Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance.
Bottom Line: We evaluated Statistical Parametric Mapping 12 (SPM12) automated segmentation for TIV measurement in place of manual segmentation and also compared it with SPM8 and FreeSurfer 5.3.0.These results suggest that SPM12 TIV estimates are an acceptable substitute for labour-intensive manual estimates even in the challenging context of multiple centres and the presence of neurodegenerative pathology.We also briefly discuss some aspects of the statistical modelling approaches to adjust for TIV.
Affiliation: Dementia Research Centre (DRC), Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK. Electronic address: firstname.lastname@example.org.Show MeSH
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Mentions: It is important to note that the tissue prior probability templates used in SPM are based on averaging multiple automatically segmented images in standard space (for example, SPM12's priors come from segmentations (using New Segment) of images from the IXI data-set, http://www.brain-development.org/ (Heckemann et al., 2003)), so there is no guarantee that the sum of grey matter, white matter and CSF classes will be exactly consistent with accepted definitions of TIV, particularly with regard to the inferior cut-off and the inclusion of blood-filled sinuses. For this reason, we used the SPM12 tissue prior maps (and corresponding average T1-weighted, T2-weighted and proton-density weighted images from the same IXI data) to create a manually-corrected TIV mask consistent with the protocol described above (though segmented at each slice). Fig. 1 shows the TIV mask applied to tissue classes. Supplementary Fig. 1 shows a typical illustration of the non-brain classes, which are almost entirely located outside the ICV.
Affiliation: Dementia Research Centre (DRC), Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK. Electronic address: email@example.com.