Screening Coronary Artery Disease Using artiFicial intelligencE in Non-contrast Computed Tomography
NCT ID: NCT06438393
Last Updated: 2024-05-31
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
1000 participants
OBSERVATIONAL
2024-06-30
2027-12-31
Brief Summary
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Detailed Description
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We designed the SAFE-CT (Screening coronary Artery disease using artiFicial intelligencE in noncontrast Computed Tomography) study to develop a state-of-art artificial intelligence method to detect CAD as defined on CTCA using high-dimensional data (radiomics) extracted from the non-contrast cardiac computed tomography (CT). The model will be trained in 15,000 subjects scanned with paired non-contrast CT and CTCA and externally validated in an independent cohort of 1,000 subjects. In a preliminary analysis, non-contrast CT radiomics improved calcium score performance and discriminated CAD with an AUC of 0.91 (95% CI: 0.83-1.00). The algorithm will be converted into a user-friendly plugin to automatically decide whether the patient needs contrast. A real-world multicentre cohort study will be planned for software prospective validation and the creation of a large-scale proteomic biobank to support the translation of imaging biomarkers worldwide.
SAFE-CT can change the current CT scanning workflow by creating software that accurately rules out any CAD in \>1/3 of patients referred for CTCA with low radiation and no contrast. This accurate machine learning model will be optimized to reach \>90% sensitivity and negative predictive value and will bring several advantages for patients and the healthcare system:
* Prevention of radiation and contrast exposition.
* Increased CTCA scanning capacity for complex cases.
* Widespread use of CT for CAD exclusion in the emergency department and in outpatient clinics of centres with no CTCA.
* Improved screening tool for CAD in asymptomatic subjects.
* Up- and downstream cost reduction.
The SAFE-CT project proposes a safer, low-cost, and personalized CTCA scanning strategy that fosters scientific and technological innovation with the potential to bring improvement to patient care and clinical practice, and, thereby, societal, and economic impact.
Conditions
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Keywords
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Study Design
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OTHER
RETROSPECTIVE
Study Groups
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Stable chest pain and unknown CAD who underwent CTCA and CCS in the same scanning session
CAD: Presence of minimal coronary artery disease (i.e., coronary stenosis 0-25%) Normal coronary arteries: No visible coronary atherosclerosis
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.
Interventions
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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.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* Known coronary artery disease
* Prior myocardial infarction
* Prior PCI or CABG
18 Years
100 Years
ALL
Yes
Sponsors
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University of Oxford
OTHER
University of Edinburgh
OTHER
Universidade do Porto
OTHER
Responsible Party
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Locations
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Faculty of Medicine of Porto
Porto, , Portugal
Countries
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Other Identifiers
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SAFE-CT
Identifier Type: -
Identifier Source: org_study_id