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      Multi-site voxel-based morphometry: Methods and a feasibility demonstration with childhood absence epilepsy

      , , , ,
      NeuroImage
      Elsevier BV

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          Abstract

          Voxel-based morphometry analysis of neurological disorders would benefit if it could use data acquired from different scanners, but scanner based contrast variation could interfere with the detection of disease-specific structural abnormalities. In this study we examine MRI data from three different sites to investigate structural differences between childhood absence epilepsy (CAE) subjects and controls. T1-weighted structural MRI scans were acquired from: Site A. 10 CAE, 213 controls; Site B. 15 CAE, 33 controls; and Site C. 19 CAE, 11 controls. The images were processed using the optimised VBM protocol. Three statistical analyses were undertaken: (1) Comparisons of CAE subjects and controls stratified by site. (2) Between-site comparison of controls from each site. (3) Factorial analysis of all data with site and disease status as factors. Consistent regions of structural change, located in the thalamic nuclei, were observed in the within-site analysis of CAE vs controls. Analysis of control scans, however, indicated site-specific differences between controls, which required that we adjust for site in combined analyses. Analysis of all data with adjustment for site confirmed the finding of thalamic atrophy in CAE cases. Combined VBM analysis of structural MRI scans acquired from different sites yield consistent patterns of structural change in CAE when site is included as a factor in the statistical analysis of the processed images. In MRI studies of diseases where only a limited number of subjects can be imaged at each site, our study supports the possibility of effective multi-site studies as long as both disease subjects and healthy controls are acquired from each site.

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          Author and article information

          Journal
          NeuroImage
          NeuroImage
          Elsevier BV
          10538119
          August 2008
          August 2008
          : 42
          : 2
          : 611-616
          Article
          10.1016/j.neuroimage.2008.05.007
          2603188
          18585930
          4aef7193-d7c5-49e2-ac3e-45ca58d4dea3
          © 2008

          https://www.elsevier.com/tdm/userlicense/1.0/

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