非阻塞性肥厚性心肌病左室肥厚、心肌纤维化和左心房功能的相关性:来自CMR-FT成像的见解

Yan Zheng, Ma Liyuan, Qian Wu, Huairong Zhang, Yuan Li, Rui Li, Li Zhu
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引用次数: 0

摘要

非阻塞性肥厚性心肌病(NOHCM)与左心室(LV)肥大和心肌纤维化相关,其进行性损害左心房(LA)功能。本研究通过心脏磁共振(CMR)成像和特征跟踪(FT)应变分析,评估了99例NOHCM患者左室肥大和纤维化对LA功能障碍的影响,根据晚期钆增强(LGE)的程度将其分为四组:无纤维化(LGE 0.75)。这些发现突出了CMR-FT作为早期检测NOHCM患者LA功能障碍的敏感和可靠工具的临床意义,甚至在明显的左室结构改变发生之前。CMR-FT识别LA机制细微变化的能力可以为风险分层提供有价值的见解,并指导早期干预策略,最终改善该患者群体的临床结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Correlation between left ventricular hypertrophy, myocardial fibrosis, and left atrial function in non-obstructive hypertrophic cardiomyopathy: insights from CMR-FT imaging.

Nonobstructive hypertrophic cardiomyopathy (NOHCM) is associated with left ventricular (LV) hypertrophy and myocardial fibrosis, which progressively impair left atrial (LA) function. This study evaluated the impact of LV hypertrophy and fibrosis on LA dysfunction using cardiac magnetic resonance (CMR) imaging and feature-tracking (FT) strain analysis in 99 NOHCM patients, who were stratified into four groups based on the extent of late gadolinium enhancement (LGE): no fibrosis (LGE < 7%), mild fibrosis (7% ≤ LGE < 15%), moderate fibrosis (15% ≤ LGE < 30%), and severe fibrosis (LGE ≥ 30%). LA functional parameters, including reservoir strain (εs), conduit strain (εe), and pump strain (εa), showed significant reductions with increasing LGE burden (P < 0.05), with functional decline detectable even in mild fibrosis cases despite preserved LV ejection fraction. LV morphological and functional indices, such as global peak wall thickness (GPWT), LV end-systolic volume (LVESV), and LGE percentage, negatively correlated with LA strain metrics (r = -0.2 to -0.7, P < 0.05). Strain analysis demonstrated high reproducibility (ICC > 0.75). These findings highlight the clinical significance of CMR-FT as a sensitive and reliable tool for early detection of LA dysfunction in NOHCM patients, even before significant LV structural changes occur. The ability of CMR-FT to identify subtle changes in LA mechanics could provide valuable insights for risk stratification and guide early intervention strategies, ultimately improving clinical outcomes in this patient population.

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