Thoracic Aortic Aneurysm Risk Assessment: A Machine Learning Approach.

Journal: JACC. Advances
Published Date: Sep 28, 2023

Abstract

BACKGROUND: Traditional methods of risk assessment for thoracic aortic aneurysm (TAA) based on aneurysm size alone have been called into question as being unreliable in predicting complications. Biomechanical function of aortic tissue may be a better predictor of risk, but it is difficult to determine in vivo.

Authors

  • Lauren Kennedy
    Department of Chemical Engineering, McGill University, Montreal, Quebec, Canada.
  • Kevin Bates
    Department of Chemical Engineering, McGill University, Montreal, Quebec, Canada.
  • Judith Therrien
    Division of Cardiology, McGill University Health Centre, Montreal, Quebec, Canada.
  • Yoni Grossman
    Division of Cardiology, McGill University Health Centre, Montreal, Quebec, Canada.
  • Masaki Kodaira
    Division of Cardiology, McGill University Health Centre, Montreal, Quebec, Canada.
  • Josephine Pressacco
    Division of Diagnostic Radiology, McGill University Health Centre, Montreal, Quebec, Canada.
  • Anthony Rosati
    Department of Chemical Engineering, McGill University, Montreal, Quebec, Canada.
  • François Dagenais
    Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec, Quebec, Canada.
  • Richard L Leask
    Department of Chemical Engineering, McGill University, Montreal, Quebec, Canada.
  • Kevin Lachapelle
    Division of Cardiac Surgery, McGill University Health Centre, Montreal, Quebec, Canada.

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