Principal Component Analysis of Body Surface Potential Mapping in Atrial Fibrillation Patients Suggests Additional ECG Lead Locations

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Abstract

Atrial fibrillation (AF) is typically detected and analyzed in a non-invasive way using the standard 12-lead ECG. However, AF substrate complexity quantification may be suboptimal using conventional ECG locations. We analyzed high-density body surface potential maps of 75 patients in persistent AF to locate regions where AF complexity was predominantly expressed and to search for potential additional lead locations. Principal component analysis was applied to 1 minute of AF for each patient on the original ECG, TQ segments and extracted atrial activity (AA). Spatial complexity k(0.95) was higher in AA or TQ segments than in ECG (median k(0.9 5), AA: 13 components, TQ: 7, ECG: 2, p < 0.001). Normalized variance described by the top 3 principal components was lower in AA and TQ segments (median %, AA: 85 %, TQ: 87 %, ECG: 99 %, p < 0.001). Maps of normalized component coefficient energy showed expression of major ECG components concentrated in the region covered by V-1 - V-6, while the major TQ and AA components were more dispersed around the precordial leads, suggesting that non-invasive assessment of AF complexity by the standard 12-lead ECG is suboptimal. Placing additional leads around the precordial leads may improve non-invasive characterization of the AF substrate.
Original languageEnglish
Pages (from-to)893-896
JournalComputing in Cardiology Conference
Volume41
Publication statusPublished - 2014

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