Clinical trial NCT05884008: Risk Evaluation by COronary CTA and Artificial intelliGence Based fuNctIonal analyZing tEchniques - I
Official title: Coronary Computed Tomography Angiography and Functional Analysis in Risk Stratification of Coronary Artery Disease: A Retrospective Cohort Study
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Coronary Artery Disease
Keywords: Coronary CTA
CT-FFR
Artificial Intelligence
Risk Stratification
Lead sponsor: Ruijin Hospital
Sponsor class: OTHER
First posted: 2023-06-01
Enrollment: 300
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: 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.

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.

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.

Eligibility criteria: 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

Primary outcomes:
measure: Coronary artery plaque risk level
timeFrame: 3 months to 5 years prior to acute myocardial infarction
Secondary outcomes:
Other outcomes:
Locations:
city: Cangzhou
country: China
facility: Cangzhou Center Hospital
state: Hebei
city: Harbin
country: China
facility: First affiliated hospital of Harbin Medical University
state: Heilongjiang
city: Zhengzhou
country: China
facility: First affiliated hospital of Zhengzhou University
state: Henan
city: Wuhan
country: China
facility: Union Hospital, Tongji Medical College, Huazhong University of Science and Techonology
state: Hubei
city: Nanjing
country: China
facility: First Hospital of Nanjing
state: Jiangsu
city: Dalian
country: China
facility: First affiliated hospital of Dalian Medical College
state: Liaoning
city: Shenyang
country: China
facility: General Hospital of Northern Theater Command
state: Liaoning
city: Shanghai
country: China
facility: Ruijin Hospital, Shanghai Jiaotong University School of Medicine
state: Shanghai
city: Shanghai
country: China
facility: Xinhua Hospital, Shanghai Jiaotong University School of Medicine
state: Shanghai
Study officials:
affiliation: Ruijin Hospital
name: Ruiyan Zhang, M.D., Ph.D.
role: PRINCIPAL_INVESTIGATOR
affiliation: Ruijin Hospital
name: Lin Lu, M.D., Ph.D.
role: STUDY_CHAIR
References: