Computational mOdelliNg of myoCardial pERfusion to Improve ouTcome Prediction Based on cOronary Artery Stenosis and Atherosclerotic Plaque Burden Assessment by Computed Tomography

NCT06337461 | Recruiting

• 1 other identifier: CCM1930
• Study Type: observational
• Target: 400
• Locations: 1 country
• Sites: 1

Brief Summary

Detection of coronary stenosis is of utmost importance in identifying vulnerable patients. The combined use of coronary computed tomography angiography at rest (CCTA) and stress myocardial computed tomography perfusion (stress-CTP) provides both anatomic and functional analysis of coronary artery disease (CAD) using a single imaging test. Stress-CTP evaluates myocardial perfusion by measuring myocardial blood flow (MBF) under pharmacologically induced stress conditions. The drawback is that stress-CTP requires additional scanning and administration of an intravenous stressor with an increase in radiation exposure and potential stressor-related side effects. The investigators recently patented a computational model that can reproduce MBF under stress conditions (Italian patent n. 102021000031475 Metodo implementato mediante computer per la simulazione del flusso sanguigno miocardico in condizioni di stress \[Computational method for simulating myocardial blood flow in stress conditions\], half owned by Centro Cardiologico Monzino, half by Politecnico di Milano). On top of this, CCTA can characterize plaque type and identify adverse plaque characteristics. Moreover, biomechanics analysis allows the study of luminal stenosis and stress within the plaque. Finally, radiomics, extracting quantitative features from medical images to create big data and identify novel imaging biomarkers, can be applied to improve the diagnostic accuracy of coronary plaques.

Conditions

Chronic Coronary Syndrome

Keywords

CT Perfusion; Myocardial Blood Flow

Outcome Measures

Primary Outcomes (1)

• Development of a computational model to predict MBF avoiding CT stress protocol

  CONCERTO main aim is to predict MBF values from cardiac CT scans without stress protocol. This aim will be achieved by improving an existing computational model. To achieve this goal, we first need to explore available information on the effect of stenosis on the pressure gradient across it and the division of flow in the coronary tree. A second step will be a ML analysis on a reasonable number of patients with known myocardial perfusion (from CT-stress) to build a suitable neural network that can predict some general features of the model parameters. This neural network will allow us to include this information in our calibration procedure and use also it for future patients in whom stress CT will no longer be necessary. Finally, a comprehensive, patient-specific model calibration strategy will be developed leveraging the results. This will allow us to apply our tool to any patient as long as a standard CT acquisition and some pressure

  May 2025

Secondary Outcomes (1)

• Improvement of CAD risk assesment

  May 2025

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

A total of 400 consecutive symptomatic patients with suspected CAD who were recruited for non-emergent, clinically indicated non-invasive coronary angiography with eventually dynamic stress computed tomography perfusion study

You may qualify if:

• Symptomatic patients with suspected CAD referred for nonemergent, clinically indicated non-invasive coronary angiography.

You may not qualify if:

• Low pre-test likelihood of CAD
• Prior myocardial infarction
• Previous history of revascularization
• Acute coronary syndrome
• Need for an emergent procedure
• Evidence of clinical instability
• Contraindication for contrast agent or impaired renal function
• Inability to sustain a breath-hold
• Pregnancy
• Atrial fibrillation or flutter
• BMI \> 35kg/m2
• Presence of pm or ICD
• Contraindications to the administration of sublingual nitrates, betablockade, and adenosine

Sponsors & Collaborators

• Centro Cardiologico Monzino: lead
• Politecnico di Milano: collaborator
• University of Bari: collaborator

Study Sites (1)

Centro Cardiologico Monzino

Milan, Milan, 20131, Italy

RECRUITING

Central Study Contacts

Gianluca Pontone, MD

CONTACT

0258002574; gianluca.pontone@cardiologicomonzino.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 14, 2024
• First Posted: March 29, 2024
• Study Start: May 22, 2023
• Primary Completion (Estimated): May 30, 2026
• Study Completion (Estimated): May 30, 2026
• Last Updated: February 3, 2026

Record last verified: 2026-01

Locations

IT (1)