NeuroImage. Clinical
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NeuroImage. Clinical · Jan 2014
Age independently affects myelin integrity as detected by magnetization transfer magnetic resonance imaging in multiple sclerosis.
Multiple sclerosis (MS) is a heterogeneous disorder with a progressive course that is difficult to predict on a case-by-case basis. Natural history studies of MS have demonstrated that age influences clinical progression independent of disease duration. ⋯ Despite matching for clinical disease duration and recording no significant WML volume difference, we demonstrated strong MTR differences in WMLs between younger and older MS patients. These data suggest that aging-related processes modify the tissue response to inflammatory injury and its clinical outcome correlates in MS.
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NeuroImage. Clinical · Jan 2014
Specific brain morphometric changes in spinal cord injury with and without neuropathic pain.
Why only certain patients develop debilitating pain after spinal chord injury and whether structural brain changes are implicated remain unknown. The aim of this study was to determine if patients with chronic, neuropathic below-level pain have specific cerebral changes compared to those who remain pain-free. Voxel-based morphometry of high resolution, T1-weighted images was performed on three subject groups comprising patients with pain (SCI-P, n = 18), patients without pain (SCI-N, n = 12) and age- and sex-matched controls (n = 18). ⋯ In the visual cortex, SCI-N showed increased grey matter, whilst the SCI-N showed reduced white matter. In conclusion, structural changes in SCI are related to the presence and degree of below-level pain and involve but are not limited to the sensorimotor cortices. Pain-related structural plasticity may hold clinical implications for the prevention and management of refractory neuropathic pain.
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NeuroImage. Clinical · Jan 2014
Independent contribution of individual white matter pathways to language function in pediatric epilepsy patients.
Patients with epilepsy and malformations of cortical development (MCDs) are at high risk for language and other cognitive impairment. Specific impairments, however, are not well correlated with the extent and locale of dysplastic cortex; such findings highlight the relevance of aberrant cortico-cortical interactions, or connectivity, to the clinical phenotype. The goal of this study was to determine the independent contribution of well-described white matter pathways to language function in a cohort of pediatric patients with epilepsy. ⋯ Scalar metrics derived from the left uncinate, inferior fronto-occipital, and arcuate fasciculi were independently associated with language function. These results support the importance of these pathways in human language function in patients with MCDs.
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NeuroImage. Clinical · Jan 2014
Randomized Controlled TrialResting state connectivity correlates with drug and placebo response in fibromyalgia patients.
Fibromyalgia is a chronic pain syndrome characterized by widespread pain, fatigue, and memory and mood disturbances. Despite advances in our understanding of the underlying pathophysiology, treatment is often challenging. New research indicates that changes in functional connectivity between brain regions, as can be measured by magnetic resonance imaging (fcMRI) of the resting state, may underlie the pathogenesis of this and other chronic pain states. ⋯ This pattern was not observed for the placebo period. However a more robust placebo response was associated with lower baseline functional connectivity between the ACC and the dorsolateral prefrontal cortex. This study indicates that ACC-IC connectivity might play a role in the mechanism of action of MLN, and perhaps more importantly fcMRI might be a useful tool to predict pharmacological treatment response.
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NeuroImage. Clinical · Jan 2014
Randomized Controlled Trial Comparative StudyRandom Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness.
Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness. ⋯ The models trained using parcelled and high-dimensional (HD) input demonstrated equivalent performance, but the former was more effective in terms of computation/memory and time costs. The sensitivity/specificity for detecting MCI-to-AD conversion (but not AD/HC classification performance) was further improved from 79.5%/75%-83.3%/81.3% by a combination of morphometric measurements with ApoE-genotype and demographics (age, sex, education). When applied to the independent AddNeuroMed cohort, the best ADNI models produced equivalent performance without substantial accuracy drop, suggesting good robustness sufficient for future clinical implementation.