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

  • Diagnostic Neuroradiology
  • Published:
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Abstract

Introduction

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.

Conclusion

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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Acknowledgments

X. Li is funded by a “poste vert” from Inserm. This work was supported by the International Laboratory on Neuroimaging and Modeling (Inserm—UPMC Univ Paris 06—Université de Montréal). The authors thank Pr. S. Lehéricy and Dr. V. Perlbarg for their helpful comments.

The authors thank Dr. Randy Buckner and his colleagues for making their OASIS data available to us.

Conflict of interest statement

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

  1. 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

    Xingfeng Li, Arnaud Messé, Guillaume Marrelec, Mélanie Pélégrini-Issac & Habib Benali

  2. LINeM, International Laboratory of Neuroimaging and Modeling, IUGM, Université de Montréal, 4565 chemin Queen-Mary, Montréal, H3W 1W5, Canada

    Xingfeng Li, Arnaud Messé, Guillaume Marrelec, Mélanie Pélégrini-Issac & Habib Benali

  3. CRM, Université de Montréal, CP 6128, Succursale Centre-ville, Montréal, H3C 3J7, Canada

    Xingfeng Li, Arnaud Messé, Guillaume Marrelec, Mélanie Pélégrini-Issac & Habib Benali

  4. UMR_S 678 Inserm/UPMC, Laboratoire d’Imagerie Fonctionnelle, Faculté de Médecine, CHU Pitié-Salpétrière, 91 Bd de l’Hôpital, 75634, Paris Cedex 13, France

    Habib Benali

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  1. Xingfeng Li
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Correspondence to Habib Benali.

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Li, X., Messé, A., Marrelec, G. et al. An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer’s disease. Neuroradiology 52, 203–213 (2010). https://doi.org/10.1007/s00234-009-0600-1

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  • DOI: https://doi.org/10.1007/s00234-009-0600-1

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