Neurite density index is sensitive to age related differences in the developing brain

神经突 索引(排版) 神经科学 生物 计算机科学 万维网 遗传学 体外
作者
Sila Genc,Charles B. Malpas,Scott K. Holland,Richard Beare,Timothy J. Silk
出处
期刊:NeuroImage [Elsevier]
卷期号:148: 373-380 被引量:132
标识
DOI:10.1016/j.neuroimage.2017.01.023
摘要

White matter development during childhood and adolescence is characterised by increasing white matter coherence and organisation. Commonly used scalar metrics, such as fractional anisotropy (FA), are sensitive to multiple mechanisms of white matter change and therefore unable to distinguish between mechanisms that change during development. We investigate the relationship between age and neurite density index (NDI) from neurite orientation dispersion and density imaging (NODDI), and the age-classification accuracy of NDI compared with FA, in a developmental cohort. Diffusion-weighted imaging data from 72 children and adolescents between the ages of 4–19 was collected (M=10.42, SD=3.99, 36 male). We compared NODDI metrics against conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD] and radial diffusivity [RD]) in terms of their relationship to age. An ROC analysis was also performed to assess the ability of each metric to classify older and younger participants. NDI exhibited a stronger relationship with age (median R2=.60) compared with MD (median R2=.39), FA (median R2=.27), AD (median R2=.14), and RD (median R2=.35) in a high proportion of white matter tracts. When participants were divided into an older and younger group, NDI achieved the best classification (median area under the curve [AUC]=.89), followed by MD (median AUC=.81), FA (median AUC=.80), RD (median AUC=.81), and AD (median AUC=.64). Our results demonstrate the sensitivity of NDI to age-related differences in white matter microstructural organisation over development. Importantly, NDI is more sensitive to such developmental changes compared to commonly used DTI metrics. This knowledge provides justification for implementing NODDI metrics in developmental studies.
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