Diagnostics (Nov 2023)

Human AI Teaming for Coronary CT Angiography Assessment: Impact on Imaging Workflow and Diagnostic Accuracy

  • Florian Andre,
  • Philipp Fortner,
  • Matthias Aurich,
  • Sebastian Seitz,
  • Ann-Kathrin Jatsch,
  • Max Schöbinger,
  • Michael Wels,
  • Martin Kraus,
  • Mehmet Akif Gülsün,
  • Norbert Frey,
  • Andre Sommer,
  • Johannes Görich,
  • Sebastian J. Buss

DOI
https://doi.org/10.3390/diagnostics13233574
Journal volume & issue
Vol. 13, no. 23
p. 3574

Abstract

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As the number of coronary computed tomography angiography (CTA) examinations is expected to increase, technologies to optimize the imaging workflow are of great interest. The aim of this study was to investigate the potential of artificial intelligence (AI) to improve clinical workflow and diagnostic accuracy in high-volume cardiac imaging centers. A total of 120 patients (79 men; 62.4 (55.0–72.7) years; 26.7 (24.9–30.3) kg/m2) undergoing coronary CTA were randomly assigned to a standard or an AI-based (human AI) coronary analysis group. Severity of coronary artery disease was graded according to CAD-RADS. Initial reports were reviewed and changes were classified. Both groups were similar with regard to age, sex, body mass index, heart rate, Agatston score, and CAD-RADS. The time for coronary CTA assessment (142.5 (106.5–215.0) s vs. 195.0 (146.0–265.5) s; p p p = 0.80). AI-based analysis significantly improves clinical workflow, even in a specialized high-volume setting, by reducing CTA analysis and overall reporting time without compromising diagnostic accuracy.

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