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Biexponential Diffusion Tensor Analysis of Human Brain Diffusion DataS. E. Maier, S. Vajapeyam, H. Mamata, C.-F. Westin, F. A. Jolesz, R. V. MulkernMagnetic Resonance in Medicine Volume 51, Pages 321-330 2004 AbstractSeveral studies have shown that in tissues over an extended range of b-factors, the signal decay deviates significantly from the basic monoexponential model. The true nature of this departure has to date not been identified. For the current study, line scan diffusion images of brain suitable for biexponential diffusion tensor analysis were acquired in normal subjects on a clinical MR system. For each of six noncollinear directions, 32 images with b-factors ranging from 5 to 5000 s/mm 2 were collected. Biexponential fits yielded parameter maps for a fast and a slow diffusion component. A subset of the diffusion data, consisting of the images obtained at the conventional range of b-factors between 5 and 972 s/mm 2, was used for monoexponential diffusion tensor analysis. Fractional anisotropy (FA) of the fast-diffusion component and the monoexponential fit exhibited no significant difference. FA of the slow-diffusion biexponential component was significantly higher, particularly in areas of lower fiber density. The principal diffusion directions for the two biexponential components and the monoexponential solution were largely the same and in agreement with known fiber tracts. The second and third diffusion eigenvector directions also appeared to be aligned, but they exhibited significant deviations in localized areas.
ReferenceMaier SE, Vajapeyam S, Mamata H, Westin CF, Jolesz FA, Mulkern RV. Biexponential diffusion tensor analysis of human brain diffusion data. Magnetic Resonance in Medicine 2004;51:321-330.Bibtex entry
@Article{maierMRM04,
author = {S. E. Maier and S. Vajapeyam and H. Mamata and C.-F. Westin
and F. A. Jolesz and R. V. Mulkern},
title = {Biexponential Diffusion Tensor Analysis of Human Brain
Diffusion Data},
volume = {51},
pages = {321--330},
journal = {Magnetic Resonance in Medicine},
year = 2004}
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