Department of Electronics, Computer Science and Systems (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy.
Med Biol Eng Comput. 2012 May;50(5):439-46. doi: 10.1007/s11517-012-0878-8. Epub 2012 Mar 9.
Considerable research effort has been devoted to the estimation of the degree of organisation of atrial fibrillation (AF), to potentially support clinical decision making. The aims of this study were to: (1) analyse the temporal variability of spatial organisation (complexity) and spectral distribution of AF in body surface potential maps (BSPM), proposing an automated implementation of the analysis and (2) assess the applicability to reduced lead-sets. Twenty-one persistent AF recordings of 3 min each (64 BSPM: 32 anterior, 32 posterior) were analysed. The relationship between spatial organisation (C) and its variability (CV) was quantified on automatically delineated TQ segments. The relationship between spectral concentration (SC) and spectral variability (SV) was quantified on the atrial activity (AA) extracted using principal component analysis. Three different lead-sets: 64, 32 anterior and 10 anterior channels were considered. Significant (p < 0.001) correlation (ρ) was found: ρ(CV, C) ≥ 0.80, ρ(SC, SV) ≤-0.83 for all lead-sets. The results suggest that a higher degree of spatial organisation is associated with reduced variability of spatial organisation over time, and lower spectral variability associated with more prominent spectral peak in the AF frequency band (4-10 Hz).
大量研究致力于评估心房颤动 (AF) 的组织程度,以潜在支持临床决策。本研究的目的是:(1) 分析体表电势图 (BSPM) 中 AF 的空间组织 (复杂性) 和频谱分布的时间可变性,提出分析的自动实现方法,(2) 评估其在导联减少情况下的适用性。分析了 21 例持续 3 分钟的 AF 记录(64 个 BSPM:32 个前,32 个后)。在自动描绘的 TQ 段上量化了空间组织 (C)与其可变性 (CV) 之间的关系。使用主成分分析提取的心房活动 (AA) 上量化了频谱浓度 (SC)与其可变性 (SV) 之间的关系。考虑了三种不同的导联组:64、32 个前和 10 个前导联。所有导联组均发现具有显著相关性 (p < 0.001):ρ(CV,C)≥0.80,ρ(SC,SV)≤-0.83。结果表明,较高的空间组织程度与随时间变化的空间组织可变性降低相关,而较低的频谱可变性与 AF 频段 (4-10 Hz) 中更明显的频谱峰值相关。