Issues with threshold masking in voxel-based morphometry of atrophied brains.
There is great interest in using automatic computational neuroanatomy tools to study ageing and neurodegenerative disease. Voxel-based morphometry (VBM) is one of the most widely used of such techniques. VBM performs voxel-wise statistical analysis of smoothed spatially normalised segmented Magnetic Resonance Images. There are several reasons why the analysis should include only voxels within a certain mask. We show that one of the most commonly used strategies for defining this mask runs a major risk of excluding from the analysis precisely those voxels where the subjects' brains were most vulnerable to atrophy. We investigate the issues related to mask construction, and recommend the use of alternative strategies which greatly decrease this danger of false negatives.
Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, WC1E 6BT, London, UK.
Gerard R
GR
Ridgway
Rohani
R
Omar
Sébastien
S
Ourselin
Derek L G
DL
Hill
Jason D
JD
Warren
Nick C
NC
Fox
D000368:Aged; D000375:Aging / Q000473:pathology; D000544:Alzheimer Disease / Q000000981:diagnostic imaging / Q000473:pathology*; D001284:Atrophy / Q000000981:diagnostic imaging / Q000473:pathology; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods*; D003704:Dementia / Q000000981:diagnostic imaging / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D011877:Radionuclide Imaging