Malone, I;
Leung, KL;
Clegg, S;
Barnes, J;
Whitwell, JL;
Ashburner, J;
Fox, NC;
(2015)
Accurate automatic estimation of total intracranial volume: a nuisance variable with less nuisance.
Neuroimage
, 104
10.1016/j.neuroimage.2014.09.034.
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Abstract
Total intracranial volume (TIV/ICV) is an important covariate for volumetric analyses of the brain and brain regions, especially in studies of neurodegenerative diseases, where it can provide a proxy of maximum pre-morbid brain volume. The gold-standard method is manual delineation of brain scans, but this requires careful work by trained operators. 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. For T1-weighted MRI acquired from 288 participants in a multi-centre clinical trial in Alzheimer's disease we find a high correlation between SPM12 TIV and manual TIV (R2=0.940, 95% Confidence Interval (0.924, 0.953)), with a small mean difference (SPM12 40.4±35.4ml lower than manual, amounting to 2.8% of the overall mean TIV in the study). The correlation with manual measurements (the key aspect when using TIV as a covariate) for SPM12 was significantly higher (p<0.001) than for either SPM8 (R2=0.577 CI (0.500, 0.644)) or FreeSurfer (R2=0.801 CI (0.744, 0.843)). 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.
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