Clinical utility of a rapid two-dimensional balanced steady-state free precession sequence with deep learning reconstruction.

Journal: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
PMID: 39079600

Abstract

BACKGROUND: Cardiovascular magnetic resonance (CMR) cine imaging is still limited by long acquisition times. This study evaluated the clinical utility of an accelerated two-dimensional (2D) cine sequence with deep learning reconstruction (Sonic DL) to decrease acquisition time without compromising quantitative volumetry or image quality.

Authors

  • Katerina Eyre
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada. Electronic address: katerina.eyre@muhc.mcgill.ca.
  • Moezedin Javad Rafiee
    Department of Medicine and Diagnostic Radiology, McGill University Health Center-Research Institute, Montreal, QC, Canada.
  • Margherita Leo
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada.
  • Junjie Ma
    College of Education and Sports Sciences, Yangtze University, Jingzhou, China.
  • Elizabeth Hillier
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada.
  • Negin Amini
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada.
  • Josephine Pressacco
    Division of Diagnostic Radiology, McGill University Health Centre, Montreal, Quebec, Canada.
  • Martin A Janich
    GE Healthcare, Munich, Germany.
  • Xucheng Zhu
    GE Healthcare, Menlo Park, CA, USA.
  • Matthias G Friedrich
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada; Area19 Medical Inc., Montreal, Canada; Division of Cardiology, McGill University, Montreal, Quebec, Canada.
  • Michael Chetrit
    Research Institute, McGill University Health Centre, Montreal, Quebec, Canada; Division of Cardiology, McGill University, Montreal, Quebec, Canada.

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