A MS‐lesion pattern discrimination plot based on geostatistics. Issue 3 (30th January 2016)

• Record Type: Journal Article
• Authors: Marschallinger, Robert; Schmidt, Paul; Hofmann, Peter; Zimmer, Claus; Atkinson, Peter M.; Sellner, Johann; Trinka, Eugen; Mühlau, Mark
• Is Part Of: Brain and behavior. Volume 6:Issue 3(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-01-30
• Subjects: Discrimination -- geostatistics -- lesion -- Multiple Sclerosis -- pattern; Neurology -- Periodicals; Neurosciences -- Periodicals; Psychology -- Periodicals; Psychiatry -- Periodicals; 616.8005
• DOI: 10.1002/brb3.430
• Languages: English
• ISSNs: 2162-3279

Abstract

Abstract: 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. Abstract : A geostatistics‐based MS‐lesion pattern description is developed. The resulting graphical representations are considered efficient exploratory data analysis tools to accompany cross‐sectional, follow‐up, and medication impact analysis.