肥厚性心肌病的心肌熵和风险预测因素:来自NHLBI HCM登记的分析。

IF 7 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
Panagiotis Antiochos, Yin Ge, Michael Jerosch-Herold, Louis-Philippe David, Bobak Heydari, Paul Kolm, Dong-Yun Kim, Rob J van der Geest, Hugh Watkins, Milind Y Desai, Carolyn Y Ho, Sarahfaye F Dolman, Patrice Desvigne-Nickens, Martin S Maron, Jeanette Schulz-Menger, Stefan K Piechnik, Evan Appelbaum, William S Weintraub, Stefan Neubauer, Christopher M Kramer, Raymond Y Kwong
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引用次数: 0

摘要

背景:熵是一种通过心血管磁共振成像测量心肌组织异质性的新方法,在肥厚性心肌病(HCM)患者中可能具有临床价值。我们的目的是研究熵与HCM风险预测因子的关联,使用国家心脏、肺和血液研究所HCM登记处。方法:利用晚期钆增强(LGE)短轴叠加图像左室(LV)心肌像素信号强度的概率分布计算熵值。熵值与人口学、遗传学、影像学和血清生物标志物以及动态动态心电图记录和欧洲心脏病学会5年心脏性猝死风险评分相关。结果:在1736例HCM患者中,左室熵与肌瘤突变、室性心动过速、房颤史、cTnT(心脏肌钙蛋白T)和NT-proBNP (n -末端前b型利钠肽)水平升高(ppppp)有显著相关性。在HCM患者中,LV熵与不良结局的临床、影像学和生物学预测因子相关,独立于LGE的存在,并且是动态心电图中室性心动过速的最强预测因子。注册:网址:https://www.clinicaltrials.gov;唯一标识符:NCT01915615。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Myocardial Entropy and Risk Predictors in Hypertrophic Cardiomyopathy: An Analysis From the NHLBI HCM Registry.

Background: Entropy, a novel measure of myocardial tissue heterogeneity by cardiovascular magnetic resonance imaging, may have clinical value in patients with hypertrophic cardiomyopathy (HCM). We aimed to investigate the associations of entropy with risk predictors in HCM, using the National Heart, Lung, and Blood Institute HCM Registry.

Methods: Entropy values were calculated using the probability distribution of pixel signal intensities of the left ventricular (LV) myocardium on the late gadolinium enhancement (LGE) short-axis stack images. Entropy values were correlated with demographic, genetic, imaging, and serum biomarkers as well as ambulatory Holter recordings and the European Society of Cardiology risk score of sudden cardiac death at 5 years.

Results: Among 1736 patients with HCM, LV entropy demonstrated significant associations with sarcomere mutations, history of ventricular tachycardia, atrial fibrillation, and elevation of cTnT (cardiac troponin T) and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels (P<0.001). Furthermore, LV entropy demonstrated an association with increased maximal LV wall thickness, LGE presence and extent, higher extracellular volume, left atrial area and function, myocardial strain (P<0.001), and was positively correlated with higher values of the European Society of Cardiology risk score (P<0.001). In the subgroup of patients without LGE (n=858), entropy values remained significantly associated with a history of ventricular tachycardia, increased maximal wall thickness, decreased myocardial strain, and the European Society of Cardiology risk score (P<0.05 for all). In both the whole cohort and in patients without LGE, LV entropy was the strongest predictor of ventricular tachycardia on Holter.

Conclusions: In patients with HCM, LV entropy demonstrated associations with clinical, imaging, and biological predictors of adverse outcomes independent of LGE presence and was the strongest predictor of ventricular tachycardia on Holter.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01915615.

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来源期刊
CiteScore
6.30
自引率
2.70%
发文量
225
审稿时长
6-12 weeks
期刊介绍: Circulation: Cardiovascular Imaging, an American Heart Association journal, publishes high-quality, patient-centric articles focusing on observational studies, clinical trials, and advances in applied (translational) research. The journal features innovative, multimodality approaches to the diagnosis and risk stratification of cardiovascular disease. Modalities covered include echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging and spectroscopy, magnetic resonance angiography, cardiac positron emission tomography, noninvasive assessment of vascular and endothelial function, radionuclide imaging, molecular imaging, and others. Article types considered by Circulation: Cardiovascular Imaging include Original Research, Research Letters, Advances in Cardiovascular Imaging, Clinical Implications of Molecular Imaging Research, How to Use Imaging, Translating Novel Imaging Technologies into Clinical Applications, and Cardiovascular Images.
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