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A novel computational model of human macular pigment optical density: correlation of macular pigment density with foveal structure
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Abstract
Macular pigment optical density (MPOD) models enhance understanding of macular xanthophyll distribution, particularly relevant to age-related macular degeneration. We investigate an existing model and introduce a novel, more accurate and biologically relevant approach.MPOD profiles from 49 eyes were obtained using dual-wavelength autofluorescence imaging, with structural data from OCT and OCT angiography. Data were analyzed using (a) an existing exponential and Gaussian sum model (MEG) and (b) a novel three Gaussians sum model (M3G). Extracted parameters generated individualized MPOD spatial models, from which gradients and volumes were derived. MEG-derived variables were analyzed against OCT/OCTA data using principal component analysis and multiple regression.M3G demonstrated a superior fit to MPOD data than MEG, enabling automated fitting without parameter manipulation and maintaining consistency for small and large datasets. M3G provided meaningful variables, including MPOD gradients, volumes and critical point eccentricities. Strong correlations included those between dependent variables of critical point eccentricities and central macular pigment volume with foveal avascular zone and foveal pit radii.M3G provides an excellent fit for foveal MPOD, enabling automated data extraction of physiologically relevant parameters. Its three-component configuration is consistent with macular xanthophyll location. M3G is similar to models of foveal structure, suggesting a fundamental relationship.
Springer Science and Business Media LLC
Title: A novel computational model of human macular pigment optical density: correlation of macular pigment density with foveal structure
Description:
Abstract
Macular pigment optical density (MPOD) models enhance understanding of macular xanthophyll distribution, particularly relevant to age-related macular degeneration.
We investigate an existing model and introduce a novel, more accurate and biologically relevant approach.
MPOD profiles from 49 eyes were obtained using dual-wavelength autofluorescence imaging, with structural data from OCT and OCT angiography.
Data were analyzed using (a) an existing exponential and Gaussian sum model (MEG) and (b) a novel three Gaussians sum model (M3G).
Extracted parameters generated individualized MPOD spatial models, from which gradients and volumes were derived.
MEG-derived variables were analyzed against OCT/OCTA data using principal component analysis and multiple regression.
M3G demonstrated a superior fit to MPOD data than MEG, enabling automated fitting without parameter manipulation and maintaining consistency for small and large datasets.
M3G provided meaningful variables, including MPOD gradients, volumes and critical point eccentricities.
Strong correlations included those between dependent variables of critical point eccentricities and central macular pigment volume with foveal avascular zone and foveal pit radii.
M3G provides an excellent fit for foveal MPOD, enabling automated data extraction of physiologically relevant parameters.
Its three-component configuration is consistent with macular xanthophyll location.
M3G is similar to models of foveal structure, suggesting a fundamental relationship.
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