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

IntroductionWhen 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.MethodsTo 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.ResultsThe results show that eVBM can reduce the number of false-positive differences in gray matter concentration.ConclusionBecause 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.

[1]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[2]  Thomas E. Nichols,et al.  Controlling the familywise error rate in functional neuroimaging: a comparative review , 2003, Statistical methods in medical research.

[3]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[4]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[5]  J. Baron,et al.  In Vivo Mapping of Gray Matter Loss with Voxel-Based Morphometry in Mild Alzheimer's Disease , 2001, NeuroImage.

[6]  J. Morris.  The Clinical Dementia Rating (CDR) , 1993, Neurology.

[7]  Guy B. Williams,et al.  The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry , 2008, NeuroImage.

[8]  Nick C Fox,et al.  Mapping the evolution of regional atrophy in Alzheimer's disease: Unbiased analysis of fluid-registered serial MRI , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[9]  John G. Csernansky,et al.  Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults , 2007, Journal of Cognitive Neuroscience.

[10]  平田 容子,et al.  Voxel-based morphometry to discriminate early Alzheimer's disease from controls , 2007 .

[11]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[12]  Emma J. Burton,et al.  A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxel-based morphometry , 2003, NeuroImage.

[13]  Stephen M. Smith,et al.  Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference , 2009, NeuroImage.

[14]  D. Bennett,et al.  MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease☆ ☆ This research was supported by grants P01 AG09466 and P30 AG10161 from the National Institute on Aging, National Institutes of Health. , 2001, Neurobiology of Aging.

[15]  J. Helpern,et al.  Quantitative MR imaging in Alzheimer disease. , 2006, Radiology.

[16]  Karl J. Friston,et al.  Voxel-based morphometry of the human brain: Methods and applications , 2005 .

[17]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[18]  Florence Rémy,et al.  Verbal episodic memory impairment in Alzheimer's disease: a combined structural and functional MRI study , 2005, NeuroImage.

[19]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[20]  M. Jenkinson.  Non-linear registration aka Spatial normalisation , 2007 .

[21]  Fred L. Bookstein,et al.  “Voxel-Based Morphometry” Should Not Be Used with Imperfectly Registered Images , 2001, NeuroImage.

[22]  N. Schuff,et al.  Comparison of methods for measuring longitudinal brain change in cognitive impairment and dementia , 2003, Neurobiology of Aging.

[23]  Karl J. Friston,et al.  Voxel-Based Morphometry , 2015 .

[24]  Karl J. Friston,et al.  Why Voxel-Based Morphometry Should Be Used , 2001, NeuroImage.

[25]  F. Fazio,et al.  Role of Integrated 18-F FDG PET/CT in Recurrent Ovarian Cancer , 2005 .

[26]  J. Baron,et al.  Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment , 2002, Neuroreport.

[27]  E. Macaluso,et al.  Episodic memory impairment in patients with Alzheimer’s disease is correlated with entorhinal cortex atrophy , 2007, Journal of Neurology.

[28]  Eini Niskanen,et al.  Voxel-based morphometry to detect brain atrophy in progressive mild cognitive impairment , 2007, NeuroImage.

[29]  Kiralee M. Hayashi,et al.  Dynamics of Gray Matter Loss in Alzheimer's Disease , 2003, The Journal of Neuroscience.

[30]  F. Collette,et al.  Alzheimer' Disease as a Disconnection Syndrome? , 2003, Neuropsychology Review.

[31]  D. Louis Collins,et al.  Sensitivity of voxel-based morphometry analysis to choice of imaging protocol at 3 T , 2009, NeuroImage.

[32]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[33]  Karl J. Friston,et al.  A Voxel-Based Method for the Statistical Analysis of Gray and White Matter Density Applied to Schizophrenia , 1995, NeuroImage.

[34]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[35]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[36]  Vince D. Calhoun,et al.  Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer's Disease: An Independent Component Analysis , 2006, The Journal of Neuroscience.

[37]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[38]  Karl J. Friston,et al.  A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains , 2001, NeuroImage.

[39]  G. Frisoni,et al.  Detection of grey matter loss in mild Alzheimer's disease with voxel based morphometry , 2002, Journal of neurology, neurosurgery, and psychiatry.