Diagnostic Value of Fully Automated Artificial Intelligence Powered Coronary Artery Calcium Scoring from 18F-FDG PET/CT

Authors
Claudia Morf, Thomas Sartoretti, Antonio G. Gennari, Alexander Maurer, Stephan Skawran, Andreas A. Giannopoulos, Elisabeth Sartoretti, Moritz Schwyzer, Alessandra Curioni-Fontecedro, Catherine Gebhard, Ronny R. Buechel, Philipp A. Kaufmann, Martin W. Huellner and Michael Messerli
Journal
Diagnostics
Related Product

CAC

Date Published
2022.08
Summary

In this study, researchers aimed to assess the feasibility and accuracy of a fully automated artificial intelligence (AI) powered coronary artery calcium scoring (CACS) method on ungated CT scans in oncologic patients undergoing 18F-FDG PET/CT. A total of 100 oncologic patients were retrospectively analyzed, comparing manual CACS on non-contrast ECG-gated CT scans with AI-CACS performed using AVIEW CAC (Coreline Soft) on ungated CT scans from 18F-FDG-PET/CT examinations. The AI-CACS tool demonstrated a sensitivity and specificity of 85% and 90% for detecting CAC, with an interscore agreement of 0.88 between manual and AI methods. Despite a generally underestimated CAC load on ungated CT by AI-CACS, the study concluded that fully automated AI-CACS using AVIEW CAC is feasible and provides an acceptable to good estimation of CAC burden in non-contrast free-breathing, ungated CT scans from 18F-FDG-PET/CT examinations.

Contact

Please leave your inquiry if you have any questions regarding our products, recruitment, investment, or any other matters.

Contact us