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Cited by 360

The DOI matches its Crossref record; 101 of the 101 references it cites were found in a registry or an index.

Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects

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Hua, Xue, Leow, Alex D., Parikshak, Neelroop, Lee, Suh, Chiang, Ming-Chang, Toga, Arthur W., Jack, Clifford R., Weiner, Michael W., Thompson, Paul M.·2008·NeuroImage

Abstract

In one of the largest brain MRI studies to date, we used tensor-based morphometry (TBM) to create 3D maps of structural atrophy in 676 subjects with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and healthy elderly controls, scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using inverse-consistent 3D non-linear elastic image registration, we warped 676 individual brain MRI volumes to a population mean geometric template. Jacobian determinant maps were created, revealing the 3D profile of local volumetric expansion and compression. We compared the anatomical distribution of atrophy in 165 AD patients (age: 75.6 ± 7.6 years), 330 MCI subjects (74.8 ± 7.5), and 181 controls (75.9 ± 5.1). Brain atrophy in selected regions-of-interest was correlated with clinical measurements - the sum-of-boxes clinical dementia rating (CDR-SB), mini-mental state examination (MMSE), and the logical memory test scores - at voxel level followed by correction for multiple comparisons. Baseline temporal lobe atrophy correlated with current cognitive performance, future cognitive decline, and conversion from MCI to AD over the following year; it predicted future decline even in healthy subjects. Over half of the AD and MCI subjects carried the ApoE4 (apolipoprotein E4) gene, which increases risk for AD; they showed greater hippocampal and temporal lobe deficits than non-carriers. ApoE2 gene carriers - 1/6 of the normal group - showed reduced ventricular expansion, suggesting a protective effect. As an automated image analysis technique, TBM reveals 3D correlations between neuroimaging markers, genes, and future clinical changes, and is highly efficient for large-scale MRI studies.

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Metadata

Authors
Hua, X., Leow, A. D., Parikshak, N., Lee, S., Chiang, M.-C., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2008-11
Volume
43
Issue
3
Pages
458-469
ISSN
1053-8119 (ISSN-L)
OpenAlex
W1973637437
Cited by
360
References
101
FWCI
21.10
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects. https://app.cochat.ai/papers/10.1016/j.neuroimage.2008.07.013
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Hua, X., Leow, A. D., Parikshak, N., Lee, S., Chiang, M.-C., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2008). Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects. NeuroImage. https://doi.org/10.1016/j.neuroimage.2008.07.013

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