The structural correlates of functional deficits in early huntington's disease.

Neuropathological studies in Huntington disease (HD) have demonstrated neuronal loss in the striatum, as well as in other brain regions including the cortex. With diffusion tensor MRI we evaluated the hypothesis that the clinical dysfunction in HD is related to regionally specific lesions of circuit-specific cortico-basal ganglia networks rather than to the striatum only. We included 27 HD and 24 controls from the TRACK-HD Paris cohort. The following assessments were used: self-paced tapping tasks, trail B making test (TMT), University of Pennsylvania smell identification test (UPSIT), and apathy scores from the problem behaviors assessment. Group comparisons of fractional anisotropy and mean diffusivity and correlations were performed using voxel-based analysis. In the cortex, HD patients showed significant correlations between: (i) self paced tapping and mean diffusivity in the parietal lobe at 1.8 Hz and prefrontal areas at 3 Hz, (ii) UPSIT and mean diffusivity in the parietal, and median temporal lobes, the cingulum and the insula, and fractional anisotropy in the insula and the external capsule, (iii) TMT B and mean diffusivity in the white matter of the superior frontal, orbital, temporal, superior parietal and post central areas, and (iv) apathy and fractional anisotropy in the white matter of the rectus gyrus. In the basal ganglia, we found correlations between the self paced tapping, UPSIT, TMT tests, and mean diffusivity in the anterior part of the putamen and the caudate nucleus. In conclusion, disruption of motor, associative and limbic cortico-striatal circuits differentially contribute to the clinical signs of the disease.

Magnetic resonance imaging of the substantia nigra in Parkinson's disease.

Until recently, conventional magnetic resonance imaging (MRI) was most often negative in Parkinson's disease or showed nonspecific findings. Recent developments in structural MRI, including relaxometry, magnetization transfer, and neuromelanin imaging, have demonstrated improved contrast and enabled more accurate visualization of deep brain nuclei, in particular, the substantia nigra. Meanwhile, diffusion imaging has provided useful biomarkers of substantia nigra degeneration, showing reduced anisotropy and anatomical connectivity with the striatum and thalamus. These advances in structural imaging are complemented by findings of magnetic resonance spectroscopy on brain metabolism and resting-state functional MRI on functional connectivity. This article presents an overview of these new structural, metabolic, and resting-state functional MRI techniques and their implications for Parkinson's disease. The techniques are reviewed in the context of their potential for better understanding the disease in terms of diagnosis and pathophysiology and as biomarkers of its progression.

Impact of outliers on diffusion tensor and Q-ball imaging: clinical implications and correction strategies.

PURPOSE: To measure the impact of corrupted images often found to occur in diffusion-weighted magnetic resonance imaging (DW-MRI). To propose a robust method for the correction of outliers, applicable to diffusion tensor imaging (DTI) and q-ball imaging (QBI). MATERIALS AND METHODS: Monte Carlo simulations were carried out to measure the impact of outliers on DTI and QBI reconstruction in a single voxel. Methods to correct outliers based on q-space interpolation and direction removal were then implemented and validated in real image data. RESULTS: Corruption in a single voxel led to clear variations in DTI and QBI metrics. In real data, the method of q-space interpolation was successful in identifying corrupted voxels and restoring them to values consistent with those of uncorrupted images. CONCLUSION: For images containing few gradient directions, where outlier removal was either impossible due to limited volumes or resulted in large changes in DTI/QBI metrics, q-space interpolation proved to be the method of choice for image restoration. A simple decision support system is proposed to assist clinicians in the correction of their corrupted DW data.