NCT06301009

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

The AI-CAC Model for Subclinical Atherosclerosis Detection on Chest X-ray: Prospective Validation Study (AI-CAC-PVS)

• Status: Unknown
• Phase: N/A
• Study type: Interventional
• Enrollment: 500 (estimated)
• Sponsor: A.O.U. Città della Salute e della Scienza · Academic / Other
• Sex: All
• Age: 40 Years – 75 Years
• Healthy volunteers: Not accepted

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.

Detailed description

The AI-CAC-PVS project is a prospective, multicenter, single-arm clinical study, with enrollment at 5 Radiology Units in Piedmont (Italy). Consecutive individuals without prior reported cardiovascular events referred for a non-contrast chest CT for the assessment of coronary artery calcium (CAC) score for cardiovascular risk stratification purposes will be considered for inclusion in the study. Individuals who agree to participate in the study will undergo a standard chest radiograph, as the only deviation from clinical practice. The CAC score will be calculated on chest CT scans according to international standards, and the result will be provided to the patient. Any subsequent changes in behavioral habits, lipid-lowering, antiplatelet, antihypertensive, and antidiabetic therapies prescribed by the attending physician will be collected in a dedicated dataset, along with the occurrence of cardiovascular events at the last available follow-up. The AI-CAC model will be applied to the chest radiograph, yielding an AI-CAC value as output. The patient, radiologist, and attending physician will not be informed of the AI-CAC value until the end of the study. The primary outcome will be the accuracy of the AI-CAC model to detect the presence of subclinical atherosclerosis on chest x-ray as compared to the CT scan (i.e. CAC \>0). The ability to predict clinical outcomes at follow-up (ASCVD, atherosclerotic cardiovascular disease events comprising myocardial infarction, ischemic stroke, coronary revascularization and cardiovascular death) will be assessed as exploratory secondary outcome.

Conditions

• Cardiovascular Diseases
• Atherosclerosis
• Coronary Artery Calcification

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	AI-CAC score	Deep-learning based prediction of the coronary artery calcium score with a plain chest x-ray

Timeline

• Start date: 2024-04-01
• Primary completion: 2025-10-01
• Completion: 2025-10-01
• First posted: 2024-03-08
• Last updated: 2024-03-08