Screening Coronary Artery Disease Using artiFicial intelligencE in Non-contrast Computed Tomography

Condition(s) studied

Investigational drug(s) / intervention(s)

CT coronary angiography and non-contrast CT: A CTCA is an X-ray computed tomography of the coronary arteries that allows visualization of coronary plaques with high temporal and spatial resolution, however, it implies the use of iodine contrast and exposition to clinically significant ionizing radiation. Non-contrast ECG-gated CT ("calcium score" - CCS image). A non-contrast cardiac CT for CCS can be performed very quickly with significantly lower radiation (\~6 times lower) than CTCA and without the need for contrast.

Study summary

This project aims to improve direct patient care by reducing the risks of futile exposure to ionizing radiation and iodinated contrast in patients referred for coronary computed tomography angiography

Eligibility

Primary outcome measure(s)

• Build a non-contrast CT radiomic signature of CAD — 3 years
• Implement a machine learning model to discriminate patients with no CAD from patients with at least minimal disease (CAD-RADS=0 vs. CAD-RADS>0). — 3 years
• Implement a machine learning model to detect coronary inflammation as defined using the Fat Attenuation Index (FAI ≥ -70.1 HU) in patients with no visible coronary plaque (CAD-RADS=0). — 3 years
• Build a user-friendly plugin to facilitate users experience and distribution of our technology in clinical practice. — 3 years
• Evaluate the real-world operationality and performance of the plugin in an international multicentre prospective cohort study. — 3 years
• Create a national registry of cardiac CT — 3 years

Trial sites (1)

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