Laura R Bear1,2,3,4, Ian J LeGrice5,6, Gregory B Sands5, Nigel A Lever5,7,8, Denis S Loiselle5,6, David J Paterson5,6,9, Leo K Cheng5, Bruce H Smaill5,6. 1. Auckland Bioengineering Institute (L.R.B., I.J.L., G.B.S., N.A.L., D.S.L., D.J.P., L.K.C., B.H.S.) laura.bear@ihu-liryc.fr. 2. University of Auckland, New Zealand. IHULIRYC, Fondation Bordeaux Université, France (L.R.B.). 3. Université de Bordeaux, France (L.R.B.). 4. Inserm, U1045, Centre de Recherche Cardio-Thoracique de Bordeaux, France (L.R.B.). 5. Auckland Bioengineering Institute (L.R.B., I.J.L., G.B.S., N.A.L., D.S.L., D.J.P., L.K.C., B.H.S.). 6. Department of Physiology (I.J.L., D.S.L., D.J.P., B.H.S.). 7. and Department of Medicine (N.A.L.). 8. Auckland City Hospital, New Zealand (N.A.L.). 9. Department of Physiology, Anatomy, and Genetics, University of Oxford, United Kingdom (D.J.P.).
Abstract
BACKGROUND: Inverse electrocardiographic mapping reconstructs cardiac electrical activity from recorded body surface potentials. This noninvasive technique has been used to identify potential ablation targets. Despite this, there has been little systematic evaluation of its reliability. METHODS: Torso and ventricular epicardial potentials were recorded simultaneously in anesthetized, closed-chest pigs (n=5), during sinus rhythm, epicardial, and endocardial ventricular pacing (70 records in total). Body surface and cardiac electrode positions were determined and registered using magnetic resonance imaging. Epicardial potentials were reconstructed during ventricular activation using experiment-specific magnetic resonance imaging-based thorax models, with homogeneous or inhomogeneous (lungs, skeletal muscle, fat) electrical properties. Coupled finite/boundary element methods and a meshless approach based on the method of fundamental solutions were compared. Inverse mapping underestimated epicardial potentials >2-fold (P<0.0001). RESULTS: Mean correlation coefficients for reconstructed epicardial potential distributions ranged from 0.60±0.08 to 0.64±0.07 across all methods. Epicardial electrograms were recovered with reasonable fidelity at ≈50% of sites (median correlation coefficient, 0.69-0.72), but variation was substantial. General activation spread was reproduced (median correlation coefficient, 0.72-0.78 for activation time maps after spatio-temporal smoothing). Epicardial foci were identified with a median location error ≈16 mm (interquartile range, 9-29 mm). Inverse mapping with meshless method of fundamental solutions was better than with finite/boundary element methods, and the latter were not improved by inclusion of inhomogeneous torso electrical properties. CONCLUSIONS: Inverse potential mapping provides useful information on the origin and spread of epicardial activation. However the spatio-temporal variability of recovered electrograms limit resolution and must constrain the accuracy with which arrhythmia circuits can be identified independently using this approach.
BACKGROUND: Inverse electrocardiographic mapping reconstructs cardiac electrical activity from recorded body surface potentials. This noninvasive technique has been used to identify potential ablation targets. Despite this, there has been little systematic evaluation of its reliability. METHODS: Torso and ventricular epicardial potentials were recorded simultaneously in anesthetized, closed-chest pigs (n=5), during sinus rhythm, epicardial, and endocardial ventricular pacing (70 records in total). Body surface and cardiac electrode positions were determined and registered using magnetic resonance imaging. Epicardial potentials were reconstructed during ventricular activation using experiment-specific magnetic resonance imaging-based thorax models, with homogeneous or inhomogeneous (lungs, skeletal muscle, fat) electrical properties. Coupled finite/boundary element methods and a meshless approach based on the method of fundamental solutions were compared. Inverse mapping underestimated epicardial potentials >2-fold (P<0.0001). RESULTS: Mean correlation coefficients for reconstructed epicardial potential distributions ranged from 0.60±0.08 to 0.64±0.07 across all methods. Epicardial electrograms were recovered with reasonable fidelity at ≈50% of sites (median correlation coefficient, 0.69-0.72), but variation was substantial. General activation spread was reproduced (median correlation coefficient, 0.72-0.78 for activation time maps after spatio-temporal smoothing). Epicardial foci were identified with a median location error ≈16 mm (interquartile range, 9-29 mm). Inverse mapping with meshless method of fundamental solutions was better than with finite/boundary element methods, and the latter were not improved by inclusion of inhomogeneous torso electrical properties. CONCLUSIONS: Inverse potential mapping provides useful information on the origin and spread of epicardial activation. However the spatio-temporal variability of recovered electrograms limit resolution and must constrain the accuracy with which arrhythmia circuits can be identified independently using this approach.
Authors: Andrew Grace; Stephan Willems; Christian Meyer; Atul Verma; Patrick Heck; Min Zhu; Xinwei Shi; Derrick Chou; Lam Dang; Christoph Scharf; Günter Scharf; Graydon Beatty Journal: JCI Insight Date: 2019-03-21
Authors: Leo K Cheng; Nipuni D Nagahawatte; Recep Avci; Peng Du; Zhongming Liu; Niranchan Paskaranandavadivel Journal: Front Neurosci Date: 2021-04-22 Impact factor: 5.152
Authors: Matthijs Cluitmans; Dana H Brooks; Rob MacLeod; Olaf Dössel; María S Guillem; Peter M van Dam; Jana Svehlikova; Bin He; John Sapp; Linwei Wang; Laura Bear Journal: Front Physiol Date: 2018-09-20 Impact factor: 4.566
Authors: Laura R Bear; Richard D Walton; Emma Abell; Yves Coudière; Michel Haissaguerre; Olivier Bernus; Rémi Dubois Journal: Front Physiol Date: 2019-02-26 Impact factor: 4.566
Authors: Pavel Jurak; Laura R Bear; Uyên Châu Nguyên; Ivo Viscor; Petr Andrla; Filip Plesinger; Josef Halamek; Vlastimil Vondra; Emma Abell; Matthijs J M Cluitmans; Rémi Dubois; Karol Curila; Pavel Leinveber; Frits W Prinzen Journal: Sci Rep Date: 2021-06-01 Impact factor: 4.379