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

Sponsor

Ruijin Hospital (Other)

Overall Status

Recruiting

CT.gov ID

NCT05884008

Collaborator

(none)

300

Enrollment

Locations

Anticipated Duration (Months)

33.3

Patients Per Site

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Coronary Artery Disease

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 establish a coronary artery disease risk stratification system by coronary CTA and anatomic, functional and radiomic analysis, assisted by artificial intelligence.

Study Design

Study Type:

Observational

Anticipated Enrollment :

300 participants

Observational Model:

Cohort

Time Perspective:

Retrospective

Official Title:

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

Actual Study Start Date :

May 1, 2023

Anticipated Primary Completion Date :

Jun 30, 2025

Anticipated Study Completion Date :

Dec 31, 2025

Outcome Measures

Primary Outcome Measures

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

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 80 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Cangzhou Center Hospital	Cangzhou	Hebei	China
2	First affiliated hospital of Harbin Medical University	Harbin	Heilongjiang	China
3	First affiliated hospital of Zhengzhou University	Zhengzhou	Henan	China
4	Union Hospital, Tongji Medical College, Huazhong University of Science and Techonology	Wuhan	Hubei	China
5	First Hospital of Nanjing	Nanjing	Jiangsu	China
6	First affiliated hospital of Dalian Medical College	Dalian	Liaoning	China
7	General Hospital of Northern Theater Command	Shenyang	Liaoning	China
8	Ruijin Hospital, Shanghai Jiaotong University School of Medicine	Shanghai	Shanghai	China	200025
9	Xinhua Hospital, Shanghai Jiaotong University School of Medicine	Shanghai	Shanghai	China