Department of Electrical Engineering, University of Minnesota, Minneapolis, Minnesota, USA.
Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota, USA.
J Cardiovasc Electrophysiol. 2021 May;32(5):1268-1280. doi: 10.1111/jce.14948. Epub 2021 Feb 22.
Catheter ablation is associated with limited success rates in patients with persistent atrial fibrillation (AF). Currently, existing mapping systems fail to identify critical target sites for ablation. Recently, we proposed and validated several techniques (multiscale frequency [MSF], Shannon entropy [SE], kurtosis [Kt], and multiscale entropy [MSE]) to identify pivot point of rotors using ex-vivo optical mapping animal experiments. However, the performance of these techniques is unclear for the clinically recorded intracardiac electrograms (EGMs), due to the different nature of the signals.
This study aims to evaluate the performance of MSF, MSE, SE, and Kt techniques to identify the pivot point of the rotor using unipolar and bipolar EGMs obtained from numerical simulations.
Stationary and meandering rotors were simulated in a 2D human atria. The performances of new approaches were quantified by comparing the "true" core of the rotor with the core identified by the techniques. Also, the performances of all techniques were evaluated in the presence of noise, scar, and for the case of the multielectrode multispline and grid catheters.
Our results demonstrate that all the approaches are able to accurately identify the pivot point of both stationary and meandering rotors from both unipolar and bipolar EGMs. The presence of noise and scar tissue did not significantly affect the performance of the techniques. Finally, the core of the rotors was correctly identified for the case of multielectrode multispline and grid catheter simulations.
The core of rotors can be successfully identified from EGMs using novel techniques; thus, providing motivation for future clinical implementations.
导管消融术在持续性心房颤动(房颤)患者中的成功率有限。目前,现有的映射系统无法识别消融的关键靶位。最近,我们提出并验证了几种技术(多尺度频率[MSF]、香农熵[SE]、峰度[Kt]和多尺度熵[MSE]),以使用离体光学映射动物实验来识别转子的枢轴点。然而,由于信号性质不同,这些技术在临床记录的心内电图(EGM)中的性能尚不清楚。
本研究旨在评估 MSF、MSE、SE 和 Kt 技术在使用数值模拟获得的单极和双极 EGM 识别转子枢轴点的性能。
在二维人类心房中模拟静止和蜿蜒的转子。通过将“真实”转子核心与技术识别的核心进行比较,定量评估新方法的性能。此外,还评估了所有技术在噪声、疤痕存在的情况下,以及在多电极多折线和网格导管的情况下的性能。
我们的结果表明,所有方法都能够从单极和双极 EGM 准确识别静止和蜿蜒转子的枢轴点。噪声和疤痕组织的存在并没有显著影响技术的性能。最后,对于多电极多折线和网格导管模拟的情况,转子的核心被正确识别。
可以使用新的技术从 EGM 中成功地识别转子的核心,为未来的临床应用提供了动力。