ITACA Institute, Universitat Politècnica de València, València, Spain.
ITACA Institute, Universitat Politècnica de València, València, Spain.
J Electrocardiol. 2023 Mar-Apr;77:58-61. doi: 10.1016/j.jelectrocard.2022.12.007. Epub 2023 Jan 3.
Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry.
Multiple‑lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes.
CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%.
Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice.
心电图成像是一种非侵入性技术,需要心脏成像来重建心脏电活动。在这项研究中,我们通过量化心脏网格在胸腔内位置不准确或几何形状不准确时的误差,探索了无图像心电图成象。
记录了 25 例心房颤动(AF)患者的多导联体表记录。通过对每位患者的医学图像进行分割,获得心脏心房网格。用每位患者的分割心房网格计算心电图成象,并与用于心电图成象估计的心房网格的误差下的心电图成象进行比较。我们通过人为地将心房在胸腔内的位置和心房网格的几何形状进行平移,来模拟心房在胸腔内的位置的不确定性,同时使用参考数据库中的心房网格来模拟心房网格的几何形状。比较了用实际网格和平移或估计网格获得的心电图成象信号的相关系数、相对差异测量星和心外膜节点中主导频率(DF)估计的误差。
将实际心房网格从原始位置平移 1cm 后获得的心电图成象信号的 CC 高于 0.97。用患者特定的心房几何形状和估计的心房几何形状获得的心电图成象的 CC 为 0.93±0.11。使用估计的心房网格进行 DF 估计的平均误差为 7.6±5.9%。
无图像心电图成象即使在复杂的心律失常中也能提供心脏电生理参数(如激活率)的稳健估计。此外,它可以允许在临床实践中更广泛地使用心电图成象。