The AI-CAC Model for Subclinical Atherosclerosis Detection on Chest X-ray
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.
- EligibilityCriteria: 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) - HealthyVolunteers: No - Gender: All - MinimumAge: 40 Years - MaximumAge: 75 Years - StdAgeList: Adult, Older Adult