March 2012
Volume 53, Issue 14
ARVO Annual Meeting Abstract  |   March 2012
Normative Distribution Indices For Microperimetry Analysis
Author Affiliations & Notes
  • Michael K. Smolek
    Louisiana Eye Research Institute, Pearl River, Louisiana
    CLEVER Eye Institute, Pearl River, Louisiana
  • Neil F. Notaroberto
    Louisiana Eye Research Institute, Pearl River, Louisiana
    EyeCare 20/20, Mandeville, Louisiana
  • Lauren E. Fereday
    Loyola University, New Orleans, Louisiana
  • Arley Jaramillo
    EyeCare 20/20, Mandeville, Louisiana
  • Footnotes
    Commercial Relationships  Michael K. Smolek, CLEVER Eye Institute (E), Louisiana Eye Research Institute (S); Neil F. Notaroberto, Louisiana Eye Research Institute (S); Lauren E. Fereday, None; Arley Jaramillo, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 4367. doi:
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      Michael K. Smolek, Neil F. Notaroberto, Lauren E. Fereday, Arley Jaramillo; Normative Distribution Indices For Microperimetry Analysis. Invest. Ophthalmol. Vis. Sci. 2012;53(14):4367.

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

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Microperimetry testing is gaining acceptance as a clinical tool with the introduction of devices such as the MAIA macular analyzer (Centervue, SpA, Padova, Italy). This study presents new indices based on a normative database that may be used in microperimetry analysis. The study also examines a graphical display for improved interpretation.


A total of 156 MAIA examinations from adults age 20 to 50 with normal vision were used as normative data for this study with informed consent. Raw data consisted of 37 stimulus point threshold readings using the standard MAIA grid pattern centered on the macula and the expert staircase method. The central grid point (S1 value) was analyzed separately due to the significantly higher brightness threshold needed at the foveola in normals. The remaining 36 points were analyzed as a group. Analysis consisted of calculations for the mean, standard deviation (SD), confidence interval of the mean (CIM), kurtosis, skewness, total sensitivity (sum of the stimulus values), and a new pattern irregularity (PI) index based on summing the absolute difference between adjacent stimulus points. The frequency distribution of each index was calculated and an asymmetrical histogram envelope function was determined by Weibull curve fitting. These histograms were then graphically presented in green in the display (see Figure). The statistical difference between the normal sensitivity distribution and any new examination is also calculated and reported. A scanning laser ophthalmoscope (SLO) image with a data overlay from the MAIA is part of the display.


For the normative data we collected, mean sensitivty = 30.92 dB; SD = 2.14; peak CIM = 0.57; peak kurtosis = -0.30; peak skewness = 0.10, peak total sensitivity = 1130; and peak PI = 33.


This method allows users to visualize multiple indices and determine statistical relevance based on color-coding (green = normal, yellow = suspect; orange = caution; red = warning). The method is particularly useful for diagnosing suspected cases of macular disease and to rule out occasional outlier readings. These numbers are specific to MAIA microperimetry and cannot be used for other brands due to differences in the total range and background illumination settings, but the graphical display concept can be applied.  

Keywords: retina • clinical research methodology • computational modeling 

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