Deep Learning-Derived Myocardial Strain.

Journal: JACC. Cardiovascular imaging
PMID: 38551533

Abstract

BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GLS) from standard echocardiography B-mode images would greatly improve post hoc research applications and may streamline patient analyses.

Authors

  • Alan C Kwan
    Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
  • Ernest W Chang
    Leon H. Charney Division of Cardiology, Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA.
  • Ishan Jain
  • John Theurer
    Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, 90048.
  • Xiu Tang
    Department of Cardiovascular Medicine, Stanford University, Stanford, CA, USA.
  • Nadia Francisco
    Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.
  • Francois Haddad
    Division of Cardiovascular Medicine (F.H.), in the Department of Medicine, Stanford University, CA.
  • David Liang
  • Alexandra Fábián
    Heart and Vascular Center, Semmelweis University, Budapest, Hungary.
  • Andrea Ferencz
    Heart and Vascular Center, Semmelweis University, Budapest, Hungary.
  • Neal Yuan
    Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Béla Merkely
    From the MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, 68 Varosmajor St, 1122 Budapest, Hungary (M.K., J.K., B.M., P.M.H.); Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (J.K., Y.K., A.I., M.T.L., B.F., H.J.A., U.H.); Center for Cause of Death Investigation, Faculty of Medicine, Hokkaido University, Hokkaido, Japan (Y.K.); Department for Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Freiburg, Germany (C.L.S.); and Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass (H.J.A.).
  • Robert Siegel
    Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Susan Cheng
    Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA.
  • Attila Kovács
    University of Szeged, Interdisciplinary Excellence Centre, Hungary.
  • Márton Tokodi
    Division of Cardiology, West Virginia University Heart & Vascular Institute, Morgantown, West Virginia.
  • David Ouyang
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.

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