Detection of late gadolinium enhancement in patients with hypertrophic cardiomyopathy using machine learning.

Journal: International journal of cardiology
PMID: 39706305

Abstract

BACKGROUND: Late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) in hypertrophic cardiomyopathy (HCM) typically represents myocardial fibrosis and may lead to fatal ventricular arrhythmias. However, CMR is resource-intensive and sometimes contraindicated. Thus, in patients with HCM, we aimed to detect LGE on CMR by applying machine learning (ML) algorithm to clinical parameters.

Authors

  • Keitaro Akita
    Division of Cardiology, Internal Medicine III, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Kenichiro Suwa
    Division of Cardiology, Internal Medicine 3, Hamamatsu University School of Medicine, Hamamatsu, Japan.
  • Kazuto Ohno
    Division of Cardiology, Internal Medicine III, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Shepard D Weiner
    Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.
  • Albree Tower-Rader
    Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Michael A Fifer
    Cardiology Division, Department of Medicine (M.A.F.), Massachusetts General Hospital, Boston.
  • Yuichiro Maekawa
    Department of Cardiology, Internal Medicine III, Hamamatsu University School of Medicine, Hamamatsu, Japan.
  • Yuichi J Shimada
    Division of Cardiology, Department of Medicine (L.W.L., M.S.M., M.P.R., Y.J.S.), Columbia University Irving Medical Center, New York, NY.

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