Neuroscience
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Huntington's disease (HD) leads to white matter (WM) degeneration that may be due to an early breakdown in axon myelination but in vivo imaging correlates of demyelination remain relatively unexplored in HD compared to other neurodegenerative diseases. This study investigated HD-related effects on a putative marker of myelin, the macromolecular proton fraction (MMPF) from quantitative magnetization transfer and on fractional anisotropy, axial and radial diffusivity from diffusion tensor MR-imaging. Microstructural differences were studied in WM pathways of the basal ganglia and motor systems known to be impaired in HD: the corpus callosum, the cortico-spinal tract, the anterior thalamic radiation, fibers between prefrontal cortex and caudate and between supplementary motor area and putamen. ⋯ Inter-individual differences in the diffusivity component correlated with patients' performance in clinical measures of the United Huntington Disease Rating Scale. In summary, HD-related reductions in MMPF suggest that myelin breakdown contributes to WM impairment in human HD and emphasize the potential of quantitative MRI metrics to inform about disease pathogenesis. Disease severity in manifest HD, however, was best captured by non-specific diffusivity metrics sensitive to multiple disease and age-related changes.
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In multiple sclerosis (MS), it would be of clinical value to be able to track the progression of axonal pathology, especially before the manifestation of clinical disability. However, non-invasive evaluation of short-term longitudinal progression of white matter integrity is challenging. This study aims at assessing longitudinal changes in the restricted (i.e. intracellular) diffusion signal fraction (FR) in early-stage MS by using ultra-high gradient strength multi-shell diffusion magnetic resonance imaging. ⋯ Taken together, our data provide evidence for progressive microstructural damage in the NAWM of early MS cases detectable already at 1-year follow-up. Our study highlights the value of multi-shell diffusion imaging for sensitive tracking of disease evolution in MS before any clinical changes are observed. This article is part of a Special Issue entitled: SI: MRI and Neuroinflammation.
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Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. ⋯ We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework.
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Multiple Sclerosis (MS) is a chronic neurological disease that represents a leading cause of disability in young adults and is characterized by inflammation and degeneration of both white matter (WM) and gray matter (GM). Defining the presence or absence of inflammation on individual basis is a key point in choosing the therapy and monitoring the treatment response. Magnetic resonance imaging (MRI) represents the most sensitive non-invasive tool to monitor inflammation in the clinical practice. ⋯ New imaging techniques have been developed to study diffuse inflammation taking place outside the focal plaques. The scope of this review is to examine the various neuroimaging techniques and those biophysical quantities that can be non-invasively detected to enlighten the different aspects of neuroinflammation. Some techniques are commonly used in the clinical practice, while others are used in the research field to better understand the pathophysiological mechanisms of the disease and the role of inflammation.
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Positron emission tomography (PET) provides spatially localized information about brain metabolism and function and innovative tracers have extended this potential to the study of neuroinflammation (NI), an important process in the pathophysiology of several neurological disorders. However, PET is limited by low spatial resolution. Conversely, Magnetic Resonance Imaging (MRI) affords high-resolution information about brain anatomy and metabolism which can complement PET-related information as well as aid in post-processing of PET data. ⋯ While, the clinical applicability and impact on diagnostic accuracy of PET/MRI in neurological disorders is still under investigation, the study of NI, a complex processes mediated by multiple metabolic pathways and hence likely characterized by different biomarkers, represents an opportunity to characterize the added value of joint MRI-PET techniques in a clinical context. This would in turn offer improved diagnostic and prognostic tools in several neurological disorders in which NI is a key mediator. This review aims at summarizing the current state as well as future potential of using hybrid PET/MRI for characterizing NI phenomena, both in terms of technical challenges and clinical relevance.