Background: Neocortical lesions (NLs) largely contribute to the pathology of multiple sclerosis (MS), although their relevance in patients’ disability remains unknown.
Objective: To assess the incidence of T1 hypointense NLs by 3.0-Tesla magnetic resonance imaging (MRI) in patients with MS and examine neocortical lesion association with cognitive impairment.
Methods: In this case-control study, 21 MS patients and 21 age-, sex- and years of education-matched healthy volunteers underwent: (i) a neuropsychological examination rating cognitive impairment (Minimal Assessment of Cognitive Function in MS); (ii) a 3.0-Tesla MRI inclusive of an isotropic 1.0 mm3 three-dimensional inversion prepared spoiled gradient-recalled-echo (3D-IRSPGR) image and T1- and T2-weighted images. Hypointensities on 3D-IRSPGR lying in the cortex, either entirely or partially were counted and association between NLs and cognitive impairment investigated.
Results: A total of 95 NLs were observed in 14 (66.7%) patients. NL+ patients performed poorer (p = 0.020) than NLpatients only on the delayed recall component of the California Verbal Learning Test. This difference lost statistical significance when a correction for white matter lesion volume was employed.
Conclusions: Although T 1 hypointense NLs may be present in a relatively high proportion of multiple sclerosis patients, the impact that they have in cognitive impairment is not independent from white matter disease.
Geurts JJ and Barkhof F.Grey matter pathology in multiple sclerosis. Lancet Neurol2008; 7: 841-851.
2.
Lassmann H.The pathological substrate of magnetic resonance alterations in multiple sclerosis . Neuroimag Clin N Am2008; 18: 563-576.
3.
Stadelmann C. , Albert M., Wegner C. and Bruck W.Cortical pathology in multiple sclerosis. Curr Opin Neurol2008; 21: 229-234.
4.
Geurts JJ, Blezer EL, Vrenken H., et al. Does high-field MR imaging improve cortical lesion detection in multiple sclerosis?J Neurol2008; 255: 183-191.
5.
Geurts JJ, Pouwels PJ, Uitdehaag BM, Polman CH, Barkhof F. and Castelijns JAIntracortical lesions in multiple sclerosis: improved detection with 3D double inversion-recovery MR imaging. Radiology2005 ; 236: 254-260.
6.
Bagnato F., Yao B., Cantor F., et al. Multisequence-imaging protocols to detect cortical lesions in patients with multiple sclerosis: observations from a post-mortem 3 Tesla imaging study. J Neurol Sci2009; 15: 80-85.
7.
Dolezal O., Dwyer MG, Horakova D., et al. Detection of cortical lesions is dependent on choice of slice thickness in patients with multiple sclerosis. Int Rev Neurobiol2007; 79: 475-489.
8.
Nelson F., Poonawalla AH, Hou P., Huang F., Wolinsky JS and Narayana PAImproved identification of intracortical lesions in multiple sclerosis with phase-sensitive inversion recovery in combination with fast double inversion recovery MR imaging. Am J Neuroradiol2007 ; 28: 1645-1649.
9.
Calabrese M. , De Stefano N., Atzori M., et al. Detection of cortical inflammatory lesions by double inversion recovery magnetic resonance imaging in patients with multiple sclerosis. Arch Neurol2007; 64: 1416-1422.
10.
Moraal B., Roosendaal SD, Pouwels PJ, et al. Multi-contrast, isotropic, single-slab 3D MR imaging in multiple sclerosis. Eur Radiol2008; 18: 2311-2320.
11.
Simon B., Schmidt S., Lukas C., Gieseke J., Träber F., Knol DL, et al. Improved in vivo detection of cortical lesions in multiple sclerosis using double inversion recovery MR imaging at 3 Tesla. Eur Radiol2010; 20: 1675-1683.
12.
Nelson F., Poonawalla A., Hou P., Wolinsky JS and Narayana PA3D MPRAGE improves classification of cortical lesions in multiple sclerosis . Mult Scler2008; 14: 1214-1219.
13.
Bagnato F., Butman JA, Gupta S., et al. In vivo detection of cortical plaques by MR imaging in patients with multiple sclerosis. Am J Neuroradiol2006; 27: 2161-2167.
14.
Bagnato F., Talagala L., Ikonomidou V., et al. In vivo visualization of multiple sclerosis cortical lesions by high resolution MRI at 3T. Proc Int Mag Reson Med2006; 14 abstract: 2097.
15.
Mainero C., Benner T., Radding A., et al. In vivo imaging cortical pathology in multiple sclerosis using ultra-high field MRI. Neurology2009; 73: 941-948.
16.
Roosendal SD , Moraal B., Pouwels PJW, et al. Accumulation of cortical lesions in MS: relation with cognitive impairment. Mult Scler2009; 15: 708-714.
17.
Calabrese M. , Agosta F., Rinaldi F., et al. Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Arch Neurol2009; 66: 1144-1150.
18.
Hoffmann S. , Tittgemeyer M. and von Cramon DYCognitive impairment in multiple sclerosis . Curr Opin Neurol2007; 20: 275-280.
19.
Benedict RH , Fischer JS, Archibald CJ, et al. Minimal neuropsychological assessment of MS patients: a consensus approach. Clin Neuropsychol2002; 16: 381-397.
20.
McDonald WI , Compston A., Edan G., et al. Recommended diagnostic criteria for MS. Ann Neurol2001; 50: 121-127.
21.
Kurtzke JFRating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology1983; 33: 1444-1452.
22.
Cutter GR, Baier ML, Rudick RA, et al. Development of a multiple sclerosis functional composite as a clinical trial outcome measure. Brain1999 ; 122: 871-882.
23.
Goodkin DE, Hertsgaard D. and Seminary J.Upper extremity function in multiple sclerosis: improving assessment sensitivity with box-and-block and nine-hole peg tests. Arch Phys Med Rehabil1998; 69: 850-854.
24.
Solari A., Radice D., Manneschi L., Motti L. and Montanari E.The multiple sclerosis functional composite: different practice effects in the three test components. J Neurol Sci2005 ; 15: 71-74.
25.
Wilkinson GSThe Wide Range Achievement Test: manual, 3rd edn. Wilmington, DE: Wide Range, 1993.
26.
Richert ND, Ostuni JL, Bash CN, Leist TP, McFarland HF and Frank JAInterferon beta-1b and intravenous methylprednisolone promote lesion recovery in multiple sclerosis. Mult Scler2001; 7: 49-58.
27.
Talaraich J. and Tournoux P.Co-planar stereotaxic atlas of the human brain. New York : Thieme, 1998.
28.
Cox RWAFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res1996 ; 29: 162-173.
29.
Center for Information Technology.About MIPAV . http://mipav.cit.nih.gov (accessed May 2010).
30.
Smith SM, Zhang Y., Jenkinson M., et al. Accurate, robust and automated longitudinal and cross-sectional brain change analysis. NeuroImage2002; 17: 479-489.
31.
Stevenson VL , Smith SM, Matthews PM, Miller DH and Thompson A.Monitoring disease activity and progression in primary progressive multiple sclerosis using MRI: sub-voxel registration to identify lesion changes and to detect cerebral atrophy. J Neurol2002; 249: 171-177.
32.
Troyer AK, Fisk JD, Archibald CJ, Ritvo PG and Murray TJConceptual reasoning as a mediator of verbal recall in patients with multiple sclerosis. J Clin Exp Neuropsychol1996; 18: 211-219.
33.
Chiaravallotti ND and DeLuca J.Cognitive impairment in multiple sclerosis . Lancet Neurol2008; 7: 1139-1151.
34.
Alexander MP , Stuss DT and Fansabedian N.California Verbal Learning Test: performance by patients with focal frontal and non-frontal lesions. Brain2003; 126: 1493-1503.
35.
Dineen RA, Vilisaar J., Hlinka J., et al. Disconnection as a mechanism for cognitive dysfunction in multiple sclerosis. Brain2009; 132: 239-249.
