@article {369016,
	title = {Correlation of localized glaucomatous visual field defects and spectral domain optical coherence tomography retinal nerve fiber layer thinning using a modified structure-function map for OCT.},
	journal = {Eye (Lond)},
	volume = {29},
	number = {4},
	year = {2015},
	month = {2015 Apr},
	pages = {525-33},
	abstract = {PurposeTo study the correlation between glaucomatous visual field (VF) defects assessed by standard automated perimetry (SAP) and peripapillary retinal nerve fiber layer (RNFL) thinning measured by spectral domain optical coherence tomography (OCT) using a modified OCT-based peripapillary RNFL structure-function map.Patients and methodsPerimetric glaucoma patients and age-matched normal control subjects were recruited from a university hospital clinic. All eyes underwent testing with the Spectralis spectral domain OCT and SAP on the same day. An OCT-based correspondence map, which correlated VF areas with peripapillary RNFL sectors was created to evaluate the relationship between glaucomatous RNFL thinning and VF loss in six nerve fiber layer bundle areas. Correlations of RNFL thinning with corresponding VF defects were examined using Spearman rank-order correlations. To demonstrate the association between localized VF defects and RNFL thickness, the theoretical curves were made according to an established log-linear model. The measured RNFL thickness values and VF defects were presented in the same scatterplot for each sector.ResultsFifty-six glaucoma patients and 85 normal subjects were included in the study. Significant association between localized VF loss and RNFL thinning was found in corresponding areas. Data from the current study fit well with established log-linear models, which compare RNFL thickness values with VF defects.ConclusionAnalysis of RNFL thinning in eyes with localized glaucomatous VF defects showed good structure-function correlation in a new OCT-based structure-function correspondence map.},
	issn = {1476-5454},
	doi = {10.1038/eye.2014.317},
	author = {Wu, H and de Boer, J F and Chen, L and Chen, T. C.}
}
