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

ConditionsCoronary Artery DiseaseCoronary Atheroscleroses
Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18-100
SponsorUniversidade do Porto

About this trial

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 criteria

This trial accepts healthy volunteers

Qualifiers

None

Disqualifiers

Missing non-contrast CT image (coronary calcium score image)

Known coronary artery disease

Prior myocardial infarction

Prior PCI or CABG

Trial population

Stable chest pain patients with unknown CAD who underwent a CTCA with paired non-contrast CT

Trial design

Design model

Other

Time perspective

Retrospective

Treatments tested in this trial

  • CT coronary angiography and non-contrast CT

    Diagnostic test

    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.

Treatment groups

1,000 Participants
are divided into 1 treatment group
Group A: Stable chest pain and unknown CAD who underwent CTCA and CCS in the same scanning session1 intervention

Trial outcomes

Primary outcomes

1

Build a non-contrast CT radiomic signature of CAD

Time frame
3 years
2

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).

Time frame
3 years
3

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).

Time frame
3 years
4

Build a user-friendly plugin to facilitate users experience and distribution of our technology in clinical practice.

Time frame
3 years

Secondary outcomes

1

Setup a human blood biobank to identify the peripheral blood mononuclear cells (PBMCs) and plasma proteomics associated with CT data and clinical outcomes.

Time frame
3 years
2

Setup a public CT imaging repository

Time frame
3 years

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Universidade do Porto

Lead sponsor

University of Oxford

Collaborator

University of Edinburgh

Collaborator

Source ClinicalTrials.gov

This trial is not recruiting at the moment. You can still explore other options: