BACKGROUND AND PURPOSE: Diffusional kurtosis imaging is an extension of DTI but includes non-Gaussian diffusion effects, allowing more comprehensive characterization of microstructural changes during brain development. Our purpose was to use diffusional kurtosis imaging to measure age-related microstructural changes in both the WM and GM of the developing human brain. MATERIALS AND METHODS: Diffusional kurtosis imaging was performed in 59 subjects ranging from birth to 4 years 7 months of age. Diffusion metrics, fractional anisotropy, and mean kurtosis were collected from VOIs within multiple WM and GM structures and subsequently analyzed with respect to age. Diffusional kurtosis tractography images at various stages of development were also generated. RESULTS: Fractional anisotropy and mean kurtosis both showed age-related increases in all WM regions, reflecting progression of diffusional anisotropy throughout development, predominantly in the first 2 years of life (eg, 70% and 157% increase in fractional anisotropy and mean kurtosis, respectively, from birth to 2 years for the splenium). However, mean kurtosis detected continued microstructural changes in WM past the fractional anisotropy plateau, accounting for more delayed isotropic changes (eg, 90% of maximum fractional anisotropy was reached at 5 months, whereas 90% of maximum mean kurtosis occurred at 18 months for the external capsule). Mean kurtosis may also provide greater characterization of GM maturation (eg, the putamen showed no change in fractional anisotropy but an 81% change in mean kurtosis from birth to 4 years 7 months). CONCLUSIONS: Mean kurtosis detects significant microstructural changes consistent with known patterns of brain maturation. In comparison with fractional anisotropy, mean kurtosis may offer a more comprehensive evaluation of age-related microstructural changes in both WM and GM and is potentially a valuable technique for studying brain development.
BACKGROUND AND PURPOSE: Diffusional kurtosis imaging is an extension of DTI but includes non-Gaussian diffusion effects, allowing more comprehensive characterization of microstructural changes during brain development. Our purpose was to use diffusional kurtosis imaging to measure age-related microstructural changes in both the WM and GM of the developing human brain. MATERIALS AND METHODS: Diffusional kurtosis imaging was performed in 59 subjects ranging from birth to 4 years 7 months of age. Diffusion metrics, fractional anisotropy, and mean kurtosis were collected from VOIs within multiple WM and GM structures and subsequently analyzed with respect to age. Diffusional kurtosis tractography images at various stages of development were also generated. RESULTS: Fractional anisotropy and mean kurtosis both showed age-related increases in all WM regions, reflecting progression of diffusional anisotropy throughout development, predominantly in the first 2 years of life (eg, 70% and 157% increase in fractional anisotropy and mean kurtosis, respectively, from birth to 2 years for the splenium). However, mean kurtosis detected continued microstructural changes in WM past the fractional anisotropy plateau, accounting for more delayed isotropic changes (eg, 90% of maximum fractional anisotropy was reached at 5 months, whereas 90% of maximum mean kurtosis occurred at 18 months for the external capsule). Mean kurtosis may also provide greater characterization of GM maturation (eg, the putamen showed no change in fractional anisotropy but an 81% change in mean kurtosis from birth to 4 years 7 months). CONCLUSIONS: Mean kurtosis detects significant microstructural changes consistent with known patterns of brain maturation. In comparison with fractional anisotropy, mean kurtosis may offer a more comprehensive evaluation of age-related microstructural changes in both WM and GM and is potentially a valuable technique for studying brain development.
Authors: Pratik Mukherjee; Jeffrey H Miller; Joshua S Shimony; Joseph V Philip; Deepika Nehra; Abraham Z Snyder; Thomas E Conturo; Jeffrey J Neil; Robert C McKinstry Journal: AJNR Am J Neuroradiol Date: 2002-10 Impact factor: 3.825
Authors: Melissa A Lancaster; Daniel V Olson; Michael A McCrea; Lindsay D Nelson; Ashley A LaRoche; L Tugan Muftuler Journal: Hum Brain Mapp Date: 2016-11 Impact factor: 5.038
Authors: Ileana O Jelescu; Jelle Veraart; Vitria Adisetiyo; Sarah S Milla; Dmitry S Novikov; Els Fieremans Journal: Neuroimage Date: 2014-12-09 Impact factor: 6.556
Authors: C Guglielmetti; J Veraart; E Roelant; Z Mai; J Daans; J Van Audekerke; M Naeyaert; G Vanhoutte; R Delgado Y Palacios; J Praet; E Fieremans; P Ponsaerts; J Sijbers; A Van der Linden; M Verhoye Journal: Neuroimage Date: 2015-10-23 Impact factor: 6.556