Miguel Rodrigo1, Andreu M Climent2, Alejandro Liberos2, Francisco Fernández-Avilés3, Omer Berenfeld4, Felipe Atienza5, Maria S Guillem6. 1. ITACA, Universitat Politècnica de València, Valencia, Spain. 2. 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. 3. 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; Facultad de Medicina. Universidad Complutense de Madrid, Madrid, Spain. 4. Center for Arrhythmia Research, University of Michigan, Ann Arbor, Michigan. 5. 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; Facultad de Medicina. Universidad Complutense de Madrid, Madrid, Spain. Electronic address: felipe.atienza@gmail.com. 6. ITACA, Universitat Politècnica de València, Valencia, Spain. Electronic address: mguisan@eln.upv.es.
Abstract
BACKGROUND: Dominant frequency (DF) and rotor mapping have been proposed as noninvasive techniques to guide localization of drivers maintaining atrial fibrillation (AF). OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
BACKGROUND: Dominant frequency (DF) and rotor mapping have been proposed as noninvasive techniques to guide localization of drivers maintaining atrial fibrillation (AF). OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.
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