Campos Fernando O, Wijesuriya Nadeev, Elliott Mark K, de Vere Felicity, Howell Sandra, Strocchi Marina, Monaci Sofia, Whitaker John, Plank Gernot, Rinaldi Christopher A, Bishop Martin J
School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Cardiology, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom.
Heart Rhythm. 2025 Jul;22(7):1790-1799. doi: 10.1016/j.hrthm.2024.12.036. Epub 2024 Dec 28.
Electrocardiographic imaging (ECGi) is a noninvasive technique for ventricular tachycardia ablation planning. However, it is limited to reconstructing epicardial surface activation. In silico pace mapping combines a personalized computational model with clinical electrocardiograms (ECGs) to generate a virtual 3-dimensional pace map.
The purpose of this study was to compare the ability of ECGi and in silico pace mapping to determine the site of ventricular pacing.
ECGi recordings were collected during left ventricular (endocardial: n=5; epicardial: n=1), septal (n=3), and right ventricular (RV) apical (n=15) pacing along with compute tomography. Personalized computed tomography-based ventricular-torso computational models were created and aligned with the 252 ECGi vest electrodes. Ventricles were paced at 1000 random sites, and the corresponding body surface potentials (BSPs) and ECGs were derived. In silico pace maps were then reconstructed by correlating all simulated ECGs or BSPs with the corresponding paced clinical signals. The distance (d) between the pacing electrode (ground truth) and the location with the strongest correlation was determined; for ECGi, the site with the earliest activation time was used.
In silico pace mapping consistently outperformed ECGi in locating the pacing origin, with the best results when all BSPs were used. During left ventricular pacing, the spatial accuracy of in silico pacing mapping was 9.5 mm with BSPs and 12.2 mm when using ECGs as compared with 30.8 mm when using ECGi. During RV pacing, d = 26.1 mm using BSPs, d = 30.9 mm using ECGs, and d = 29.1 mm using ECGi.
In silico pace mapping is more accurate than ECGi in detecting paced activation. Performance was optimal when all BSPs were used and reduced during RV apical pacing.
心电图成像（ECGi）是一种用于室性心动过速消融规划的非侵入性技术。然而，它仅限于重建心外膜表面激活。计算机模拟起搏标测将个性化计算模型与临床心电图（ECG）相结合，以生成虚拟三维起搏标测图。
本研究的目的是比较ECGi和计算机模拟起搏标测确定心室起搏部位的能力。
在左心室（心内膜：n = 5；心外膜：n = 1）、间隔（n = 3）和右心室（RV）心尖部（n = 15）起搏期间收集ECGi记录，并进行计算机断层扫描。创建基于个性化计算机断层扫描的心室-躯干计算模型，并将其与252个ECGi背心电极对齐。在1000个随机部位进行心室起搏，并导出相应的体表电位（BSP）和ECG。然后通过将所有模拟的ECG或BSP与相应的起搏临床信号相关联来重建计算机模拟起搏标测图。确定起搏电极（真实位置）与相关性最强的位置之间的距离（d）；对于ECGi，使用激活时间最早的部位。
在定位起搏起源方面，计算机模拟起搏标测始终优于ECGi，使用所有BSP时效果最佳。在左心室起搏期间，使用BSP时计算机模拟起搏标测的空间精度为9.5 mm，使用ECG时为12.2 mm，而使用ECGi时为30.8 mm。在RV起搏期间，使用BSP时d = 26.1 mm，使用ECG时d = 30.9 mm，使用ECGi时d = 29.1 mm。
在检测起搏激活方面，计算机模拟起搏标测比ECGi更准确。使用所有BSP时性能最佳，在RV心尖部起搏期间性能降低。
