Regional segmentation strategy for DTI analysis of human corpus callosum indicates motor function deficit in mild cognitive impairment.

BACKGROUND: The corpus callosum is the largest white matter tract in the human brain, involved in inter-hemispheric transfer and integration of lateralised visual, sensory-motor, language, and cognitive information. Microstructural alterations are implicated in ageing as well as various neurological conditions. NEW METHOD: Cross-sectional diffusion-weighted images of 107 healthy adults were used to create a linear regression model of the ageing corpus callosum and its sub-regions to evaluate the impact of analysis by sub-region, and to test for deviations from healthy ageing parameters in 28 subjects with mild cognitive impairment (MCI). Alterations in diffusion properties including fractional anisotropy, mean, radial and axial diffusivities were investigated as a function of age. RESULTS: Changes in DTI parameters showed age-dependent regional differences, likely arising from axonal diameter variation across cross-sectional regions of interest in the corpus callosum. Patterns suggestive of degeneration with healthy ageing were observed in all regions. Diffusion parameters in sub-regions projecting to pre-motor, primary, and supplementary motor areas of the brain differed for MCI versus healthy controls, and MCI subjects were more likely than healthy controls to experience a reduction in motor skills. COMPARISON WITH EXISTING METHODS: Statistical analyses of the corpus callosum by five manually-defined sub-regions, instead of a single manually-defined region of interest, revealed region-specific changes in microstructure in healthy ageing and MCI, and accounted for clinically-evaluated differences in motor skills between cohorts. CONCLUSION: This method will support future studies of corpus callosum, enabling identification and measurement of white matter changes that are undetectable with the single ROI approach.

Synchrotron XRF imaging of Alzheimer's disease basal ganglia reveals linear dependence of high-field magnetic resonance microscopy on tissue iron concentration.

BACKGROUND: Chemical imaging of the human brain has great potential for diagnostic and monitoring purposes. The heterogeneity of human brain iron distribution, and alterations to this distribution in Alzheimer's disease, indicate iron as a potential endogenous marker. The influence of iron on certain magnetic resonance imaging (MRI) parameters increases with magnetic field, but is under-explored in human brain tissues above 7 T. NEW METHOD: Magnetic resonance microscopy at 9.4 T is used to calculate parametric images of chemically-unfixed post-mortem tissue from Alzheimer's cases (n = 3) and healthy controls (n = 2). Iron-rich regions including caudate nucleus, putamen, globus pallidus and substantia nigra are analysed prior to imaging of total iron distribution with synchrotron X-ray fluorescence mapping. Iron fluorescence calibration is achieved with adjacent tissue blocks, analysed by inductively coupled plasma mass spectrometry or graphite furnace atomic absorption spectroscopy. RESULTS: Correlated MR images and fluorescence maps indicate linear dependence of R2, R2* and R2' on iron at 9.4 T, for both disease and control, as follows: [R2(s-1) = 0.072[Fe] + 20]; [R2*(s-1) = 0.34[Fe] + 37]; [R2'(s-1) = 0.26[Fe] + 16] for Fe in µg/g tissue (wet weight). COMPARISON WITH EXISTING METHODS: This method permits simultaneous non-destructive imaging of most bioavailable elements. Iron is the focus of the present study as it offers strong scope for clinical evaluation; the approach may be used more widely to evaluate the impact of chemical elements on clinical imaging parameters. CONCLUSION: The results at 9.4 T are in excellent quantitative agreement with predictions from experiments performed at lower magnetic fields.