DIR-visible grey matter lesions and atrophy in multiple sclerosis: partners in crime?

Background The extent and clinical relevance of grey matter (GM) pathology in multiple sclerosis (MS) are increasingly recognised. GM pathology may present as focal lesions, which can be visualised using double inversion recovery (DIR) MRI, or as diffuse pathology, which can manifest as atrophy. It is, however, unclear whether the diffuse atrophy centres on focal lesions. This study aimed to determine if GM lesions and GM atrophy colocalise, and to assess their independent relationship with motor and cognitive deficits in MS. Methods Eighty people with MS and 30 healthy controls underwent brain volumetric T1-weighted and DIR MRI at 3 T, and had a comprehensive neurological and cognitive assessment. Probability mapping of GM lesions marked on the DIR scans and voxel- based morphometry (assessing GM atrophy) were carried out. The associations of GM lesion load and GM volume with clinical scores were tested. Results DIR-visible GM lesions were most commonly found in the right cerebellum and most apparent in patients with primary progressive MS. Deep GM structures appeared largely free from lesions, but showed considerable atrophy, particularly in the thalamus, caudate, pallidum and putamen, and this was most apparent in secondary progressive patients with MS. Very little co-localisation of GM atrophy and lesions was seen, and this was generally confined to the cerebellum and postcentral gyrus. In both regions, GM lesions and volume independently correlated with physical disability and cognitive performance. Conclusions DIR-detectable GM lesions and GM atrophy do not significantly overlap in the brain but, when they do, they independently contribute to clinical disability.

[1]  David H. Miller,et al.  Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: A voxel-based analysis study , 2015, Multiple sclerosis.

[2]  M. Ron,et al.  The grey matter correlates of impaired decision-making in multiple sclerosis , 2014, Journal of Neurology, Neurosurgery & Psychiatry.

[3]  Simon Hametner,et al.  Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron , 2014, Journal of Neurology, Neurosurgery & Psychiatry.

[4]  Stephen M. Smith,et al.  Permutation inference for the general linear model , 2014, NeuroImage.

[5]  David H. Miller,et al.  Memory in multiple sclerosis is linked to glutamate concentration in grey matter regions , 2014, Journal of Neurology, Neurosurgery & Psychiatry.

[6]  Christine C. Boucard,et al.  White-matter lesions drive deep gray-matter atrophy in early multiple sclerosis: support from structural MRI , 2013, Multiple sclerosis.

[7]  Massimiliano Calabrese,et al.  Measurement and clinical effect of grey matter pathology in multiple sclerosis , 2012, The Lancet Neurology.

[8]  Xavier Golay,et al.  Improved detection of cortical MS lesions with phase-sensitive inversion recovery MRI , 2012, Journal of Neurology, Neurosurgery & Psychiatry.

[9]  F. Barkhof,et al.  Postmortem verification of MS cortical lesion detection with 3D DIR , 2012, Neurology.

[10]  Jeremy D. Schmahmann,et al.  Functional topography of the cerebellum for motor and cognitive tasks: An fMRI study , 2012, NeuroImage.

[11]  Jeffrey A. Cohen,et al.  Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria , 2011, Annals of neurology.

[12]  O. Ciccarelli,et al.  Consensus recommendations for MS cortical lesion scoring using double inversion recovery MRI , 2011, Neurology.

[13]  A Giorgio,et al.  Imaging distribution and frequency of cortical lesions in patients with multiple sclerosis , 2010, Neurology.

[14]  David H. Miller,et al.  Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes , 2010, Journal of magnetic resonance imaging : JMRI.

[15]  M. Filippi,et al.  A 3‐year magnetic resonance imaging study of cortical lesions in relapse‐onset multiple sclerosis , 2009, Annals of neurology.

[16]  Bart Rypma,et al.  Examination of processing speed deficits in multiple sclerosis using functional magnetic resonance imaging , 2009, Journal of the International Neuropsychological Society.

[17]  Joaquín Goñi,et al.  Contribution of white matter lesions to gray matter atrophy in multiple sclerosis: evidence from voxel-based analysis of T1 lesions in the visual pathway. , 2009, Archives of neurology.

[18]  Massimo Filippi,et al.  A voxel-based morphometry study of grey matter loss in MS patients with different clinical phenotypes , 2008, NeuroImage.

[19]  KS Cardinal,et al.  A longitudinal fMRI study of the paced auditory serial addition task , 2008, Multiple sclerosis.

[20]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[21]  Massimo Filippi,et al.  Normal-appearing white and grey matter damage in MS , 2007, Journal of Neurology.

[22]  Chiara Romualdi,et al.  Cortical atrophy is relevant in multiple sclerosis at clinical onset , 2007, Journal of Neurology.

[23]  Ramon Casanova,et al.  Biological parametric mapping: A statistical toolbox for multimodality brain image analysis , 2007, NeuroImage.

[24]  Alan J. Thompson,et al.  Localization of grey matter atrophy in early RRMS , 2006, Journal of Neurology.

[25]  P. Matthews,et al.  Neocortical neuronal, synaptic, and glial loss in multiple sclerosis , 2006, Neurology.

[26]  Mara Cercignani,et al.  Regional gray matter atrophy in early primary progressive multiple sclerosis: a voxel-based morphometry study. , 2006, Archives of neurology.

[27]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[28]  Dieter Vaitl,et al.  Evidence for a direct association between cortical atrophy and cognitive impairment in relapsing–remitting MS , 2006, NeuroImage.

[29]  Frederik Barkhof,et al.  Cortical lesions in multiple sclerosis: combined postmortem MR imaging and histopathology. , 2005, AJNR. American journal of neuroradiology.

[30]  A. Dale,et al.  Focal thinning of the cerebral cortex in multiple sclerosis. , 2003, Brain : a journal of neurology.

[31]  B. Trapp,et al.  Subpial Demyelination in the Cerebral Cortex of Multiple Sclerosis Patients , 2003, Journal of neuropathology and experimental neurology.

[32]  D. Wade,et al.  The Adult Memory and Information Processing Battery (AMIPB) test of information-processing speed: a study of its reliability and feasibility in patients with multiple sclerosis , 2003, Clinical rehabilitation.

[33]  A. Dale,et al.  Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.

[34]  J. Kurtzke Rating neurologic impairment in multiple sclerosis , 1983, Neurology.

[35]  Wenyaw Chan,et al.  Statistical Methods in Medical Research , 2013, Model. Assist. Stat. Appl..

[36]  B. Oken,et al.  Cognition and fatigue in multiple sclerosis: Potential effects of medications with central nervous system activity. , 2006, Journal of rehabilitation research and development.

[37]  D. Purdie Statistical Methods in Medical Research, 4th edn , 2003 .

[38]  Tim Shallice,et al.  The Hayling and Brixton Tests , 1997 .

[39]  G. Huston The Hospital Anxiety and Depression Scale. , 1987, The Journal of rheumatology.