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Pauline J Bland BSE, Christopher M Putnam OD, Carl J Bassi PhD

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Presentation on theme: "Pauline J Bland BSE, Christopher M Putnam OD, Carl J Bassi PhD"— Presentation transcript:

1 A Comparison of Methods to Describe Macular Pigment Optical Density Spatial Distribution
Pauline J Bland BSE, Christopher M Putnam OD, Carl J Bassi PhD University of Missouri – St. Louis College of Optometry Purpose Results Several studies have established the spatial distribution of macular pigment optical density (MPOD) as an exponential decay function with increasing foveal eccentricity. While most commercially available devices emphasize a foveal MPOD measure, it has been recognized that there is a low correlation between foveal versus overall spatial distribution of MPOD. This study examined the shape of the MPOD spatial distribution pattern by comparing fit functions and kurtosis calculations. Spatial mapping of MPOD across all subjects was highly reliable. The average r2 values for the Gaussian and Lorentzian fit functions are 0.89 and 0.95, respectively. No significant correlation was found between the Lorentzian AUC and foveal MPOD nor between the Gaussian AUC and foveal MPOD (Table 1). A large range of kurtosis values were measured within the study sample. Two subject distributions are shown in Figure 4. The binomial test (z = -4.05) was significant at p < Experimental Methods A customized heterochromatic flicker photometry device was used to measure MPOD in 22 subjects at discrete retinal eccentricities (Figure 1 and 2) using a 10 circular stimulus. For each subject, MPOD values for all 4 meridians were averaged at each retinal eccentricity. Figure 1 - Example of a radial pattern depicting the 8 principle meridians. MPOD was measured at 00, 20, 40, 60 and 80 along superior, inferior, nasal and temporal meridians. Figure 2 - A novel device used to measure MPOD at varying retinal eccentricities. Figure 4 – OriginPro9 plots for a leptokurtotic MPOD distribution (left) and a platykurtotic MPOD distribution (right) with Gaussian and Lorentzian fit functions. OriginPro9 (Northampton, MA) (Figure 3) was utilized to plot each subject’s spatial distribution pattern. Each spatial distribution was fit to both a Gaussian and a Lorentzian function. Area under the curve (AUC) was calculated for each subject using both fit functions and compared to their foveal MPOD measurement. Kurtosis values were calculated for each subject’s spatial distribution pattern. A binomial test was performed comparing predicted shape (leptokurtotic or platykurtotic) versus best fit function. Table 1 – Pearson correlations of Lorentzian AUC and Gaussian AUC with foveal measures of MPOD. Lorentzian AUC Gaussian AUC Foveal MPOD Pearson Correlation 0.10 0.09 Sig. (2-tailed) 0.66 0.68 N 22 Conclusions Consistent with previous findings, the Lorentzian function better describes the spatial distribution of MPOD. Kurtosis values may serve as another option for describing the spatial distribution pattern. Further study is needed to examine relationships among foveal measures of MPOD, other integrated measures of MPOD, and kurtosis. References Nolan JM, Stringham JM, Beatty S, Snodderly DM. Spatial profile of macular pigment and its relationship to foveal architecture. IOVS. 2008; 49(5): Stringham JM, Fuld K, Wenzel AJ. Spatial properties of photophobia. IOVS. 2004; 45(10): Hammond BR, Wooten BR, Snodderly DM. Individual variations in the spatial profile of human macular pigment. J Opt Soc Am A. 1997; 14(6): Trieschmann M, Van Kuijk FJGM, Alexander R, Hermans P, Luthert P, Bird AC, Pauleikhoff D. Macular pigment in the human retina: histological evaluation of localization and distribution. Eye. 2007; 22(1): Figure 3 – Example of OriginPro 9 GUI for plot generation and output of Gaussian and Lorentzian fit functions.


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