Automated quantification of T1 and T2 relaxation times in liver mpMRI using deep learning: a sequence-adaptive approach.

Journal: European radiology experimental
Published Date: Jun 14, 2025

Abstract

OBJECTIVES: To evaluate a deep learning sequence-adaptive liver multiparametric MRI (mpMRI) assessment with validation in different populations using total and segmental T1 and T2 relaxation time maps.

Authors

  • Lukas Zbinden
    ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, 3008, Bern, Switzerland.
  • Samuel Erb
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Bern, Switzerland.
  • Damiano Catucci
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Freiburgstrasse 10, 3010, Bern, Switzerland.
  • Lars Doorenbos
    ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
  • Leona Hulbert
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Bern, Switzerland.
  • Annalisa Berzigotti
    Hepatology, University Clinic for Visceral Surgery and Medicine, Berne-Inselspital, Switzerland.
  • Michael Brönimann
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Bern, Switzerland.
  • Lukas Ebner
  • Andreas Christe
  • Verena Carola Obmann
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Freiburgstrasse 10, 3010, Bern, Switzerland.
  • Raphael Sznitman
    ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
  • Adrian Thomas Huber
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, Freiburgstrasse 10, 3010, Bern, Switzerland. adrian.huber@insel.ch.

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