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

A

Azienda Ospedaliera Città della Salute e della Scienza di Torino

Status

Not yet enrolling

Conditions

Cardiovascular Diseases
Coronary Artery Calcification
Atherosclerosis

Treatments

Diagnostic Test: AI-CAC score

Study type

Interventional

Funder types

Other

Identifiers

NCT06301009
AI-CAC-PVS

Details and patient eligibility

About

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.

Full 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.

Enrollment

500 estimated patients

Sex

All

Ages

40 to 75 years old

Volunteers

No Healthy Volunteers

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)

Trial design

Primary purpose

Prevention

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

500 participants in 1 patient group

AI-CAC arm
Experimental group
Description:
All patients included in the study and undergoing AI-CAC calculation on a chest x-ray
Treatment:
Diagnostic Test: AI-CAC score

Trial contacts and locations

0

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Central trial contact

Fabrizio D'Ascenzo, MD

Data sourced from clinicaltrials.gov

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