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心房颤动基质标测中左心房壁厚度的识别

Identification of left atrial wall thickness in substrate mapping of atrial fibrillation.

作者信息

Liu Wei, Li Shijie, Dou Lina, Hu Chunai, Han Bing

机构信息

Department of Cardiology, Xuzhou Central Hospital (Southeast University Affiliated Hospital), Xuzhou, Jiangsu, China.

Department of Cardiology, Peixian People's Hospital, Xuzhou, Jiangsu, China.

出版信息

Front Cardiovasc Med. 2025 Jun 25;12:1592532. doi: 10.3389/fcvm.2025.1592532. eCollection 2025.

Abstract

OBJECTIVE

The objective of this study was to assess the clinical relevance of left atrial wall thickness (LAWT) in identifying electrophysiological substrate abnormalities.

METHODS

Eighty-two patients with atrial fibrillation undergoing first-time catheter ablation at Xuzhou Central Hospital between March 2016 and May 2023 were enrolled in this study. The left atrium was anatomically segmented into five regions, with all patients undergoing delayed gadolinium-enhanced magnetic resonance imaging (LGE-MRI) for quantitative assessment of parameters including left atrial wall thickness (LAWT, epicardial fat excluded). Bipolar voltage mapping was systematically performed to delineate low-voltage zones (LVZs) and calculate their relative area proportion within the total atrial surface for each patient. The regional segmentation method for left atrial voltage mapping was consistent with that used in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI). Univariate and multivariate logistic regression analyses were conducted to identify clinical factors associated with LVZ formation. Receiver operating characteristic (ROC) curve analysis was employed to determine the optimal LAWT cutoff value for LVZ prediction, along with its corresponding sensitivity and specificity. Additionally, regional comparative analyses were performed between LGE-MRI-derived wall thickness measurements and their corresponding low-voltage zones identified by three-dimensional electroanatomic mapping.

RESULTS

The study cohort comprised 82 atrial fibrillation patients (44 paroxysmal AF, 38 persistent AF). Mean LAWT significantly differed between paroxysmal and persistent AF groups (2.6 ± 0.5 mm vs. 2.3 ± 0.4 mm,  = 0.02). Multivariate analysis identified age (OR = 1.111, 95% CI:1.03-1.19,  = 0.007), left atrial volume (OR = 1.029, 95% CI:1.003-1.055,  = 0.026), and LAWT (OR = 0.044, 95% CI:0.007-0.272,  = 0.001) as independent predictors of LVZs. Regional analysis revealed the septal wall was thinnest (1.76 ± 0.9 mm), followed by posterior (1.95 ± 0.4 mm) and bottom walls (2.62 ± 0.6 mm), with roof (2.89 ± 0.5 mm) and anterior walls (3.0 ± 0.4 mm) being thickest. Correspondingly, septal LVZ area was most extensive (22.5 ± 10.2%), exceeding posterior (15.3 ± 10.6%), bottom (12.6 ± 12.0%), roof (11.8 ± 10.0%), and anterior walls (10.8 ± 12.1%). ROC analysis demonstrated LAWT ≤ 2.3 mm predicted LVZs with 71% sensitivity and 68.2% specificity (AUC = 0.723,  < 0.001). Additional predictors included age >64.5 years (AUC = 0.722, sensitivity 65.9%, specificity 73.7%) and left atrial volume >119.2 ml (AUC = 0.682, sensitivity 61.4%, specificity 78.9%).

CONCLUSIONS

This study demonstrate that LAWT significantly correlate with both atrial fibrillation progression and electroanatomical remodeling. Notably, regions exhibiting LAWT ≤ 2.3 mm predict more extensive LVZs. Our findings suggest that non-invasive LGE-MRI-based measurement of LAWT may enhance the detection rate of left atrial pathological substrates.

摘要

目的

本研究旨在评估左心房壁厚度(LAWT)在识别电生理基质异常方面的临床相关性。

方法

选取2016年3月至2023年5月在徐州中心医院首次接受导管消融的82例房颤患者纳入本研究。将左心房在解剖学上分为五个区域,所有患者均接受延迟钆增强磁共振成像(LGE-MRI),以定量评估包括左心房壁厚度(LAWT,排除心外膜脂肪)在内的参数。系统地进行双极电压标测,以描绘低电压区(LVZ),并计算每位患者LVZ在整个心房表面的相对面积比例。左心房电压标测的区域分割方法与延迟钆增强磁共振成像(LGE-MRI)中使用的方法一致。进行单因素和多因素逻辑回归分析,以确定与LVZ形成相关的临床因素。采用受试者工作特征(ROC)曲线分析来确定预测LVZ的最佳LAWT截断值及其相应的敏感性和特异性。此外,还对LGE-MRI得出的壁厚度测量值与其通过三维电解剖标测确定的相应低电压区进行了区域比较分析。

结果

研究队列包括82例房颤患者(44例阵发性房颤,38例持续性房颤)。阵发性房颤组和持续性房颤组的平均LAWT有显著差异(2.6±0.5mm对2.3±0.4mm,P=0.02)。多因素分析确定年龄(OR=1.111,95%CI:1.03-1.19,P=0.007)、左心房容积(OR=1.029,95%CI:1.003-1.055,P=0.026)和LAWT(OR=0.044,95%CI:0.007-0.272,P=0.001)是LVZ的独立预测因素。区域分析显示,间隔壁最薄(1.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e68/12238022/6e63fc76f9c4/fcvm-12-1592532-g001.jpg

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