Relationship of grey and white matter abnormalities with distance from the surface of the brain in multiple sclerosis.
OBJECTIVE
To assess the association between proximity to the inner (ventricular and aqueductal) and outer (pial) surfaces of the brain and the distribution of normal appearing white matter (NAWM) and grey matter (GM) abnormalities, and white matter (WM) lesions, in multiple sclerosis (MS).


METHODS
67 people with relapse-onset MS and 30 healthy controls were included in the study. Volumetric T1 images and high-resolution (1 mm3) magnetisation transfer ratio (MTR) images were acquired and segmented into 12 bands between the inner and outer surfaces of the brain. The first and last bands were discarded to limit partial volume effects with cerebrospinal fluid. MTR values were computed for all bands in supratentorial NAWM, cerebellar NAWM and brainstem NA tissue, and deep and cortical GM. Band WM lesion volumes were also measured.


RESULTS
Proximity to the ventricular surfaces was associated with progressively lower MTR values in the MS group but not in controls in supratentorial and cerebellar NAWM, brainstem NA and in deep and cortical GM. The density of WM lesions was associated with proximity to the ventricles only in the supratentorial compartment, and no link was found with distance from the pial surfaces.


CONCLUSIONS
In MS, MTR abnormalities in NAWM and GM are related to distance from the inner and outer surfaces of the brain, and this suggests that there is a common factor underlying their spatial distribution. A similar pattern was not found for WM lesions, raising the possibility that different factors promote their formation.
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa and IRCCS AOU San Martino-IST, Genoa, Italy.
Matteo
M
Pardini
Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK.
Carole H
CH
Sudre
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK.
Ferran
F
Prados
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Department of Neurology, University Hospital Basel, Basel, Switzerland.
Özgür
Ö
Yaldizli
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK.
Varun
V
Sethi
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK School of Psychology and Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK School of Psychological Sciences, University of Manchester, Manchester UK.
Nils
N
Muhlert
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK.
Rebecca S
RS
Samson
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK.
Steven H
SH
van de Pavert
Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK.
M Jorge
MJ
Cardoso
Department of Medical Physics and Bioengineering, Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK Dementia Research Centre, UCL Institute of Neurology, London, UK.
Sebastien
S
Ourselin
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK Brain MRI 3T Center, C. Mondino National Neurological Institute, Pavia, Italy Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy.
Claudia A M
CA
Gandini Wheeler-Kingshott
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.
David H
DH
Miller
Department of Neuroinflammation, NMR Research Unit, Queen Square MS Centre, UCL Institute of Neurology, London, UK National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre, London, UK.
Declan T
DT
Chard
D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging* / Q000473:pathology*; D001931:Brain Mapping; D001933:Brain Stem / Q000000981:diagnostic imaging / Q000473:pathology; D002531:Cerebellum / Q000000981:diagnostic imaging / Q000473:pathology; D002535:Cerebral Aqueduct / Q000000981:diagnostic imaging; D002540:Cerebral Cortex / Q000000981:diagnostic imaging / Q000473:pathology; D002552:Cerebral Ventricles / Q000000981:diagnostic imaging; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D005260:Female; D066128:Gray Matter / Q000000981:diagnostic imaging* / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D020529:Multiple Sclerosis, Relapsing-Remitting / Q000000981:diagnostic imaging* / Q000473:pathology*; D010841:Pia Mater / Q000000981:diagnostic imaging / Q000473:pathology; D012016:Reference Values; D066127:White Matter / Q000000981:diagnostic imaging* / Q000473:pathology*