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The EMERALD II study is a multinational, multicenter, and retrospective study. ACS patients who underwent CCTA from 2 months to 3 years prior to the event will be retrospectively identified. Plaques in the non-culprit vessels will be regarded as a primary control group.
The mechanisms of plaque rupture are not fully understood. Hemodynamic forces, plaque vulnerability, and the interaction between these factors may cause plaque instability and subsequent acute coronary syndrome (ACS). Previously, the first-in-human study, EMERALD I, showed that the addition of hemodynamic parameters calculated noninvasively from coronary computed tomography (CCTA) using computational fluid dynamics (CFD) improved the ability to predict the risk of acute coronary syndrome (ACS) compared with conventional approaches based on anatomical stenosis severity and adverse plaque characteristics. To validate the increment in discrimination and reclassification ability of a prediction model with hemodynamic parameters over a model with anatomical stenosis severity and adverse plaque characteristics. In this regard, we designed the subsequent EMERALD II study. In the EMERALD II study, we will refine methods for hemodynamic analysis and validate the previous algorithms on a much larger patient population. The study population will be divided into derivation and validation cohorts. Machine learning methods will be used to define a plaque rupture risk score based on plaque morphology, composition and hemodynamic forces in the derivation cohort, then the algorithm's prediction ability will be tested in the validation cohort.
Acute Myocardial Infarction
Coronary CT angiography
Samsung Medical Center, Sungkyunkwan University School of Medicine
Korea, Republic of
Enrolling by invitation
Seoul National University Hospital
Published on BioPortfolio: 2018-07-24T12:38:13-0400
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