BACKGROUND AND PURPOSE: Lesion burden and brain volume changes are frequent end points in research but nowadays are becoming important in the clinical practice of multiple sclerosis (MS). The objective of this study was to investigate the correlation between magnetic resonance imaging (MRI) measures obtained by in-house developed ScanView software and commonly used volumetric techniques for assessment of T2 lesion and whole brain volumes and their changes. METHODS: Together 3,340 MRI scans from 209 patients after first demyelinating event suggestive of MS, 181 relapsing-remitting MS patients and 43 controls were analyzed. The average number of MRI scans and follow-up duration was 8.2 and 6.5 years, respectively. All MRI scans were performed in a single center but independently analyzed in two neuroimaging centers. Volumetric analysis by ScanView software was applied in Prague. Commonly used techniques, such as SIENA, SIENAX, and Jim software, were applied in Buffalo. Correlations between MRI measures were evaluated using correlation coefficients. Intraindividual variability of longitudinal MRI data was estimated by mean squared error. RESULTS: The associations of the cross-sectional and longitudinal MRI measures between commonly used techniques and ScanView were significant (r/rho = .83-.95). The associations of cross-sectional MRI measures were stronger (r/rho = .90-.95) compared with longitudinal ones (r = .83). Standardized intraindividual variability of whole brain % volume change was greater in ScanView compared with SIENA (mean squared error .32 vs. .21; P < .001). CONCLUSIONS: We found relatively strong correlations of cross-sectional and longitudinal data obtained by both techniques. However, SIENA showed lower intraindividual variability than the ScanView method in measuring whole brain volume loss over time.

Department of Neurology and Center of Clinical Neuroscience 1st Faculty of Medicine and General University Hospital Charles University Prague Czech Republic

Department of Neurology School of Medicine and Biomedical Sciences University at Buffalo State University of New York Buffalo NY

Department of Radiodiagnostics 1st Faculty of Medicine and General University Hospital Charles University Prague Czech Republic

Department of Statistics and Probability University of Economics Prague Czech Republic

IRCCS S Maria Nascente Don Gnocchi Foundation Milan Italy

MR Imaging Clinical Translational Research Center School of Medicine and Biomedical Sciences University at Buffalo State University of New York Buffalo NY

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