Conventional and Quantitative Magnetic Resonance Imaging and Cognitive Impairment in Multiple Sclerosis

Conventional and Quantitative Magnetic Resonance Imaging and Cognitive Impairment in Multiple Sclerosis

Constantine A Soulellis, Tench Christopher R

European Neurological Review, 2009;4(2):70-3

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Abstract
An estimated 30–70% of patients with multiple sclerosis (MS) have some cognitive impairment. Cognitive function depends on a spectrum of faculties including information processing speed, sustained attention, recent memory and executive function. The broad definition of cognition has resulted in different assessments of function, and repeatable batteries of tests have been devised to gain an overall and repeatable view of cognition in MS. Many studies have attempted to find an association between cognitive function and MS pathology using magnetic resonance imaging (MRI). Conventional MRI has been used to show the relationship between cognitive impairment and MS lesion volume and/or brain volume (reflecting atrophy). Studies using quantitative MRI to estimate the degree of abnormality in tissue that is normal-appearing on conventional MRI have also found correlations with cognitive function. Longitudinally, cognitive decline has been found to correlate with changing MRI-detectable pathology in some studies. However, consistency between studies has been lacking, and the large number of cognitive tests available makes direct comparison of different studies difficult. Focus on specific cognitive domains may alleviate this issue in future studies.

Keywords
Multiple sclerosis, cognitive function, magnetic resonance imaging, cross-sectional studies, longitudinal studies, quantitative imaging, conventional imaging, attention, working memory

Disclosure: The authors have no conflicts of interest to declare.
Acknowledgements: The authors’ work has been supported in part by the University of Nottingham, The Multiple Sclerosis Society of the Great Britain and Northern Ireland and the EU (Marie Curie International Fellowships).
Received: 4 January 2009 Accepted: 25 May 2009
Correspondence: Cris S Constantinescu, Division of Clinical Neurology, School of Clinical Sciences, University of Nottingham, NG7 2UH, UK. E: Cris.constantinescu@nottingham.ac.uk

Multiple Sclerosis
Multiple sclerosis (MS) is a chronic inflammatory disease affecting the central nervous system (CNS) that is characterised by multiple areas of demyelination, focal and diffuse inflammation, axonal damage and loss and gliosis. The disease course falls into different broad clinical categories, including relapsing–remitting (RR), secondary progressive (SP) and primary progressive (PP) MS. Patients who do not have clinically definite MS according to the criteria1,2 but do have an isolated event suggestive of MS are said to have clinically isolated syndrome (CIS).

Magnetic Resonance Imaging Measures in Multiple Sclerosis
MS lesions can be visualised with remarkable clarity using magnetic resonance imaging (MRI), which is used as a diagnostic tool and has also greatly improved our understanding of the mechanisms of MS by giving us the opportunity to study the pathology in vivo. There is vast literature on the use of MRI in the study of MS, the bulk of which has focused on conventional MRI.

Conventional T2-weighted spin echo images reveal the lesions,3 which appear hyperintense, most completely of the different contrasts. The T2 MS lesion burden has probably been the most commonly used MRI outcome measure in large clinical trials, and is quantified by count, area or volume. Despite accurately depicting the distribution of MS lesions, correlation with clinical measures such as the expanded disability status scale (EDSS)4 is poor. Explanations for this ‘clinico-radiological paradox’ include lack of pathological specificity, re-myelination and cortical plasticity. Another explanation is the lack of spatial information in the lesion burden measures, location of the lesion within the brain being paramount in determining effect.

Other conventional MRI measures have been used in an attempt to overcome some of the limitations of T2-weighted imaging. T1 relaxation time contrast is thought to reflect more specifically axonal loss, so the apparent lesion burden may correlate better with disability. Gadolinium-enhanced T1-weighted images are reported to show lesions where the blood–brain barrier has been breached, and indicate new or active lesions and therefore active disease. Tissue loss, or atrophy, has also been estimated using high-resolution images. This loss has also been found to correlate with disability to varying degrees.

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Keywords:
Multiple sclerosis, cognitive function, magnetic resonance imaging, cross-sectional studies, longitudinal studies, quantitative imaging, conventional imaging, attention, working memory, treatment Multiple sclerosis, Multiple sclerosis symptoms, Multiple sclerosis causes,

References:
  1. Poser CM, et al., Ann Neurol, 1983;13:227–31.
  2. McDonald WI, et al., Ann Neurol, 2001;50:121–7.
  3. Ormerod IE, et al., Brain, 1987;110:1579–1616.
  4. Kurtzke JF, Neurology, 1983;33:1444–52.
  5. Rao SM, et al., Neurology, 1991;41:692–6.
  6. Rao SM, et al., Neurology, 1989;39:161–6.
  7. Lincoln NB, et al., Mult Scler, 2008;14:123–8.
  8. Boringa JB, et al., Mult Scler, 2001;7:263–7.
  9. Achiron A, et al., J Neurol Sci, 2006;245:47–51.
  10. Gronwall DM, Percept Mot Skills, 1977;44:367–73.
  11. Whitaker JN, et al., Mult Scler, 1995;1:37–47.
  12. Cutter GR, et al., Brain, 1999;122:871–2.
  13. Huber SJ, et al., Arch Neurol, 1987;44:732–6.
  14. Franklin GM, et al., Neurology, 1988;38:1826–9.
  15. Swirsky-Sacchetti, T, et al., Neurology, 1992;42:1291–5.
  16. Edwards SG, et al., Acta Neurol Scand, 2001;104:214–23.
  17. Miki Y, et al., Neurology, 1998;50:1301–6.
  18. Moriarty DM, et al., Am J Neuroradiol, 1999;20:1956–62.
  19. Lazeron RH, et al., Mult Scler, 2000;6:280–85.
  20. Charil A, et al., Neuroimage, 2003;19:532–44.
  21. Houtchens MK, et al., Neurology, 2007;69:1213–23.
  22. Glanz BI, et al., Mult Scler, 2007;13:1004–10.
  23. Mariani C, et al., J Neurol, 1991;238:395–400.
  24. Mattioli F, et al., Acta Neurol Scand, 1993;87:465–8.
  25. Hohol MJ, et al., Arch Neurol, 1997;54:1018–25.
  26. Zivadinov R, et al., J Neurol Neurosurg Psychiatry, 2001;70:773–80.
  27. Sperling RA, et al., Arch Neurol, 2001;58:115–21.
  28. Piras MR, et al., J Neurol Neurosurg Psychiatry, 2003;74:878–85.
  29. Camp SJ, et al., Brain, 2005;128:2891–8.
  30. Filippi M, et al., J Neurol Neurosurg Psychiatry, 2000;68:157–61.
  31. Zivadinov R, et al., Neuroradiology, 2001;43:272–8.
  32. Rovaris M, et al., J Neurol Sci, 2002;195:103–9.
  33. Benedict RH, et al., Mult Scler, 2007;13:722–30.
  34. Mori S, et al., Ann Neurol, 1999;45:265–9.
  35. Tench CR, et al., Magn Reson Med, 2002;47:967–72.
  36. Lin X, et al., J Neurol Sci, 2005;237:13–19.
  37. Smith SM, et al., Neuroimage, 2006;31:1487–1505.
  38. Dineen RA, et al., Brain, 2009;132:239–49.
  39. Mainero C, et al., Neuroimage, 2004;21:858–67.
  40. Penner IK, et al., J Neurol, 2007;254:II53–7.

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