Analysis of Predictive Model of Coronary Vulnerable Plaque under Hemodynamic Numerical Simulation

Abstract

Objective. Vulnerable plaque is considered to be the cause of most clinical coronary arteries, and linear cytokines are an important factor causing plaque instability. Early prediction of vulnerable plaque is of great significance in the treatment of cardiovascular diseases. Methods. Computational fluid dynamics (CFD) was used to simulate the hemodynamics around plaques, and the serum biochemical markers in 224 patients with low-risk acute coronary syndrome (ACS) were analyzed. Vulnerable plaques were predicted according to the distribution of biochemical markers in serum. Results. CFD can accurately capture the hemodynamic characteristics around the plaque. The patient’s age, history of hyperlipidemia, apolipoprotein B (apoB), adiponectin (ADP), and sE-Selection were risk factors for vulnerable plaque. Area under curve (AUC) values corresponding to the five biochemical markers were 0.601, 0.523, 0.562, 0.519, 0.539, and the AUC value after the combination of the five indicators was 0.826. Conclusion. The combination of multiple biochemical markers to predict vulnerable plaque was of high diagnostic value, and this method was convenient and noninvasive, which was worthy of clinical promotion.