April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
An Algorithm For Optimizing Temporal Frequencies When Measuring Macular Pigment Using Heterochromatic Flicker Photometry
Author Affiliations & Notes
  • Kevin J. O'Brien
    Vision Sciences Laboratory, University of Georgia, Athens, Georgia
  • Bill Smollon
    Department of Psychology, Brown University, Providence, Rhode Island
  • Bill Wooten
    Department of Psychology, Brown University, Providence, Rhode Island
  • Billy Hammond, Jr.
    Vision Sciences Laboratory, University of Georgia, Athens, Georgia
  • Footnotes
    Commercial Relationships  Kevin J. O'Brien, None; Bill Smollon, Macular Metrics (E); Bill Wooten, Macular Metrics (E); Billy Hammond, Jr., None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 3627. doi:
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      Kevin J. O'Brien, Bill Smollon, Bill Wooten, Billy Hammond, Jr.; An Algorithm For Optimizing Temporal Frequencies When Measuring Macular Pigment Using Heterochromatic Flicker Photometry. Invest. Ophthalmol. Vis. Sci. 2011;52(14):3627.

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

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Abstract

Purpose: : The HFP technique for measuring macular pigment optical density (MPOD) relies on temporal presentations that must accommodate for many factors including age, disease state, and stimulus conditions such as size and the retinal site tested. Hence, a simple algorithm is needed that will allow the optimal flicker setting for a given set of conditions. Critical flicker fusion (CFF) values can be taken quickly and easily allowing a customized flicker frequency to be derived (e.g., Stringham et al., 2008, EER, 87, 445-53). In this study, we expand that algorithm to a new densitometer that can be used in clinical applications and to a wider age-range of subjects.

Methods: : Five measures of CFF frequency were taken using both a centrally fixated (foveal) target and a peripherally fixated (perifoveal) target. HFP was then used to assess MPOD repeatedly, varying the frequency of the HFP stimulus between each trial (Macular Metrics IITM). The HFP frequency yielding the lowest range of values was taken as the subject’s "ideal" HFP frequency. This procedure was performed for both the foveal and perifoveal HFP task. For both the foveal and perifoveal presentations, average CFF frequency and "ideal" HFP frequency were linearly correlated and were used to generate a predictive algorithm.

Results: : Foveal CFF frequency and "ideal" foveal HFP frequency were found to strongly, positively correlate (p<0.05). Likewise, perifoveal CFF frequency and "ideal" perifoveal HFP frequency were strongly, positively correlated (p<0.05). The data were used to create linear functions for use as an algorithm. This algorithm, based on a simple CFF measure, can be used to select a HFP frequency which will be useful in increasing the reliability of a subject’s observations and reducing the standard deviation on MPOD measurements.

Conclusions: : By assessing CFF frequency, which can be reliably measured in naïve subjects, a frequency for HFP used to measure MPOD can be estimated. Using an algorithm generated in this fashion permits an experimenter or clinician to accurately and non-invasively assess MPOD while reducing subject fatigue and maintaining a high level of accuracy.

Keywords: macular pigment • macula/fovea 
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