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multiple sclerosis

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Multiple sclerosis (MS) is a disease affecting approximately 1 out of 1000 people in the U.S. Patients suffer from a variety of neurologic symptoms such as problems of vision, gait impairment, weakness or unpleasant sensations in arms and legs, urinary incontinence. The disease typically manifests itself in people in their 20s and 30s, and progresses over years and decades, often severely limiting the independence and productivity of those affected. Disease progression varies from patient to patient and is unpredictable.

The pathologic hallmark of MS is the presence of demyelinating/inflammatory lesions in the brain and spinal cord. The appearance and progression of such lesions is best demonstrated in the living patient by magnetic resonance imaging (MRI) [1,2,5-7,18].

Quantitative image analysis enables reproducible estimates of brain components such as white matter (WM), white matter signal abnormalities (WMSA), gray matter (GM), and cerebrospinal fluid (CSF) [13-14].

Using the methods we developed for in-vivo quantitative tissue analysis we demonstrated correlations between changes in WMSA and changes in clinical status, represented by scales of disability and cognition [16]. Such linkage established quantitative MRI as a valid measure of disease progression in clinical trials evaluating the efficacy of novel treatment of MS.

Our main goals for image processing in MS are:

Our database includes over 1500 MRI exams of the brain in more than 100 MS patients. A normative database of over 70 healthy volunteers, representing age groups between 18 and 80 years, was also studied [15]. Currently, the MRI protocols underlying quantitative tissue estimates are routine for the MS patient undergoing MRI in our department. Further research in our group is geared towards developing high-resolution MRI techniques to achieve more precision in the estimate of disease progression, and enable adequate monitoring of individual patients [12].

Current members of the group working on quantitative imaging of MS at BWH are:

The MS Clinic at the Center for Neurologic Diseases (Director: Howard L. Weiner, MD) is our clinical partner at BWH/MGH. Several clinical and scientific collaborations are being pursued nationally and internationally.

References:

    1. Meier et al. Seasonal Prevalence of MS Disease Activity. Neurology 2010 Editorial
    2. Meier et al. Disease modeling in multiple sclerosis: assessment and quantification of sources of variability in brain parenchymal fraction measurements. Neuroimage. 2010
    3. Sampat et al. Regional White Matter Atrophy Based Classification of Multiple Sclerosis in Cross-Sectional and Longitudinal Data. AJNR 2009
    4. Yang et al. Segmentation of Subtraction Images for the Measurement of Lesion Change in Multiple Sclerosis. AJNR 2008
    5. Meier et al. MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007
    6. Meier et al. Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007
    7. Meier et al. MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006
    8. Wu et al. Automated Segmentation of Multiple Sclerosis Lesion Subtypes with Multichannel MRI. NeuroImage 2006
    9. Liu et al. Multiple Sclerosis Medical Image Analysis and Information Management. J Neuroimaging 2005
    10. Meier et al. Magnetic resonance imaging surrogates of multiple sclerosis pathology and their relationship to central nervous system atrophy. J Neuroimaging 2004
    11. Meier et al. Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003
    12. Mugler et al. Optimized Single-slab Three-dimensional Spin-echo MR Imaging of the Brain. Radiology 2000
    13. Guttmann et al. Quantitative follow-up of patients with multiple sclerosis using MRI: reproducibility. JMRI 1999
    14. Kikinis et al. Quantitative follow-up of patients with multiple sclerosis using MRI: technical aspects. JMRI 1999
    15. Guttmann et al. White matter changes with normal aging. Neurology 1998
    16. Hohol et al. Serial Neuropsychological Assessment and Magnetic Resonance Imaging Analysis in Multiple Sclerosis. Arch Neurol. 1997
    17. Warfield et al. Automatic Identification of Gray Matter Structures from MRI to Improve the Segmentation of White Matter Lesions. J Image Guid Surg. 1995
    18. Guttmann et al. The evolution of multiple sclerosis lesions on serial MR. AJNR Am. J. Neuroradiol. 1995



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