3,975 research outputs found

    Validation and Opportunities of Electrocardiographic Imaging: From Technical chievements to Clinical Applications

    Get PDF
    [EN] Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and non-invasively reconstructed in a digitized model of the patient's three-dimensional heart, which has led to clinical interest in ECGI's ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI's ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose 'best' practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists, and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique toward a useful role in clinical practice.This study received financial support from the Hein Wellens Fonds, the Cardiovascular Research and Training Institute (CVRTI), the Nora Eccles Treadwell Foundation, the National Institute of General Medical Sciences of the National Institutes of Health (P41GM103545), the National Institutes of Health (NIH HL080093), the French government as part of the Investments of the Future program managed by the National Research Agency (ANR-10-IAHU-04), from the VEGA Grant Agency in Slovakia (2/0071/16), from the Slovak Research and Development Agency (APVV-14-0875), the Fondo Europeo de Desarrollo Regional (FEDER), the Instituto de Salud Carlos III (PI17/01106) and from Conselleria d'Educacio, Investigacio, Cultura i Esport de la Generalitat Valenciana (AICO/2018/267) and NIH grant (HL125998) and National Science Foundation (ACI-1350374).Cluitmans, M.; Brooks, D.; Macleod, RS.; Dossel, O.; Guillem Sánchez, MS.; Van Dam, P.; Svehlikova, J.... (2018). Validation and Opportunities of Electrocardiographic Imaging: From Technical chievements to Clinical Applications. Frontiers in Physiology. 9. https://doi.org/10.3389/fphys.2018.01305S9Andrews, C. M., Srinivasan, N. T., Rosmini, S., Bulluck, H., Orini, M., Jenkins, S., … Rudy, Y. (2017). Electrical and Structural Substrate of Arrhythmogenic Right Ventricular Cardiomyopathy Determined Using Noninvasive Electrocardiographic Imaging and Late Gadolinium Magnetic Resonance Imaging. Circulation: Arrhythmia and Electrophysiology, 10(7). doi:10.1161/circep.116.005105Aras, K., Good, W., Tate, J., Burton, B., Brooks, D., Coll-Font, J., … MacLeod, R. (2015). Experimental Data and Geometric Analysis Repository—EDGAR. Journal of Electrocardiology, 48(6), 975-981. doi:10.1016/j.jelectrocard.2015.08.008Austen, W., Edwards, J., Frye, R., Gensini, G., Gott, V., Griffith, L., … Roe, B. (1975). A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation, 51(4), 5-40. doi:10.1161/01.cir.51.4.5Bayley, R. H., & Berry, P. M. (1962). The electrical field produced by the eccentric current dipole in the nonhomogeneous conductor. American Heart Journal, 63(6), 808-820. doi:10.1016/0002-8703(62)90065-0Bear, L. R., Huntjens, P. R., Walton, R. D., Bernus, O., Coronel, R., & Dubois, R. (2018). Cardiac electrical dyssynchrony is accurately detected by noninvasive electrocardiographic imaging. Heart Rhythm, 15(7), 1058-1069. doi:10.1016/j.hrthm.2018.02.024Bear, L. R., LeGrice, I. J., Sands, G. B., Lever, N. A., Loiselle, D. S., Paterson, D. J., … Smaill, B. H. (2018). How Accurate Is Inverse Electrocardiographic Mapping? Circulation: Arrhythmia and Electrophysiology, 11(5). doi:10.1161/circep.117.006108Berger, T., Fischer, G., Pfeifer, B., Modre, R., Hanser, F., Trieb, T., … Hintringer, F. (2006). Single-Beat Noninvasive Imaging of Cardiac Electrophysiology of Ventricular Pre-Excitation. Journal of the American College of Cardiology, 48(10), 2045-2052. doi:10.1016/j.jacc.2006.08.019Berger, T., Pfeifer, B., Hanser, F. F., Hintringer, F., Fischer, G., Netzer, M., … Seger, M. (2011). Single-Beat Noninvasive Imaging of Ventricular Endocardial and Epicardial Activation in Patients Undergoing CRT. PLoS ONE, 6(1), e16255. doi:10.1371/journal.pone.0016255Dubois, R., Pashaei, A., Duchateau, J., & Vigmond, E. (2016). Evaluation of Combined Noninvasive Electrocardiographic Imaging and Phase Mapping approach for Atrial Fibrillation: A Simulation Study. 2016 Computing in Cardiology Conference (CinC). doi:10.22489/cinc.2016.037-540Duchateau, J., Potse, M., & Dubois, R. (2017). Spatially Coherent Activation Maps for Electrocardiographic Imaging. IEEE Transactions on Biomedical Engineering, 64(5), 1149-1156. doi:10.1109/tbme.2016.2593003Erem, B., Brooks, D. H., van Dam, P. M., Stinstra, J. G., & MacLeod, R. S. (2011). Spatiotemporal estimation of activation times of fractionated ECGs on complex heart surfaces. 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. doi:10.1109/iembs.2011.6091455Erem, B., van Dam, P. M., & Brooks, D. H. (2014). Identifying Model Inaccuracies and Solution Uncertainties in Noninvasive Activation-Based Imaging of Cardiac Excitation Using Convex Relaxation. IEEE Transactions on Medical Imaging, 33(4), 902-912. doi:10.1109/tmi.2014.2297952Erkapic, D., & Neumann, T. (2015). Ablation of Premature Ventricular Complexes Exclusively Guided by Three-Dimensional Noninvasive Mapping. Cardiac Electrophysiology Clinics, 7(1), 109-115. doi:10.1016/j.ccep.2014.11.010Everett, T. H., Lai-Chow Kok, Vaughn, R. H., Moorman, R., & Haines, D. E. (2001). Frequency domain algorithm for quantifying atrial fibrillation organization to increase defibrillation efficacy. IEEE Transactions on Biomedical Engineering, 48(9), 969-978. doi:10.1109/10.942586Faes, L., & Ravelli, F. (2007). A morphology-based approach to the evaluation of atrial fibrillation organization. IEEE Engineering in Medicine and Biology Magazine, 26(4), 59-67. doi:10.1109/memb.2007.384097Fitzpatrick, A. P., Gonzales, R. P., Lesh, M. D., odin, G. W., Lee, R. J., & Scheinman, M. M. (1994). New algorithm for the localization of accessory atrioventricular connections using a baseline electrocardiogram. Journal of the American College of Cardiology, 23(1), 107-116. doi:10.1016/0735-1097(94)90508-8Geselowitz, D. B. (1989). On the theory of the electrocardiogram. Proceedings of the IEEE, 77(6), 857-876. doi:10.1109/5.29327Geselowitz, D. B. (1992). Description of cardiac sources in anisotropic cardiac muscle. Journal of Electrocardiology, 25, 65-67. doi:10.1016/0022-0736(92)90063-6Ghanem, R. N., Jia, P., Ramanathan, C., Ryu, K., Markowitz, A., & Rudy, Y. (2005). Noninvasive Electrocardiographic Imaging (ECGI): Comparison to intraoperative mapping in patients. Heart Rhythm, 2(4), 339-354. doi:10.1016/j.hrthm.2004.12.022Ghosh, S., Rhee, E. K., Avari, J. N., Woodard, P. K., & Rudy, Y. (2008). Cardiac Memory in Patients With Wolff-Parkinson-White Syndrome. Circulation, 118(9), 907-915. doi:10.1161/circulationaha.108.781658Ghosh, S., Silva, J. N. A., Canham, R. M., Bowman, T. M., Zhang, J., Rhee, E. K., … Rudy, Y. (2011). Electrophysiologic substrate and intraventricular left ventricular dyssynchrony in nonischemic heart failure patients undergoing cardiac resynchronization therapy. Heart Rhythm, 8(5), 692-699. doi:10.1016/j.hrthm.2011.01.017Grace, A., Verma, A., & Willems, S. (2017). Dipole Density Mapping of Atrial Fibrillation. European Heart Journal, 38(1), 5-9. doi:10.1093/eurheartj/ehw585Dorset, D. L. (1996). Electron crystallography. Acta Crystallographica Section B Structural Science, 52(5), 753-769. doi:10.1107/s0108768196005599Haissaguerre, M., Hocini, M., Denis, A., Shah, A. J., Komatsu, Y., Yamashita, S., … Dubois, R. (2014). Driver Domains in Persistent Atrial Fibrillation. Circulation, 130(7), 530-538. doi:10.1161/circulationaha.113.005421HAISSAGUERRE, M., HOCINI, M., SHAH, A. J., DERVAL, N., SACHER, F., JAIS, P., & DUBOIS, R. (2013). Noninvasive Panoramic Mapping of Human Atrial Fibrillation Mechanisms: A Feasibility Report. Journal of Cardiovascular Electrophysiology, 24(6), 711-717. doi:10.1111/jce.12075Han, C., Pogwizd, S. M., Killingsworth, C. R., & He, B. (2011). Noninvasive imaging of three-dimensional cardiac activation sequence during pacing and ventricular tachycardia. Heart Rhythm, 8(8), 1266-1272. doi:10.1016/j.hrthm.2011.03.014Bin He, Guanglin Li, & Xin Zhang. (2003). Noninvasive imaging of cardiac transmembrane potentials within three-dimensional myocardium by means of a realistic geometry anisotropic heart model. IEEE Transactions on Biomedical Engineering, 50(10), 1190-1202. doi:10.1109/tbme.2003.817637Bin He, & Dongsheng Wu. (2001). Imaging and visualization of 3-D cardiac electric activity. IEEE Transactions on Information Technology in Biomedicine, 5(3), 181-186. doi:10.1109/4233.945288Horáček, B. M., Sapp, J. L., Penney, C. J., Warren, J. W., & Wang, J. J. (2011). Comparison of epicardial potential maps derived from the 12-lead electrocardiograms with scintigraphic images during controlled myocardial ischemia. Journal of Electrocardiology, 44(6), 707-712. doi:10.1016/j.jelectrocard.2011.08.009Horáček, B. M., Wang, L., Dawoud, F., Xu, J., & Sapp, J. L. (2015). Noninvasive electrocardiographic imaging of chronic myocardial infarct scar. Journal of Electrocardiology, 48(6), 952-958. doi:10.1016/j.jelectrocard.2015.08.035Jamil-Copley, S., Vergara, P., Carbucicchio, C., Linton, N., Koa-Wing, M., Luther, V., … Kanagaratnam, P. (2015). Application of Ripple Mapping to Visualize Slow Conduction Channels Within the Infarct-Related Left Ventricular Scar. Circulation: Arrhythmia and Electrophysiology, 8(1), 76-86. doi:10.1161/circep.114.001827Janssen, A. M., Potyagaylo, D., Dössel, O., & Oostendorp, T. F. (2017). Assessment of the equivalent dipole layer source model in the reconstruction of cardiac activation times on the basis of BSPMs produced by an anisotropic model of the heart. Medical & Biological Engineering & Computing, 56(6), 1013-1025. doi:10.1007/s11517-017-1715-xKnecht, S., Sohal, M., Deisenhofer, I., Albenque, J.-P., Arentz, T., Neumann, T., … Rostock, T. (2017). Multicentre evaluation of non-invasive biatrial mapping for persistent atrial fibrillation ablation: the AFACART study. EP Europace, 19(8), 1302-1309. doi:10.1093/europace/euw168Kuck, K.-H., Schaumann, A., Eckardt, L., Willems, S., Ventura, R., Delacrétaz, E., … Hansen, P. S. (2010). Catheter ablation of stable ventricular tachycardia before defibrillator implantation in patients with coronary heart disease (VTACH): a multicentre randomised controlled trial. The Lancet, 375(9708), 31-40. doi:10.1016/s0140-6736(09)61755-4Identification of Rotors during Human Atrial Fibrillation Using Contact Mapping and Phase Singularity Detection: Technical Considerations. (2017). IEEE Transactions on Biomedical Engineering, 64(2), 310-318. doi:10.1109/tbme.2016.2554660Leong, K. M. W., Ng, F. S., Yao, C., Roney, C., Taraborrelli, P., Linton, N. W. F., … Varnava, A. M. (2017). ST-Elevation Magnitude Correlates With Right Ventricular Outflow Tract Conduction Delay in Type I Brugada ECG. Circulation: Arrhythmia and Electrophysiology, 10(10). doi:10.1161/circep.117.005107Chenguang Liu, Eggen, M. D., Swingen, C. M., Iaizzo, P. A., & Bin He. (2012). Noninvasive Mapping of Transmural Potentials During Activation in Swine Hearts From Body Surface Electrocardiograms. IEEE Transactions on Medical Imaging, 31(9), 1777-1785. doi:10.1109/tmi.2012.2202914MacLeod, R. S., Ni, Q., Punske, B., Ershler, P. R., Yilmaz, B., & Taccardi, B. (2000). Effects of heart position on the body-surface electrocardiogram. Journal of Electrocardiology, 33, 229-237. doi:10.1054/jelc.2000.20357Metzner, A., Wissner, E., Tsyganov, A., Kalinin, V., Schlüter, M., Lemes, C., … Kuck, K.-H. (2017). Noninvasive phase mapping of persistent atrial fibrillation in humans: Comparison with invasive catheter mapping. Annals of Noninvasive Electrocardiology, 23(4), e12527. doi:10.1111/anec.12527Modre, R., Tilg, B., Fischer, G., Hanser, F., Messnarz, B., Seger, M., … Roithinger, F. X. (2003). Atrial Noninvasive Activation Mapping of Paced Rhythm Data. Journal of Cardiovascular Electrophysiology, 14(7), 712-719. doi:10.1046/j.1540-8167.2003.02558.xNarayan, S. M., Krummen, D. E., Shivkumar, K., Clopton, P., Rappel, W.-J., & Miller, J. M. (2012). Treatment of Atrial Fibrillation by the Ablation of Localized Sources. Journal of the American College of Cardiology, 60(7), 628-636. doi:10.1016/j.jacc.2012.05.022NG, J., KADISH, A. H., & GOLDBERGER, J. J. (2007). Technical Considerations for Dominant Frequency Analysis. Journal of Cardiovascular Electrophysiology, 18(7), 757-764. doi:10.1111/j.1540-8167.2007.00810.xOosterhoff, P., Meijborg, V. M. F., van Dam, P. M., van Dessel, P. F. H. M., Belterman, C. N. W., Streekstra, G. J., … Oostendorp, T. F. (2016). Experimental Validation of Noninvasive Epicardial and Endocardial Activation Imaging. Circulation: Arrhythmia and Electrophysiology, 9(8). doi:10.1161/circep.116.004104Oster, H. S., Taccardi, B., Lux, R. L., Ershler, P. R., & Rudy, Y. (1997). Noninvasive Electrocardiographic Imaging. Circulation, 96(3), 1012-1024. doi:10.1161/01.cir.96.3.1012Oster, H. S., Taccardi, B., Lux, R. L., Ershler, P. R., & Rudy, Y. (1998). Electrocardiographic Imaging. Circulation, 97(15), 1496-1507. doi:10.1161/01.cir.97.15.1496PEDRÓN-TORRECILLA, J., RODRIGO, M., CLIMENT, A. M., LIBEROS, A., PÉREZ-DAVID, E., BERMEJO, J., … GUILLEM, M. S. (2016). Noninvasive Estimation of Epicardial Dominant High-Frequency Regions During Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 27(4), 435-442. doi:10.1111/jce.12931Ploux, S., Lumens, J., Whinnett, Z., Montaudon, M., Strom, M., Ramanathan, C., … Bordachar, P. (2013). Noninvasive Electrocardiographic Mapping to Improve Patient Selection for Cardiac Resynchronization Therapy. Journal of the American College of Cardiology, 61(24), 2435-2443. doi:10.1016/j.jacc.2013.01.093Potyagaylo, D., Segel, M., Schulze, W. H. W., & Dössel, O. (2013). Noninvasive Localization of Ectopic Foci: A New Optimization Approach for Simultaneous Reconstruction of Transmembrane Voltages and Epicardial Potentials. Lecture Notes in Computer Science, 166-173. doi:10.1007/978-3-642-38899-6_20Punshchykova, O., Švehlíková, J., Tyšler, M., Grünes, R., Sedova, K., Osmančík, P., … Kneppo, P. (2016). Influence of Torso Model Complexity on the Noninvasive Localization of Ectopic Ventricular Activity. Measurement Science Review, 16(2), 96-102. doi:10.1515/msr-2016-0013RAMANATHAN, C., & RUDY, Y. (2001). Electrocardiographic Imaging: II. Effect of Torso Inhomogeneities on Noninvasive Reconstruction of Epicardial Potentials, Electrograms, and Isochrones. Journal of Cardiovascular Electrophysiology, 12(2), 241-252. doi:10.1046/j.1540-8167.2001.00241.xReddy, V. Y., Reynolds, M. R., Neuzil, P., Richardson, A. W., Taborsky, M., Jongnarangsin, K., … Josephson, M. E. (2007). Prophylactic Catheter Ablation for the Prevention of Defibrillator Therapy. New England Journal of Medicine, 357(26), 2657-2665. doi:10.1056/nejmoa065457Rodrigo, M., Climent, A. M., Liberos, A., Fernández-Avilés, F., Berenfeld, O., Atienza, F., & Guillem, M. S. (2017). Technical Considerations on Phase Mapping for Identification of Atrial Reentrant Activity in Direct- and Inverse-Computed Electrograms. Circulation: Arrhythmia and Electrophysiology, 10(9). doi:10.1161/circep.117.005008ROTEN, L., PEDERSEN, M., PASCALE, P., SHAH, A., ELIAUTOU, S., SCHERR, D., … HAÏSSAGUERRE, M. (2012). Noninvasive Electrocardiographic Mapping for Prediction of Tachycardia Mechanism and Origin of Atrial Tachycardia Following Bilateral Pulmonary Transplantation. Journal of Cardiovascular Electrophysiology, 23(5), 553-555. doi:10.1111/j.1540-8167.2011.02250.xRudy, Y. (2013). Noninvasive Electrocardiographic Imaging of Arrhythmogenic Substrates in Humans. Circulation Research, 112(5), 863-874. doi:10.1161/circresaha.112.279315Ghosh, S., Avari, J. N., Rhee, E. K., Woodard, P. K., & Rudy, Y. (2008). Noninvasive electrocardiographic imaging (ECGI) of epicardial activation before and after catheter ablation of the accessory pathway in a patient with Ebstein anomaly. Heart Rhythm, 5(6), 857-860. doi:10.1016/j.hrthm.2008.03.011Rudy, Y., Plonsey, R., & Liebman, J. (1979). The effects of variations in conductivity and geometrical parameters on the electrocardiogram, using an eccentric spheres model. Circulation Research, 44(1), 104-111. doi:10.1161/01.res.44.1.104SALINET, J. L., TUAN, J. H., SANDILANDS, A. J., STAFFORD, P. J., SCHLINDWEIN, F. S., & NG, G. A. (2013). Distinctive Patterns of Dominant Frequency Trajectory Behavior in Drug-Refractory Persistent Atrial Fibrillation: Preliminary Characterization of Spatiotemporal Instability. Journal of Cardiovascular Electrophysiology, 25(4), 371-379. doi:10.1111/jce.12331Dalu, Y. (1978). Relating the multipole moments of the heart to activated parts of the epicardium and endocardium. Annals of Biomedical Engineering, 6(4), 492-505. doi:10.1007/bf02584552Sánchez, C., Bueno-Orovio, A., Pueyo, E., & Rodríguez, B. (2017). Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics. Frontiers in Bioengineering and Biotechnology, 5. doi:10.3389/fbioe.2017.00029Sanders, P., Berenfeld, O., Hocini, M., Jaïs, P., Vaidyanathan, R., Hsu, L.-F., … Haïssaguerre, M. (2005). Spectral Analysis Identifies Sites of High-Frequency Activity Maintaining Atrial Fibrillation in Humans. Circulation, 112(6), 789-797. doi:10.1161/circulationaha.104.517011Sapp, J. L., Bar-Tal, M., Howes, A. J., Toma, J. E., El-Damaty, A., Warren, J. W., … Horáček, B. M. (2017). Real-Time Localization of Ventricular Tachycardia Origin From the 12-Lead Electrocardiogram. JACC: Clinical Electrophysiology, 3(7), 687-699. doi:10.1016/j.jacep.2017.02.024Sapp, J. L., Dawoud, F., Clements, J. C., & Horáček, B. M. (2012). Inverse Solution Mapping of Epicardial Potentials. Circulation: Arrhythmia and Electrophysiology, 5(5), 1001-1009. doi:10.1161/circep.111.970160Sapp, J. L., Wells, G. A., Parkash, R., Stevenson, W. G., Blier, L., Sarrazin, J.-F., … Tang, A. S. L. (2016). Ventricular Tachycardia Ablation versus Escalation of Antiarrhythmic Drugs. New England Journal of Medicine, 375(2), 111-121. doi:10.1056/nejmoa1513614Schulze, W. H. W., Chen, Z., Relan, J., Potyagaylo, D., Krueger, M. W., Karim, R., … Dössel, O. (2016). ECG imaging of ventricular tachycardia: evaluation against simultaneous non-contact mapping and CMR-derived grey zone. Medical & Biological Engineering & Computing, 55(6), 979-990. doi:10.1007/s11517-016-1566-xShah, D. C., Jaïs, P., Haïssaguerre, M., Chouairi, S., Takahashi, A., Hocini, M., … Clémenty, J. (1997). Three-dimensional Mapping of the Common Atrial Flutter Circuit in the Right Atrium. Circulation, 96(11), 3904-3912. doi:10.1161/01.cir.96.11.3904Shome, S., & Macleod, R. (s. f.). Simultaneous High-Resolution Electrical Imaging of Endocardial, Epicardial and Torso-Tank Surfaces Under Varying Cardiac Metabolic Load and Coronary Flow. Lecture Notes in Computer Science, 320-329. doi:10.1007/978-3-540-72907-5_33SIMMS, H. D., & GESELOWITZ, D. B. (1995). Computation of Heart Surface Potentials Using the Surface Source Model. Journal of Cardiovascular Electrophysiology, 6(7), 522-531. doi:10.1111/j.1540-8167.1995.tb00425.xSvehlikova, J., Teplan, M., & Tysler, M. (2018). Geometrical constraint of sources in noninvasive localization of premature ventricular contractions. Journal of Electrocardiology, 51(3), 370-377. doi:10.1016/j.jelectrocard.2018.02.013Tsyganov, A., Wissner, E., Metzner, A., Mironovich, S., Chaykovskaya, M., Kalinin, V., … Kuck, K.-H. (2018). Mapping of ventricular arrhythmias using a novel noninvasive epicardial and endocardial electrophysiology system. Journal of Electrocardiology, 51(1), 92-98. doi:10.1016/j.jelectrocard.2017.07.018Umapathy, K., Nair, K., Masse, S., Krishnan, S., Rogers, J., Nash, M. P., & Nanthakumar, K. (2010). Phase Mapping of Cardiac Fibrillation. Circulation: Arrhythmia and Electrophysiology, 3(1), 105-114. doi:10.1161/circep.110.853804Van Dam, P. M., Oostendorp, T. F., Linnenbank, A. C., & van Oosterom, A. (2009). Non-Invasive Imaging of Cardiac Activation and Recovery. Annals of Biomedical Engineering, 37(9), 1739-1756. doi:10.1007/s10439-009-9747-5Van Oosterom, A. (2001). Genesis of the T wave as based on an equivalent surface source model. Journal of Electrocardiology, 34(4), 217-227. doi:10.1054/jelc.2001.28896Van Oosterom, A. (2002). Solidifying the solid angle. Journal of Electrocardiology, 35(4), 181-192. doi:10.1054/jelc.2002.37176Van Oosterom, A. (2004). ECGSIM: an interactive tool for stu

    Physiology-based regularization of the electrocardiographic inverse problem

    Get PDF
    The inverse problem of electrocardiography aims at noninvasively reconstructing electrical activity of the heart from recorded body-surface electrocardiograms. A crucial step is regularization, which deals with ill-posedness of the problem by imposing constraints on the possible solutions. We developed a regularization method that includes electrophysiological input. Body-surface potentials are recorded and a computed tomography scan is performed to obtain the torso-heart geometry. Propagating waveforms originating from several positions at the heart are simulated and used to generate a set of basis vectors representing spatial distributions of potentials on the heart surface. The real heart-surface potentials are then reconstructed from the recorded body-surface potentials by finding a sparse representation in terms of this basis. This method, which we named 'physiology-based regularization' (PBR), was compared to traditional Tikhonov regularization and validated using in vivo recordings in dogs. PBR recovered details of heart-surface electrograms that were lost with traditional regularization, attained higher correlation coefficients and led to improved estimation of recovery times. The best results were obtained by including approximate knowledge about the beat origin in the PBR basis

    A priori model independent inverse potential mapping: the impact of electrode positioning

    Get PDF
    __Introduction:__ In inverse potential mapping, local epicardial potentials are computed from recorded body surface potentials (BSP). When BSP are recorded with only a limited number of electrodes, in general biophysical a priori models are applied to facilitate the inverse computation. This study investigated the possibility of deriving epicardial potential information using only 62 torso electrodes in the absence of an a priori model. __Methods:__ Computer simulations were used to determine the optimal in vivo positioning of 62 torso electrodes. Subsequently, three different electrode configurations, i.e., surrounding the thorax, concentrated precordial (30 mm inter-electrode distance) and super-concentrated precordial (20 mm inter-electrode distance) were used to record BSP from three healthy volunteers. Magnetic resonance imaging (MRI) was performed to register the electrode positions with respect to the anatomy of the patient. Epicardial potentials were inversely computed from the recorded BSP. In order to determine the reconstruction quality, the super-concentrated electrode configuration was applied in four patients with an implanted MRI-conditional pacemaker system. The distance between the position of the ventricular lead tip on MRI and the inversely reconstructed pacing site was determined. __Results:__ The epicardial potential distribution reconstructed using the super-concentrated electrode configuration demonstrated the highest correlation (R = 0.98; p < 0.01) with the original epicardial source model. A mean localization error of 5.3 mm was found in the pacemaker patients. __Conclusion:__ This study demonstrated the feasibility of deriving detailed anterior epicardial potential information using only 62 torso electrodes without the use of an a priori model

    Personalized noninvasive imaging of volumetric cardiac electrophysiology

    Get PDF
    Three-dimensionally distributed electrical functioning is the trigger of mechanical contraction of the heart. Disturbance of this electrical flow is known to predispose to mechanical catastrophe but, due to its amenability to certain intervention techniques, a detailed understanding of subject-specific cardiac electrophysiological conditions is of great medical interest. In current clinical practice, body surface potential recording is the standard tool for diagnosing cardiac electrical dysfunctions. However, successful treatments normally require invasive catheter mapping for a more detailed observation of these dysfunctions. In this dissertation, we take a system approach to pursue personalized noninvasive imaging of volumetric cardiac electrophysiology. Under the guidance of existing scientific knowledge of the cardiac electrophysiological system, we extract the subject specific cardiac electrical information from noninvasive body surface potential mapping and tomographic imaging data of individual subjects. In this way, a priori knowledge of system physiology leads the physiologically meaningful interpretation of personal data; at the same time, subject-specific information contained in the data identifies parameters in individual systems that differ from prior knowledge. Based on this perspective, we develop a physiological model-constrained statistical framework for the quantitative reconstruction of the electrical dynamics and inherent electrophysiological property of each individual cardiac system. To accomplish this, we first develop a coupled meshfree-BE (boundary element) modeling approach to represent existing physiological knowledge of the cardiac electrophysiological system on personalized heart-torso structures. Through a state space system approach and sequential data assimilation techniques, we then develop statistical model-data coupling algorithms for quantitative reconstruction of volumetric transmembrane potential dynamics and tissue property of 3D myocardium from body surface potential recoding of individual subjects. We also introduce a data integration component to build personalized cardiac electrophysiology by fusing tomographic image and BSP sequence of the same subject. In addition, we develop a computational reduction strategy that improves the efficiency and stability of the framework. Phantom experiments and real-data human studies are performed for validating each of the framework’s major components. These experiments demonstrate the potential of our framework in providing quantitative understanding of volumetric cardiac electrophysiology for individual subjects and in identifying latent threats in individual’s heart. This may aid in personalized diagnose, treatment planning, and fundamentally, prevention of fatal cardiac arrhythmia

    Current Status and Future of Cardiac Mapping in Atrial Fibrillation

    Get PDF

    Non-invasive identification of atrial fibrillation drivers

    Full text link
    Atrial fibrillation (AF) is one of the most common cardiac arrhythmias. Nowadays the fibrillatory process is known to be provoked by the high-frequency reentrant activity of certain atrial regions that propagates the fibrillatory activity to the rest of the atrial tissue, and the electrical isolation of these key regions has demonstrated its effectiveness in terminating the fibrillatory process. The location of the dominant regions represents a major challenge in the diagnosis and treatment of this arrhythmia. With the aim to detect and locate the fibrillatory sources prior to surgical procedure, non-invasive methods have been developed such as body surface electrical mapping (BSPM) which allows to record with high spatial resolution the electrical activity on the torso surface or the electrocardiographic imaging (ECGI) which allows to non-invasively reconstruct the electrical activity in the atrial surface. Given the novelty of these systems, both technologies suffer from a lack of scientific knowledge about the physical and technical mechanisms that support their operation. Therefore, the aim of this thesis is to increase that knowledge, as well as studying the effectiveness of these technologies for the localization of dominant regions in patients with AF. First, it has been shown that BSPM systems are able to noninvasively identify atrial rotors by recognizing surface rotors after band-pass filtering. Furthermore, the position of such surface rotors is related to the atrial rotor location, allowing the distinction between left or right atrial rotors. Moreover, it has been found that the surface electrical maps in AF suffer a spatial smoothing effect by the torso conductor volume, so the surface electrical activity can be studied with a relatively small number of electrodes. Specifically, it has been seen that 12 uniformly distributed electrodes are sufficient for the correct identification of atrial dominant frequencies, while at least 32 leads are needed for non-invasive identification of atrial rotors. Secondly, the effect of narrowband filtering on the effectiveness of the location of reentrant patterns was studied. It has been found that this procedure allows isolating the reentrant electrical activity caused by the rotor, increasing the detection rate for both invasive and surface maps. However, the spatial smoothing caused by the regularization of the ECGI added to the temporal filtering causes a large increase in the spurious reentrant activity, making it difficult to detect real reentrant patterns. However, it has been found that maps provided by the ECGI without temporal filtering allow the correct detection of reentrant activity, so narrowband filtering should be applied for intracavitary or surface signal only. Finally, we studied the stability of the markers used to detect dominant regions in ECGI, such as frequency maps or the rotor presence. It has been found that in the presence of alterations in the conditions of the inverse problem, such as electrical or geometrical noise, these markers are significantly more stable than the ECGI signal morphology from which they are extracted. In addition, a new methodology for error reduction in the atrial spatial location based on the curvature of the curve L has been proposed. The results presented in this thesis showed that BSPM and ECGI systems allows to non-invasively locate the presence of high-frequency rotors, responsible for the maintenance of AF. This detection has been proven to be unambiguous and robust, and the physical and technical mechanisms that support this behavior have been studied. These results indicate that both non-invasive systems provide information of great clinical value in the treatment of AF, so their use can be helpful for selecting and planning atrial ablation procedures.La fibrilación auricular (FA) es una de las arritmias cardiacas más frecuentes. Hoy en día se sabe que el proceso fibrilatorio está provocado por la actividad reentrante a alta frecuencia de ciertas regiones auriculares que propagan la actividad fibrilatoria en el resto del tejido auricular, y se ha demostrado que el aislamiento eléctrico de estas regiones dominantes permite detener el proceso fibrilatorio. La localización de las regiones dominantes supone un gran reto en el diagnóstico y tratamiento de la FA. Con el objetivo de poder localizar las fuentes fibrilatorias con anterioridad al procedimiento quirúrgico, se han desarrollado métodos no invasivos como la cartografía eléctrica de superficie (CES) que registra con gran resolución espacial la actividad eléctrica en la superficie del torso o la electrocardiografía por imagen (ECGI) que permite reconstruir la actividad eléctrica en la superficie auricular. Dada la novedad de estos sistemas, existe una falta de conocimiento científico sobre los mecanismos físicos y técnicos que sustentan su funcionamiento. Por lo tanto, el objetivo de esta tesis es aumentar dicho conocimiento, así como estudiar la eficacia de ambas tecnologías para la localización de regiones dominantes en pacientes con FA. En primer lugar, ha visto que los sistemas CES permiten identificar rotores auriculares mediante el reconocimiento de rotores superficiales tras el filtrado en banda estrecha. Además, la posición de los rotores superficiales está relacionada con la localización de dichos rotores, permitiendo la distinción entre rotores de aurícula derecha o izquierda. Por otra parte, se ha visto que los mapas eléctricos superficiales durante FA sufren una gran suavizado espacial por el efecto del volumen conductor del torso, lo que permite que la actividad eléctrica superficial pueda ser estudiada con un número relativamente reducido de electrodos. Concretamente, se ha visto que 12 electrodos uniformemente distribuidos son suficientes para una correcta identificación de frecuencias dominantes, mientras que son necesarios al menos 32 para una correcta identificación de rotores auriculares. Por otra parte, también se ha estudiado el efecto del filtrado en banda estrecha sobre la eficacia de la localización de patrones reentrantes. Así, se ha visto que este procedimiento permite aislar la actividad eléctrica reentrante provocada por el rotor, aumentando la tasa de detección tanto para señal obtenida de manera invasiva como para los mapas superficiales. No obstante, este filtrado temporal sobre la señal de ECGI provoca un gran aumento de la actividad reentrante espúrea que dificulta la detección de patrones reentrantes reales. Sin embargo, los mapas ECGI sin filtrado temporal permiten la detección correcta de la actividad reentrante, por lo el filtrado debería ser aplicado únicamente para señal intracavitaria o superficial. Por último, se ha estudiado la estabilidad de los marcadores utilizados en ECGI para detectar regiones dominantes, como son los mapas de frecuencia o la presencia de rotores. Se ha visto que en presencia de alteraciones en las condiciones del problema inverso, como ruido eléctrico o geométrico, estos marcadores son significativamente más estables que la morfología de la propia señal ECGI. Además, se ha propuesto una nueva metodología para la reducción del error en la localización espacial de la aurícula basado en la curvatura de la curva L. Los resultados presentados en esta tesis revelan que los sistemas de CES y ECGI permiten localizar de manera no invasiva la presencia de rotores de alta frecuencia. Esta detección es univoca y robusta, y se han estudiado los mecanismos físicos y técnicos que sustentan dicho comportamiento. Estos resultados indican que ambos sistemas no invasivos proporcionan información de gran valor clínico en el tratamiento de la FA, por lo que su uso puede ser de gran ayuda para la selección y planificaciLa fibril·lació auricular (FA) és una de les arítmies cardíaques més freqüents. Hui en dia es sabut que el procés fibrilatori està provocat per l'activitat reentrant de certes regions auriculars que propaguen l'activitat fibril·latoria a la resta del teixit auricular, i s'ha demostrat que l'aïllament elèctric d'aquestes regions dominants permet aturar el procés fibrilatori. La localització de les regions dominants suposa un gran repte en el diagnòstic i tractament d'aquesta arítmia. Amb l'objectiu de poder localitzar fonts fibril·latories amb anterioritat al procediment quirúrgic s'han desenvolupat mètodes no invasius com la cartografia elèctrica de superfície (CES) que registra amb gran resolució espacial l'activitat elèctrica en la superfície del tors o l'electrocardiografia per imatge (ECGI) que permet obtenir de manera no invasiva l'activitat elèctrica en la superfície auricular. Donada la relativa novetat d'aquests sistemes, existeix una manca de coneixement científic sobre els mecanismes físics i tècnics que sustenten el seu funcionament. Per tant, l'objectiu d'aquesta tesi és augmentar aquest coneixement, així com estudiar l'eficàcia d'aquestes tecnologies per a la localització de regions dominants en pacients amb FA. En primer lloc, s'ha vist que els sistemes CES permeten identificar rotors auriculars mitjançant el reconeixement de rotors superficials després del filtrat en banda estreta. A més, la posició dels rotors superficials està relacionada amb la localització d'aquests rotors, permetent la distinció entre rotors de aurícula dreta o esquerra. També s'ha vist que els mapes elèctrics superficials durant FA pateixen un gran suavitzat espacial per l'efecte del volum conductor del tors, el que permet que l'activitat elèctrica superficial pugui ser estudiada amb un nombre relativament reduït d'elèctrodes. Concretament, s'ha vist que 12 elèctrodes uniformement distribuïts són suficients per a una correcta identificació de freqüències dominants auriculars, mentre que són necessaris almenys 32 per a una correcta identificació de rotors auriculars. D'altra banda, també s'ha estudiat l'efecte del filtrat en banda estreta sobre l'eficàcia de la localització de patrons reentrants. Així, s'ha vist que aquest procediment permet aïllar l'activitat elèctrica reentrant provocada pel rotor, augmentant la taxa de detecció tant pel senyal obtingut de manera invasiva com per als mapes superficials. No obstant això, aquest filtrat temporal sobre el senyal de ECGI provoca un gran augment de l'activitat reentrant espúria que dificulta la detecció de patrons reentrants reals. A més, els mapes proporcionats per la ECGI sense filtrat temporal permeten la detecció correcta de l'activitat reentrant, per la qual cosa el filtrat hauria de ser aplicat únicament per a senyal intracavitària o superficial. Per últim, s'ha estudiat l'estabilitat dels marcadors utilitzats en ECGI per a detectar regions auriculars dominants, com són els mapes de freqüència o la presència de rotors. S'ha vist que en presència d'alteracions en les condicions del problema invers, com soroll elèctric o geomètric, aquests marcadors són significativament més estables que la morfologia del mateix senyal ECGI. A més, s'ha proposat una nova metodologia per a la reducció de l'error en la localització espacial de l'aurícula basat en la curvatura de la corba L. Els resultats presentats en aquesta tesi revelen que els sistemes de CES i ECGI permeten localitzar de manera no invasiva la presència de rotors d'alta freqüència. Aquesta detecció és unívoca i robusta, i s'han estudiat els mecanismes físics i tècnics que sustenten aquest comportament. Aquests resultats indiquen que els dos sistemes no invasius proporcionen informació de gran valor clínic en el tractament de la FA, pel que el seu ús pot ser de gran ajuda per a la selecció i planificació de procediments d'ablació auricular.Rodrigo Bort, M. (2016). Non-invasive identification of atrial fibrillation drivers [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/75346TESISPremios Extraordinarios de tesis doctorale

    Bayesian Inference with Combined Dynamic and Sparsity Models: Application in 3D Electrophysiological Imaging

    Get PDF
    Data-driven inference is widely encountered in various scientific domains to convert the observed measurements into information that cannot be directly observed about a system. Despite the quickly-developing sensor and imaging technologies, in many domains, data collection remains an expensive endeavor due to financial and physical constraints. To overcome the limits in data and to reduce the demand on expensive data collection, it is important to incorporate prior information in order to place the data-driven inference in a domain-relevant context and to improve its accuracy. Two sources of assumptions have been used successfully in many inverse problem applications. One is the temporal dynamics of the system (dynamic structure). The other is the low-dimensional structure of a system (sparsity structure). In existing work, these two structures have often been explored separately, while in most high-dimensional dynamic system they are commonly co-existing and contain complementary information. In this work, our main focus is to build a robustness inference framework to combine dynamic and sparsity constraints. The driving application in this work is a biomedical inverse problem of electrophysiological (EP) imaging, which noninvasively and quantitatively reconstruct transmural action potentials from body-surface voltage data with the goal to improve cardiac disease prevention, diagnosis, and treatment. The general framework can be extended to a variety of applications that deal with the inference of high-dimensional dynamic systems

    A novel simplified approach to radiofrequency catheter ablation of idiopathic ventricular outflow tract premature ventricular contractions : from substrate analysis to results

    Get PDF
    Summary: Premature ventricular contractions (PVCs) are a common finding in the general population. The most common site of PVCs, in patients without structural heart disease, is the right ventricular outflow tract (RVOT) and the left ventricular outflow tract (LVOT). The prognosis associated with frequent PVCs depends on the presence of structural heart disease, so that idiopathic PVCs have been considered benign. Recently however, evidence has emerged that a small percentage of those patients may present with polymorphic ventricular tachycardia or ventricular fibrillation or evolve to left ventricular dysfunction. Catheter ablation is indicated for frequent symptomatic PVCs refractory to medical therapy or in case of patient’s preference. Currently, catheter ablation is based on activation mapping, confirmed by pace mapping match of at least 11/12 ECG leads between the paced beat and the PVC morphology. The acute success rate ranges from 78% to 100% according to the series, and to the location of the PVCs. Remote magnetic navigation presents as a good option for PVC ablation offering a high success rate with better safety profile. Intraprocedural low PVC burden occurs in up to 30% to 48% of cases, resulting in either, cancelation of the ablation procedure in up to 11% of patients, or reduction of the success rate from 85% to 56% when ablation is attempted with pace mapping only. Recently non-invasive mapping systems based on the electrocardiogram analysis (ECGI) have been developed. These systems are capable of mapping an arrhythmia with just one beat, instead of the usual point by point acquisition, being especially useful in the case of rare arrhythmias. EGGI also constitutes a valuable noninvasive tool for studying the mechanisms of arrhythmias. With this system we were able to demonstrate the presence of an electrophysiological substrate in the RVOT of patients with PVCs and apparently normal hearts. It has been accepted for many years that in patients with idiopathic PVCs from the outflow tracts, the RVOT displays normal electroanatomical mapping features and electrophysiological properties. However, we have demonstrated that there is a substrate for idiopathic PVCs in the form of low voltage areas (LVAs) that are not detected by usual image methods including cardiac magnetic resonance (CMR). We described for the first time, the association between the presence of ST-segment elevation in V1-V2 at the 2nd intercostal space (ICS) with LVAs across the RVOT and have proposed it as a non-invasive electrocardiographic marker of LVAs. We also identified the presence of abnormal potentials in intracardiac electrograms at the ablation site during diastole, after the T wave of the surface ECG that became presystolic during the PVC and were called diastolic potentials (DPs). In Chapter V we describe in detail the study that validated those findings and evaluated the feasibility and efficacy of a proposed simplified substrate approach, for catheter ablation in patients with low intraprocedural PVC burden, defined as less than 2 PVCs/min in the first 5 minutes of the procedure. It consists of fast mapping of the RVOT in sinus rhythm looking for LVAs and DPs, identifying the area, and finally performing a restricted activation map of the PVCs at that area. Briefly, it was a prospective single-arm clinical trial at two centers and three groups were studied: a) patients with low intraprocedural PVC burden that underwent ablation with the novel simplified approach method (study group); b) patients with low intraprocedural PVC burden that underwent ablation using the standard activation mapping method between 2016 and 2018 (historical group); and c) patients without PVCs, subjected to catheter ablation of supraventricular tachycardias that agreed to have a voltage map of the RVOT in sinus rhythm performed (validation group). The calculated sample size was 38 patients in each group. The exclusion criteria were as follows: known structural heart disease, history of sustained ventricular arrhythmias, inability to perform CMR, previous ablation and standard 12-Lead ECG with evidence of conduction or electrical disease or abnormal QRS morphology were excluded. Patients in the study and validation groups, had an ECG performed at the 2nd ICS and the RVOT mapped in sinus rhythm to assess the presence of ST-segment elevation, and LVAS and DPs, respectively. The results were compared between both groups. The study group and the historical group were compared regarding the efficacy of the new simplified ablation method in terms of abolishment of the PVCs and improvement of procedure speed and success rate. When available, ECGI was performed in the study group to evaluate the accuracy of the method to identify the site of origin of the PVCs. The ECGI was performed with two systems, the Amycard (EP Solutions SA, Switzerland) and the VIVO (Catheter Precision, NJ USA). The prevalence of LVAs and DPs was significantly higher in the study group in comparison with the validation group, respectively, 71% vs 11%, p<0.0001 and 87% vs 8%, p<0.0001. The ST-segment elevation was a good predictor of LVAS with a sensitivity of 87%, specificity of 96%, positive predictor value of 93% and negative predictor value of 91%. The novel simplified approach abolished the PVCs in 90% of the patients as opposed to 47% of patients in the historical group, p<0.0001. Only 74% patients underwent ablation in the historical group versus 100% in the study group. In patients that underwent ablation, the procedure time was significantly lower in the study group when comparing to the historical group, 130 (100-164) vs 183 (160-203) min, p<0.0001 and the success rate was significantly higher, 90% vs 64%, p=0.013. The recurrence rate in patients with a successful ablation after a median follow-up time of 1060 (574-1807) days, was not significantly different between both groups, Log-Rank=0.125 ECGI before ablation was performed in 17 patients in the study group. In 6 patients the ECGI was performed just with the Amycard system, in two just with the VIVO system and in 9 patients both systems were used. We found a good agreement between the ECGI and the invasive mapping, with the predicted site of origin being in the same or contiguous segment of the ablation site in 14/15 patients (93%) with the Amycard system and in 100% of patients with the VIVO system. When both systems were used simultaneously, the agreement between them was 8/9 (90%). So, in conclusion, the proposed approach partially based on substrate mapping including searching for LVAs and DPs, proved to be feasible, faster, and more efficient than the previous approach based exclusively on activation mapping. ST-segment elevation at the 2nd ICS proved to be a good predictor of LVAs. ECGI was a valuable tool to noninvasively predict the site of origin the arrhythmia
    corecore