Impact of Epicardial Adipose Tissue on Coronary Plaque Composition and Major Adverse Cardiac Event Rate. A New Systematic Approach for Risk Stratification in Patients with Suspected Coronary Artery Disease: Results from the PROMISE trial

急性冠状动脉综合征（Acute coronary syndrome，ACS）是冠状动脉疾病（coronary artery disease，CAD）的总称，是工业化国家最常见的死亡原因之一。到目前为止，在疑似CAD的患者中，有创冠状动脉造影和功能测试（包括运动心电图、负荷超声心动图和负荷心肌灌注成像）是排除有症状患者CAD的金标准方法，即使预检概率较低或中等。这些模态仅递送关于冠状动脉的管腔的信息，并且仅递送关于冠状动脉壁和周围解剖结构的有限信息。在过去的十年中，计算机断层扫描（CT）已发展成为一种并行的非侵入性方式，可用于排除CAD症状的患者。根据大型随机多中心试验，CT显示出与上述功能测试方法相当的灵敏度和特异性。与这些模式相比，CT具有明显的优势，可以提供有关周围结构（如心外膜脂肪组织（EAT））的额外证据。据推测，EAT可能具有外分泌和内分泌作用，并可能在直接相邻的冠状动脉壁中引发炎症过程，导致CAD的发展。EAT的体积和密度是否影响动脉粥样硬化的形成，导致易损斑块的形成，增加主要不良心脏事件（MACE）的发生率，目前尚不清楚。甚至冠状动脉斑块的组成也可能取决于EAT的体积和密度。由于空间和时间分辨率的提高，现在CT数据可以用于冠状动脉斑块的准确成分分析。除了常规的高风险冠状动脉斑块特征的视觉识别之外，CT还允许对斑块化合物进行定量分析，例如纤维化、脂肪和钙化组织。我们假设EAT体积和密度增加的患者可能更频繁地出现高危斑块特征，本研究的主要目的是在一个大型队列中研究EAT体积和衰减对冠状动脉斑块组成和MACE发生率的影响，随访时间中位数为25个月。这项研究是随机前瞻性多中心成像研究的一部分，用于评估胸痛试验（PROMISE试验），该试验招募了10，000多名疑似CAD患者。所有4589例患者的CT数据将被纳入我们的研究，这些患者被随机分配到解剖测试组并接受心脏CT检查。除了在疑似CAD患者中改善基于CT的风险分层外，EAT分析和冠状动脉斑块成分分析应为未来在德国和欧洲进行的多中心大数据研究奠定基础。

Acute coronary syndrome, on behalf of coronary artery disease (CAD), is one of the most common causes of death in industrialized nations. Until now, in patients with suspected CAD, invasive coronary angiography and functional testing including exercise electrocardiogram, stress echocardiography and stress myocardial perfusion imaging are the gold standard methods for exclusion of CAD in symptomatic patients even with low or intermediate pretest probability. These modalities deliver only information about the lumen of coronary arteries and only limited information about the coronary wall and surrounding anatomical structures. In the last decade, computed tomography (CT) has developed into a parallel non-invasive modality, which can be used for exclusion of CAD in symptomatic patients. According to large randomized multicenter trials, CT demonstrates sensitivity and specificity comparable to the aforementioned functional testing methods. In comparison to these modalities, CT has a clear advantage to deliver additional evidence about surrounding structures such as epicardial adipose tissue (EAT). It is assumed that EAT might have exocrine and endocrine effects and may initiate inflammation-processes in the directly neighboring coronary artery wall resulting in development of CAD. It is still unclear if the volume and density of EAT influence the atherogenesis, lead to genesis of vulnerable coronary plaques and increase rate of major adverse cardiac events (MACE). Even the coronary plaque composition might depend on the volume and density of the EAT. Due to improved spatial and temporal resolution, now CT data can be used for accurate composition analysis of coronary plaques. Besides the routine visual identification of high risk coronary plaque features, CT allows a quantitative analysis of the plaque compounds such as fibrotic, fatty and calcified tissue. We assume that patients with increased volume and density of EAT might present high-risk plaque features more frequently.The primary aim of this study is to investigate the effect of EAT volume and attenuation on the coronary plaque composition and the rate of MACE in median 25 months follow-up in a large cohort. The investigation is a part of the randomized PROspective Multicenter Imaging Study for Evaluation of chest pain trial (PROMISE Trial), which enrolled more than 10,000 patients with suspected CAD. The CT data of all 4589 patients, who were randomized into the anatomical testing arm and received cardiac CT examination, will be included in our study. Besides the improvement of the CT based risk stratification in patients with suspected CAD, the EAT analysis and the coronary plaque composition analysis should build a base for future multicenter, big data studies in Germany and Europe.