OCT) and to determine the association of these structural parameters with visual field indices. METHODS: Fifty-six glaucomatous eyes and 65 healthy control eyes were enrolled in this retrospective cross-sectional study. Each subject had a 24-2 full threshold test on a Humphrey visual field analyzer and an optical coherence tomographic evaluation. The parameters from the fast RNFL thickness algorithm and the fast optic disc algorithm were analyzed by an ROC curve, and we sought to determine the association of these parameters with visual field indices by linear and logarithmic regression. RESULTS: The area under the receiver operating characteristic curve (AUROC) value of the fast optic disc algorithm parameters ranged from 0.78 to 0.79 and that of the fast RNFL thickness algorithm parameters ranged from 0.74 to 0.81. The associations between the parameters from the fast optic disc algorithm and from the fast RNFL thickness algorithm with visual field indices were statistically significant (P<0.001). CONCLUSIONS: The fast optic disc algorithm and the fast RNFL algorithm revealed comparable diagnostic ability in discriminating glaucoma and significant associations with visual field indices.
