Gharbalchi No F, Serinagaoglu Dogrusoz Y, Onak O N, Weber G-W
Biomedical Engineering Graduate Program, METU, Ankara, Turkey.
Biomedical Engineering Graduate Program, METU, Ankara, Turkey; Electrical and Electronics Engineering Department, METU, Ankara, Turkey.
J Electrocardiol. 2020 May-Jun;60:44-53. doi: 10.1016/j.jelectrocard.2020.02.017. Epub 2020 Mar 5.
Noninvasive electrocardiographic imaging (ECGI) is used for obtaining high-resolution images of the electrical activity of the heart, and is a powerful method with the potential to detect certain arrhythmias. However, there is no 'best' lead configuration in the literature to measure the torso potentials. This paper evaluates ECGI reconstructions using various reduced leadset configurations, explores whether one can find a common reduced leadset configuration that can accurately reconstruct the electrograms for datasets with different pacing sites, and compares two activation time estimation methods.
We used 23 ventricularly-paced datasets with pacing sites on different regions of the epicardium. Starting with a full 192‑leadset, we found "optimized" reduced leadsets specific to each dataset; we considered 64‑lead and 32‑lead configurations. Based on the histogram of individual "optimized" lead selections, we found a common reduced leadset. We compared the ECGI reconstructions and activation times of the individually optimized lead configurations with the common lead configurations.
Both 64‑lead configurations had similar performances to the 192‑leadset. 32‑leadset configurations, on the other hand, yielded noisy reconstructions, which affected their performance.
There are no statistically significant differences in the performance of the inverse solutions when a 64‑lead common reduced leadset is used to estimate the electrograms and their respective pacing sites compared to using the full leadset. 32‑lead configurations, on the other hand, require a more careful study to improve their performance. The activation time method used significantly affects the pacing site estimation performance, especially with fewer electrodes.
无创心电图成像(ECGI)用于获取心脏电活动的高分辨率图像,是检测某些心律失常的有力方法。然而,文献中没有用于测量躯干电位的“最佳”导联配置。本文评估了使用各种简化导联配置的ECGI重建,探讨是否能找到一种通用的简化导联配置,以准确重建不同起搏部位数据集的心电图,并比较了两种激活时间估计方法。
我们使用了23个心外膜不同区域起搏的心室起搏数据集。从完整的192导联开始,我们为每个数据集找到了“优化”的简化导联;我们考虑了64导联和32导联配置。基于各个“优化”导联选择的直方图,我们找到了一个通用的简化导联。我们将单独优化的导联配置与通用导联配置的ECGI重建和激活时间进行了比较。
两种64导联配置的性能与192导联相似。另一方面,32导联配置产生了有噪声的重建,影响了其性能。
与使用完整导联相比,当使用64导联通用简化导联估计心电图及其各自的起搏部位时,逆解的性能没有统计学上的显著差异。另一方面,32导联配置需要更仔细的研究来提高其性能。所使用的激活时间方法对起搏部位估计性能有显著影响,尤其是电极数量较少时。