AI-augmented reconstruction provides improved image quality and enables shorter breath-holds in contrast-enhanced liver MRI.

Journal: European radiology experimental
PMID: 40310491

Abstract

BACKGROUND: To compare liver image quality and lesion detection using an AI-augmented T1-weighted sequence on hepatobiliary-phase gadoxetate-enhanced magnetic resonance imaging (MRI).

Authors

  • Francesca Castagnoli
    Department of Radiology, Royal Marsden Hospital, London, UK. francesca.castagnoli@rmh.nhs.uk.
  • Mihaela Rata
    Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
  • Joshua Shur
    Department of Radiology, Royal Marsden Hospital, London, UK.
  • Georgina Hopkinson
    Department of Radiology, Royal Marsden Hospital, London, UK.
  • Alison Macdonald
    Department of Radiology, Royal Marsden Hospital, London, UK.
  • David Stockton
    Department of Radiology, Royal Marsden Hospital, London, UK.
  • Marcel Dominik Nickel
    MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany.
  • Stephan Kannengiesser
    MR Application Predevelopment, Siemens Healthineers AG, Erlangen, Germany.
  • Christina Messiou
    Department of Radiology, Royal Marsden Hospital, Sutton, UK.
  • Dow-Mu Koh
    Department of Radiology, Royal Marsden Hospital, Sutton, UK.
  • Jessica Mary Winfield
    Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.

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