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Related Concept Videos

Multiple Sclerosis l: Introduction01:19

Multiple Sclerosis l: Introduction

Multiple sclerosis is a chronic autoimmune disease of the central nervous system (CNS) that affects the brain, spinal cord, and optic nerves. It is an inflammatory demyelinating disorder and a leading cause of neurological disability in young adults.EpidemiologyMS commonly begins between 20 and 40 years of age and is twice as common in women. Its exact cause remains unclear, but genetic susceptibility contributes, with higher risk in first-degree relatives and identical twins. A greater...

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Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease

Giuseppe Pontillo1, Ferran Prados1, Jordan Colman1

  • 1From the Queen Square Multiple Sclerosis Centre (G.P., F.P., J.C., B.K., O.A.-M., S.A.-A., A. Bianchi, W.J.B., R. Christensen, E.C., S. Collorone, M.A.F., Y.H., A.H., S. Mohamud, R.N., A.T.T., J.W., C.Y., O.C., F.B.), Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, United Kingdom; MS Center Amsterdam (G.P., H.V., F.B.), Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Departments of Advanced Biomedical Sciences and Electrical Engineering and Information Technology (G.P., A. Brunetti, S. Cocozza), University of Naples "Federico II," Italy; Centre for Medical Image Computing (F.P., B.K., F.B.), Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; E-Health Center (F.P.), Universitat Oberta de Catalunya, Barcelona, Spain; Institute of Neuroradiology (B.B., C.L.), St. Josef Hospital, Ruhr-University Bochum, Germany; Department of Advanced Medical and Surgical Sciences (A. Bisecco, A.G.), University of Campania "Luigi Vanvitelli," Naples, Italy; Translational Imaging in Neurology (ThINK) Basel (A.C., C. Granziera), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, University of Basel; Neurologic Clinic and Policlinic (A.C., C. Granziera, J.K.), MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Switzerland; Department of Neurosciences, Biomedicine and Movement Sciences (M. Calabrese, M. Castellaro), University of Verona; Department of Information Engineering (M. Castellaro), University of Padova; Department of Medicine, Surgery and Neuroscience (R. Cortese, N.D.S.), University of Siena, Italy; Department of Neurology (C.E., D.P.), Medical University of Graz, Austria; Neuroimaging Research Unit (M.F., M.A.R., P.V.), Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Neurology Unit, Neurorehabilitation Unit, Neurophysiology Service, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.F., M.A.R., P.V.), Milan; Department of Neurosciences (C. Gasperini, S.R.), San Camillo-Forlanini Hospital, Rome, Italy; Department of Neurology (G.G.-E., S.G.), Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (H.F.F.H., E.A.H., G.O.N.), Oslo University Hospital; Institute of Clinical Medicine (H.F.F.H., E.A.H., G.O.N.), and Department of Psychology (E.A.H.), University of Oslo, Norway; Neuroimmunology and Multiple Sclerosis Unit Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM) (S.L., E.M.-H.), Hospital Clinic Barcelona, Fundació de Recerca Clínic Barcelona-Institut d'Investigacions Biomèdiques August Pi i Su, Barcelona, Spain; Department of Neurology (C.L.), St. Josef Hospital, Ruhr-University Bochum, Germany; Nuffield Department of Clinical Neurosciences (S. Messina, J.P.), University of Oxford, United Kingdom; Department of Molecular Medicine and Medical Biotechnology (M.M.), and Department of Neurosciences and Reproductive and Odontostomatological Sciences (M.P.), University of Naples "Federico II"; Department of Human Neurosciences (M.P.), Sapienza University of Rome, Italy; Section of Neuroradiology (A.R.), Department of Radiology, and Centre d'Esclerosi Múltiple de Catalunya (Cemcat) (J.S.-G.), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain; MS Center Amsterdam (E.M.M.S.), Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Department of Neurology and Center of Clinical Neuroscience (T.U.), and Department of Radiology (M.V.), First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic; MS Center Amsterdam (M.M.S.), Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC location VUmc, the Netherlands; Centre for Medical Image Computing (J.H.C.), Department of Computer Science, and Dementia Research Centre (J.H.C., F.B.), UCL Queen Square Institute of Neurology, University College London, United Kingdom.

Neurology
|November 4, 2024
PubMed
Summary

A new brain-predicted disease duration gap (DD gap) model for multiple sclerosis (MS) shows sensitivity to MS lesions and brain atrophy. This MS-specific biomarker complements brain-age gap analysis in explaining physical disability progression.

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence in Medicine
  • Neurology

Background:

  • Differentiating normal brain aging from neurodegeneration in multiple sclerosis (MS) is crucial.
  • The brain-age paradigm may not fully capture MS-specific pathological changes.
  • Developing disease-specific biomarkers is essential for understanding MS progression.

Purpose of the Study:

  • To investigate a disease-specific model to complement the brain-age gap (BAG) in patients with MS.
  • To develop and validate a brain-predicted disease duration gap (DD gap) as a measure of MS-specific brain damage.
  • To assess the relationship between the DD gap, BAG, and physical disability.

Main Methods:

  • Retrospective analysis of 3D T1-weighted brain MRI scans from a large multicentric cohort of patients with MS (PwMS).
  • Training a 3D DenseNet model to predict disease duration (DD) and using DeepBrainNet for age prediction.
  • Validation of the DD gap against Expanded Disability Status Scale (EDSS) scores cross-sectionally and longitudinally.

Main Results:

  • The DD gap model showed sensitivity to MS lesions and brain atrophy, unlike the brain-age model.
  • The DD gap significantly explained physical disability (EDSS) changes, both cross-sectionally and longitudinally.
  • The DD gap provided incremental value in explaining disability worsening compared to BAG alone.

Conclusions:

  • The brain-predicted DD gap is a sensitive, MS-specific biomarker reflecting disease severity and progression.
  • This DD gap measure complements the brain-age paradigm in assessing physical disability in MS.
  • The DD gap holds potential for clinical use in monitoring MS disease severity and progression.