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

Status Not yet recruiting

Clinical Trial 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.

Clinical Trial 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. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT06301009
Study type	Interventional
Source	Azienda Ospedaliera Città della Salute e della Scienza di Torino
Contact	Fabrizio D'Ascenzo, MD
Phone	+390116335575
Email	fabrizio.dascenzo@gmail.com
Status	Not yet recruiting
Phase	N/A
Start date	April 1, 2024
Completion date	October 1, 2025

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Clinical trials are conducted in a series of steps, called phases - each phase is designed to answer a separate research question.

Phase 1: Researchers test a new drug or treatment in a small group of people for the first time to evaluate its safety, determine a safe dosage range, and identify side effects.
Phase 2: The drug or treatment is given to a larger group of people to see if it is effective and to further evaluate its safety.
Phase 3: The drug or treatment is given to large groups of people to confirm its effectiveness, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug or treatment to be used safely.
Phase 4: Studies are done after the drug or treatment has been marketed to gather information on the drug's effect in various populations and any side effects associated with long-term use.

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

Clinical Trial Summary

Clinical Trial Description

Study Design

Related Conditions & MeSH terms