An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer's disease.
BACKGROUND
When characterizing regional cerebral gray matter differences in structural magnetic resonance images (sMRI) by voxel-based morphometry (VBM), one faces a known drawback of VBM, namely that histogram unequalization in the intensity images introduces false-positive results.


METHODS
To overcome this limitation, we propose to improve VBM by a new approach (called eVBM for enhanced VBM) that takes the histogram distribution of the sMRI into account by adding a histogram equalization step within the VBM procedure. Combining this technique with two most widely used VBM software packages (FSL and SPM), we studied GM variability in a group of 62 patients with Alzheimer's disease compared to 73 age-matched elderly controls.


RESULTS
The results show that eVBM can reduce the number of false-positive differences in gray matter concentration.


CONCLUSIONS
Because it takes advantage of the properties of VBM while improving sMRI histogram distribution at the same time, the proposed method is a powerful approach for analyzing gray matter differences in sMRI and may be of value in the investigation of sMRI gray and white matter abnormalities in a variety of brain diseases.
Li
Xingfeng
X
Laboratoire d'Imagerie Fonctionnelle, and LINeM, GHU Pitié-Salpêtrière, Inserm, UPMC Univ Paris 06, UMR_S 678, 91 bd de l'Hôpital, 75634, Paris, Cedex 13, France.
Messé
Arnaud
A
Marrelec
Guillaume
G
Pélégrini-Issac
Mélanie
M
Benali
Habib
H
D000368:Aged; D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000473:pathology*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D012984:Software