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心脏磁共振衍生的左心室机械离散度改善肥厚型心肌病的风险分层及其与瘢痕异质性的相关性。

Cardiac Magnetic Resonance-Derived Left Ventricular Mechanical Dispersion Improves Risk Stratification of Hypertrophic Cardiomyopathy and its Correlations with Scar Heterogeneity.

作者信息

Zhao Xiaoying, Song Yujiao, Zhang Li, Wang Lujing, Zhao Xinxiang, Wang Jin

机构信息

Department of Radiology, The Second Affiliated Hospital of Kunming Medical University, Dianmiandadao No. 374, Kunming, 650101, Yunnan, China.

Department of Radiology, Guiqian International General Hospital, 1 Dongfeng Avenue, Wudang District, Guiyang, 550024, Guizhou, China.

出版信息

J Cardiovasc Transl Res. 2025 Jun 2. doi: 10.1007/s12265-025-10631-0.

Abstract

The accuracy of prevalent risk models recommended by American Heart Association/American College of Cardiology(AHA/ACC) and European Society of Cardiology(ESC) for hypertrophic cardiomyopathy(HCM) patients is suboptimal. We assessed the utility of cardiac magnetic resonance(CMR)-3D left ventricular mechanical dispersion(LVMD) in the prognostic stratification of 159 HCM and explore the correlation with myocardial fibrosis heterogeneity. Entropy demonstrated linear correlations with 3D LVMD. Patients experienced endpoint events exhibited significantly higher radial LVMD(LVMD-R), circumferential LVMD(LVMD-C), and longitudinal LVMD(LVMD-L). Kaplan-Meier analyses demonstrated that HCM patients with elevated LVMD had a higher risk of primary and secondary endpoint events. In multivariable Cox analysis incorporated the guidelines risk classification, both LVMD-C and LVMD-L emerged as significant predictors for endpoint events. We developed a model incorporated the 2022 ESC risk stratification in combination with LVMD-C and LVMD-L and revealed that combined model significantly outperformed the guidelines alone. Additionally, entropy demonstrated linear correlations with LVMD.

摘要

美国心脏协会/美国心脏病学会(AHA/ACC)和欧洲心脏病学会(ESC)推荐的用于肥厚型心肌病(HCM)患者的现有风险模型准确性欠佳。我们评估了心脏磁共振成像(CMR)-三维左心室机械离散度(LVMD)在159例HCM患者预后分层中的效用,并探讨其与心肌纤维化异质性的相关性。熵与三维LVMD呈线性相关。发生终点事件的患者表现出显著更高的径向LVMD(LVMD-R)、圆周LVMD(LVMD-C)和纵向LVMD(LVMD-L)。Kaplan-Meier分析表明,LVMD升高的HCM患者发生主要和次要终点事件的风险更高。在纳入指南风险分类的多变量Cox分析中,LVMD-C和LVMD-L均成为终点事件的显著预测因素。我们开发了一个结合2022 ESC风险分层以及LVMD-C和LVMD-L的模型,结果显示该联合模型明显优于单独的指南。此外,熵与LVMD呈线性相关。

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