Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition.

Journal: Osteoarthritis and cartilage
Published Date: Feb 3, 2021

Abstract

BACKGROUND: Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely disabling disease with high prevalence and considerable socioeconomic and individual burden. Early, potentially reversible cartilage degeneration is characterized by distinct changes in cartilage composition and ultrastructure, while the tissue's morphology remains largely unaltered. Hence, early degenerative changes may not be diagnosed by clinical standard diagnostic tools.

Authors

  • K Linka
    Institute of Continuum and Materials Mechanics, Hamburg University of Technology, Hamburg, 21073, Germany. Electronic address: kevin.linka@tuhh.de.
  • J Thüring
    Department of Diagnostic and Interventional Radiology, Aachen University Hospital, Aachen, 52074, Germany. Electronic address: jthuering@ukaachen.de.
  • L Rieppo
    Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Finland. Electronic address: lassi.rieppo@oulu.fi.
  • R C Aydin
    Institute of Materials Research, Materials Mechanics, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany. Electronic address: Roland.Aydin@hzg.de.
  • C J Cyron
    Institute of Continuum and Materials Mechanics, Hamburg University of Technology, Hamburg, 21073, Germany; Institute of Materials Research, Materials Mechanics, Helmholtz-Zentrum Geesthacht, Geesthacht, Germany. Electronic address: christian.cyron@tuhh.de.
  • C Kuhl
    Department of Diagnostic and Interventional Radiology, Aachen University Hospital, Aachen, 52074, Germany. Electronic address: ckuhl@ukaachen.de.
  • D Merhof
    Institute of Imaging & Computer Vision, RWTH Aachen University, 52074 Aachen, Germany.
  • D Truhn
    Department of Diagnostic and Interventional Radiology, Aachen University Hospital, Aachen, 52074, Germany; Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, 52074, Germany. Electronic address: dtruhn@ukaachen.de.
  • S Nebelung
    Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Dusseldorf, 40225, Dusseldorf, Germany. Electronic address: snebelung@ukaachen.de.

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