Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial.

Journal: JMIR research protocols
Published Date: May 21, 2025

Abstract

BACKGROUND: Invasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rare but serious risks including myocardial infarction, stroke, major bleeding, and death. A large proportion of elective outpatients undergoing ICA have nonobstructive CAD, highlighting the suboptimal use of this test. Coronary computed tomographic angiography (CCTA) is a noninvasive option that provides similar information with less risk and is recommended as a first-line test for patients with low-to-intermediate risk of CAD. Leveraging artificial intelligence (AI) to appropriately direct patients to ICA or CCTA based on the predicted probability of disease may improve the efficiency and safety of diagnostic pathways.

Authors

  • Jeremy Petch
    Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Canada.
  • Juan Pablo Tabja Bortesi
    Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.
  • Tej Sheth
    Division of Cardiology, Hamilton General Hospital, Hamilton Health Sciences, McMaster University, Hamilton, ON, Canada.
  • Madhu Natarajan
    Population Health Research Institute, Hamilton, ON, Canada.
  • Natalia Pinilla-Echeverri
    Division of Cardiology, Hamilton General Hospital, Hamilton Health Sciences, McMaster University, Hamilton, ON, Canada.
  • Shuang Di
    Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, Canada.
  • Shrikant I Bangdiwala
    Population Health Research Institute, McMaster University, Canada; Department of Health Research Methods, Evidence, and Impact, McMaster University, Canada. Electronic address: shrikant.bangdiwala@phri.ca.
  • Karen Mosleh
    Centre for Evidence-Based Implementation, Hamilton Health Sciences, Hamilton, ON, Canada.
  • Omar Ibrahim
  • Kevin R Bainey
    Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada.
  • Julian Dobranowski
    Department of Medical Imaging, McMaster University, Hamilton, ON, Canada.
  • Maria P Becerra
    Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.
  • Katie Sonier
    Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.
  • Jon-David Schwalm
    Population Health Research Institute, Hamilton, ON, Canada.

Keywords

External Resources

Popular Topics
Recent Journals