Diffusion Tensor Imaging Abnormalities in Cognitively Impaired Multiple Sclerosis Patients

Background: Cognitive impairment can add to the burden of disease in patients with multiple sclerosis (MS). The aim of this study was to assess the relative importance of diffusion tensor imaging (DTI) indices derived from normal appearing white matter (NAWM) and grey matter (NAGM) in determining cognitive dysfunction in MS patients. Methods: Sixty two MS patients [51 female, mean age= 41 (sd=9.6) years, median expanded disability status scale (EDSS)=2.5] meeting modified McDonald criteria for MS underwent neuropsychological testing using the Neuropsychological Screening Battery for MS (NSBMS) and magnetic resonance imaging (MRI, 1.5T GE) that included DTI sequences. Total T1 hypointense and T2 hyperintense lesion volumes were obtained using semi-automated software. Lesion volumes were subtracted from whole-brain parenchyma to obtain measures of NAWM and NAGM. Fractional anisotropy (FA) of NAWM and mean diffusivity (MD) of NAGM were obtained. Results: Cognitive impairment was present in 11 patients (18%). These patients had higher EDSS scores, were less educated, and were more likely to have secondary progressive MS. They also had higher hypointense (p=0.001) and hyperintense (p=0.004) lesion volumes, greater NAWM atrophy (p=0.007), lower FA of total NAWM (p=0.003), and higher MD of total NAGM (p=0.015). Using a logistic regression analysis, and after controlling for demographic and disease-related differences between groups, FA of NAWM emerged as a significant predictor of cognitive impairment adding to the variance derived from lesion and atrophy data. Conclusion: This study underlies the important role of normal-appearing brain tissue in the pathogenesis of MS-related cognitive impairment.

[1]  M. Rovaris,et al.  Cognitive dysfunction in patients with mildly disabling relapsing–remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging , 2002, Journal of the Neurological Sciences.

[2]  M. Rovaris,et al.  Will Rogers phenomenon in multiple sclerosis , 2008, Annals of neurology.

[3]  A J Thompson,et al.  Multiple sclerosis: a preliminary study of selected variables affecting rehabilitation outcome , 1999, Multiple sclerosis.

[4]  HERMAN BUSCHKE,et al.  Evaluating storage, retention, and retrieval in disordered memory and learning , 1974, Neurology.

[5]  R. Benedict Standards for sample composition and impairment classification in neuropsychological studies of multiple sclerosis , 2009, Multiple sclerosis.

[6]  T. Hammeke,et al.  Memory disturbance in chronic progressive multiple sclerosis. , 1984, Archives of neurology.

[7]  N. De Stefano,et al.  Neocortical volume decrease in relapsing–remitting MS patients with mild cognitive impairment , 2004, Neurology.

[8]  M. Blinkenberg,et al.  Cortical cerebral metabolism correlates with MRI lesion load and cognitive dysfunction in MS , 2000, Neurology.

[9]  Marco Rovaris,et al.  Cognitive impairment and structural brain damage in benign multiple sclerosis , 2008, Neurology.

[10]  J Foong,et al.  Correlates of executive function in multiple sclerosis: the use of magnetic resonance spectroscopy as an index of focal pathology. , 1999, The Journal of neuropsychiatry and clinical neurosciences.

[11]  D. Mohr,et al.  The unique impact of changes in normal appearing brain tissue on cognitive dysfunction in secondary progressive multiple sclerosis patients , 2004, Multiple sclerosis.

[12]  D. Gronwall Paced Auditory Serial-Addition Task: A Measure of Recovery from Concussion , 1977, Perceptual and motor skills.

[13]  Stephen M. Rao,et al.  Cognitive dysfunction in multiple sclerosis. , 1991, Neurology.

[14]  D. Auer,et al.  Disconnection as a mechanism for cognitive dysfunction in multiple sclerosis. , 2009, Brain : a journal of neurology.

[15]  Emilio Portaccio,et al.  Multiple sclerosis-related cognitive changes: A review of cross-sectional and longitudinal studies , 2006, Journal of the Neurological Sciences.

[16]  Eric Achten,et al.  Transverse diffusivity of cerebral parenchyma predicts visual tracking performance in relapsing–remitting multiple sclerosis , 2009, Brain and Cognition.

[17]  Rohit Bakshi,et al.  Independent contributions of cortical gray matter atrophy and ventricle enlargement for predicting neuropsychological impairment in multiple sclerosis , 2007, NeuroImage.

[18]  Robert Zivadinov,et al.  Diffusion-weighted imaging predicts cognitive impairment in multiple sclerosis , 2007, Multiple sclerosis.

[19]  E. Warrington,et al.  Cognitive abnormalities in multiple sclerosis: a psychometric and MRI study , 1991, Psychological Medicine.

[20]  R. Benedict,et al.  Validity of the Beck Depression Inventory-Fast Screen in multiple sclerosis , 2003, Multiple sclerosis.

[21]  Rohit Bakshi,et al.  Gray and white matter brain atrophy and neuropsychological impairment in multiple sclerosis , 2006, Neurology.

[22]  M. Ron,et al.  Clinically isolated lesions of the type seen in multiple sclerosis: a cognitive, psychiatric, and MRI follow up study. , 1992, Journal of neurology, neurosurgery, and psychiatry.

[23]  M Rovaris,et al.  Cortical/subcortical disease burden and cognitive impairment in patients with multiple sclerosis. , 2000, AJNR. American journal of neuroradiology.

[24]  G Luccichenti,et al.  Cognitive impairment and its relation with disease measures in mildly disabled patients with relapsing–remitting multiple sclerosis: baseline results from the Cognitive Impairment in Multiple Sclerosis (COGIMUS) study , 2009, Multiple sclerosis.

[25]  Massimo Filippi,et al.  Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. , 2009, Archives of neurology.

[26]  M Rovaris,et al.  Changes in the normal appearing brain tissue and cognitive impairment in multiple sclerosis , 2000, Journal of neurology, neurosurgery, and psychiatry.

[27]  Natasa Kovacevic,et al.  A Robust Method for Extraction and Automatic Segmentation of Brain Images , 2002, NeuroImage.

[28]  D. Goodkin,et al.  Clinical and demographic predictors of cognitive performance in multiple sclerosis. Do diagnostic type, disease duration, and disability matter? , 1990, Archives of neurology.

[29]  Rohit Bakshi,et al.  Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. , 2004, Archives of neurology.

[30]  J. Benito-León,et al.  Health‐related quality of life and its relationship to cognitive and emotional functioning in multiple sclerosis patients , 2002, European journal of neurology.

[31]  S. Reingold,et al.  Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria” , 2005, Annals of neurology.