| Literature DB >> 27431758 |
Viola Biberacher1, Paul Schmidt2, Anisha Keshavan3, Christine C Boucard4, Ruthger Righart4, Philipp Sämann5, Christine Preibisch6, Daniel Fröbel6, Lilian Aly7, Bernhard Hemmer8, Claus Zimmer6, Roland G Henry3, Mark Mühlau4.
Abstract
Brain volumetric measurements in multiple sclerosis (MS) reflect not only disease-specific processes but also other sources of variability. The latter has to be considered especially in multicenter and longitudinal studies. Here, we compare data generated by three different 3-Tesla magnetic resonance scanners (Philips Achieva; Siemens Verio; GE Signa MR750). We scanned two patients diagnosed with relapsing remitting MS six times per scanner within three weeks (T1w and FLAIR, 3D). We assessed T2-hyperintense lesions by an automated lesion segmentation tool and determined volumes of grey matter (GM), white matter (WM) and whole brain (GM+WM) from the lesion-filled T1-weighted images using voxel-based morphometry (SPM8/VBM8) and SIENAX (FSL). We measured cortical thickness using FreeSurfer from both, lesion-filled and original T1-weighted images. We quantified brain volume changes with SIENA. In both patients, we found significant differences in total lesion volume, global brain tissue volumes and cortical thickness measures between the scanners. Morphometric measures varied remarkably between repeated scans at each scanner, independent of the brain imaging software tool used. We conclude that for cross-sectional multicenter studies, the effect of different scanners has to be taken into account. For longitudinal monocentric studies, the expected effect size should exceed the size of false positive findings observed in this study. Assuming a physiological loss of brain volume of about 0.3% per year in healthy adult subjects (Good et al., 2001), which may double in MS (De Stefano et al., 2010; De Stefano et al., 2015), with current tools reliable estimation of brain atrophy in individual patients is only possible over periods of several years.Entities:
Keywords: Magnetic resonance imaging; Multiple sclerosis; Scanner-related variability
Mesh:
Year: 2016 PMID: 27431758 DOI: 10.1016/j.neuroimage.2016.07.035
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556