April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Noise-Corrected Maximum-Likelihood Analysis of Global Visual Field Progression
Author Affiliations & Notes
  • David W. Richards
    Ophthalmology, Univ of South Florida Coll of Med, Tampa, Florida
  • Samantha Roland
    Ophthalmology, Univ of South Florida Coll of Med, Tampa, Florida
  • Gretta Fridman
    Ophthalmology, Univ of South Florida Coll of Med, Tampa, Florida
  • Arthur Snider
    Electrical Engineering, Univ of South Florida, Tampa, Florida
  • Footnotes
    Commercial Relationships  David W. Richards, To be submitted for patent or licensing. (P); Samantha Roland, None; Gretta Fridman, None; Arthur Snider, To be submitted for patent or licensing. (P)
  • Footnotes
    Support  Internal Grant, Univ of South Florida College of Medicine
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 4155. doi:
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    • Get Citation

      David W. Richards, Samantha Roland, Gretta Fridman, Arthur Snider; Noise-Corrected Maximum-Likelihood Analysis of Global Visual Field Progression. Invest. Ophthalmol. Vis. Sci. 2011;52(14):4155.

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

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Abstract

Purpose: : To develop a mathematical measure of global visual field change while accounting for all quantifiable effects that interfere with estimation of this change.

Methods: : We retrospectively analyzed 92 Zeiss-Humphrey (ZH) 24-2 Sita-Standard visual fields (VFs) of 10 eyes of 10 glaucoma patients. There were 7 to11 serial VFs per eye extending over 4 to 8 years. All eyes had acuities of 20/40 or better and combined false positive + false negative rates of < 20%. Mean Defect (MD) ranged from -19 to 0, and Pattern Standard Deviation (PSD) from 2.17 to 15.63. Raw sensitivity (S) and Total Deviation (TD) maps were used in the analysis. A histogram of TD revealed a bimodal distribution, whose low-end secondary peak was determined to be due to non-thresholded (NT) points ( S = "<0") . This is one source of "noise". A second type of noise was the non-Gaussian distribution of TD, after elimination of NT points. A third source was fluctuation over time at individual TD locations ("loci"). Using transformation of variable, elimination of NT points, and calculation of pointwise time-variability of transformed TD at each locus, we calculated the Maximum-Likelihood (ML) global rate of change (R) of TD for each eye, with corresponding 1-sigma uncertainty (sigR). R and sigR were compared with the corresponding parameters (RZH and sigRZH) derived using MD and PSD from ZH as input.

Results: : R and RZH were not significantly different (p = 0.16, Mann-Whitney U Test ), but sigR (mean 0.222 db/year) was significantly smaller than sigRZH (mean 1.33 db/year) (p <0.001, Mann-Whitney U Test ).

Conclusions: : There is a clinical need for a sensitive measure of global visual field change (Caprioli J, Am J of Ophthalmology 2008; 145; 191-192; Johnson C, Glaucoma Today 2010; 8; 34 ). The standard ZH parameters MD and VFI (Visual Field Index) include averages over all loci within a VF and are subject to contamination by inclusion of NT points, as well as by two other types of noise. Correction for all three types of noise and ML analysis improve the statistical accuracy of measurement of global VF change.

Keywords: visual fields 
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