Artificial Intelligence Applications in Cardiac CT Imaging for Ischemic Disease Assessment.

Journal: Echocardiography (Mount Kisco, N.Y.)
PMID: 39927866

Abstract

Artificial intelligence (AI) has transformed medical imaging by detecting insights and patterns often imperceptible to the human eye, enhancing diagnostic accuracy and efficiency. In cardiovascular imaging, numerous AI models have been developed for cardiac computed tomography (CCT), a primary tool for assessing coronary artery disease (CAD). CCT provides comprehensive, non-invasive assessment, including plaque burden, stenosis severity, and functional assessments such as CT-derived fractional flow reserve (FFRct). Its prognostic value in predicting major adverse cardiovascular events (MACE) has increased the demand for CCT, consequently adding to radiologists' workloads. This review aims to examine AI's role in CCT for ischemic heart disease, highlighting its potential to streamline workflows and improve the efficiency of cardiac care through machine learning and deep learning applications.

Authors

  • Gianluca G Siciliano
    Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
  • Carlotta Onnis
    Translational Laboratory for Cardiothoracic Imaging and Artificial Intelligence, Department of Radiology and Imaging Sciences, Emory University, 100 Woodruff Circle, Atlanta, GA 30322, USA; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari-Polo di Monserrato, SS 554 km 4,500 Monserrato, Cagliari 09042, Italy. Electronic address: https://twitter.com/CarlottaOnnis.
  • Jaret Barr
    Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
  • Marly van Assen
    Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
  • Carlo N De Cecco
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260 (S.S.M., D.M., M.v.A., C.N.D.C., R.R.B., C.T., A.V.S., A.M.F., B.E.J., L.P.G., U.J.S.); Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany (S.S.M., T.J.V.); Stanford University School of Medicine, Department of Radiology, Stanford, Calif (D.M.); Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (C.N.D.C.); Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC (R.R.B.); Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany (C.T.); Department of Cardiology, Munich University Clinic, Ludwig-Maximilians-University, Munich, Germany (C.T.); Siemens Medical Solutions USA, Malvern, Pa (P.S.); and Department of Emergency Medicine, Medical University of South Carolina, Charleston, SC (A.J.M.).

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