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. 2008 Dec;28(6):1345-50.
doi: 10.1002/jmri.21604.

Age-related non-Gaussian diffusion patterns in the prefrontal brain

Affiliations

Age-related non-Gaussian diffusion patterns in the prefrontal brain

Maria F Falangola et al. J Magn Reson Imaging. 2008 Dec.

Abstract

Purpose: To characterize age-related MR diffusion patterns of the prefrontal brain cortex microstructure using a new method for investigating the non-Gaussian behavior of water diffusion called diffusional kurtosis imaging (DKI).

Materials and methods: Measures of mean diffusivity (MD), fractional anisotropy (FA) and mean kurtosis (MK) were compared in the prefrontal brain cortex of 24 healthy volunteers (adolescents, young adults, and elderly) ranging from age 13 to 85 years. A Mann-Whitney test was used to compare subject groups with respect to the diffusion measures, and linear regression was used to characterize the change in each diffusion measure as a function of age.

Results: We found significant age-related changes in the elderly adult group, with increase of MD and decrease of FA.

Conclusion: The current study demonstrates distinct mean kurtosis patterns for different age-ranges, with significant age-related correlation for mean kurtosis (MK) and MK peak position, showing that diffusional kurtosis is able to characterize and measure age-related diffusion changes for both grey and white matter, in the developing and aging brain.

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Figures

Figure 1
Figure 1
Prefrontal ROIs superimposed on each of the five DKI axial slices. Note that the ROI extended from the most anterior point containing brain tissue to the dorsal border of the genu of the corpus callosum (gCC), and included gray matter, white matter and CSF.
Figure 2
Figure 2
A–C: Histograms from the prefrontal brain for FA (A), MD (B), and MK (C) for the adolescent (dashed lines), Adult (dotted lines) and Elderly (solid lines) age groups. D–H: Scatter plot of mean FA (D), MD (E), MK (F), MK-Grey (G), and MK-White (H) matter peak location versus age and the regression function to predict each measure as a piecewise linear function of age with a knots at ages 18 and 47. Adolescent (●); Adults (■); Elderly (▲).

References

    1. Brody H. The aging brain. Acta Neurol Scand. 1992;137:40–44. review. - PubMed
    1. Guttmann CR, Jolesz FA, Kikinis R, et al. White matter changes with normal aging. Neurology. 1998;50:972–978. - PubMed
    1. Miller AK, Alston RL, Corsellis JA. Variation with age in the volumes of grey and white matter in the cerebral hemispheres of man: measurements with an image analyser. Neuropathol Appl Neurobiol. 1980;6:119–132. - PubMed
    1. Raz N, Rodrigue KM. Differential aging of the brain: patterns, cognitive correlates and modifiers. Neurosci Biobehav Rev. 2006;30:730–748. review. - PMC - PubMed
    1. Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage. 2001;14:21–36. - PubMed

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