Clinical trial NCT06337461: Computational MOdelliNg of MyoCardial PERfusion to Improve OuTcome Prediction Based on COronary Artery Stenosis and Atherosclerotic Plaque Burden Assessment by Computed Tomography
Official title: Computational MOdelliNg of MyoCardial PERfusion to Improve OuTcome Prediction Based on COronary Artery Stenosis and Atherosclerotic Plaque Burden Assessment by Computed Tomography
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Chronic Coronary Syndrome
Keywords: CT Perfusion
Myocardial Blood Flow
Lead sponsor: Centro Cardiologico Monzino
Sponsor class: OTHER
Collaborators: name: Politecnico di Milano
name: University of Bari
First posted: 2024-03-29
Enrollment: 400
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: 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

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.


Eligibility criteria: 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

Primary outcomes:
measure: Development of a computational model to predict MBF avoiding CT stress protocol
timeFrame: May 2025
Secondary outcomes:
measure: Improvement of CAD risk assesment
timeFrame: May 2025
Other outcomes:
Locations:
city: Milan
country: Italy
facility: Centro Cardiologico Monzino
Study officials:
References: