Reduced neurite density in the brain and cervical spinal cord in relapsing-remitting multiple sclerosis: A NODDI study.


Journal

Multiple sclerosis (Houndmills, Basingstoke, England)
ISSN: 1477-0970
Titre abrégé: Mult Scler
Pays: England
ID NLM: 9509185

Informations de publication

Date de publication:
11 2020
Historique:
pubmed: 5 11 2019
medline: 25 9 2021
entrez: 5 11 2019
Statut: ppublish

Résumé

Multiple sclerosis (MS) affects both brain and spinal cord. However, studies of the neuraxis with advanced magnetic resonance imaging (MRI) are rare because of long acquisition times. We investigated neurodegeneration in MS brain and cervical spinal cord using neurite orientation dispersion and density imaging (NODDI). The aim of this study was to investigate possible alterations, and their clinical relevance, in neurite morphology along the brain and cervical spinal cord of relapsing-remitting MS (RRMS) patients. In total, 28 RRMS patients and 20 healthy controls (HCs) underwent brain and spinal cord NODDI at 3T. Physical and cognitive disability was assessed. Individual maps of orientation dispersion index (ODI) and neurite density index (NDI) in brain and spinal cord were obtained. We examined differences in NODDI measures between groups and the relationships between NODDI metrics and clinical scores using linear regression models adjusted for age, sex and brain tissue volumes or cord cross-sectional area (CSA). Patients showed lower NDI in the brain normal-appearing white matter (WM) and spinal cord WM than HCs. In patients, a lower NDI in the spinal cord WM was associated with higher disability. Reduced neurite density occurs in the neuraxis but, especially when affecting the spinal cord, it may represent a mechanism of disability in MS.

Sections du résumé

BACKGROUND
Multiple sclerosis (MS) affects both brain and spinal cord. However, studies of the neuraxis with advanced magnetic resonance imaging (MRI) are rare because of long acquisition times. We investigated neurodegeneration in MS brain and cervical spinal cord using neurite orientation dispersion and density imaging (NODDI).
OBJECTIVE
The aim of this study was to investigate possible alterations, and their clinical relevance, in neurite morphology along the brain and cervical spinal cord of relapsing-remitting MS (RRMS) patients.
METHODS
In total, 28 RRMS patients and 20 healthy controls (HCs) underwent brain and spinal cord NODDI at 3T. Physical and cognitive disability was assessed. Individual maps of orientation dispersion index (ODI) and neurite density index (NDI) in brain and spinal cord were obtained. We examined differences in NODDI measures between groups and the relationships between NODDI metrics and clinical scores using linear regression models adjusted for age, sex and brain tissue volumes or cord cross-sectional area (CSA).
RESULTS
Patients showed lower NDI in the brain normal-appearing white matter (WM) and spinal cord WM than HCs. In patients, a lower NDI in the spinal cord WM was associated with higher disability.
CONCLUSION
Reduced neurite density occurs in the neuraxis but, especially when affecting the spinal cord, it may represent a mechanism of disability in MS.

Identifiants

pubmed: 31682198
doi: 10.1177/1352458519885107
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1647-1657

Subventions

Organisme : Medical Research Council
ID : MR/S026088/1
Pays : United Kingdom

Auteurs

Sara Collorone (S)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK.

Niamh Cawley (N)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK.

Francesco Grussu (F)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.

Ferran Prados (F)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.

Francesca Tona (F)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK.

Alberto Calvi (A)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Department of Pathophysiology and Transplantation, Neurodegenerative Disease Unit, La Fondazione IRCCS Ospedale Maggiore Policlinico Mangiagalli e Regina Elena, University of Milan, Milan, Italy.

Baris Kanber (B)

Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.

Torben Schneider (T)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Philips UK, Guildford, UK.

Lucas Kipp (L)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Stanford MS Center, Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA.

Hui Zhang (H)

Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.

Daniel C Alexander (DC)

Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK.

Alan J Thompson (AJ)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK.

Ahmed Toosy (A)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK.

Claudia Am Gandini Wheeler-Kingshott (CAG)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy/Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy.

Olga Ciccarelli (O)

NMR Research Unit, Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Institute of Neurology, Faculty of Brain Sciences, University College London (UCL), London, UK/National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK.

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