A MS-lesion pattern discrimination plot based on geostatistics
Brain Behav. 2016 Jan 30:e00430. [Epub ahead of print]
|Authors/Editors:||Marschallinger R, Schmidt P, Hofmann P, Zimmer C, Atkinson PM, Sellner J, Trinka E, Mühlau M.|
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.