Feed-forward neural networks using cerebral MR spectroscopy and DTI might predict neurodevelopmental outcome in preterm neonates.

Journal: European radiology
PMID: 32683551

Abstract

OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-MRS) and diffusion tensor imaging (DTI) at term-equivalent age (TEA).

Authors

  • T Janjic
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria. tanja.janjic@i-med.ac.at.
  • S Pereverzyev
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
  • M Hammerl
    Department of Paediatrics II, Neonatology, Medical University of Innsbruck, Innsbruck, Austria.
  • V Neubauer
    Department of Paediatrics II, Neonatology, Medical University of Innsbruck, Innsbruck, Austria.
  • H Lerchner
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
  • V Wallner
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
  • R Steiger
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
  • U Kiechl-Kohlendorfer
    Department of Paediatrics II, Neonatology, Medical University of Innsbruck, Innsbruck, Austria.
  • M Zimmermann
    Department of Paediatrics II, Neonatology, Medical University of Innsbruck, Innsbruck, Austria.
  • A Buchheim
    Institute of Psychology, University of Innsbruck, Innsbruck, Austria.
  • A E Grams
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.
  • E R Gizewski
    Department of Neuroradiology, Medical University of Innsbruck, Anichstraße 35, 6020, Innsbruck, Austria.

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