Bibliografie tematiche / Electromechanical Wave Imaging

Letteratura scientifica selezionata sul tema "Electromechanical Wave Imaging"

Autore: Grafiati

Pubblicato: 1 giugno 2024

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Articoli di riviste sul tema "Electromechanical Wave Imaging":

Provost, Jean, Vu Thanh-Hieu Nguyen, Diégo Legrand, Stan Okrasinski, Alexandre Costet, Alok Gambhir, Hasan Garan e Elisa E. Konofagou. "Electromechanical wave imaging for arrhythmias". Physics in Medicine and Biology 56, n. 22 (25 ottobre 2011): L1—L11. http://dx.doi.org/10.1088/0031-9155/56/22/f01.

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Costet, Alexandre, Lea Melki, Vincent Sayseng, Nadira Hamid, Koki Nakanishi, Elaine Wan, Rebecca Hahn, Shunichi Homma e Elisa Konofagou. "Electromechanical wave imaging and electromechanical wave velocity estimation in a large animal model of myocardial infarction". Physics in Medicine & Biology 62, n. 24 (21 novembre 2017): 9341–56. http://dx.doi.org/10.1088/1361-6560/aa96d0.

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Zheng, Lu, Hui Dong, Xiaoyu Wu, Yen-Lin Huang, Wenbo Wang, Weida Wu, Zheng Wang e Keji Lai. "Interferometric imaging of nonlocal electromechanical power transduction in ferroelectric domains". Proceedings of the National Academy of Sciences 115, n. 21 (7 maggio 2018): 5338–42. http://dx.doi.org/10.1073/pnas.1722499115.

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Abstract (sommario):

The electrical generation and detection of elastic waves are the foundation for acoustoelectronic and acoustooptic systems. For surface acoustic wave devices, microelectromechanical/nanoelectromechanical systems, and phononic crystals, tailoring the spatial variation of material properties such as piezoelectric and elastic tensors may bring significant improvements to the system performance. Due to the much slower speed of sound than speed of light in solids, it is desirable to study various electroacoustic behaviors at the mesoscopic length scale. In this work, we demonstrate the interferometric imaging of electromechanical power transduction in ferroelectric lithium niobate domain structures by microwave impedance microscopy. In sharp contrast to the traditional standing-wave patterns caused by the superposition of counterpropagating waves, the constructive and destructive fringes in microwave dissipation images exhibit an intriguing one-wavelength periodicity. We show that such unusual interference patterns, which are fundamentally different from the acoustic displacement fields, stem from the nonlocal interaction between electric fields and elastic waves. The results are corroborated by numerical simulations taking into account the sign reversal of piezoelectric tensor in oppositely polarized domains. Our work paves ways to probe nanoscale electroacoustic phenomena in complex structures by near-field electromagnetic imaging.

Grubb, Christopher S., Lea Melki, Daniel Y. Wang, James Peacock, Jose Dizon, Vivek Iyer, Carmine Sorbera et al. "Noninvasive localization of cardiac arrhythmias using electromechanical wave imaging". Science Translational Medicine 12, n. 536 (25 marzo 2020): eaax6111. http://dx.doi.org/10.1126/scitranslmed.aax6111.

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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.

Provost, J., Wei-Ning Lee, K. Fujikura e E. E. Konofagou. "Electromechanical Wave Imaging of Normal and Ischemic HeartsIn Vivo". IEEE Transactions on Medical Imaging 29, n. 3 (marzo 2010): 625–35. http://dx.doi.org/10.1109/tmi.2009.2030186.

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Melki, Lea, Melina Tourni e Elisa E. Konofagou. "Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation". IEEE Transactions on Medical Imaging 40, n. 9 (settembre 2021): 2258–71. http://dx.doi.org/10.1109/tmi.2021.3074808.

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Konofagou, Elisa E., Jianwen Luo, Deepak Saluja, Daniel O. Cervantes, James Coromilas e Kana Fujikura. "Noninvasive electromechanical wave imaging and conduction-relevant velocity estimation in vivo". Ultrasonics 50, n. 2 (febbraio 2010): 208–15. http://dx.doi.org/10.1016/j.ultras.2009.09.026.

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Provost, Jean, Alok Gambhir, John Vest, Hasan Garan e Elisa E. Konofagou. "A clinical feasibility study of atrial and ventricular electromechanical wave imaging". Heart Rhythm 10, n. 6 (giugno 2013): 856–62. http://dx.doi.org/10.1016/j.hrthm.2013.02.028.

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Provost, Jean, Alexandre Costet, Elaine Wan, Alok Gambhir, William Whang, Hasan Garan e Elisa E. Konofagou. "Assessing the atrial electromechanical coupling during atrial focal tachycardia, flutter, and fibrillation using electromechanical wave imaging in humans". Computers in Biology and Medicine 65 (ottobre 2015): 161–67. http://dx.doi.org/10.1016/j.compbiomed.2015.08.005.

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Boissiere, Julien, Mathieu Gautier, Marie-Christine Machet, Gilles Hanton, Pierre Bonnet e Veronique Eder. "Doppler tissue imaging in assessment of pulmonary hypertension-induced right ventricle dysfunction". American Journal of Physiology-Heart and Circulatory Physiology 289, n. 6 (dicembre 2005): H2450—H2455. http://dx.doi.org/10.1152/ajpheart.00524.2005.

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Abstract (sommario):

We aimed to assess the accuracy of Doppler tissue imaging (DTI) in detecting right ventricle (RV) dysfunction and electromechanical coupling alteration following pulmonary hypertension (PHT) in rat. PHT was induced by chronic hypoxia exposure (hypoxic PHT) or monocrotaline treatment (monocrotaline PHT). In both PHT models, we observed transparietal RV pressure increase and remodeling, including hypertrophy and dilation. Conventional echocardiography provided evidence for pulmonary outflow impairment with midsystolic notch and acceleration time decrease in PHT groups (21.7 ± 1.6 and 13.2 ± 2.9 ms in hypoxic and monocrotaline PHT groups vs. 28.1 ± 1.0 ms in control). RV shortening fraction was decreased in the monocrotaline PHT group compared with the hypoxic PHT and control groups. Combining conventional Doppler and DTI was more helpful to detect RV diastolic dysfunction in the monocrotaline PHT group (E/Ea ratio = 17.0 ± 1.4) compared with the hypoxic PHT and control groups (11.5 ± 0.7 and 10.2 ± 0.4, respectively). Tei index measured using DTI highlighted global RV dysfunction in the monocrotaline PHT group (1.36 ± 0.24 vs. 0.92 ± 0.05 and 0.86 ± 0.05 in the hypoxic PHT and control groups, respectively). Q-Sm time measured from the onset of Q wave to the onset of DTI Sm wave was increased in both PHT groups. PHT-induced electromechanical coupling alteration was confirmed by in vitro activation-contraction delay measurements on isolated RV papillary muscle, and both Q-Sm time and activation-contraction delay were correlated with PHT severity. We demonstrated that Q-Sm time measured in DTI was an easily and convenient index to detect early RV electromechanical coupling alteration in both moderate and severe PHT.

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Tesi sul tema "Electromechanical Wave Imaging":

Robert, Jade. "Développement de modalités d'imagerie ultrasonore pour le guidage et le suivi interventionnel du traitement des arythmies cardiaques". Electronic Thesis or Diss., Lyon, 2022. http://www.theses.fr/2022LYSE1005.

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Les arythmies cardiaques sont, aujourd’hui encore, un enjeu de santé publique majeur. Certains types d’arythmies affectent plusieurs dizaines de millions de personnes dans le monde, tandis que d’autres sont la cause principale de mort subite cardiaque. Dans les cas les plus sévères, il est impératif de recourir à un traitement, afin de préserver l’intégrité du patient. Or, les méthodes interventionnelles, de guidage et de suivi de ce traitement, sont limitées, menant ainsi à un taux de récurrence parfois élevé, en fonction du type d’arythmie. Cette thèse s’intéresse alors au développement de modalités d’imagerie ultrarapide ultrasonore, pouvant pallier ces limitations. Ces modalités sont l’imagerie de l’onde électromécanique et l’élastographie passive, et pourraient offrir des informations pertinentes, jusqu’alors indisponible en clinique. Dans un premier temps, des études ex-vivo, sur cœurs isolés travaillants, ont été conduites afin d’évaluer le potentiel de l’imagerie de l’onde électromécanique. Une étude en aveugle a permis de démontrer qu’il était possible de détecter avec précision le type de stimulation et la source de contraction dans 79% des cas. Puis, deux études in-vivo, sur modèle porcin ont permis d’étudier la faisabilité de l’imagerie de l’onde électromécanique sur deux types de sondes, plus adaptées à un contexte interventionnel. Des ondes pouvant être associées à la contraction cardiaque ont été visualisées dans les deux études. Néanmoins, la visualisation dynamique de l’onde de contraction a été plus complexe dans un contexte in-vivo, puisqu’elle nécessite une interprétation, nécessairement subjective, d’un lecteur expérimenté. Pour répondre à cette limitation, une nouvelle méthode d’analyse temps-fréquence des données ultrasonores a été mise en place afin d’aboutir à une représentation plus objective de la contraction cardiaque, et ne nécessitant pas d’utilisateur expérimenté. La méthode a été validée, qualitativement et quantitativement, sur données ex-vivo, vis-à-vis de la méthode de référence utilisée en imagerie de l’onde électromécanique dans la littérature. En appliquant la méthode aux données des études in-vivo, il a pu être démontré que les schémas de contraction décrits sont similaires entre deux stimulations consécutives, et que la source de contraction est correctement positionnée lorsque la sonde de stimulation est située dans le plan. Notamment, la zone de contraction observée était cohérente avec la zone de stimulation dans le plan d’imagerie dans 81% des cas, lors des acquisitions réalisées à l’aide d’une sonde intracardiaque. Des études ex-vivo, sur échantillons cardiaques, ont été mises en place afin d’évaluer la faisabilité de détection des lésions simples et des schémas de lésions thermiques par élastographie passive. Il a été démontré sur un grand nombre d’échantillons (41 sur n = 51, 80% sur deux études) qu’une augmentation locale de la rigidité (d’un facteur 1.6 à 2.5 en moyenne), des zones lésées, était visible par élastographie. Les répartitions des lésions détectés sont cohérentes et les dimensions correctement estimées (manuellement, 1.1 à 2.8 mm d’erreur absolue, en moyenne), bien que les surfaces de lésions obtenues par élastographie passive soient encore approximatives. Finalement, une étude in-vivo sur modèle porcin a permis de démontrer la faisabilité de détecter des lésions thermiques individuelles ou en ligne par élastographie passive
Cardiac arrhythmias remain a major public health issue today. Some types of arrhythmias affect tens of millions of people worldwide, while others are the main cause of sudden cardiac death. In the most severe cases, it is imperative perform a treatment in order to preserve the integrity of the patient. However, interventional methods for guiding and monitoring this treatment are limited, sometimes leading to high recurrence rates, depending on the type of arrhythmia. This thesis focuses on the development of ultrafast ultrasound imaging modalities that can overcome these limitations. These modalities are Electromechanical Wave Imaging and Passive Elastography, and could provide relevant information, until now unavailable in clinic. First, ex-vivo studies on isolated working hearts were conducted to evaluate the potential of Electromechanical Wave Imaging. A blind study demonstrated that it was possible to accurately detect the type of stimulation and the source of contraction in 79% of cases. Then, two in-vivo studies, conducted on porcine model, allowed to study the feasibility of the electromechanical wave imaging on two types of probes, more adapted to an interventional context. Waves that could be associated with cardiac contraction were visualized in both studies. Nevertheless, dynamic visualization of the contraction wave was more complex in an in-vivo context, as it requires subjective interpretation of a trained reader. To address this limitation, a novel method based on time-frequency analysis of ultrasound data was developed to provide a more objective representation of the cardiac contraction, without the need of a trained reader. The method was validated, qualitatively and quantitatively, on ex-vivo data, against the reference method used for Electromechanical Wave Imaging in the literature. By applying the method to the data from the in-vivo studies, it could be demonstrated that the described contraction patterns are similar between two consecutive stimulations with same conditions, and that the contraction source is correctly positioned when the stimulation probe is located in the plane. Notably, the observed contraction area was consistent with the pacing area, when located in the imaging plane, in 81% of the cases, during the study performed with an intracardiac probe. Ex-vivo studies on cardiac samples were performed to evaluate the feasibility of detecting single lesions and thermal injury patterns by Passive Elastography. It was demonstrated on a large number of samples (41 out of n = 51, 80% on two studies) that a local stiffness increase (by a factor of 1.6 to 2.5 on average), of the injured areas, was visible by elastography. The distributions of the detected lesions were consistent, and the dimensions correctly estimated (manually, 1.1 to 2.8 mm error on average), although the lesion areas detected by passive elastography were still approximate. Finally, an in-vivo study on a porcine model demonstrated the feasibility of detecting individual or in-line thermal lesions with this method

Provost, Jean. "Electromechanical Wave Imaging". Thesis, 2012. https://doi.org/10.7916/D83J3B2N.

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Cardiac conduction abnormalities and arrhythmias are associated with stroke, heart failure, and sudden cardiac death, and remain a major cause of death and disability. However, the imaging tools currently available to the physician to guide these treatments by mapping the activation sequence of the heart are invasive, ionizing, time-consuming, and costly. In this dissertation, Electromechanical Wave Imaging (EWI) is described with an aim to characterize normal and abnormal rhythms noninvasively, transmurally, at the point of care, and in real time. More specifically, the methods to map the electromechanical wave (EW), i.e., the transient deformations occurring in response to the electrical activation of the heart, are developed and optimized. The correlation between EW and the electrical activation sequence during both normal and abnormal rhythms is demonstrated in canines in vivo and in silico. Finally, EWI is shown to noninvasively detect and characterize arrhythmias and conduction disorders in humans. Novel ultrasound imaging methodologies were developed to track the EW. Radio-frequency (RF) frames acquired at high frame rates were used in conjunction with cross-correlation algorithms to map the onset of the small, localized, transient deformations resulting from the electrical activation and forming the EW. To validate the capability of the EW to characterize cardiac rhythm, it was compared against the electrical activation in vivo and in silico. A high correlation between the electrical and electromechanical activations was obtained in normal canines in vivo during various pacing schemes and sinus rhythm. An in vivo-in silico framework was also developed to demonstrate that this correlation is maintained transmurally and independently of the imaging angle. EWI was also validated in abnormal canine hearts in vivo during ischemia, left bundle branch block, or atrio-ventricular dissociation. In a clinical feasibility study, we demonstrated that EWI was capable of noninvasively mapping normal and abnormal activation patterns in all four cardiac chambers of human subjects using a readily available clinical ultrasound scanner. Specifically, EWI maps were generated for three heart failure patients with cardiac resynchronization therapy (CRT) devices and for three patients with atrial flutter who subsequently underwent catheter mapping and radiofrequency ablation. Preliminary validation of EWI maps against invasive transcutaneous electroanatomical cardiac mapping was also demonstrated. EWI has the potential of becoming a noninvasive and highly translational technology that can serve as a unique imaging tool for the early detection, diagnosis and treatment monitoring and follow-up of arrhythmias and conduction disorders through ultrasound-based mapping of the transmural electromechanical activation sequence reliably, at the point of care, and in real time.

Costet, Alexandre. "Electromechanical wave imaging for the in vivo characterization and assessment of cardiac arrhythmias". Thesis, 2016. https://doi.org/10.7916/D81G0MHB.

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Cardiac diseases and conduction disorders are associated with stroke, heart failure and sudden cardiac death and are a major health concern worldwide. In the US alone, more than 14 million people suffer from heart rhythm disorders. Current mapping and characterization techniques in the clinic involve invasive procedures, which are time-consuming, costly, and may involve ionizing radiation. In this dissertation, we introduce Electromechanical Wave Imaging (EWI) as a non-invasive, ultrasound-based treatment planning tool for pre-procedure characterization and assessment of arrhythmia in the clinic. In particular, standard EWI processing methods for mapping the electromechanical wave (EW), i.e. the onset of the mechanical activity following the depolarization of the heart, are described and detailed. Next, validation of EWI is performed with 3D electromechanical mapping and the EW propagation is shown to follow the electrical activation in all four chambers of the heart. Demonstration of the value of EWI for the characterization of cardiac arrhythmia is accomplished in vivo in a large animal model. First, EWI is shown capable of localizing the earliest region of activation in the ventricles during pacing from a standard pacemaker lead, as well as during pacing from a novel biological pacemaker. Repeatability is also demonstrated between consecutive cardiac cycle during normal sinus rhythm and during pacing. Then, in the atria, we demonstrate that EWI is capable of accurately identifying focal sources while pacing from several locations in both the left and right atria. In addition to being capable of localizing the focal source, EWI is also shown capable of differentiating between endocardial and epicardial focal sources. Finally, it is shown that EWI can correctly identify regions of infarction and monitor formation of infarcts over several days, after ligation of the left anterior descending coronary artery of canine hearts. Novel processing techniques aimed at extracting quantitative parameters from EWI estimates are then developed and implemented. Details of the implementation of processing methods for estimating the velocity of the EW propagation are presented, and a study of the EW velocity values in a canine heart before and after infarct formation is conducted. Electromechanical cycle length mapping (ECLM), which is aimed at extracting local rates of electromechanical activation in the heart, is then introduced and its implementation detailed. ECLM is subsequently validated in a paced canine heart in vivo. Finally, initial clinical feasibility is demonstrated. First, in the study of treatment of chaotic arrhythmia such as in the case of atrial fibrillation patients undergoing direct current cardioversion, ECLM is shown to be able to confirm acute treatment success. Then, the clinical value of EWI in the electrophysiology lab as a treatment planning tool for the characterization of focal arrhythmia is shown in ventricular tachycardia and Wolff-Parkinson-White patients. EWI is currently only a step away from real-world clinical application. As a non-invasive, ultrasound-based imaging modality, EWI is capable of providing relevant insights into the origins of an arrhythmia and has the potential to position itself in the clinic as a uniquely valuable pre-procedure planning tool for the non-invasive characterization of focal arrhythmias.

Melki, Lea. "Electromechanical Wave Imaging in the clinic: localization of atrial and ventricular arrhythmias and quantification of cardiac resynchronization therapy response". Thesis, 2020. https://doi.org/10.7916/d8-nxy6-ks03.

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Cardiac conduction abnormalities can often lead to heart failure, stroke and sudden cardiac death. Heart disease stands as the leading cause of mortality and morbidity in the United States, accounting for 30% of all deaths. Early detection of malfunctions such as arrhythmias and systolic heart failure, the two heart conditions studied in this dissertation, would definitely help reduce the burden cardiovascular diseases have on public health and overcome the current clinical challenges. The imaging techniques currently available to doctors for cardiac activation sequence mapping are invasive, ionizing, time-consuming and costly. Thus, there is an undeniable urgent need for a non-invasive and reliable imaging tool, which could play a crucial role in the early diagnosis of conduction diseases and allow physicians to choose the best course of action. The 12-lead electrocardiogram (ECG) is the current non-invasive clinical tool routinely used to diagnose and localize cardiac arrhythmias prior to intracardiac catheter ablation. However, it has limited accuracy and can be subject to operator bias. Besides, QRS complex narrowing on the clinical ECG after pacing device implantation is also used for response assessment in patients undergoing Cardiac Resynchronization Therapy (CRT). The latter is an established treatment for systolic heart failure patients who have Left Bundle Branch Block as well as a reduced ejection fraction and prolonged QRS duration. Yet, it is still not well understood why 30 to 40 % of CRT recipients do not respond. Echocardiography, due to its portability and ease-of-use, is the most frequently used imaging modality in clinical cardiology. In this dissertation, we assess the clinical performance of Electromechanical Wave Imaging (EWI) as a high frame rate ultrasound-based functional modality that can non-invasively map the electromechanical activation of the heart, i.e., the transient deformations immediately following the electrical activation. The objective of this dissertation is to demonstrate the potential clinical value of EWI for both arrhythmia detection and CRT characterization applications. The first step in translating EWI to the clinic was ensuring that the technique could reli- ably and reproducibly measure the electromechanical activation sequence independently of the probe angle and imaging view in healthy human volunteers (n=7). This dissertation then demonstrated the accuracy of EWI for localizing a variety of ventricular and atrial arrhythmias (accessory pathways in Wolff-Parkinson-White (WPW) syndrome, premature ventricular contractions, focal atrial tachycardia and macro-reentrant atrial flutter) in pediatric (n=14) and adult (n=55) patients prior to catheter ablation more accurately than 12-lead ECG predictions, as validated against electroanatomical mapping. Additionally, 3D-rendered EWI isochrones were illustrated to be capable of significantly distinguishing different biventricular pacing conditions (p≤0.05) with the RWAT and LWAT metrics, assessing the ventricular dyssynchrony change in heart failure patients (n=16) undergoing CRT, and visualizing it in 3D. EWI also provided quantification of %𝘙𝘔𝘓𝘝 in CRT patients (n=38): the amount of left-ventricular resynchronized myocardium, which was found to be a reliable response predictor at 3-, 6-, or 9-month clinical follow-up through its post-CRT values by significantly identifying super-responders from non-responders within 24 hours of implantation (p≤0.05). Furthermore, 3D-rendered isochrones successfully characterized the ventricular activation resulting from His Bundle pacing for the first time (n=4), which was undistinguishable from true physiological activation in sinus rhythm healthy volunteers with the EWI-based activation time distribution dispersion metric. The dispersion was, however, reported to significantly discriminate novel His pacing from other more conventional biventricular pacing schemes (p≤0.01). Finally, we developed and optimized a fully automated zero-crossing algorithm towards a faster, more robust and less observer dependent EWI isochrone generation process. The support vector machine (SVM) and Random Forest machine learning models were both shown capable of successfully identifying the accessory pathway in WPW patients and the pacing electrode location in paced canines. Nevertheless, the best performing algorithm was hereby proven to be the Random Forest classifier with n=200 trees with a precision rising to 97%, and a predictivity that was not impacted by the type of testing dataset it was applied to (human or canine). Overall, in this dissertation, we established the clinical potential of EWI as a viable assisting visual feedback tool, that could not only be used for diagnosis and treatment planning prior to surgical procedures, but also for monitoring during, and assessing long-term resolution of arrhythmia after catheter ablation or heart failure after a CRT implant.

Libri sul tema "Electromechanical Wave Imaging":

Provost, Jean. Electromechanical Wave Imaging. [New York, N.Y.?]: [publisher not identified], 2012.

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Costet, Alexandre. Electromechanical wave imaging for the in vivo characterization and assessment of cardiac arrhythmias. [New York, N.Y.?]: [publisher not identified], 2016.

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Capitoli di libri sul tema "Electromechanical Wave Imaging":

Konofagou, Elisa. "Electromechanical Wave Imaging". In Cardiac Mapping, 1083–95. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119152637.ch85.

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Atti di convegni sul tema "Electromechanical Wave Imaging":

Özsoy, Çağla, Ali Özbek, Xosé Luís Deán-Ben e Daniel Razansky. "Ultrafast imaging of cardiac electromechanical wave propagation with volumetric optoacoustic tomography". In Photons Plus Ultrasound: Imaging and Sensing 2020, a cura di Alexander A. Oraevsky e Lihong V. Wang. SPIE, 2020. http://dx.doi.org/10.1117/12.2545890.

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Schleifer, Hannah, Jad El Harake, Melina Tourni, Yik Tung Tracy Ling e Elisa Konofagou. "Myocardial Infarction Detection Using Combined Myocardial Elastography and Electromechanical Wave Imaging". In 2023 IEEE International Ultrasonics Symposium (IUS). IEEE, 2023. http://dx.doi.org/10.1109/ius51837.2023.10308190.

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Konofagou, E., Jianwen Luo, D. Saluja, K. Fujikura, D. Cervantes e J. Coromilas. "11B-1 Noninvasive Electromechanical Wave Imaging and Conduction Velocity Estimation In Vivo". In 2007 IEEE Ultrasonics Symposium. IEEE, 2007. http://dx.doi.org/10.1109/ultsym.2007.247.

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Tourni, Melina, Alexandra Channing, Seungyeon Han, Mary Kucinski e Elisa Konofagou. "Electromechanical Wave Imaging for pediatric mitral valve disease characterization in the clinic". In 2023 IEEE International Ultrasonics Symposium (IUS). IEEE, 2023. http://dx.doi.org/10.1109/ius51837.2023.10308206.

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Luo, J., K. Fujikura, E. Konofagou, D. Cervantes e J. Coromilas. "2I-6 Imaging the Electromechanical Wave Activation of the Left Ventricle in Vivo". In 2006 IEEE Ultrasonics Symposium. IEEE, 2006. http://dx.doi.org/10.1109/ultsym.2006.234.

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Provost, Jean, Wei-Ning Lee, Kana Fujikura e Elisa E. Konofagou. "Non-invasive localization and quantification of graded ischemia using Electromechanical Wave Imaging in vivo". In 2009 IEEE International Ultrasonics Symposium. IEEE, 2009. http://dx.doi.org/10.1109/ultsym.2009.5441811.

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Tourni, Melina, Lea Melki, Rachel Weber e Elisa Konofagou. "Automated Electromechanical Wave Imaging at Reduced Frame Rates During Sinus Rhythm Using Machine Learning". In 2021 IEEE International Ultrasonics Symposium (IUS). IEEE, 2021. http://dx.doi.org/10.1109/ius52206.2021.9593463.

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Melki, Lea, Christopher S. Grubb, Rachel Weber, Pierre Nauleau, Hasan Garan, Elaine Wan, Eric S. Silver, Leonardo Liberman e Elisa E. Konofagou. "3D-rendered Electromechanical Wave Imaging for Localization of Accessory Pathways in Wolff-Parkinson-White Minors*". In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8857876.

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Provost, J., W.-N. Lee, K. Fujikura e E. E. Konofagou. "Electromechanical Wave Imaging for non-invasive localization and quantification of partially ischemic regions in vivo". In 2010 36th Annual Northeast Bioengineering Conference. IEEE, 2010. http://dx.doi.org/10.1109/nebc.2010.5458126.

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Grondin, Julien, Dafang Wang, Elaine Wan, Natalia Trayanova e Elisa Konofagou. "Notice of Removal: 3-D electromechanical wave imaging in the heart in silico and in vivo". In 2017 IEEE International Ultrasonics Symposium (IUS). IEEE, 2017. http://dx.doi.org/10.1109/ultsym.2017.8092908.

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