Prognostic value of epicardial adipose tissue volume in combination with coronary plaque and flow assessment for the prediction of major adverse cardiac events
Introduction
Epicardial adipose tissue (EAT) has gained increasing attention due to its pathophysiological and metabolic influence on coronary tissue inflammation. With a crucial impact on atherosclerosis genesis, it has been declared a “promotor of atherosclerotic plaque progression and vulnerability” [1].
While invasive coronary angiography (ICA) provides the gold standard in the assessment of CAD, coronary CT angiography (CCTA) has increasingly emerged as a reliable and viable non-invasive alternative, and is recommended for the evaluation of CAD according to current guidelines [2], [3]. Beyond anatomical stenosis grading, CCTA requires both good temporal and spatial resolution for the adequate visualization and quantification of atherosclerotic plaques as precursors of adverse coronary events [4], [5].
Recent studies have shown the incremental value of additional risk stratification and prognostication by evaluating coronary plaque extent and morphology [6], [7]. Besides plaque composition and the presence of high-risk plaque features that are correlated with adverse outcomes, the assessment of EAT has become the subject of increasing scientific investigation, with emerging evidence showing association with the development of obstructive CAD [8], [9]. EAT is defined as a metabolically active visceral fat deposit located between the heart and pericardium, directly encompassing the coronary arteries and therefore representing the pericoronary adipose tissue (PCAT). Proven as an endocrine organ, EAT produces cytokines, growth factors, as well as vaso- and bioactive molecules known as adipokines, which can exert either a direct paracrine impact on surrounding coronary arteries and myocardium or a vasocrine effect through the local circulatory system [10]. Recent studies suggest that EAT has a complex bidirectional interaction with the underlying vascular wall and thus may serve as a surrogate marker of coronary artery inflammation mediated by dysregulated metabolism, previously described in detail [10], [11].
Due to its high spatial resolution in combination with providing a three-dimensional view of the coronary anatomy, non-contrast enhanced multidetector computed tomography (MDCT) is currently the preferred method for EAT volume assessment [12].
New findings underline the improved predictive ability of EAT quantification for the detection of obstructive CAD along with increased cardiac risk stratification beyond traditional cardiovascular risk factors [13], [14]. However, most studies focus on the association between EAT volume quantification and significant CAD. Thus, we assessed the added prognostic value of EAT volume quantification to coronary plaque and CT-derived fractional flow reserve (CT-FFR) for the prediction of major adverse cardiac events (MACE).
Section snippets
Study population
The protocol of this retrospective study and a waiver of informed consent were approved by the Institutional Review Board in compliance with the Health Insurance Portability and Accountability Act (HIPAA) of 1996. A retrospective analysis was performed on patients who underwent CCTA for the evaluation of suspected or known CAD between July 2014 and November 2017. Data collected from medical records included patient demographics, cardiovascular risk factors, clinical signs/symptoms, imaging
Patient characteristics
A total of 117 patients who underwent cCTA and ICA and were followed up for the occurrence of MACE and were retrospectively analyzed. Overall, the mean age was 58 ± 10 years with 71 (61%) male patients. Patients developing MACE showed significantly higher Morise score (12 ± 4.2 vs. 10 ± 2.7, p = 0.03) and diabetes rate (11 (57%) vs. 24 (24%) patients, p = 0.008). The median follow-up period was 40.4 months (IQR 26.2–60.1) with 19 MACE (16%). Overall, 3 patients had cardiac deaths and 14
Discussion
In the present study, we demonstrate that EAT volume quantification on non-contrast cardiac CT images provides additional and significantly improved prognostic performance for the prediction of future adverse cardiac events. While previous investigations showed predictive capability for cardiovascular risk stratification using clinical risk scores, plaque composition, plaque features, and CT-FFR as sole parameters [26], [27], [28], [29], our proposed model using a combination of these markers
Declaration of Competing Interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: No funding was received. Dr. Schoepf receives institutional research support and/or honoraria for speaking and consulting from Bayer, Bracco, Elucid BioImaging, Guerbet, HeartFlow Inc., Keya Medical, and Siemens Healthineers. Dr. Tesche has received speaker’s fees from Siemens Healthineers and Heartflow Inc. Dr. Varga-Szemes receives institutional research and
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2022, AtherosclerosisCitation Excerpt :Thus, diabetes, as a well-known independent cardiovascular risk factor for CAD and plaque progression with increased rates in morbidity and mortality, shows strong association with EAT [3,4]. In line, several prior studies using coronary CT angiography (CCTA) have demonstrated the relationship between EAT and atherosclerotic plaques including high-risk plaque features with increased risk of adverse cardiovascular events [5–7]. Additionally, CCTA has emerged as the preferred non-invasive imaging modality for precise quantification of both EAT and coronary plaque composition and burden within a single examination [8,9].
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