• Tomas Uher, Jan Krasensky, Lukas Sobisek, Zdenek Seidl, Niels Bergsland, Michael G Dwyer, Eva Kubala Havrdova, Robert Zivadinov, Dana Horakova, and Manuela Vaneckova.
• Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
• J Neuroimaging. 2018 May 1; 28 (3): 328-337.

Background And PurposeA relatively high intraindividual variability of longitudinal magnetic resonance imaging (MRI) of brain volume loss (BVL) measurements over time renders challenging its application to individual multiple sclerosis (MS) patients. Objective of this study was to investigate if high-frequency brain MRI monitoring affects identification of pathological BVL in an individual patient.MethodsOne hundred fifty-seven relapsing-remitting MS patients had seven MRI scans over 12 months follow-up. All 1,585 MRI scans were performed on the same 1.5T scanner using an identical scanning protocol. Volumetric analysis was performed by ScanView and SIENA software. Linear regression analysis was used for estimation of annualized BVL, with a cutoff greater than .4% defined as pathological. We compared proportions of patients with pathological BVL obtained by analysis of different number of MRI time-points.ResultsAn analysis of seven MRI scans (months 0, 2, 4, 6, 8, 10, and 12) showed pathological BVL in 105 (65%) of patients. When three MRI scans were included (months 0, 6, and 12), we found 10 (6.4%) false negative and 9 (5.7%) false positive results compared with the analysis of seven MRI scans, used as a reference for assessment of pathological BVL. Analysis of two MRI time-points (months 0 and 12) showed 10 (6.4%) false negative and 13 (8.3%) false positive results compared with analysis of seven MRI time-points. Change in the accuracy of pathological BVL between results obtained by analysis of seven and two time-points was 14.7%.ConclusionsHigh-frequency MRI monitoring may have a considerable effect on improving the precision of precisely identifying pathological BVL in individual patients. However, limitations in translation to clinical practice remain.Copyright © 2018 by the American Society of Neuroimaging.

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