Prognostic value of a novel artificial intelligence-based coronary computed tomography angiography-derived ischaemia algorithm for patients with suspected coronary artery disease.

Journal: European heart journal. Cardiovascular Imaging
Published Date:

Abstract

AIMS: Coronary computed tomography angiography (CTA) imaging is used to diagnose patients with suspected coronary artery disease (CAD). A novel artificial intelligence-guided quantitative computed tomography ischaemia algorithm (AI-QCTischaemia) aims to identify myocardial ischaemia directly from CTA images and may be helpful to improve risk stratification. The aims were to investigate (i) the prognostic value of AI-QCTischaemia amongst symptomatic patients with suspected CAD entering diagnostic imaging with coronary CTA and (ii) the prognostic value of AI-QCTischaemia separately amongst patients with no/non-obstructive CAD (≤50% visual diameter stenosis) and obstructive CAD (>50% visual diameter stenosis).

Authors

  • Sarah Bär
    Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Department of Cardiology, Bern University Hospital Inselspital, Bern, Switzerland.
  • Takeru Nabeta
    Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Teemu Maaniitty
    Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Department of Clinical Physiology, Nuclear Medicine, and PET, Turku University Hospital, Turku, Finland.
  • Antti Saraste
    Heart Center, Turku University Hospital, University of Turku, Turku, Finland.
  • Jeroen J Bax
    Departments of Cardiology, Heart Lung Centre, Leiden University Medical Center, Leiden, The Netherlands.
  • James P Earls
    Cleerly inc., New York, United States.
  • James K Min
    3 Department of Radiology, Weill Cornell Medicine , New York, New York.
  • Juhani Knuuti
    Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.