Clinical trial NCT06410690: Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS
Official title: Rustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Coronary Artery Disease
Coronary Computed Tomography Angiography
Lead sponsor: Centro Cardiologico Monzino
Sponsor class: OTHER
Collaborators: name: Fondazione IRCCS Policlinico San Matteo di Pavia
name: Politecnico di Milano
name: Scientific Institute San Raffaele
First posted: 2024-05-13
Enrollment: 4000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who performed CCTA and meet all inclusion criteria

Brief summary: 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.


Eligibility criteria: 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

Primary outcomes:
measure: 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
timeFrame: January 2026
measure: Quantitative assessment of the atherosclerotic burden and high risk plaque features
timeFrame: January 2026
Secondary outcomes:
Other outcomes:
Locations:
city: Milan
country: Italy
facility: Centro Cardiologico Monzino
state: MI
city: Milan
country: Italy
facility: Centro Cardiologico Monzino
Study officials:
References: