Rodrigo Miguel, Climent Andreu M, Liberos Alejandro, Fernández-Avilés Francisco, Berenfeld Omer, Atienza Felipe, Guillem Maria S
ITACA, Universitat Politècnica de València, Valencia, Spain.
ITACA, Universitat Politècnica de València, Valencia, Spain; Cardiology Department, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; CIBERCV, Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares, Madrid, Spain.
Heart Rhythm. 2017 Aug;14(8):1224-1233. doi: 10.1016/j.hrthm.2017.04.017. Epub 2017 Apr 10.
Dominant frequency (DF) and rotor mapping have been proposed as noninvasive techniques to guide localization of drivers maintaining atrial fibrillation (AF).
The purpose of this study was to evaluate the robustness of both techniques in identifying atrial drivers noninvasively under the effect of electrical noise or model uncertainties.
Inverse-computed DFs and phase maps were obtained from 30 different mathematical AF simulations. Epicardial highest dominant frequency (HDF) regions and rotor location were compared with the same inverse-computed measurements after addition of noise to the ECG, size variations of the atria, and linear or angular deviations in the atrial location inside the thorax.
Inverse-computed electrograms (EGMs) individually correlated poorly with the original EGMs in the absence of induced uncertainties (0.45 ± 0.12) and were worse with 10-dB noise (0.22 ± 0.11), 3-cm displacement (0.01 ± 0.02), or 36° rotation (0.02 ± 0.03). However, inverse-computed HDF regions showed robustness against induced uncertainties: from 82% ± 18% match for the best conditions, down to 73% ± 23% for 10-dB noise, 77% ± 21% for 5-cm displacement, and 60% ± 22% for 36° rotation. The distance from the inverse-computed rotor to the original rotor was also affected by uncertainties: 0.8 ± 1.61 cm for the best conditions, 2.4 ± 3.6 cm for 10-dB noise, 4.3 ± 3.2 cm for 4-cm displacement, and 4.0 ± 2.1 cm for 36° rotation. Restriction of rotor detections to the HDF area increased rotor detection accuracy from 4.5 ± 4.5 cm to 3.2 ± 3.1 cm (P <.05) with 0-dB noise.
The combination of frequency and phase-derived measurements increases the accuracy of noninvasive localization of atrial rotors driving AF in the presence of noise and uncertainties in atrial location or size.
主导频率(DF)和转子标测已被提议作为指导维持心房颤动(AF)的驱动因素定位的非侵入性技术。
本研究的目的是评估这两种技术在电噪声或模型不确定性影响下非侵入性识别心房驱动因素的稳健性。
从30种不同的数学AF模拟中获得逆计算的DF和相位图。将心外膜最高主导频率(HDF)区域和转子位置与在心电图中添加噪声、心房大小变化以及胸腔内心房位置的线性或角度偏差后相同的逆计算测量结果进行比较。
在没有诱导不确定性的情况下,逆计算的心电图(EGM)与原始EGM的个体相关性较差(0.45±0.12),在10 dB噪声(0.22±0.11)、3 cm位移(0.01±0.02)或36°旋转(0.02±0.03)时更差。然而,逆计算的HDF区域显示出对诱导不确定性的稳健性:在最佳条件下匹配率为82%±18%,在10 dB噪声时降至73%±23%,在5 cm位移时为77%±21%,在36°旋转时为60%±22%。逆计算的转子到原始转子的距离也受到不确定性的影响:在最佳条件下为0.8±1.61 cm,在10 dB噪声时为2.4±3.6 cm,在4 cm位移时为4.3±3.2 cm,在36°旋转时为4.0±2.1 cm。将转子检测限制在HDF区域可将转子检测精度从4.5±4.5 cm提高到3.2±3.1 cm(P<.05),噪声为0 dB。
在存在噪声以及心房位置或大小的不确定性的情况下,频率和相位衍生测量的组合提高了驱动AF的心房转子非侵入性定位的准确性。