Coronary Artery Disease
Conditions
Keywords
Coronary CTA, CT-FFR, Risk Stratification, Artificial Intelligence
Brief summary
This study is a multicenter, prospective clinical cohort study. The study intends to continuously enroll patients with coronary heart disease. All subjects will undergo coronary CTA (followed by anatomic, functional and radiomics analysis), proteomics research as well as clinical follow-up of cardiovascular events. The purpose of this study is to establish a new, non-invasive cardiovascular disease risk stratification system.
Detailed description
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 evaluate the accuracy of early identification of cardiovascular high-risk groups based on the functional evaluation model based on coronary CTA images through a multi-center, prospective clinical cohort study, so as to establish an early, non-invasive and accurate risk classification of cardiovascular events in coronary heart disease.
Interventions
None listed
Sponsors
Ruijin Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
* Age 18-80 years * Clinically significant angina pectoris, suspecting coronary artery disease
Exclusion criteria
* Unsuitable for coronary CTA (such as severe renal impairment, uncontrolled thyroid condition, allergic to iodine, etc.) * Without a visible plaque (defined as ≥ 30% stenosis) in major coronary arteries in coronary CTA * Prior history of myocardial infarction or heart failure * Prior history of percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) * Severe renal or liver failure * Familial hypercholesterolemia * Estimated survival ≤1 year * Malignant tumor * Poor coordinance, unable to follow-up
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Major Adverse Cardiovascular Events | 2 years | Including cardiovascular death, myocardial infarction, and stroke |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cardiovascular death | 2 years | Death due to cardiovascular events |
| Myocardial infarction | 2 years | Including STEMI and NSTEMI |
| Stroke | 2 years | Including ischemic and hemorrhagic stroke |
| Coronary Revascularization | 2 years | Including percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) |
Countries
China
Contacts
Primary ContactXiaoqun Wang, M.D., Ph.D.
Backup ContactShuo Feng, M.D., Ph.D.
Outcome results
None listed