Assessing the diagnostic accuracy and prognostic utility of artificial intelligence detection and grading of coronary artery calcification on nongated computed tomography (CT) thorax.

Journal: Clinical radiology
Published Date: Mar 22, 2025

Abstract

AIMS: This study assessed the diagnostic accuracy and prognostic implications of an artificial intelligence (AI) tool for coronary artery calcification (CAC) assessment on nongated, noncontrast thoracic computed tomography (CT).

Authors

  • B Shear
    University of Bristol, Beacon House, Queens Rd, Bristol BS8 1QU, UK.
  • J Graby
    Department of Cardiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK; Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
  • D Murphy
    Department of Cardiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK; Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
  • K Strong
    University of Bristol, Beacon House, Queens Rd, Bristol BS8 1QU, UK.
  • A Khavandi
    Department of Cardiology, Royal United Hospital, Combe Park, Bath, BA1 3NG, UK.
  • T A Burnett
    University of Guelph, Ridgetown Campus, Ridgetown, ON, Canada N0P 2C0.
  • P F P Charters
    Department of Radiology, Royal United Hospital, Combe Park, Bath, Avon, BA1 3NG, UK.
  • J C L Rodrigues
    Department for Health, University of Bath, Claverton Down, Bath, BA2 7AY, UK; Department of Radiology, Royal United Hospital, Combe Park, Bath, Avon, BA1 3NG, UK. Electronic address: j.rodrigues1@nhs.net.

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