Performance of large language models for CAD-RADS 2.0 classification derived from cardiac CT reports.

Journal: Journal of cardiovascular computed tomography
Published Date:

Abstract

BACKGROUND: The Coronary Artery Disease-Reporting and Data System (CAD-RADS) 2.0 offers standardized guidelines for interpreting coronary artery disease in cardiac CT. Accurate and consistent CAD-RADS 2.0 scoring is crucial for comprehensive disease characterization and clinical decision-making. This study investigates the capability of large language models (LLMs) to autonomously generate CAD-RADS 2.0 scores from cardiac CT reports.

Authors

  • Philipp Georg Arnold
    Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany.
  • Maximilian Frederik Russe
    Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany.
  • Fabian Bamberg
    Department of Diagnostic and Interventional Radiology, University Medical Center Tübingen, Tübingen, Germany.
  • Tilman Emrich
    Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA.
  • Milán Vecsey-Nagy
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary.
  • Ayaat Ashi
    School of Medicine, Cardiff University, Neuadd Meirionnydd, Cardiff, United Kingdom.
  • Dmitrij Kravchenko
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA; Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany.
  • Akos Varga-Szemes
    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.).
  • Martin Soschynski
    Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany.
  • Alexander Rau
    Department of Neuroradiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Elmar Kotter
    Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany.
  • Muhammad Taha Hagar
    Department of Diagnostic and Interventional Radiology, Medical Center, University of Freiburg, Faculty of Medicine, Freiburg, Germany; Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, USA. Electronic address: hagarmu@musc.edus.

Keywords

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