Song Yu-Jiao, Zhao Xiao-Ying, Wang Lu-Jing, Ning Ting, Chen Ming-Tian, Liu Pei, Chen Si-Wen, Zhao Xin-Xiang
Department of Radiology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Cardiovasc Diabetol. 2025 May 3;24(1):192. doi: 10.1186/s12933-025-02720-w.
Epicardial adipose tissue (EAT) comprises three distinct lipid components, each exerting differential effects on cardiovascular diseases. During disease progression, dynamic alterations in lipid composition and spatial distribution contribute to the inherent heterogeneity of EAT. The excessive activation of inflammatory cells may contribute to chronic inflammation, promoting atherosclerosis and cardiac diseases. However, the role of EAT in patients with myocardial infarction (MI) who develop heart failure with preserved ejection fraction (HFpEF) remains unclear. This study aims to quantify the overall and perivascular volumes of EAT using cardiac magnetic resonance (CMR) imaging and assess its heterogeneity, exploring the predictive value of EAT heterogeneity and different EAT volumes combined with inflammatory cells for the occurrence of HFpEF in MI patients with normal left ventricular ejection fraction (LVEF).
This retrospective cohort study enrolled patients diagnosed with MI with preserved LVEF via clinical assessment and CMR at the Second Affiliated Hospital of Kunming Medical University between January 2015 and July 2023. Patients who did not undergo percutaneous coronary intervention (PCI) were followed, with the incidence of HFpEF serving as the primary endpoint. The cohort was stratified into two groups: those without HFpEF and those who developed HFpEF.Cardiac structure, function, EAT volume, and infarct volume parameters were obtained using the CMR post-processing software CVI-42, while EAT heterogeneity parameters entropy were derived using Python software. Independent sample t-tests, non-parametric tests, and chi-square tests were employed to analyze the differences in clinical baseline data and CMR metrics between the two groups. Spearman's rank correlation was utilized to analyze the associations between EAT parameters and inflammatory cells, inflammatory markers, and diastolic dysfunction indicators. Furthermore, we conducted univariate and multivariate Cox regression analyses to determine the predictive value of each parameter for the development of HFpEF in MI patients. Time-dependent ROC curves were generated to evaluate the efficacy of each parameter in predicting HFpEF, the AIC values of each parameter and the final model were calculated to evaluate the predictive performance. The optimal cut-off values were identified using time-dependent ROC curves in R software, and Kaplan-Meier event-survival curves were plotted to illustrate the event-free rates based on these optimal thresholds.The median follow-up time was calculated using the reverse Kaplan-Meier method.
A total of 203 MI patients with normal LVEF were included, with 74 in the HFpEF group and 129 in the non-HFpEF group. No significant differences were observed between the two groups regarding age, sex, and infarct volume; however, significant statistical differences were noted in BMI, diabetes, renal failure, leukocytes, neutrophils, monocytes, total EAT, EAT entropy, left ventricular EAT (LV EAT), left atrial end-systolic volume (LAESV), triglycerides, NHR, MHR and LACI(Left atrioventricular coupling index) (P < 0.05). Both overall and local EAT volumes showed a positive correlation with leukocytes and monocytes,as well as with the inflammatory markers MHR and SIRI. Furthermore, EAT volume exhibited a positive correlation with the LACI, a marker of diastolic dysfunction. Univariate and multivariate Cox regression analyses indicated that BMI, diabetes, monocyte, LV EAT, and EAT entropy are independent risk factors for HFpEF. And the AIC value of the multivariate regression model was the smallest.Further time-dependent ROC analysis revealed that the maximum AUC for BMI was 0.67, while the AUC for LV EAT was 0.63, and EAT entropy was 0.60, the maximum AUC for monocyte was 0.70, and the combined prediction of LV EAT and EAT entropy had a maximum AUC of 0.70. After a median follow-up of 34 months, Kaplan-Meier survival curves demonstrated that LV EAT greater than 21.23 mL was associated with the occurrence of HFpEF, whereas EAT entropy was not.
In patients with chronic MI, normal LVEF, and no prior PCI, the occurrence of HFpEF is not correlated with infarct volume; however, BMI, diabetes, monocyte, LV EAT, and EAT entropy are independent risk factors for HFpEF with significant predictive value, with the highest predictive efficacy observed monocyte and when combining EAT entropy and LV EAT. Additionally, both overall and local EAT volumes exhibit a moderate positive correlation with leukocytes,monocytes and inflammatory markers, and were also positively correlated with diastolic dysfunction. This suggests that, in clinical practice, beyond traditional indicators, there should be an increased focus on EAT heterogeneity and perivascular EAT in MI patients with normal LVEF who have not undergone PCI to to reduce the incidence of HFpEF.
心外膜脂肪组织(EAT)由三种不同的脂质成分组成,每种成分对心血管疾病的影响各异。在疾病进展过程中,脂质组成和空间分布的动态变化导致了EAT固有的异质性。炎症细胞的过度激活可能导致慢性炎症,促进动脉粥样硬化和心脏疾病。然而,EAT在发生射血分数保留的心力衰竭(HFpEF)的心肌梗死(MI)患者中的作用仍不明确。本研究旨在利用心脏磁共振(CMR)成像量化EAT的总体积和血管周围体积,并评估其异质性,探讨EAT异质性和不同EAT体积结合炎症细胞对左心室射血分数(LVEF)正常的MI患者发生HFpEF的预测价值。
本回顾性队列研究纳入了2015年1月至2023年7月在昆明医科大学第二附属医院通过临床评估和CMR诊断为LVEF保留的MI患者。对未接受经皮冠状动脉介入治疗(PCI)的患者进行随访,将HFpEF的发生率作为主要终点。该队列分为两组:未发生HFpEF的患者和发生HFpEF的患者。使用CMR后处理软件CVI-42获取心脏结构、功能、EAT体积和梗死体积参数,而EAT异质性参数熵则使用Python软件得出。采用独立样本t检验、非参数检验和卡方检验分析两组之间临床基线数据和CMR指标的差异。利用Spearman等级相关性分析EAT参数与炎症细胞、炎症标志物和舒张功能障碍指标之间的关联。此外,我们进行了单变量和多变量Cox回归分析,以确定每个参数对MI患者发生HFpEF的预测价值。生成时间依赖性ROC曲线以评估每个参数预测HFpEF的效能,计算每个参数和最终模型的AIC值以评估预测性能。使用R软件中的时间依赖性ROC曲线确定最佳截断值,并绘制Kaplan-Meier事件生存曲线以说明基于这些最佳阈值的无事件发生率。使用反向Kaplan-Meier方法计算中位随访时间。
共纳入203例LVEF正常的MI患者,其中HFpEF组74例,非HFpEF组129例。两组在年龄、性别和梗死体积方面无显著差异;然而,在BMI、糖尿病、肾功能衰竭、白细胞、中性粒细胞、单核细胞、总EAT、EAT熵、左心室EAT(LV EAT)、左心房收缩末期容积(LAESV)、甘油三酯、NHR、MHR和左房室耦合指数(LACI)方面存在显著统计学差异(P < 0.05)。总体和局部EAT体积均与白细胞和单核细胞以及炎症标志物MHR和SIRI呈正相关。此外,EAT体积与舒张功能障碍标志物LACI呈正相关。单变量和多变量Cox回归分析表明,BMI、糖尿病、单核细胞、LV EAT和EAT熵是HFpEF的独立危险因素。多变量回归模型的AIC值最小。进一步的时间依赖性ROC分析显示,BMI的最大AUC为0.67,LV EAT的AUC为0.63,EAT熵为0.60,单核细胞的最大AUC为0.70,LV EAT和EAT熵的联合预测最大AUC为0.70。中位随访34个月后,Kaplan-Meier生存曲线表明,LV EAT大于21.23 mL与HFpEF的发生相关,而EAT熵则不然。
在慢性MI、LVEF正常且未接受过PCI的患者中,HFpEF的发生与梗死体积无关;然而,BMI、糖尿病、单核细胞、LV EAT和EAT熵是HFpEF的独立危险因素,具有显著的预测价值,其中单核细胞以及EAT熵与LV EAT联合预测时预测效能最高。此外,总体和局部EAT体积均与白细胞、单核细胞和炎症标志物呈中度正相关,并且与舒张功能障碍也呈正相关。这表明,在临床实践中,除了传统指标外,对于未接受PCI的LVEF正常的MI患者,应更加关注EAT异质性和血管周围EAT,以降低HFpEF的发生率。