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Forschungsdatenbank PMU-SQQUID

A MS-lesion pattern discrimination plot based on geostatistics.
Marschallinger, R; Schmidt, P; Hofmann, P; Zimmer, C; Atkinson, PM; Sellner, J; Trinka, E; Mühlau, M;
BRAIN BEHAV. 2016; 6(3): e00430
Originalarbeiten (Zeitschrift)


Marschallinger Robert
Sellner Johann
Trinka Eugen


A geostatistical approach to characterize MS-lesion patterns based on their geometrical properties is presented.
A dataset of 259 binary MS-lesion masks in MNI space was subjected to directional variography. A model function was fit to express the observed spatial variability in x, y, z directions by the geostatistical parameters Range and Sill.
Parameters Range and Sill correlate with MS-lesion pattern surface complexity and total lesion volume. A scatter plot of ln(Range) versus ln(Sill), classified by pattern anisotropy, enables a consistent and clearly arranged presentation of MS-lesion patterns based on geometry: the so-called MS-Lesion Pattern Discrimination Plot.
The geostatistical approach and the graphical representation of results are considered efficient exploratory data analysis tools for cross-sectional, follow-up, and medication impact analysis.

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