Coronary Artery Disease Clinical Trial
— SAFE-CTOfficial title:
Screening Coronary Artery Disease Using artiFicial intelligencE in Non-contrast Computed Tomography
NCT number | NCT06438393 |
Other study ID # | SAFE-CT |
Secondary ID | |
Status | Not yet recruiting |
Phase | |
First received | |
Last updated | |
Start date | June 2024 |
Est. completion date | December 2027 |
Verified date | February 2024 |
Source | Universidade do Porto |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
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
Status | Not yet recruiting |
Enrollment | 1000 |
Est. completion date | December 2027 |
Est. primary completion date | June 2027 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 100 Years |
Eligibility | Inclusion Criteria: - Patient with stable chest pain who underwent a CTCA Exclusion Criteria: - Missing non-contrast CT image (coronary calcium score image) - Known coronary artery disease - Prior myocardial infarction - Prior PCI or CABG |
Country | Name | City | State |
---|---|---|---|
Portugal | Faculty of Medicine of Porto | Porto |
Lead Sponsor | Collaborator |
---|---|
Universidade do Porto | University of Edinburgh, University of Oxford |
Portugal,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Build a non-contrast CT radiomic signature of CAD | 3 years | ||
Primary | 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 | ||
Primary | 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 | ||
Primary | Build a user-friendly plugin to facilitate users experience and distribution of our technology in clinical practice. | 3 years | ||
Primary | Evaluate the real-world operationality and performance of the plugin in an international multicentre prospective cohort study. | 3 years | ||
Primary | Create a national registry of cardiac CT | 3 years | ||
Secondary | Setup a human blood biobank to identify the peripheral blood mononuclear cells (PBMCs) and plasma proteomics associated with CT data and clinical outcomes. | 3 years | ||
Secondary | Setup a public CT imaging repository | 3 years |
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