BACKGROUND: Accurate determination of regional areas of arrhythmic triggers is of key interest to diagnose arrhythmias and optimize their treatment. Electromechanical wave imaging (EWI) is an ultrasound technique that can image the transient deformation in the myocardium after electrical activation and therefore has the potential to detect and characterize location of triggers of arrhythmias. OBJECTIVES: The objectives of this study were to investigate the relationship between the electromechanical and the electrical activation of the left ventricular (LV) endocardial surface during epicardial and endocardial pacing and during sinus rhythm as well as to map the distribution of electromechanical delays. METHODS: In this study, 6 canines were investigated. Two external electrodes were sutured onto the epicardial surface of the LV. A 64-electrode basket catheter was inserted through the apex of the LV. Ultrasound channel data were acquired at 2000 frames/s during epicardial and endocardial pacing and during sinus rhythm. Electromechanical and electrical activation maps were synchronously obtained from the ultrasound data and the basket catheter, respectively. RESULTS: The mean correlation coefficient between electromechanical and electrical activation was 0.81 for epicardial anterior pacing, 0.79 for epicardial lateral pacing, 0.69 for endocardial pacing, and 0.56 for sinus rhythm. CONCLUSION: The electromechanical activation sequence determined by EWI follows the electrical activation sequence and more specifically in the case of pacing. This finding is of key interest in the role that EWI can play in the detection of the anatomical source of arrhythmias and the planning of pacing therapies such as cardiovascular resynchronization therapy.
BACKGROUND: Accurate determination of regional areas of arrhythmic triggers is of key interest to diagnose arrhythmias and optimize their treatment. Electromechanical wave imaging (EWI) is an ultrasound technique that can image the transient deformation in the myocardium after electrical activation and therefore has the potential to detect and characterize location of triggers of arrhythmias. OBJECTIVES: The objectives of this study were to investigate the relationship between the electromechanical and the electrical activation of the left ventricular (LV) endocardial surface during epicardial and endocardial pacing and during sinus rhythm as well as to map the distribution of electromechanical delays. METHODS: In this study, 6 canines were investigated. Two external electrodes were sutured onto the epicardial surface of the LV. A 64-electrode basket catheter was inserted through the apex of the LV. Ultrasound channel data were acquired at 2000 frames/s during epicardial and endocardial pacing and during sinus rhythm. Electromechanical and electrical activation maps were synchronously obtained from the ultrasound data and the basket catheter, respectively. RESULTS: The mean correlation coefficient between electromechanical and electrical activation was 0.81 for epicardial anterior pacing, 0.79 for epicardial lateral pacing, 0.69 for endocardial pacing, and 0.56 for sinus rhythm. CONCLUSION: The electromechanical activation sequence determined by EWI follows the electrical activation sequence and more specifically in the case of pacing. This finding is of key interest in the role that EWI can play in the detection of the anatomical source of arrhythmias and the planning of pacing therapies such as cardiovascular resynchronization therapy.
Authors: Jonathan M Cordeiro; Lindsey Greene; Cory Heilmann; Daniel Antzelevitch; Charles Antzelevitch Journal: Am J Physiol Heart Circ Physiol Date: 2003-12-11 Impact factor: 4.733
Authors: Partho P Sengupta; Vijay K Krishnamoorthy; Josef Korinek; Jagat Narula; Mani A Vannan; Steven J Lester; Jamil A Tajik; James B Seward; Bijoy K Khandheria; Marek Belohlavek Journal: J Am Soc Echocardiogr Date: 2007-05 Impact factor: 5.251
Authors: Partho P Sengupta; Bijoy K Khandheria; Josef Korinek; Jianwen Wang; Arshad Jahangir; James B Seward; Marek Belohlavek Journal: J Am Coll Cardiol Date: 2005-12-01 Impact factor: 24.094
Authors: Jean Provost; Vu Thanh-Hieu Nguyen; Diégo Legrand; Stan Okrasinski; Alexandre Costet; Alok Gambhir; Hasan Garan; Elisa E Konofagou Journal: Phys Med Biol Date: 2011-10-25 Impact factor: 3.609
Authors: Jens-Uwe Voigt; Thomas-Michael Schneider; Stephan Korder; Mariola Szulik; Emre Gürel; Werner G Daniel; Frank Rademakers; Frank A Flachskampf Journal: Eur Heart J Date: 2009-03-18 Impact factor: 29.983
Authors: Jean Provost; Alexandre Costet; Elaine Wan; Alok Gambhir; William Whang; Hasan Garan; Elisa E Konofagou Journal: Comput Biol Med Date: 2015-08-24 Impact factor: 4.589
Authors: Lea Melki; Christopher S Grubb; Rachel Weber; Pierre Nauleau; Hasan Garan; Elaine Wan; Eric S Silver; Leonardo Liberman; Elisa E Konofagou Journal: JACC Clin Electrophysiol Date: 2019-01-30
Authors: Christopher S Grubb; Lea Melki; Daniel Y Wang; James Peacock; Jose Dizon; Vivek Iyer; Carmine Sorbera; Angelo Biviano; David A Rubin; John P Morrow; Deepak Saluja; Andrew Tieu; Pierre Nauleau; Rachel Weber; Salma Chaudhary; Irfan Khurram; Marc Waase; Hasan Garan; Elisa E Konofagou; Elaine Y Wan Journal: Sci Transl Med Date: 2020-03-25 Impact factor: 17.956
Authors: Lea Melki; Daniel Y Wang; Christopher S Grubb; Rachel Weber; Angelo Biviano; Elaine Y Wan; Hasan Garan; Elisa E Konofagou Journal: J Am Soc Echocardiogr Date: 2021-03-04 Impact factor: 7.722