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The AI-CAC Model for Subclinical Atherosclerosis Detection on Chest X-ray

500 participantsStarted 2024-04-01

Plain-language summary

The AI-CAC model is an artificial intelligence system capable of assessing the presence of subclinical atherosclerosis on a simple chest radiograph. The present study will provide prospective validation of its diagnostic performance in a primary prevention population with a clinical indication for coronary artery calcium (CAC) testing.

Who can participate

Age range40 Years – 75 Years

SexALL

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Inclusion Criteria: * Consent to participate in the study * Age between 40 and 75 years * Clinical indication from the treating physician to undergo chest CT for CAC score evaluation Exclusion Criteria: * Prior cardiovascular events (myocardial infarction, coronary revascularization, transient ischemic attack, stroke, symptomatic peripheral vascular disease, arterial revascularization of peripheral districts) * Cancer or other chronic diseases with an estimated prognosis of less than five years * Technical contraindications to the execution of chest CT with electrocardiographic gating (highly penetrant atrial fibrillation, frequent ventricular extrasystoles)

What they're measuring

Diagnostic accuracy of the AI-CAC score to identify the presence of subclinical atherosclerosis on chest x-ray

Timeframe: Through study completion (anticipated average follow-up of 1 year).

Trial details

NCT IDNCT06301009

SponsorA.O.U. Città della Salute e della Scienza

Sponsor typeOTHER

Study typeINTERVENTIONAL

Primary completion2025-10-01

Contact for this trial

Fabrizio D'Ascenzo, MD

+390116335575 fabrizio.dascenzo@gmail.com

View on ClinicalTrials.gov More Cardiovascular Diseases trials