Deep learning for standardized, MRI-based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema.

Journal: European radiology
Published Date: Feb 1, 2023

Abstract

OBJECTIVES: To contribute to a more in-depth assessment of shape, volume, and asymmetry of the lower extremities in patients with lipedema or lymphedema utilizing volume information from MR imaging.

Authors

  • Sebastian Nowak
    From the Quantitative Imaging Lab, Department of Radiology.
  • Andreas Henkel
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
  • Maike Theis
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
  • Julian Luetkens
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
  • Sergej Geiger
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
  • Alois M Sprinkart
    From the Quantitative Imaging Lab, Department of Radiology.
  • Claus C Pieper
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
  • Ulrike I Attenberger
    Department of Diagnostic and Interventional Radiology, Quantitative Imaging Lab Bonn (QILaB), University Hospital Bonn (Universitätsklinikum Bonn), Venusberg-Campus 1, 53127, Bonn, Germany.

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