Voxel-based morphometry to discriminate early Alzheimer's disease from controls

University of Tsukuba, Tsukuba, Ibaraki, Japan
Neuroscience Letters (Impact Factor: 2.03). 08/2005; 382(3):269-74. DOI: 10.1016/j.neulet.2005.03.038
Source: PubMed


We assessed the accuracy of voxel-based morphometry (VBM) using a three-dimensional T1-weighted MRI in discriminating Alzheimer's disease (AD) in the very early stage of amnestic type of mild cognitive impairment and age-matched healthy controls. We randomly divided these subjects into two groups. The first group comprising 30 AD patients and 41 controls was used to identify the area with the most significant gray matter loss in patients compared to normal controls based on the voxel-based analysis of a group comparison. The second group comprising 31 patients and 41 controls was used to determine the discrimination accuracy of VBM. A Z-score map for a gray matter image of a subject was obtained by comparison with mean and standard deviation gray matter images of the controls for each voxel after anatomical standardization and voxel normalization to global mean using the following equation; Z-score=([control mean]-[individual value])/(control S.D.). Receiver operating characteristic curves for a Z-score in the bilateral medial temporal areas including the entorhinal cortex with the most significant loss in the first group showed a high discrimination accuracy of 87.8%. This result would open up a possibility for early diagnosis of AD using VBM.


Available from: Kiyotaka Nemoto, Jul 02, 2015
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    • "Free software for this procedure, called VSRAD (voxel-based specific regional analysis system for Alzheimer's disease), has made it possible to estimate hippocampal atrophy easily and speedily. It has been reported that hippocampal atrophy as estimated by VSRAD was stronger in diabetic patients as compared with nondiabetic people, and the atrophy was associated with impaired cognitive function [9, 10] , in agreement with our recent cross-sectional study [11] . Therefore, we performed a 3-year longitudinal observation on brain atrophy as assessed with VSRAD in well-controlled elderly outpatients with type 2 diabetes in the present study. "
    [Show abstract] [Hide abstract] ABSTRACT: Background/Aims: We conducted a 3-year longitudinal study concerning factors associated with changes in brain atrophy in elderly diabetic patients. Methods: We evaluated hippocampal and global brain atrophy using automatic voxel-based morphometry of structural magnetic resonance images, 4 cognitive function tests, and cerebral small vessel disease (SVD) in 66 diabetic patients. Results: During the 3-year follow-up, hippocampal and global brain atrophy advanced, and cognitive functions worsened. For changes in hippocampal atrophy, changes in estimated glomerular filtration rate (eGFR), albuminuria, and being an ApoE ε4 carrier were independent factors; change in the number of silent brain infarctions was an independent factor for changes in global brain atrophy. A significant association of changes in eGFR and albuminuria with hippocampal atrophy remained after adjusting for confounders including SVD. Both types of brain atrophy at baseline were significantly correlated with cognitive impairment at baseline and especially associated with changes in delayed word recall during the follow-up after adjusting for confounders. Conclusion: Changes in eGFR and albuminuria during follow-up were independent risk factors for hippocampal atrophy, which was associated with decline in delayed word recall, suggesting that management of chronic kidney disease may prevent the progression of hippocampal atrophy.
    Full-text · Article · Feb 2016
    • "In more detail, VBM techniques investigate structural differences in areas with poorly defined structural landmarks (e.g., prefrontal areas) and provide explorative analysis of structural differences484950. Recently, VBM has been applied to detect early atrophic changes in AD[44,515253. It can provide statistical results for comparisons of patients with AD and HCs[44]. "
    [Show abstract] [Hide abstract] ABSTRACT: High-dimensional classification approaches have been widely used to investigate magnetic resonance imaging (MRI) data for automatic classification of Alzheimer’s disease (AD). This paper describes the use of t-test based feature-ranking approach as part of a novel feature selection procedure, where the number of top features is determined using the Fisher Criterion. The proposed classification system involves five systematic levels. First, voxel-based morphometry technique is used to compare the global and local differences of gray matter in patients with AD versus healthy controls (HCs). The significant local differences in gray matter volume are then selected as volumes of interests (VOIs). Second, the voxel clusters are employed as VOIs, where each voxel is considered to be a feature. Third, all the features are ranked using t-test scores. In this regard, the Fisher Criterion between the AD and HC groups is calculated for a changing number of ranked features, where the vector size maximizing the Fisher Criterion is selected as the optimal number of top discriminative features. Fourth, the classification is performed using support vector machine. Finally, data fusion methods among atrophy clusters are used to improve the classification performance. The experimental results indicate that the performance of the proposed system could compete well with the state-of-the-art techniques reported in the literature.
    No preview · Article · Dec 2015 · Magnetic Resonance Imaging
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    • "After full text screening, 38 articles were excluded for different reasons (Figure 1). Finally, 30 [7, articles published between 1995 and 2014 met the selection criteria and had accessible information concerning grey matter changes between AD and HC. The clinical and demographic data of participants in all included studies are presented inTable 1 . "
    [Show abstract] [Hide abstract] ABSTRACT: Voxel-based morphometry (VBM) using structural brain MRI has been widely used for the assessment of impairment in Alzheimer's disease (AD), but previous studies in VBM studies on AD remain inconsistent. We conducted meta-analyses to integrate the reported studies to determine the consistent grey matter alterations in AD based on VBM method. The PubMed, ISI Web of Science, EMBASE and Medline database were searched for articles between 1995 and June 2014. Manual searches were also conducted, and authors of studies were contacted for additional data. Coordinates were extracted from clusters with significant grey matter difference between AD patients and healthy controls (HC). Meta-analysis was performed using a new improved voxel-based meta-analytic method, Effect Size Signed Differential Mapping (ES-SDM). Thirty data-sets comprising 960 subjects with AD and 1195 HC met inclusion criteria. Grey matter volume (GMV) reduction at 334 coordinates in AD and no GMV increase were found in the current meta-analysis. Significant reductions in GMV were robustly localized in the limbic regions (left parahippocampl gyrus and left posterior cingulate gyrus). In addition, there were GM decreases in right fusiform gyrus and right superior frontal gyrus. The findings remain largely unchanged in the jackknife sensitivity analyses. Our meta-analysis clearly identified GMV atrophy in AD. These findings confirm that the most prominent and replicable structural abnormalities in AD are in the limbic regions and contributes to the understanding of pathophysiology underlying AD.
    Full-text · Article · Dec 2015 · Translational Neurodegeneration
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