A MS‐lesion pattern discrimination plot based on geostatistics

INTRODUCTION: A geostatistical approach to characterize MS‐lesion patterns based on their geometrical properties is presented. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.