Measurement and clinical effect of grey matter pathology in multiple sclerosis
ABSTRACT During the past 10 years, the intense involvement of the grey matter of the CNS in the pathology of multiple sclerosis has become evident. On gross inspection, demyelination in the grey matter is rather inconspicuous, and lesions in the grey matter are mostly undetectable with traditional MRI sequences. However, the results of immunohistochemical studies have shown extensive involvement of grey matter, and researchers have developed and applied new MRI acquisition methods as a result. Imaging techniques specifically developed to visualise grey matter lesions indicate early involvement, and image analysis techniques designed to measure the volume of grey matter show progressive loss. Together, these techniques have shown that grey matter pathology is associated with neurological and neuropsychological disability, and the strength of this association exceeds that related to white matter lesions or whole brain atrophy. By focusing on the latest insights into the in-vivo measurement of grey matter lesions and atrophy, we can assess their clinical effects.
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ABSTRACT: Multiple sclerosis (MS) is a chronic disorder of the central nervous system (CNS) in which the complex interplay between inflammation and neurodegeneration determines varying degrees of neurological disability. For this reason, it is very difficult to express an accurate prognosis based on purely clinical information in the individual patient at an early disease stage. Magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers are promising sources of prognostic information with a good potential of quantitative measure, sensitivity, and reliability. However, a comprehensive MS outcome prediction model combining multiple parameters is still lacking. Current relevant literature addressing the topic of clinical, MRI, and CSF markers as predictors of MS disability progression is reviewed here.Disease markers 11/2013; 35(6):687-699. DOI:10.1155/2013/484959
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ABSTRACT: Glial cells play an important role in normal brain function and emerging evidence would suggest that their dysfunction may be responsible for some epileptic disease states. Neuroimaging of glial cells is desirable, but there are no clear methods to assess neither their function nor localization. Magnetic resonance imaging (MRI) is now part of a standardized epilepsy imaging protocol to assess patients. Structural volumetric and T2-weighted imaging changes can assist in making a positive diagnosis in a majority of patients. The alterations reported in structural and T2 imaging is predominately thought to reflect early neuronal loss followed by glial hypertrophy. MR spectroscopy for myo-inositol is a being pursued to identify glial alterations along with neuronal markers. Diffusion weighted imaging (DWI) is ideal for acute epileptiform events, but is not sensitive to either glial cells or neuronal long-term changes found in epilepsy. However, DWI variants such as diffusion tensor imaging or q-space imaging may shed additional light on aberrant glial function in the future. The sensitivity and specificity of PET radioligands, including those targeting glial cells (translocator protein) hold promise in being able to image glial cells. As the role of glial function/dysfunction in epilepsy becomes more transparent, neuroimaging methods will evolve to assist the clinician and researcher in visualizing their location and function.Neurochemistry International 05/2013; DOI:10.1016/j.neuint.2013.05.001
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ABSTRACT: Gray matter atrophy provides important insights into neurodegeneration in multiple sclerosis (MS) and can be used as a marker of neuroprotection in clinical trials. Jacobian integration is a method for measuring volume change that uses integration of the local Jacobian determinants of the nonlinear deformation field registering two images, and is a promising tool for measuring gray matter atrophy. Our main objective was to compare the statistical power of the Jacobian integration method to commonly used methods in terms of the sample size required to detect a treatment effect on gray matter atrophy. We used multi-center longitudinal data from relapsing-remitting MS patients and evaluated combinations of cross-sectional and longitudinal pre-processing with SIENAX/FSL, SPM, and FreeSurfer, as well as the Jacobian integration method. The Jacobian integration method outperformed these other commonly used methods, reducing the required sample size by a factor of 4-5. The results demonstrate the advantage of using the Jacobian integration method to assess neuroprotection in MS clinical trials.10/2013; 4:10-17. DOI:10.1016/j.nicl.2013.10.015