title: VBM lesion detection depends on the normalization template: a study using simulated atrophy.
abstract: Structural neuroimaging studies are of great interest for neuroscientists, which are reflected in the rising number of papers using voxel-based morphometry (VBM). One major step in VBM is the transformation of images to a standard template, a spatial normalization necessary to ensure that homologous regions are compared while interindividual characteristics are maintained. Templates can be created in different ways, and this may affect the likelihood that differences in gray/white matter density between groups are detected. However, studies investigating the interaction of normalization template and VBM accuracy are sparse. Existing work is based on patient-control group comparisons, and the emerging results are inconclusive. The present paper therefore used simulated atrophy in a simplified one-lesion model to systematically study template effects of VBM analyses implemented in SPM. This allowed us to characterize template-specific biases in reference to a set of prespecified parameters of anatomical difference. The data suggest that the likelihood of correctly detecting the prespecified lesion is modulated by the normalization template. Thereby, the relationship between template-related VBM accuracy and specific group/study characteristics is complex, and there does not appear to be one 'best template.' Our data show that template effects are critical and clearly suggest that the choice of template needs careful consideration in relation to the specific research question and study constraints.
authors.affiliation: Department of Psychology, University of Surrey, GU2 7XH Guildford, UK. shan.shen@surrey.ac.uk
authors.forename: Shan
authors.initials: S
authors.lastname: Shen
authors.forename: Andre J
authors.initials: AJ
authors.lastname: Szameitat
authors.forename: Annette
authors.initials: A
authors.lastname: Sterr
mesh_terms: D000328:Adult; D000465:Algorithms; D001284:Atrophy / Q000473:pathology; D001921:Brain / Q000473:pathology*; D001927:Brain Diseases / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity