Opportunities for Understanding MS Mechanisms and Progression With MRI Using Large-Scale Data Sharing and Artificial Intelligence.

Journal: Neurology
Published Date: Oct 4, 2021

Abstract

Patients with multiple sclerosis (MS) have heterogeneous clinical presentations, symptoms, and progression over time, making MS difficult to assess and comprehend in vivo. The combination of large-scale data sharing and artificial intelligence creates new opportunities for monitoring and understanding MS using MRI. First, development of validated MS-specific image analysis methods can be boosted by verified reference, test, and benchmark imaging data. Using detailed expert annotations, artificial intelligence algorithms can be trained on such MS-specific data. Second, understanding disease processes could be greatly advanced through shared data of large MS cohorts with clinical, demographic, and treatment information. Relevant patterns in such data that may be imperceptible to a human observer could be detected through artificial intelligence techniques. This applies from image analysis (lesions, atrophy, or functional network changes) to large multidomain datasets (imaging, cognition, clinical disability, genetics). After reviewing data sharing and artificial intelligence, we highlight 3 areas that offer strong opportunities for making advances in the next few years: crowdsourcing, personal data protection, and organized analysis challenges. Difficulties as well as specific recommendations to overcome them are discussed, in order to best leverage data sharing and artificial intelligence to improve image analysis, imaging, and the understanding of MS.

Authors

  • Hugo Vrenken
    VU University Medical Center, Amsterdam, The Netherlands.
  • Mark Jenkinson
    Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Dzung L Pham
    Clinical Center, National Institutes of Health, Bethesda MD 20814, USA.
  • Charles R G Guttmann
    Partners MS Center, Brigham and Women's Hospital, Brookline, Massachusetts, United States of America.
  • Deborah Pareto
    Magnetic Resonance Unit, Dept of Radiology, Vall d'Hebron University Hospital, Spain.
  • Michel Paardekooper
    From the MS Center Amsterdam (H.V., A.d.S., V.W.), Amsterdam Neuroscience, Department of Radiology and Nuclear Medicine, Amsterdam UMC (M.P.), the Netherlands; Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB (M.J.), Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, UK; Human Imaging and Image Processing Core (D.L.P.), Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation, Bethesda, MD; Center for Neurological Imaging (C.R.G.G.), Department of Radiology, Brigham and Women's Hospital, Boston, MA; Section of Neuroradiology (Department of Radiology) (D.P.), Vall d'Hebron University Hospital and Research Institute (VHIR), Autonomous University Barcelona, Spain; Neuroimaging Research Unit (M.A.R.), Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; AMIGO (M.J.C.), School of Biomedical Engineering and Imaging Sciences, King's College London; and Institutes of Neurology & Healthcare Engineering (F.B.), UCL London, UK.
  • Alexandra de Sitter
    From the MS Center Amsterdam (H.V., A.d.S., V.W.), Amsterdam Neuroscience, Department of Radiology and Nuclear Medicine, Amsterdam UMC (M.P.), the Netherlands; Wellcome Centre for Integrative Neuroimaging (WIN), FMRIB (M.J.), Nuffield Department of Clinical Neurosciences (NDCN), University of Oxford, UK; Human Imaging and Image Processing Core (D.L.P.), Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation, Bethesda, MD; Center for Neurological Imaging (C.R.G.G.), Department of Radiology, Brigham and Women's Hospital, Boston, MA; Section of Neuroradiology (Department of Radiology) (D.P.), Vall d'Hebron University Hospital and Research Institute (VHIR), Autonomous University Barcelona, Spain; Neuroimaging Research Unit (M.A.R.), Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; AMIGO (M.J.C.), School of Biomedical Engineering and Imaging Sciences, King's College London; and Institutes of Neurology & Healthcare Engineering (F.B.), UCL London, UK.
  • Maria A Rocca
    Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
  • Viktor Wottschel
    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Location VUmc, Amsterdam, The Netherlands; Queen Square MS Centre, University College London, London, United Kingdom. Electronic address: v.wottschel@amsterdamumc.nl.
  • M Jorge Cardoso
    Department of Biomedical EngineeringSchool of Biomedical Engineering and Imaging SciencesKing's College London WC2R 2LS London U.K.
  • Frederik Barkhof
    MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands.

Keywords

External Resources

Popular Topics
Recent Journals