A Deep Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging.

Journal: Investigative radiology
Published Date: Jan 31, 2022

Abstract

OBJECTIVES: Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring of disease course in multiple sclerosis (MS). However, its prognostic value for predicting disease worsening is still being debated. The aim of this study was to propose a deep learning algorithm to predict disease worsening at 2 years of follow-up on a multicenter cohort of MS patients collected from the Italian Neuroimaging Network Initiative using baseline MRI, and compare it with 2 expert physicians.

Authors

  • Loredana Storelli
    From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience.
  • Matteo Azzimonti
  • Mor Gueye
  • Carmen Vizzino
    From the Neuroimaging Research Unit, Division of Neuroscience.
  • Paolo Preziosa
  • Gioachino Tedeschi
    Department of Advanced Medical and Surgical Sciences, and 3T MRI Center, University of Campania "Luigi Vanvitelli," Naples.
  • Nicola De Stefano
    University of Siena, Siena, Italy.
  • Patrizia Pantano
  • Massimo Filippi
    Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Scientific Institute and University Vita-Salute San Raffaele, Milan, Italy.
  • Maria A Rocca
    Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.

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