3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry

Xue Hua, Alex D. Leow, Suh Lee, Andrea D. Klunder, Arthur W. Toga, Natasha Lepore, Yi Yu Chou, Caroline Brun, Ming Chang Chiang, Marina Barysheva, Clifford R. Jack, Matt A. Bernstein, Paula J. Britson, Chadwick P. Ward, Jennifer L. Whitwell, Bret Borowski, Adam S. Fleisher, Nick C. Fox, Richard G. Boyes, Josephine BarnesDanielle J Harvey, John Kornak, Norbert Schuff, Lauren Boreta, Gene E. Alexander, Michael W. Weiner, Paul M. Thompson, Alzheimer's Disease Neuroimaging Initiative the Alzheimer's Disease Neuroimaging Initiative

Research output: Contribution to journalArticle

138 Scopus citations

Abstract

Tensor-based morphometry (TBM) creates three-dimensional maps of disease-related differences in brain structure, based on nonlinearly registering brain MRI scans to a common image template. Using two different TBM designs (averaging individual differences versus aligning group average templates), we compared the anatomical distribution of brain atrophy in 40 patients with Alzheimer's disease (AD), 40 healthy elderly controls, and 40 individuals with amnestic mild cognitive impairment (aMCI), a condition conferring increased risk for AD. We created an unbiased geometrical average image template for each of the three groups, which were matched for sex and age (mean age: 76.1 years+/- 7.7 SD). We warped each individual brain image (N = 120) to the control group average template to create Jacobian maps, which show the local expansion or compression factor at each point in the image, reflecting individual volumetric differences. Statistical maps of group differences revealed widespread medial temporal and limbic atrophy in AD, with a lesser, more restricted distribution in MCI. Atrophy and CSF space expansion both correlated strongly with Mini-Mental State Exam (MMSE) scores and Clinical Dementia Rating (CDR). Using cumulative p-value plots, we investigated how detection sensitivity was influenced by the sample size, the choice of search region (whole brain, temporal lobe, hippocampus), the initial linear registration method (9- versus 12-parameter), and the type of TBM design. In the future, TBM may help to (1) identify factors that resist or accelerate the disease process, and (2) measure disease burden in treatment trials.

Original languageEnglish (US)
Pages (from-to)19-34
Number of pages16
JournalNeuroImage
Volume41
Issue number1
DOIs
StatePublished - May 15 2008

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

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    Hua, X., Leow, A. D., Lee, S., Klunder, A. D., Toga, A. W., Lepore, N., Chou, Y. Y., Brun, C., Chiang, M. C., Barysheva, M., Jack, C. R., Bernstein, M. A., Britson, P. J., Ward, C. P., Whitwell, J. L., Borowski, B., Fleisher, A. S., Fox, N. C., Boyes, R. G., ... the Alzheimer's Disease Neuroimaging Initiative, A. D. N. I. (2008). 3D characterization of brain atrophy in Alzheimer's disease and mild cognitive impairment using tensor-based morphometry. NeuroImage, 41(1), 19-34. https://doi.org/10.1016/j.neuroimage.2008.02.010