Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS

Coronary artery disease (CAD) is among the leading cause of death and disability. Identification of patients at high risk of cardiovascular events is pivotal. However, current risk stratification based on imaging and known biomarkers is suboptimal. The objective of this proposal is to develop a multicriteria decision model for non-invasive assessment of vulnerable atherosclerotic patients and to evaluate its ability to predict the occurrence of an adverse event in intermediate-to-high risk patients with suspected or known CAD. The planned workflow includes a first step using a retrospective cohort of patients undergoing clinically indicated coronary angiography (CCTA) to develop an integrated application for automatic coronary artery segmentation, quantitative plaque analysis, biomechanics and fluid dynamics, based on machine learning, radiomics and computational analysis approaches and validated against the reference standard for each tool. The second step will apply this new methodology to a larger retrospective cohort of patients with the integration of genomic biomarker assessment to derive the most accurate risk stratification model to properly identify vulnerable patients and vulnerable plaques with respect to outcome. Finally, in the third step, the derived predictive model will be prospectively validated in an independent cohort of patients from an ongoing study (CTP-PRO study) to assess the robustness and accuracy of the proposed solution.

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Key information

Conditions

Coronary Artery Disease Arterial Occlusive Diseases Arteriosclerosis Cardiovascular Diseases Coronary Computed Tomography Angiography Coronary Disease Heart Diseases Myocardial Ischemia Vascular Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Centro Cardiologico Monzino, Milan, MI, Italy

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

patients (age ≥ 18 years) with known or suspected CAD referred for clinically indicated diagnostic evaluation;
CCTA performed with state-of-the-art scanner technology, i.e., scanners with more than 64 slices.

Exclusion criteria

performance of any non-invasive diagnostic test within 90 days before enrolment;
low-to-intermediate pre-test likelihood of CAD according to the updated Diamond-Forrester risk model score;
acute coronary syndrome;
evidence of clinical instability;
contraindication to contrast agent administration and/or impaired renal function;
inability to sustain a breath hold;
pregnancy;
cardiac arrhythmias;- presence of a pacemaker or implantable cardioverter defibrillator;
contraindications to the administration of sublingual nitrates, β-blockers or adenosine;
structural cardiomyopathy

Treatment and study plan

Primary outcomes

Creation of an automated integrative artificial intelligence (AI) approach for the stratification of CAD patients and assessment of vulnerable coronary plaques at risk of acute complications

Time frame: January 2026

The main aim of the project develop a multicriteria decision model for the automatic (AI-assisted) non-invasive assessment of vulnerable atherosclerotic patients and evaluate the ability of this model to predict the occurrence of adverse event in intermediate-to-high risk patients with suspected or known CAD.

As adverse events, we will consider the annual rate of events, intended as death or hospitalization for revascularization (either CABG or PCI)
Quantitative assessment of the atherosclerotic burden and high risk plaque features

Time frame: January 2026
- Extent and severity of coronary atherosclerosis (Leaman Score, number of lesions);
- Vulnerability indices: plaque burden (total plaque volume, plaque density), LAP, PR, NRS and SC;
- Fluid dynamic indexes of the coronary artery such as the CT derived Fractional Flow Reserve

Study contacts

Contact information is provided by the study sponsor or research team.

Gianluca Pontone

CONTACT

[email protected]

0258002574 ext. +39

Sponsors and collaborators

Lead sponsor

Centro Cardiologico Monzino

Other

Collaborators

Fondazione IRCCS Policlinico San Matteo di Pavia
Politecnico di Milano
Scientific Institute San Raffaele

Registry information

Official study title

Rustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS

Acronym: AI-CORPS

Important dates

Study start: 2023
Primary completion: 2026
Study completion: 2026
First posted: May 13, 2024
Registry last updated: May 29, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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