Analysis of MTR histograms in multiple sclerosis using principal components and multiple discriminant analysis.

Abstract

Magnetization transfer ratio (MTR) histograms have the potential to characterize subtle diffuse changes in multiple sclerosis (MS) and other white matter disease. A new method is described which gives improved correlation with the Expanded Disability Status Scale (EDSS). Classification of individual subjects into normal and MS subgroups is shown. Principal component analysis (PCA) and multiple discriminant analysis (MDA) are shown to give results superior to methods of MTR histogram analysis using traditional features such as peak height and peak location. Scatterplots confirm the improved separation between groups achieved using the MDA score. The histogram analysis provides a comparison of two classification approaches, based on PCA and MDA, to recognize differences between normal controls and the four different subgroups of MS disease (and all MS patients). Multiple linear regression of these PCs vs. EDSS established an MR-based measure of disease. Using a central 60-mm slab of brain tissue, the success rate of binary classification between control and MS subgroups using MDA was 75-95%, depending on which two groups were being compared. Multiple regression analysis of EDSS with the first three PCs as independent variables was significant (r = 0.83 for secondary progressive MS, and r = 0.80 for all MS patients).