Automated Plaque Characterization and Functional Analysis of Coronary CTA Based on OCT Images Using Artificial Intelligence
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- By taking OCT results as the standard, evaluating the accuracy of automated plaque characterization and functional significance of coronary stenosis using CTA images computation.
研究概览
简要总结
This trial is a single-center, prospective, observational clinical study. All patients who have at least one coronary artery stenosis of 30%-90% in diameter ≥ 2mm confirmed by CCTA, and who are scheduled to undergo clinically indicated invasive coronary angiography (ICA) and optical coherence tomography (OCT) evaluation and/or treatment will be eligible for enrollment. We proposed a novel approach that integrates CCTA, ICA and OCT images to automatically measure plaque characterization and calculate CT-FFR using computational fluid dynamics (CFD) simulation and artificial intelligence deep learning.
详细描述
Acute coronary syndrome (ACS) is one of the leading causes of coronary artery disease (CAD) death worldwide. Vulnerable plaque rupture is a primary underlying cause of luminal thrombosis responsible for provoking ACS. Therefore, identifying high-risk plaques before ACS occurs has been a major research goal and requires further clinical perspectives. Coronary computed tomography angiography (CCTA) is a comprehensive, non-invasive and cost-effective imaging assessment approach, which can provide the ability to identify the characteristics and morphology of high-risk atherosclerotic plaques associated with ACS. Optical coherence tomography (OCT) is a new, light-based, intravascular imaging technique that provides high-resolution, cross-sectional images of coronary artery anatomy. Due to its superior resolution, OCT is more accurate in measuring the sites of plaque vulnerability, distinguishing the differences in its composition, informing about the anatomic severity of epicardial stenoses, and also provides input for computational models to assess functional severity.
The objectives of the study are: (1) To construct an artificial intelligence model for identifying coronary plaque components on CTA images using OCT as the reference standard. (2) To conduct fluid mechanics simulation including blood vessel wall and plaque by using geometric and physiological models of blood vessels and plaques, and to provide more accurate functional parameters (CT-FFR).
The enrollment criteria will be (1) Patients who presented with stable angina pectoris or acute coronary syndrome; (2) patients who meet the indications for coronary CT angiography, percutaneous coronary angiography and intravascular imaging; (3) Among those patients, patients who have at least one coronary artery stenosis of 30% - 90% in diameter ≥ 2mm confirmed by CCTA.
Data collected will include CCTA, full angiographic, and OCT images. Combined with CTA/ICA/OCT images of multiple modalities, this study will develop a novel images analysis technology to automatically extract vascular lumen, plaque characterization, fluid-solid mechanical properties, and myocardial ischemia conditions using computational fluid dynamics (CFD) simulation and artificial intelligence deep learning.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥18 years and able to understand the purpose of the study and sign the informed consent;
- •Patients who presented with stable angina pectoris or acute coronary syndrome;
- •Patients who meet the indications for coronary CT angiography, percutaneous coronary angiography and intravascular imaging;
- •Among those patients, patients who have at least one coronary artery stenosis of 30% - 90% in diameter ≥ 2mm confirmed by CCTA.
排除标准
- •Known pregnancy or breastfeeding at the time of enrollment;
- •Hemodynamic instability;
- •Allergy to contrast media or aspirin, adenosine etc.;
- •History of stroke or transient ischemic attack (TIA) within 12 months before surgery;
- •Known renal insufficiency (e.g. serum creatinine >2.0mg/dL, or creatinine clearance ≤30 mL/min), or need for dialysis, or acute kidney failure (as per physician judgment);
- •Leukopenia (WBC<4.0*10*9/L), thrombocytopenia (PLT<100*10*9/L) or thrombocytopenia (PLT>300*10*9/L);
- •Subjects who receiving oral or intravenous immunosuppressant therapy (other than inhaled steroids) or have an autoimmune disease (e.g., AIDS, SLE; except diabetes);
- •Any other factors that researchers consider not suitable for inclusion or completion of this study.
结局指标
主要结局
By taking OCT results as the standard, evaluating the accuracy of automated plaque characterization and functional significance of coronary stenosis using CTA images computation.
时间窗: Immediately after OCT scan
By taking OCT results as the standard, evaluating the accuracy of automated plaque characterization and functional significance of coronary stenosis using CTA images computation.
次要结局
未报告次要终点
研究者
Yu Bo
Director of Department of Cardiology
Harbin Medical University