Regional brain axial and radial diffusivity changes during development - PubMed (original) (raw)

Comparative Study

Regional brain axial and radial diffusivity changes during development

Rajesh Kumar et al. J Neurosci Res. 2012 Feb.

Abstract

The developing human brain shows rapid myelination and axonal changes during childhood, adolescence, and early adulthood, requiring successive evaluations to determine normative values for potential pathological assessment. Fiber characteristics can be examined by axial and radial diffusivity procedures, which measure water diffusion parallel and perpendicular to axons and show primarily axonal status and myelin changes, respectively. Such measures are lacking from widespread sites for the developing brain. Diffusion tensor imaging data were acquired from 30 healthy subjects (age 17.7 ± 4.6 years, range 8-24 years, body mass index 21.5 ± 4.5 kg/m(2), 18 males) using a 3.0-Tesla MRI scanner. Diffusion tensors were calculated, principal eigenvalues determined, and axial and radial diffusivity maps calculated and normalized to a common space. A set of regions of interest was outlined from widespread brain areas within rostral, thalamic, hypothalamic, cerebellar, and pontine regions, and average diffusivity values were calculated using normalized diffusivity maps and these regions of interest masks. Age-related changes were assessed with Pearson's correlations, and gender differences evaluated with Student's t-tests. Axial and radial diffusivity values declined with age in the majority of brain areas, except for midhippocampus, where axial diffusivity values correlated positively with age. Gender differences emerged within putamen, thalamic, hypothalamic, cerebellar, limbic, temporal, and other cortical sites. Documentation of normal axial and radial diffusivity values will help assess disease-related tissue changes. Axial and radial diffusivities change with age,with fiber structure and organization differing between sexes in several brain areas. The findings may underlie gender-based functional characteristics, and mandate partitioning age- and gender-related changes during developmental brain pathology evaluation.

Copyright © 2011 Wiley Periodicals, Inc.

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Figures

Fig. 1

Fig. 1

Mean background images, derived from normalized and averaged b0 images of all individuals, with regions-of-interest (ROIs). The rectangular ROIs were used to calculate regional axial and radial diffusivity values, which are shown only for the left side on background images for clarity. 1, frontal white matter; 2, anterior cingulate; 3, caudate nucleus; 4, anterior insula; 5, mid insula; 6, posterior insula; 7, midline occipital gray matter; 8, globus pallidus; 9, anterior thalamus; 10, mid thalamus; 11, posterior thalamus; 12, occipital white matter; 13, putamen; 14, frontal gray matter; 15, ventral hippocampus; 16, mid hippocampus; 17, dorsal hippocampus; 18, amygdala; 19, ventral temporal white matter; 20, mid temporal white matter; 21, dorsal temporal white matter; 22, anterior corpus callosum; 23, mid corpus callosum; 24, posterior corpus callosum; 25, caudal pons; 26, mid pons; 27, ventral pons; 28, mid cingulate; 29, posterior cingulate; 30, hypothalamus; 31, superior cerebellar peduncle; 32, mid cerebellar peduncle; 33, inferior cerebellar peduncle; 34 cerebellar deep nuclei; 35, caudal cerebellar cortex; 36, rostral cerebellar cortex.

Fig. 2

Fig. 2

Correlations between combined, and separately, male, and female axial and radial diffusivity values, derived from multiple rostral brain sites, and age. Corresponding sold and dotted lines on the scatter plots display best fit lines for the combined, male, and female data.

Fig. 3

Fig. 3

Rostral brain sites showing correlations between combined, male, and female axial and radial diffusivity values and age. Figure conventions are the same as in Fig. 2.

Fig. 4

Fig. 4

Thalamic, pontine, and cerebellar regions showing correlations between combined, male, and female, axial and radial diffusivity values and age. Figure conventions are the same as in Fig. 2.

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