April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Estimating the Relationship between Variability and Measured Sensitivity in VFs using Large-Scale Patient Data Series
Author Affiliations & Notes
  • Richard A. Russell
    NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust & UCL Institute of Ophthalmology, London, United Kingdom
    Optometry & Visual Science, City University, London, United Kingdom
  • Rizwan Malik
    NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust & UCL Institute of Ophthalmology, London, United Kingdom
  • David P. Crabb
    Optometry & Visual Science, City University, London, United Kingdom
  • Ananth C. Viswanathan
    NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust & UCL Institute of Ophthalmology, London, United Kingdom
    Optometry & Visual Science, City University, London, United Kingdom
  • David F. Garway-Heath
    NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust & UCL Institute of Ophthalmology, London, United Kingdom
    Optometry & Visual Science, City University, London, United Kingdom
  • Footnotes
    Commercial Relationships  Richard A. Russell, None; Rizwan Malik, None; David P. Crabb, None; Ananth C. Viswanathan, None; David F. Garway-Heath, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 5490. doi:https://doi.org/
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Richard A. Russell, Rizwan Malik, David P. Crabb, Ananth C. Viswanathan, David F. Garway-Heath; Estimating the Relationship between Variability and Measured Sensitivity in VFs using Large-Scale Patient Data Series. Invest. Ophthalmol. Vis. Sci. 2011;52(14):5490. doi: https://doi.org/.

      Download citation file:


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

      ×
  • Supplements
Abstract
 
Purpose:
 

Evaluation of visual field (VF) damage is largely based on pointwise sensitivity data from standard automated perimetry; however, measurements are highly variable (as shown by frequency-of-seeing and test-retest studies), which significantly impedes assessment of progression. The aim of this study was to characterize VF variability by level of sensitivity using a statistical method to quantify heteroscedasticity.

 
Methods:
 

68,099 Humphrey 24-2 SITA Standard VFs from 8,252 patients (14,137 eyes) visiting Moorfields Eye Hospital from 1997-2009 were studied. Each eye’s VF series was analyzed using pointwise linear regression of sensitivity over time, with residuals (difference from fitted value) from each regression pooled according to the fitted sensitivities (to the nearest dB). Average variability was calculated as the median residual for each whole dB sensitivity level.

 
Results:
 

The median (interquartile range, IQR) patient age, follow-up and series length was 66 (55-74) years, 5.3 (3.1-7.5) years and 4 (3-8) VFs, respectively. The inferred variability is shown (cf. Artes et al. and Henson et al. estimates) in Figure 1. Overall, there is good agreement with Artes et al.; however, in the 35-40dB range, Artes et al. estimates are much smaller. This likely reflects the real-world nature of a clinical dataset with a higher rate of false-positive responses.

 
Conclusions:
 

This study highlights a new approach for characterizing VF variability with sensitivity. A great strength of the method is that inference is based on thousands of clinic patients rather than the tens of subjects in test-retest studies. The results are important for helping clinicians to distinguish real VF progression from noise and will be used in models for glaucoma progression detection.  

 
Keywords: visual fields • perimetry • computational modeling 
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×