Longitudinal stability of MRI for mapping brain change using tensor-based morphometry

Alex D. Leow, Andrea D. Klunder, Clifford R Jr. Jack, Arthur W. Toga, Anders M. Dale, Matthew A Bernstein, Paula J. Britson, Jeffrey L. Gunter, Chadwick P. Ward, Jennifer Lynn Whitwell, Bret J. Borowski, Adam S. Fleisher, Nick C. Fox, Danielle Harvey, John Kornak, Norbert Schuff, Colin Studholme, Gene E. Alexander, Michael W. Weiner, Paul M. Thompson

Research output: Contribution to journalArticle

163 Citations (Scopus)

Abstract

Measures of brain change can be computed from sequential MRI scans, providing valuable information on disease progression, e.g., for patient monitoring and drug trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy, but its sensitivity depends on the contrast and geometric stability of the images. As part of the Alzheimer's Disease Neuroimaging Initiative (ADNI), 17 normal elderly subjects were scanned twice (at a 2-week interval) with several 3D 1.5 T MRI pulse sequences: high and low flip angle SPGR/FLASH (from which Synthetic T1 images were generated), MP-RAGE, IR-SPGR (N = 10) and MEDIC (N = 7) scans. For each subject and scan type, a 3D deformation map aligned baseline and follow-up scans, computed with a nonlinear, inverse-consistent elastic registration algorithm. Voxelwise statistics, in ICBM stereotaxic space, visualized the profile of mean absolute change and its cross-subject variance; these maps were then compared using permutation testing. Image stability depended on: (1) the pulse sequence; (2) the transmit/receive coil type (birdcage versus phased array); (3) spatial distortion corrections (using MEDIC sequence information); (4) B1-field intensity inhomogeneity correction (using N3). SPGR/FLASH images acquired using a birdcage coil had least overall deviation. N3 correction reduced coil type and pulse sequence differences and improved scan reproducibility, except for Synthetic T1 images (which were intrinsically corrected for B1-inhomogeneity). No strong evidence favored B0 correction. Although SPGR/FLASH images showed least deviation here, pulse sequence selection for the ADNI project was based on multiple additional image analyses, to be reported elsewhere.

Original languageEnglish (US)
Pages (from-to)627-640
Number of pages14
JournalNeuroImage
Volume31
Issue number2
DOIs
StatePublished - Jun 2006

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Brain Mapping
Neuroimaging
Alzheimer Disease
Brain
Physiologic Monitoring
Atrophy
Disease Progression
Magnetic Resonance Imaging
Growth
Pharmaceutical Preparations

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

Cite this

Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. / Leow, Alex D.; Klunder, Andrea D.; Jack, Clifford R Jr.; Toga, Arthur W.; Dale, Anders M.; Bernstein, Matthew A; Britson, Paula J.; Gunter, Jeffrey L.; Ward, Chadwick P.; Whitwell, Jennifer Lynn; Borowski, Bret J.; Fleisher, Adam S.; Fox, Nick C.; Harvey, Danielle; Kornak, John; Schuff, Norbert; Studholme, Colin; Alexander, Gene E.; Weiner, Michael W.; Thompson, Paul M.

In: NeuroImage, Vol. 31, No. 2, 06.2006, p. 627-640.

Research output: Contribution to journalArticle

Leow, AD, Klunder, AD, Jack, CRJ, Toga, AW, Dale, AM, Bernstein, MA, Britson, PJ, Gunter, JL, Ward, CP, Whitwell, JL, Borowski, BJ, Fleisher, AS, Fox, NC, Harvey, D, Kornak, J, Schuff, N, Studholme, C, Alexander, GE, Weiner, MW & Thompson, PM 2006, 'Longitudinal stability of MRI for mapping brain change using tensor-based morphometry', NeuroImage, vol. 31, no. 2, pp. 627-640. https://doi.org/10.1016/j.neuroimage.2005.12.013
Leow, Alex D. ; Klunder, Andrea D. ; Jack, Clifford R Jr. ; Toga, Arthur W. ; Dale, Anders M. ; Bernstein, Matthew A ; Britson, Paula J. ; Gunter, Jeffrey L. ; Ward, Chadwick P. ; Whitwell, Jennifer Lynn ; Borowski, Bret J. ; Fleisher, Adam S. ; Fox, Nick C. ; Harvey, Danielle ; Kornak, John ; Schuff, Norbert ; Studholme, Colin ; Alexander, Gene E. ; Weiner, Michael W. ; Thompson, Paul M. / Longitudinal stability of MRI for mapping brain change using tensor-based morphometry. In: NeuroImage. 2006 ; Vol. 31, No. 2. pp. 627-640.
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