March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Correlations Between Perimetric Global Indices And Different Measures Of Retinal Nerve Fiber Layer Thickness
Author Affiliations & Notes
  • Deborah Goren
    Devers Eye Institute, Legacy Research Institute, Portland, Oregon
  • Stuart K. Gardiner
    Devers Eye Institute, Legacy Research Institute, Portland, Oregon
  • Shaban Demirel
    Devers Eye Institute, Legacy Research Institute, Portland, Oregon
  • Footnotes
    Commercial Relationships  Deborah Goren, None; Stuart K. Gardiner, None; Shaban Demirel, None
  • Footnotes
    Support  NEI EY019674, Legacy Good Samaritan Foundation
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 713. doi:
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      Deborah Goren, Stuart K. Gardiner, Shaban Demirel; Correlations Between Perimetric Global Indices And Different Measures Of Retinal Nerve Fiber Layer Thickness. Invest. Ophthalmol. Vis. Sci. 2012;53(14):713.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To determine which method of measuring retinal nerve fiber layer thickness (RNFLt) correlates best with standard automated perimetry (SAP) metrics of functional damage.

Methods: : 400 eyes from 209 participants with high-risk ocular hypertension or early glaucoma from the Portland Progression Project (P3) were tested using different imaging devices (Spectralis OCT, HRT, and GDx Pro) to obtain 3 estimates of RNFLt. One functional test (SAP) was also performed. All of the tests were performed on the same day. The mean sensitivity (MS) and mean deviation (MD) from SAP, were linearized using the equations MSLin=10MS*0.1 and MDLin=10MD*0.1. Pearson correlations were calculated between the different RNFLt estimates and the functional metrics. Corresponding significance values were calculated using generalized estimating equations (GEE) to account for correlated data from two eyes of an individual. Variance ratios were calculated based on the retest variability of each metric and these ratios were then used in Deming regressions to define the relation between structural and functional metrics.

Conclusions: : Functional measures MSLin and MDLin correlated best with OCT measures of RNFLt, second best with GDx and worst with HRT. This suggests that the ability of OCT to predict functional status (SAP MS and MD) may be better than the other 2 measures of RNFLt.

Keywords: perimetry • nerve fiber layer 
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