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Robert J, Bessiere F, Cao E, Loyer V, Abell E, Vaillant F, Quesson B, Catheline S, Lafon C. Spectral Analysis of Tissue Displacement for Cardiac Activation Mapping: Ex Vivo Working Heart and In Vivo Study. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2022; 69:942-956. [PMID: 34941506 DOI: 10.1109/tuffc.2021.3137989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Characterizing myocardial activation is of major interest for understanding the underlying mechanism of cardiac arrhythmias. Electromechanical wave imaging (EWI) is an ultrafast ultrasound-based method used to map the propagation of the local contraction triggered by electrical activation of the heart. This study introduces a novel way to characterize cardiac activation based on the time evolution of the instantaneous frequency content of the cardiac tissue displacement curves. The first validation of this method was performed on an ex vivo dataset of 36 acquisitions acquired from two working heart models in paced rhythms. It was shown that the activation mapping described by spectral analysis of interframe displacement is similar to the standard EWI method based on zero-crossing of interframe strain. An average median error of 3.3 ms was found in the ex vivo dataset between the activation maps obtained with the two methods. The feasibility of mapping cardiac activation by EWI was then investigated on two open-chest pigs during sinus and paced rhythms in a pilot trial of cardiac mapping with an intracardiac probe. Seventy-five acquisitions were performed with reasonable stability and analyzed with the novel algorithm to map cardiac contraction propagation in the left ventricle (LV). Sixty-one qualitatively continuous isochrones were successfully computed based on this method. The region of contraction onset was coherently described while pacing in the imaging plane. These findings highlight the potential of implementing EWI acquisition on intracardiac probes and emphasize the benefit of performing short time-frequency analysis of displacement data to characterize cardiac activation in vivo.
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Melki L, Tourni M, Konofagou EE. Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2258-2271. [PMID: 33881993 PMCID: PMC8410624 DOI: 10.1109/tmi.2021.3074808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Standard Electromechanical Wave Imaging isochrone generation relies on manual selection of zero-crossing (ZC) locations on incremental strain curves for a number of pixels in the segmented myocardium for each echocardiographic view and patient. When considering large populations, this becomes a time-consuming process, that can be limited by inter-observer variability and operator bias. In this study, we developed and optimized an automated ZC selection algorithm, towards a faster more robust isochrone generation approach. The algorithm either relies on heuristic-based baselines or machine learning classifiers. Manually generated isochrones, previously validated against 3D intracardiac mapping, were considered as ground truth during training and performance evaluation steps. The machine learning models applied herein for the first time were: i) logistic regression; ii) support vector machine (SVM); and iii) Random Forest. The SVM and Random Forest classifiers successfully identified accessory pathways in Wolff-Parkinson-White patients, characterized sinus rhythm in humans, and localized the pacing electrode location in left ventricular paced canines on the resulting isochrones. Nevertheless, the best performing classifier was proven to be Random Forest with a precision rising from 89.5% to 97%, obtained with the voting approach that sets a probability threshold upon ZC candidate selection. Furthermore, the predictivity was not dependent on the type of testing dataset it was applied to, contrary to SVM that exhibited a 5% drop in precision on the canine testing dataset. Finally, these findings indicate that a machine learning approach can reduce user variability and considerably decrease the durations required for isochrone generation, while preserving accurate activation patterns.
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Melki L, Wang DY, Grubb CS, Weber R, Biviano A, Wan EY, Garan H, Konofagou EE. Cardiac Resynchronization Therapy Response Assessment with Electromechanical Activation Mapping within 24 Hours of Device Implantation: A Pilot Study. J Am Soc Echocardiogr 2021; 34:757-766.e8. [PMID: 33675941 DOI: 10.1016/j.echo.2021.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 02/14/2021] [Accepted: 02/14/2021] [Indexed: 10/22/2022]
Abstract
BACKGROUND Cardiac resynchronization therapy (CRT) response assessment relies on the QRS complex narrowing criterion. Yet one third of patients do not improve despite narrowed QRS after implantation. Electromechanical wave imaging (EWI) is a quantitative echocardiography-based technique capable of noninvasively mapping cardiac electromechanical activation in three dimensions. The aim of this exploratory study was to investigate the EWI technique, sensitive to ventricular dyssynchrony, for informing CRT response on the day of implantation. METHODS Forty-four patients with heart failure with left bundle branch block or right ventricular (RV) paced rhythm and decreased left ventricular ejection fraction (LVEF; mean, 25.3 ± 9.6%) underwent EWI without and with CRT within 24 hours of device implantation. Of those, 16 were also scanned while in left ventricular (LV) pacing. Improvement in LVEF at 3-, 6-, or 9-month follow-up defined (1) super-responders (ΔLVEF ≥ 20%), (2) responders (10% ≤ ΔLVEF < 20%), and (3) nonresponders (ΔLVEF ≤ 5%). Three-dimensionally rendered electromechanical maps were obtained under RV, LV, and biventricular CRT pacing conditions. Mean RV free wall and LV lateral wall activation times were computed. The percentage of resynchronized myocardium was measured by quantifying the percentage of the left ventricle activated within 120 msec of QRS onset. Correlations between percentage of resynchronized myocardium and type of CRT response were assessed. RESULTS LV lateral wall activation time was significantly different (P ≤ .05) among all three pacing conditions in the 16 patients: LV lateral wall activation time with CRT in biventricular pacing (73.1 ± 17.6 msec) was lower compared with LV pacing (89.5 ± 21.5 msec) and RV pacing (120.3 ± 17.8 msec). Retrospective analysis showed that the percentage of resynchronized myocardium with CRT was a reliable response predictor within 24 hours of implantation for significantly (P ≤ .05) identifying super-responders (n = 7; 97.7 ± 1.9%) from nonresponders (n = 17; 89.9 ± 9.9%). CONCLUSION Electromechanical activation mapping constitutes a valuable three-dimensional visualization tool within 24 hours of implantation and could potentially aid in the timely assessment of CRT response rates, including during implantation for adjustment of lead placement and pacing outcomes.
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Affiliation(s)
- Lea Melki
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York
| | - Daniel Y Wang
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Christopher S Grubb
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Rachel Weber
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York
| | - Angelo Biviano
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Elaine Y Wan
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Hasan Garan
- Division of Cardiology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
| | - Elisa E Konofagou
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York; Department of Radiology, Columbia University Irving Medical Center, New York, New York.
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Andersen MS, Moore C, LeFevre M, Arges K, Friedman DJ, Atwater BD, Kisslo J, Søgaard P, Struijk JJ, von Ramm OT, Schmidt SE. Contractile Fronts In The Interventricular Septum: A Case For High Frame Rate Echocardiographic Imaging. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:2181-2192. [PMID: 32561068 DOI: 10.1016/j.ultrasmedbio.2020.04.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Revised: 04/22/2020] [Accepted: 04/24/2020] [Indexed: 06/11/2023]
Abstract
The real time high frame rate (HFR) 2-dimensional ultrasound system, T5, at Duke University is capable of imaging at up to 1000 images per second for adult cardiac imaging. A method for detecting and visualizing the mechanical contraction fronts using HFR echocardioagraphy-derived Strain Rate Image (SRI) was described in 26 patients. The Tissue Shortening Onset front durations for echocardiographic normal patients were significantly shorter than conduction disorder patients with left bundle branch block (LBBB) with intrinsic conduction and conduction disorder patients without LBBB (non-LBBB) with simulated LBBB (sLBBB). Echocardiographic normal patients had significantly higher correlation coefficients between their SRIs and spatially inverted versions of themselves compared to non-LBBB patients with intrinsic conduction and sLBBB. In conclusion, SRIs could spatially resolve contractile event fronts in patients.
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Affiliation(s)
| | | | | | | | | | | | - Joseph Kisslo
- Duke University Medical Center, Durham, NC 27710, USA
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Grubb CS, Melki L, Wang DY, Peacock J, Dizon J, Iyer V, Sorbera C, Biviano A, Rubin DA, Morrow JP, Saluja D, Tieu A, Nauleau P, Weber R, Chaudhary S, Khurram I, Waase M, Garan H, Konofagou EE, Wan EY. Noninvasive localization of cardiac arrhythmias using electromechanical wave imaging. Sci Transl Med 2020; 12:eaax6111. [PMID: 32213631 PMCID: PMC7234276 DOI: 10.1126/scitranslmed.aax6111] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 02/21/2020] [Indexed: 12/13/2022]
Abstract
Cardiac arrhythmias are a major cause of morbidity and mortality worldwide. The 12-lead electrocardiogram (ECG) is the current noninvasive clinical tool used to diagnose and localize cardiac arrhythmias. However, it has limited accuracy and is subject to operator bias. Here, we present electromechanical wave imaging (EWI), a high-frame rate ultrasound technique that can noninvasively map with high accuracy the electromechanical activation of atrial and ventricular arrhythmias in adult patients. This study evaluates the accuracy of EWI for localization of various arrhythmias in all four chambers of the heart before catheter ablation. Fifty-five patients with an accessory pathway (AP) with Wolff-Parkinson-White (WPW) syndrome, premature ventricular complexes (PVCs), atrial tachycardia (AT), or atrial flutter (AFL) underwent transthoracic EWI and 12-lead ECG. Three-dimensional (3D) rendered EWI isochrones and 12-lead ECG predictions by six electrophysiologists were applied to a standardized segmented cardiac model and subsequently compared to the region of successful ablation on 3D electroanatomical maps generated by invasive catheter mapping. There was significant interobserver variability among 12-lead ECG reads by expert electrophysiologists. EWI correctly predicted 96% of arrhythmia locations as compared with 71% for 12-lead ECG analyses [unadjusted for arrhythmia type: odds ratio (OR), 11.8; 95% confidence interval (CI), 2.2 to 63.2; P = 0.004; adjusted for arrhythmia type: OR, 12.1; 95% CI, 2.3 to 63.2; P = 0.003]. This double-blinded clinical study demonstrates that EWI can localize atrial and ventricular arrhythmias including WPW, PVC, AT, and AFL. EWI when used with ECG may allow for improved treatment for patients with arrhythmias.
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Affiliation(s)
- Christopher S Grubb
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Lea Melki
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY 10032, USA
| | - Daniel Y Wang
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - James Peacock
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Jose Dizon
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Vivek Iyer
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Carmine Sorbera
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Angelo Biviano
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - David A Rubin
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - John P Morrow
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Deepak Saluja
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Andrew Tieu
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY 10032, USA
| | - Pierre Nauleau
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY 10032, USA
| | - Rachel Weber
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY 10032, USA
| | - Salma Chaudhary
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Irfan Khurram
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Marc Waase
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Hasan Garan
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Elisa E Konofagou
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY 10032, USA.
- Department of Radiology, Columbia University Medical Center, New York, NY 10032, USA
| | - Elaine Y Wan
- Division of Cardiology, Department of Medicine and Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
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Bessière F, Zorgani A, Robert J, Daunizeau L, Cao E, Vaillant F, Abell E, Quesson B, Catheline S, Chevalier P, Lafon C. High Frame Rate Ultrasound for Electromechanical Wave Imaging to Differentiate Endocardial From Epicardial Myocardial Activation. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:405-414. [PMID: 31767455 DOI: 10.1016/j.ultrasmedbio.2019.10.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 10/04/2019] [Accepted: 10/18/2019] [Indexed: 06/10/2023]
Abstract
Differentiation between epicardial and endocardial ventricular activation remains a challenge despite the latest technologies available. The aim of the present study was to develop a new tool method, based on electromechanical wave imaging (EWI), to improve arrhythmogenic substrate activation analysis. Experiments were conducted on left ventricles (LVs) of four isolated working mode swine hearts. The protocol aimed at demonstrating that different patterns of mechanical activation could be observed whether the ventricle was in sinus rhythm, paced from the epicardium or from the endocardium. A total of 72 EWI acquisitions were recorded on the anterior, lateral and posterior segments of the LV. A total of 54 loop records were blindly assigned to two readers. EWI sequences interpretations were correct in 89% of cases. The overall agreement rate between the two readers was 83%. When in a paced ventricle, the origin of the wave front was focal and originated from the endocardium or the epicardium. In sinus rhythm, wave front was global and activated within the entire endocardium toward the epicardium at a speed of 1.7 ± 0.28 m·s-1. Wave front speeds were respectively measured when the endocardium or the epicardium were paced at a speed of 1.1 ± 0.35 m·s-1 versus 1.3 ± 0.34 m·s-1 (p = NS). EWI activation mapping allows activation localization within the LV wall and calculation of the wave front propagation speed through the muscle. In the future, this technology could help localize activation within the LV thickness during complex ablation procedures.
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Affiliation(s)
- Francis Bessière
- Hôpital Cardiologique Louis Pradel, Hospices Civils de Lyon, Lyon, France; LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France.
| | - Ali Zorgani
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Jade Robert
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Loïc Daunizeau
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Elodie Cao
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Fanny Vaillant
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France; Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France; INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, 33000 Bordeaux, France
| | - Emma Abell
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France; Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France; INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, 33000 Bordeaux, France
| | - Bruno Quesson
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France; Université de Bordeaux, Centre de Recherche Cardio-Thoracique de Bordeaux, Bordeaux, France; INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, 33000 Bordeaux, France
| | - Stéphane Catheline
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Philippe Chevalier
- Hôpital Cardiologique Louis Pradel, Hospices Civils de Lyon, Lyon, France; Université de Lyon, Lyon, France
| | - Cyril Lafon
- LabTAU, INSERM, Centre Léon Bérard, Université Lyon 1, Univ Lyon, Lyon, France; Université de Lyon, Lyon, France
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Melki L, Grubb CS, Weber R, Nauleau P, Garan H, Wan E, Silver ES, Liberman L, Konofagou EE. 3D-rendered Electromechanical Wave Imaging for Localization of Accessory Pathways in Wolff-Parkinson-White Minors .. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:6192-6195. [PMID: 31947257 DOI: 10.1109/embc.2019.8857876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Arrhythmia localization prior to catheter ablation is critical for clinical decision making and treatment planning. The current standard lies in 12-lead electrocardiogram (ECG) interpretation, but this method is non-specific and anatomically limited. Accurate localization requires intracardiac catheter mapping prior to ablation. Electromechanical Wave Imaging (EWI) is a high frame-rate ultrasound modality capable of non-invasively mapping the electromechanical activation in all cardiac chambers in vivo. In this study, we evaluate 3D-rendered EWI as a technique for consistently localizing the accessory pathway (AP) in Wolff-Parkinson-White (WPW) pediatric patients. A 2000 Hz EWI diverging sequence was used to transthoracically image 13 patients with evidence of ECG pre-excitation, immediately prior to catheter ablation and after successful ablation whenever possible. 3D-rendered activation maps were generated by co-registering and interpolating the 4 resulting multi-2D isochrones. A blinded electrophysiologist predicted the AP location on 12-lead ECG prior to ablation. Double-blinded EWI isochrones and clinician assessments were compared to the successful ablation site as confirmed by intracardiac mapping using a segmented template of the heart with 19 ventricular regions. 3D-rendered EWI was shown capable of consistently localizing AP in all the WPW cases. Clinical ECG interpretation correctly predicted the origin with an accuracy of 53.8%, respectively 84.6% when considering predictions in immediately adjacent segments correct. Our method was also capable of assessing the difference in activation pattern from before to after successful ablation on the same patient. These findings indicate that EWI could inform current diagnosis and expedite treatment planning of WPW ablation procedures.
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Andersen MV, Moore C, Søgaard P, Friedman D, Atwater BD, Arges K, LeFevre M, Struijk JJ, Kisslo J, Schmidt SE, von Ramm OT. Quantitative Parameters of High-Frame-Rate Strain in Patients with Echocardiographically Normal Function. ULTRASOUND IN MEDICINE & BIOLOGY 2019; 45:1197-1207. [PMID: 30773380 DOI: 10.1016/j.ultrasmedbio.2018.11.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 10/30/2018] [Accepted: 11/12/2018] [Indexed: 06/09/2023]
Abstract
Recently, we developed a high-frame-rate echocardiographic imaging system capable of acquiring images at rates up to 2500 per second. High imaging rates were used to quantify longitudinal strain parameters in patients with echocardiographically normal function. These data can serve as a baseline for comparing strain parameters in disease states. The derived timing data also reveal the propagation of mechanical events in the left ventricle throughout the cardiac cycle. High-frame-rate echocardiographic images were acquired from 17 patients in the apical four-chamber view using Duke University's phased array ultrasound system, T5. B-Mode images were acquired at 500-1000 images per second by employing 16:1 or 32:1 parallel processing in receive, a scan depth ≤14 cm and an 80° field of view with a 3.5-MegaHertZ (MHz), 96-element linear array. The images were analyzed using a speckle tracking algorithm tailored for high-frame-rate echocardiographic images developed at Aalborg and Duke University. Four specific mechanical events were defined using strain curves from six regions along the myocardial contour of the left ventricle. The strain curves measure the local deformation events of the myocardium and are independent of the overall cardiac motion. We observed statistically significant differences in the temporal sequence among different myocardial segments for the first mechanical event described, myocardial tissue shortening onset (p < 0.01). We found that the spatial origin of tissue shortening was located near the middle of the interventricular septum in patients with echocardiographically normal function. The quantitative parameters defined here, based on high-speed strain measurements in patients with echocardiographically normal function, can serve as a means of assessing degree of contractile abnormality in the myocardium and enable the identification of contraction propagation. The relative timing pattern among specific events with respect to the Q wave may become an important new metric in assessing cardiac function and may, in turn, improve diagnosis and prognosis.
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Affiliation(s)
| | | | - Peter Søgaard
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | | | | | | | | | | | - Joseph Kisslo
- Duke University Hospital, Durham, North Carolina, USA
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9
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Melki L, Grubb CS, Weber R, Nauleau P, Garan H, Wan E, Silver ES, Liberman L, Konofagou EE. Localization of Accessory Pathways in Pediatric Patients With Wolff-Parkinson-White Syndrome Using 3D-Rendered Electromechanical Wave Imaging. JACC Clin Electrophysiol 2019; 5:427-437. [PMID: 31000096 DOI: 10.1016/j.jacep.2018.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Revised: 12/02/2018] [Accepted: 12/04/2018] [Indexed: 11/25/2022]
Abstract
OBJECTIVES This study sought to demonstrate the feasibility of electromechanical wave imaging (EWI) for localization of accessory pathways (AP) prior to catheter ablation in a pediatric population. BACKGROUND Prediction of AP locations in patients with Wolff-Parkinson-White syndrome is currently based on analysis of 12-lead electrocardiography (ECG). In the pediatric population, specific algorithms have been developed to aid in localization, but these can be unreliable. EWI is a noninvasive imaging modality relying on a high frame rate ultrasound sequence capable of visualizing cardiac electromechanical activation. METHODS Pediatric patients with ventricular pre-excitation presenting for catheter ablation were imaged with EWI immediately prior to the start of the procedure. Two clinical pediatric electrophysiologists predicted the location of the AP based on ECG. Both EWI and ECG predictions were blinded to the results of catheter ablation. EWI and ECG localizations were subsequently compared with the site of successful ablation. RESULTS Fifteen patients were imaged with EWI. One patient was excluded for poor echocardiographic windows and the inability to image the entire ventricular myocardium. EWI correctly predicted the location of the AP in all 14 patients. ECG analysis correctly predicted 11 of 14 (78.6%) of the AP locations. CONCLUSIONS EWI was shown to be capable of consistently localizing accessory pathways. EWI predicted the site of successful ablation more frequently than analysis of 12-lead ECG. EWI isochrones also provide anatomical visualization of ventricular pre-excitation. These findings suggest that EWI can predict AP locations, and EWI may have the potential to better inform clinical electrophysiologists prior to catheter ablation procedures.
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Affiliation(s)
- Lea Melki
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York
| | - Christopher S Grubb
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Rachel Weber
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York
| | - Pierre Nauleau
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York
| | - Hasan Garan
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Elaine Wan
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, New York
| | - Eric S Silver
- Pediatric Electrophysiology, Division of Pediatric Cardiology, Department of Pediatrics, Columbia University Medical Center, New York, New York
| | - Leonardo Liberman
- Pediatric Electrophysiology, Division of Pediatric Cardiology, Department of Pediatrics, Columbia University Medical Center, New York, New York
| | - Elisa E Konofagou
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York; Department of Radiology, Columbia University Medical Center, New York, New York.
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Sayseng V, Grondin J, Konofagou EE. Optimization of Transmit Parameters in Cardiac Strain Imaging With Full and Partial Aperture Coherent Compounding. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2018; 65:684-696. [PMID: 29752226 PMCID: PMC5985980 DOI: 10.1109/tuffc.2018.2807765] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Coherent compounding methods using the full or partial transmit aperture have been investigated as a possible means of increasing strain measurement accuracy in cardiac strain imaging; however, the optimal transmit parameters in either compounding approach have yet to be determined. The relationship between strain estimation accuracy and transmit parameters-specifically the subaperture, angular aperture, tilt angle, number of virtual sources, and frame rate-in partial aperture (subaperture compounding) and full aperture (steered compounding) fundamental mode cardiac imaging was thus investigated and compared. Field II simulation of a 3-D cylindrical annulus undergoing deformation and twist was developed to evaluate accuracy of 2-D strain estimation in cross-sectional views. The tradeoff between frame rate and number of virtual sources was then investigated via transthoracic imaging in the parasternal short-axis view of five healthy human subjects, using the strain filter to quantify estimation precision. Finally, the optimized subaperture compounding sequence (25-element subperture, 90° angular aperture, 10 virtual sources, 300-Hz frame rate) was compared to the optimized steered compounding sequence (60° angular aperture, 15° tilt, 10 virtual sources, 300-Hz frame rate) via transthoracic imaging of five healthy subjects. Both approaches were determined to estimate cumulative radial strain with statistically equivalent precision (subaperture compounding E(SNRe %) = 3.56, and steered compounding E(SNRe %) = 4.26).
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Nauleau P, Melki L, Wan E, Konofagou E. Technical Note: A 3-D rendering algorithm for electromechanical wave imaging of a beating heart. Med Phys 2017. [PMID: 28626939 DOI: 10.1002/mp.12411] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Arrhythmias can be treated by ablating the heart tissue in the regions of abnormal contraction. The current clinical standard provides electroanatomic 3-D maps to visualize the electrical activation and locate the arrhythmogenic sources. However, the procedure is time-consuming and invasive. Electromechanical wave imaging is an ultrasound-based noninvasive technique that can provide 2-D maps of the electromechanical activation of the heart. In order to fully visualize the complex 3-D pattern of activation, several 2-D views are acquired and processed separately. They are then manually registered with a 3-D rendering software to generate a pseudo-3-D map. However, this last step is operator-dependent and time-consuming. METHODS This paper presents a method to generate a full 3-D map of the electromechanical activation using multiple 2-D images. Two canine models were considered to illustrate the method: one in normal sinus rhythm and one paced from the lateral region of the heart. Four standard echographic views of each canine heart were acquired. Electromechanical wave imaging was applied to generate four 2-D activation maps of the left ventricle. The radial positions and activation timings of the walls were automatically extracted from those maps. In each slice, from apex to base, these values were interpolated around the circumference to generate a full 3-D map. RESULTS In both cases, a 3-D activation map and a cine-loop of the propagation of the electromechanical wave were automatically generated. The 3-D map showing the electromechanical activation timings overlaid on realistic anatomy assists with the visualization of the sources of earlier activation (which are potential arrhythmogenic sources). The earliest sources of activation corresponded to the expected ones: septum for the normal rhythm and lateral for the pacing case. CONCLUSIONS The proposed technique provides, automatically, a 3-D electromechanical activation map with a realistic anatomy. This represents a step towards a noninvasive tool to efficiently localize arrhythmias in 3-D.
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Affiliation(s)
- Pierre Nauleau
- Department of Biomedical Engineering, Columbia University, 1210 Amsterdam Avenue, New York, NY, 10027, USA
| | - Lea Melki
- Department of Biomedical Engineering, Columbia University, 1210 Amsterdam Avenue, New York, NY, 10027, USA
| | - Elaine Wan
- Department of Medicine - Division of Cardiology, College of Physicians and Surgeons, Columbia University, 161 Fort Washington Avenue, New York, NY, 10032, USA
| | - Elisa Konofagou
- Department of Biomedical Engineering, Columbia University, 1210 Amsterdam Avenue, New York, NY, 10027, USA.,Department of Radiology, Columbia University, 622 W 168th Street, New York, NY, 10032, USA
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