Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: An ADNI study of 515 subjects

Xue Hua, Suh Lee, Igor Yanovsky, Alex D. Leow, Yi Yu Chou, April J. Ho, Boris Gutman, Arthur W. Toga, Clifford R. Jack, Matt A. Bernstein, Eric M. Reiman, Danielle J. Harvey, John Kornak, Norbert Schuff, Gene E Alexander, Michael W. Weiner, Paul M. Thompson

Research output: Contribution to journalArticle

105 Citations (Scopus)

Abstract

Tensor-based morphometry (TBM) is a powerful method to map the 3D profile of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We optimized a TBM-based image analysis method to determine what methodological factors, and which image-derived measures, maximize statistical power to track brain change. 3D maps, tracking rates of structural atrophy over time, were created from 1030 longitudinal brain MRI scans (1-year follow-up) of 104 AD patients (age: 75.7 ± 7.2 years; MMSE: 23.3 ± 1.8, at baseline), 254 amnestic MCI subjects (75.0 ± 7.2 years; 27.0 ± 1.8), and 157 healthy elderly subjects (75.9 ± 5.1 years; 29.1 ± 1.0), as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). To determine which TBM designs gave greatest statistical power, we compared different linear and nonlinear registration parameters (including different regularization functions), and different numerical summary measures derived from the maps. Detection power was greatly enhanced by summarizing changes in a statistically-defined region-of-interest (ROI) derived from an independent training sample of 22 AD patients. Effect sizes were compared using cumulative distribution function (CDF) plots and false discovery rate methods. In power analyses, the best method required only 48 AD and 88 MCI subjects to give 80% power to detect a 25% reduction in the mean annual change using a two-sided test (at α = 0.05). This is a drastic sample size reduction relative to using clinical scores as outcome measures (619 AD/6797 MCI for the ADAS-Cog, and 408 AD/796 MCI for the Clinical Dementia Rating sum-of-boxes scores). TBM offers high statistical power to track brain changes in large, multi-site neuroimaging studies and clinical trials of AD.

Original languageEnglish (US)
Pages (from-to)668-681
Number of pages14
JournalNeuroImage
Volume48
Issue number4
DOIs
StatePublished - Dec 2009
Externally publishedYes

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Neuroimaging
Alzheimer Disease
Brain
Cognitive Dysfunction
Power (Psychology)
Sample Size
Atrophy
Dementia
Healthy Volunteers
Magnetic Resonance Imaging
Outcome Assessment (Health Care)
Clinical Trials

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

Cite this

Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry : An ADNI study of 515 subjects. / Hua, Xue; Lee, Suh; Yanovsky, Igor; Leow, Alex D.; Chou, Yi Yu; Ho, April J.; Gutman, Boris; Toga, Arthur W.; Jack, Clifford R.; Bernstein, Matt A.; Reiman, Eric M.; Harvey, Danielle J.; Kornak, John; Schuff, Norbert; Alexander, Gene E; Weiner, Michael W.; Thompson, Paul M.

In: NeuroImage, Vol. 48, No. 4, 12.2009, p. 668-681.

Research output: Contribution to journalArticle

Hua, X, Lee, S, Yanovsky, I, Leow, AD, Chou, YY, Ho, AJ, Gutman, B, Toga, AW, Jack, CR, Bernstein, MA, Reiman, EM, Harvey, DJ, Kornak, J, Schuff, N, Alexander, GE, Weiner, MW & Thompson, PM 2009, 'Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: An ADNI study of 515 subjects', NeuroImage, vol. 48, no. 4, pp. 668-681. https://doi.org/10.1016/j.neuroimage.2009.07.011
Hua, Xue ; Lee, Suh ; Yanovsky, Igor ; Leow, Alex D. ; Chou, Yi Yu ; Ho, April J. ; Gutman, Boris ; Toga, Arthur W. ; Jack, Clifford R. ; Bernstein, Matt A. ; Reiman, Eric M. ; Harvey, Danielle J. ; Kornak, John ; Schuff, Norbert ; Alexander, Gene E ; Weiner, Michael W. ; Thompson, Paul M. / Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry : An ADNI study of 515 subjects. In: NeuroImage. 2009 ; Vol. 48, No. 4. pp. 668-681.
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