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

March 22, 2024 updated by: Centro Cardiologico Monzino

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.

Study Overview

Status

Recruiting

Study Type

Observational

Enrollment (Estimated)

400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

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

Description

Inclusion Criteria:

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

Exclusion Criteria:

  • 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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Development of a computational model to predict MBF avoiding CT stress protocol
Time Frame: May 2025

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. Building the neural network from the measured blood flow maps will allow us to include this information in our calibration procedure and also use 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 Outcome Measures

Outcome Measure
Measure Description
Time Frame
Improvement of CAD risk assesment
Time Frame: May 2025
The second Aim is to improve CAD risk assessment by integrating the information from the perfusion computation model with imaging and radiomics features
May 2025

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 22, 2023

Primary Completion (Estimated)

May 30, 2025

Study Completion (Estimated)

May 30, 2025

Study Registration Dates

First Submitted

March 14, 2024

First Submitted That Met QC Criteria

March 22, 2024

First Posted (Actual)

March 29, 2024

Study Record Updates

Last Update Posted (Actual)

March 29, 2024

Last Update Submitted That Met QC Criteria

March 22, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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