Risk Evaluation by COronary CTA and Artificial intelliGence Based fuNctIonal analyZing tEchniques - I

Study Overview
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Brief Summary
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This study is a multicenter, retrospective imaging study. The study intends to retrospectively enroll patients with acute myocardial infarction who had received coronary CTA in a certain time-window before this event. All coronary CTA will be analyzed by anatomic, functional and radiomic analysis, assisted by artificial intelligence. The purpose of this study is to establish a coronary artery disease risk stratification system by coronary CTA.

Detailed Description
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Coronary angiography has been the gold standard for the diagnosis of coronary heart disease and PCI decision-making. However, the value of CAG in risk stratification is limited due to its invasive nature and lack of ability to evaluate coronary physiology and plaque characteristics, which often leads to over-treatment or under-treatment. In recent years, with the development and improvement of imaging technology, the resolution and diagnostic accuracy of coronary artery CTA have been greatly improved, and the subsequent anatomy and function (non-invasive CT-FFR, etc.) have made the assessment of coronary artery lesion risk multi-dimensional. Comprehensive and accurate coronary artery CTA scan plays a positive role in establishing the appropriate standard for PCI and improving the prognosis of patients. However, the existing problems of coronary artery CTA are insufficient imaging studies, complex image analysis, inconsistent diagnostic criteria, and insufficient clinical evidence. This study is one of the series of clinical studies on the topic of Risk Evaluation by COronary Computed Tomography and Artificial Intelligence Based fuNctIonal analyZing tEchniques (RECOGNIZE). The purpose of the study is to establish a coronary artery disease risk stratification system by coronary CTA and anatomic, functional and radiomic analysis, assisted by artificial intelligence.

Official Title
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Coronary Computed Tomography Angiography and Functional Analysis in Risk Stratification of Coronary Artery Disease: A Retrospective Cohort Study

Conditions
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Coronary Artery Disease

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age between 18-80 years old Received coronary CT angiography 3 months to 5 years prior to acute coronary myocardial infarction. CCTA identified coronary atherosclerotic plaques with diameter stenosis ≥ 10% Exclusion Criteria: Familial hypercholesterolemia Prior history of percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) Prior history of myocardial infarction before the recent event Severe liver or renal insufficiency

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 80 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Coronary artery plaque risk level | Coronary plaque risk was determined using an artificial intelligence (AI) guided risk stratification model based on Coronary CTA structural, functional and radiomic analysis. | 3 months to 5 years prior to acute myocardial infarction | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Coronary CTA, CT-FFR, Artificial Intelligence, Risk Stratification