@article{07d6757918b14254a09d166c19bf590c,
title = "Longitudinal stability of MRI for mapping brain change using tensor-based morphometry",
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.",
author = "Leow, {Alex D.} and Klunder, {Andrea D.} and Jack, {Clifford R.} and Toga, {Arthur W.} and Dale, {Anders M.} and Bernstein, {Matt A.} and Britson, {Paula J.} and Gunter, {Jeffrey L.} and Ward, {Chadwick P.} and Whitwell, {Jennifer L.} and Borowski, {Bret J.} and Fleisher, {Adam S.} and Fox, {Nick C.} and Danielle Harvey and John Kornak and Norbert Schuff and Colin Studholme and Alexander, {Gene E.} and Weiner, {Michael W.} and Thompson, {Paul M.}",
note = "Funding Information: This project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI; Principal Investigator: Michael Weiner; NIH grant number U01 AG024904). ADNI is funded by the National Institute of Aging, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and the Foundation for the National Institutes of Health, through generous contributions from the following companies and organizations: Pfizer Inc., Wyeth Research, Bristol-Myers Squibb, Eli Lilly and Company, GlaxoSmithKline, Merck & Co. Inc., AstraZeneca AB, Novartis Pharmaceuticals Corporation, the Alzheimer's Association, Eisai Global Clinical Development, Elan Corporation plc, Forest Laboratories and the Institute for the Study of Aging (ISOA), with participation from the U.S. Food and Drug Administration. The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. Algorithm development for this study was also funded by the NIA, NIBIB, the National Library of Medicine and the National Center for Research Resources (AG016570, EB01651, LM05639, RR019771 to PT). Author contributions were as follows: AL, AK and PT performed the image analyses and CJ and MW designed the overall evaluation of serial MRI reproducibility as part of the preparatory imaging phase of ADNI. AT, AD, MB, PB, JG, CW, JW, BB, NF, DH, JK, NS, CS and GA assisted with the image acquisition, design of the study, quality control, pre-processing, analysis and databasing, and AF recruited subjects at UCSD. We also acknowledge the help of Heidi A. Ward, Ph.D. (GE Healthcare) in investigating IR-SPGR image quality.",
year = "2006",
month = jun,
doi = "10.1016/j.neuroimage.2005.12.013",
language = "English (US)",
volume = "31",
pages = "627--640",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",
number = "2",
}