Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.

Journal: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
PMID: 38522522

Abstract

BACKGROUND: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images is usually straightforward, but diagnostic uncertainty arises when reporters are not sure whether the observed LGE is genuine or not. This uncertainty might be resolved by repetition (to remove artifact) or further acquisition of intersecting images, but this must take place before the scan finishes. Real-time quality assurance by humans is a complex task requiring training and experience, so being able to identify which images have an intermediate likelihood of LGE while the scan is ongoing, without the presence of an expert is of high value. This decision-support could prompt immediate image optimization or acquisition of supplementary images to confirm or refute the presence of genuine LGE. This could reduce ambiguity in reports.

Authors

  • Sameer Zaman
    Department of Computing, National Heart and Lung Institute, Imperial College London, Imperial College Healthcare NHS Trust, London, UK.
  • Kavitha Vimalesvaran
    Imperial College London (J.P.H., C.C.S., G.D.C., K.A., K.V., D.P.F., M.J.S.-S.).
  • Digby Chappell
    Imperial College London, Exhibition Road, London, SW7 2AZ, UK.
  • Marta Varela
    National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Nicholas S Peters
    National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Road, W12 0HS, London, UK.
  • Hunain Shiwani
    Cardiac Imaging Department, Barts Heart Centre, St Bartholomew's Hospital, London, UK.
  • Kristopher D Knott
    Cardiac Imaging Department, Barts Heart Centre, St Bartholomew's Hospital, London, UK; Institute of Cardiovascular Science, University College London, London, UK.
  • Rhodri H Davies
    Cardiac Imaging Department, Barts Heart Centre, St Bartholomew's Hospital, London, UK; Institute of Cardiovascular Science, University College London, London, UK.
  • James C Moon
    Cardiac Imaging Department, Barts Heart Centre, St Bartholomew's Hospital, London, UK; Institute of Cardiovascular Science, University College London, London, UK. Electronic address: j.moon@ucl.ac.uk.
  • Anil A Bharath
    Department of Bioengineering, Imperial College London, London, United Kingdom.
  • Nick Wf Linton
    Imperial College Healthcare NHS Trust, London W12 0HS, UK; Department of Bioengineering, Imperial College London, London SW7 2AZ, UK. Electronic address: n.linton@imperial.ac.uk.
  • Darrel P Francis
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Graham D Cole
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • James P Howard
    Department of Cardiology, National Heart and Lung Institute, Imperial College London, London, United Kingdom. Electronic address: jphoward@doctors.org.uk.

Keywords

External Resources

Popular Topics
Recent Journals