In this study we used γ-metrics, derived from anomalous diffusion signal representation, as well as DTI, NODDI, DKI derived parameters to assess physiological (i.e. the iron content) and microstructural (myelin damage, axonal disintegration, neuron cell loss) modifications in cerebral WM and scGM of middle- and older-aged subjects. We found that γ-metrics are remarkably sensitive and provide complementary information compared to DTI-metrics, MK and NODDI to detect modifications in frontal WM, where substantial changes are expected with aging. Also, the combined use of these techniques may unravel different patterns of modifications of the ageing brain.
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