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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.
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.
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| 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 |
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Exclusion Criteria:
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This study is a retrospective imaging study. Clinical records and image of patients received coronary CT angiography 3 months to 5 years prior to acute coronary myocardial infarction from nine clinical centers across P.R. China will be gathered.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xiaoqun Wang, M.D., Ph.D. | Contact | +86 13651839760 | xiaoqun_wang@hotmail.com | |
| Shuo Feng, M.D., Ph.D. | Contact | +86 15921388296 | fengshuorv@hotmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Ruiyan Zhang, M.D., Ph.D. | Ruijin Hospital | Principal Investigator |
| Lin Lu, M.D., Ph.D. | Ruijin Hospital | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Cangzhou Center Hospital | Recruiting | Cangzhou | Hebei | China |
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| ID | Term |
|---|---|
| D003324 | Coronary Artery Disease |
| ID | Term |
|---|---|
| D003327 | Coronary Disease |
| D017202 | Myocardial Ischemia |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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| First affiliated hospital of Harbin Medical University | Recruiting | Harbin | Heilongjiang | China |
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| First affiliated hospital of Zhengzhou University | Recruiting | Zhengzhou | Henan | China |
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| Union Hospital, Tongji Medical College, Huazhong University of Science and Techonology | Recruiting | Wuhan | Hubei | China |
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| First Hospital of Nanjing | Recruiting | Nanjing | Jiangsu | China |
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| First affiliated hospital of Dalian Medical College | Recruiting | Dalian | Liaoning | China |
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| General Hospital of Northern Theater Command | Recruiting | Shenyang | Liaoning | China |
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| Ruijin Hospital, Shanghai Jiaotong University School of Medicine | Recruiting | Shanghai | Shanghai Municipality | 200025 | China |
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| Xinhua Hospital, Shanghai Jiaotong University School of Medicine | Recruiting | Shanghai | Shanghai Municipality | China |
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| D001161 |
| Arteriosclerosis |
| D001157 | Arterial Occlusive Diseases |
| D014652 | Vascular Diseases |