• N K Focke, G Helms, S Kaspar, C Diederich, V Tóth, P Dechent, A Mohr, and W Paulus.
• Department of Clinical Neurophysiology, University Medical Center, Georg-August University Göttingen, Göttingen, Germany. nfocke@uni-goettingen.de
• Neuroimage. 2011 Jun 1; 56 (3): 1164-70.

AbstractVoxel-based morphometry (VBM) is a widely applied method in computational neurosciences but it is currently recommended to compare only data collected at a single MRI scanner. Multi-site VBM would be a desirable approach to increase group size and, thus, statistical power. We aimed to assess if multi-site VBM is feasible on similar hardware and compare the magnitude of inter- and intra-scanner differences. 18 healthy subjects were scanned in two identical 3T MRI scanners using different head coil designs, twice in scanner A and once in scanner B. 3D T1-weighted images were processed with SPM8 and FSL4.1 and compared as paired t-test (scan versus re-scan) on a voxel basis by means of a general linear model (GLM). Additionally, coefficient-of-difference (coeffD) maps were calculated for respective pairs of gray matter segmentations. We found considerable inter-scanner differences clearly exceeding a commonly used GLM significance threshold of p<0.05 (FWE corrected). The spatial pattern of detected differences was dependent on whether SPM8 or FSL4.1 was used. The inclusion of global correcting factors either aggravated (SPM8) or reduced the GLM detected differences (FSL4.1). The coeffD analysis revealed markedly higher variability within the FSL4.1 stream both for the inter- and the intra-scanner comparison. A lowered bias cutoff (30 mm FWHM) in SPM8 improved the comparability for cortical areas. Intra-scanner scan/re-scan differences were generally weaker and did not exceed a p<0.05 (FWE corrected) threshold in the GLM analysis. At 3T profound inter-scanner differences are to be expected that could severely confound an unbalanced VBM analysis. These are like related to the receive bias of the radio-frequency hardware.Copyright © 2011 Elsevier Inc. All rights reserved.

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