title: Neuroimaging in multiple sclerosis.
abstract: Conventional magnetic resonance imaging (MRI) has routinely been used to improve the accuracy of multiple sclerosis (MS) diagnosis and prognosis. Metrics derived from conventional MRI are now routinely used to detect therapeutic effects and extend clinical observations. However, conventional MRI measures, such as the use of lesion volume and count of gadolinium-enhancing and T2 lesions, have insufficient sensitivity and specificity to reveal the true degree of pathological changes occurring in MS. They cannot distinguish between inflammation, edema, demyelination, Wallerian degeneration, and axonal loss. In addition, they do not show a reliable correlation with clinical measures of disability and do not provide a complete assessment of therapeutic outcomes. Recent neuropathologic studies of typical chronic MS brains reveal macroscopic demyelination in cortical and deep gray matter (GM) that cannot be detected by currently available MRI techniques. Therefore, there is a pressing need for the development of newer MRI techniques to detect these lesions. Newer metrics of MRI analysis, including T1-weighted hypointense lesions, central nervous system atrophy measures, magnetization transfer imaging, magnetic resonance spectroscopy, and diffusion tensor imaging, are able to capture a more global picture of the range of tissue alterations caused by inflammation and neurodegeneration. At this time, they provide the only proof--albeit indirect--that important occult pathology is occurring in the GM. However, evidence is increasing that these nonconventional MRI measures correlate better with both existing and developing neurological impairment and disability when compared to conventional metrics.
authors.affiliation: Buffalo Neuroimaging Analysis Center, The Jacobs Neurological Institute, State University of New York at Buffalo, School of Medicine and Biomedical Sciences, Buffalo, New York 14203, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Zivadinov
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Cox
mesh_terms: D002490:Central Nervous System / Q000473:pathology*; D003952:Diagnostic Imaging / Q000145:classification / Q000379:methods*; D006801:Humans; D009103:Multiple Sclerosis / Q000473:pathology*