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| Name | Class |
|---|---|
| Fondazione IRCCS Policlinico San Matteo di Pavia | OTHER |
| Politecnico di Milano | OTHER |
| Scientific Institute San Raffaele | OTHER |
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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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Retrospective Cohort | For the retrospective study, we will enrol 3,000 patients >18 years old who underwent CCTA and meet all of the inclusion and exclusion criteria, with at least 4-year follow-up. The primary endpoint and patient characteristics will be those of the CTP-PRO study. Since women are less affected by CAD, at a ratio of 35:65, to correct for this expected imbalance we will weight recruitment to obtain relatively sex-balanced cohorts. In subgroups of patients, available data from invasive coronary angiography, FFR and OCT will be collected to help develop, test and refine the diagnostic performance of the automated AI tools. | ||
| Prospective Cohort | The cohort will include subjects prospectively enrolled in the CCTA arm of the CTP-PRO study. The subjects will be followed-up for 24 months after CCTA. |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 | 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) | January 2026 |
| Quantitative assessment of the atherosclerotic burden and high risk plaque features |
| January 2026 |
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Inclusion Criteria:
Exclusion Criteria:
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Patients who performed CCTA and meet all inclusion criteria
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Gianluca Pontone | Contact | 0258002574 | +39 | gianluca.pontone@cardiologicomonzino.it |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Centro Cardiologico Monzino | Recruiting | Milan | Milan | 20131 | Italy |
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| ID | Term |
|---|---|
| D003324 | Coronary Artery Disease |
| ID | Term |
|---|---|
| D003327 | Coronary Disease |
| D017202 | Myocardial Ischemia |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| Centro Cardiologico Monzino | Recruiting | Milan | MI | 20131 | Italy |
|
| D001161 |
| Arteriosclerosis |
| D001157 | Arterial Occlusive Diseases |
| D014652 | Vascular Diseases |