An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer's disease.

Neuroradiology
Xingfeng LiHabib Benali

Abstract

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

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Citations

Mar 14, 2013·Expert Opinion on Medical Diagnostics·Luis Hernandez-Garcia, Martin Buschkuehl
Feb 20, 2020·Magnetic Resonance in Medical Sciences : MRMS : an Official Journal of Japan Society of Magnetic Resonance in Medicine·Masami GotoHiroyuki Daida
Nov 24, 2020·Journal of Neuroimaging : Official Journal of the American Society of Neuroimaging·Wei LiuGuangxiang Chen

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