Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis.

Journal: RMD open
Published Date: Jun 25, 2025

Abstract

INTRODUCTION: Systemic sclerosis (SSc) is a complex inflammatory vasculopathy with diverse symptoms and variable disease progression. Despite its known impact on body composition (BC), clinical decision-making has yet to incorporate these biomarkers. This study aims to extract quantitative BC imaging biomarkers from CT scans to assess disease severity, define BC phenotypes, track changes over time and predict survival.

Authors

  • Malte Maria Sieren
    Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany. malte.sieren@uksh.de.
  • Hanna Grasshoff
    Department of Rheumatology and Clinical Immunology, University Hospital Schleswig Holstein, Lübeck Campus, Lubeck, Schleswig-Holstein, Germany.
  • Gabriela Riemekasten
    Clinic for Rheumatology and Clinical Immunology, University Medical Center Schleswig Holstein Campus Lübeck, 23538 Lübeck, Germany.
  • Lennart Berkel
  • Felix Nensa
    Institute for AI in Medicine (IKIM), University Hospital Essen, 45131 Essen, Germany.
  • René Hosch
    Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Germany.
  • Jörg Barkhausen
    Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein (UKSH) Lübeck, Lübeck, Germany.
  • Roman Kloeckner
    Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Germany.
  • Franz Wegner
    Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.

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