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A recent study using an epicardial-only electrocardiographic imaging (ECGI), suggests that the agreement of ECGI activation mapping and that of the contact mapping for ventricular arrhythmias (VA) is poor. The aim of this study was to assess the diagnostic value of two endo -epicardial ECGI systems using different cardiac sources and the agreement between them. We performed 69 ECGI procedures in 52 patients referred for ablation of VA at our center. One system based on the extracellular potentials was used in 26 patients, the other based on the equivalent double layer model in 9, and both in 17 patients. The first uses up to 224 leads and the second just the 12‑lead ECG. The localization of the VA was done using a segmental model of the ventricles. A perfect match (PM) was defined as a predicted location within the same anatomic segment, whereas a near match (NM) as a predicted location within the same segment or a contiguous one. 44 patients underwent ablation, corresponding to 58 ECGI procedures (37 with the first and 21 with the second system). The percentage of PMs and NMs was not significantly different between the two systems, respectively 76% and 95%, p = 0.077, and 97% and 100%, p = 1.000. In 14 patients that underwent ablation and had the ECGI performed with both systems, raw agreement for PMs was 79%, p = 0.250 for disagreement. ECGI systems were useful to identify the origin of the VAs, and the results were reproducible regardless the cardiac source. • Endo-Epicardial ECGI systems correctly identify the origin of ventricular arrhythmias. • ECGI systems may use different cardiac sources. • The agreement between ECGI systems using different sources is fair [ABSTRACT FROM AUTHOR]

Aims: Evaluate right ventricular outflow tract (RVOT) activation duration (AD) and speed, invasively and with the electrocardiographic imaging (ECGI), as predictors of the origin of the PVCs, validating the ECGI.Methods: 18 consecutive patients, 8 males, median age 55 (35-63) years that underwent ablation of PVCs with inferior axis and had ECGI performed before ablation. Isochronal activation maps of the RVOT in PVC were obtained with the ECGI and invasively. Total RVOT AD was measured as the time between earliest and latest activated region, and propagation speed by measuring the area of the first 10 ms of activation. Cut-off values for AD, activation speed and number of 10 ms isochrones to predict the origin of the PVCs, were obtained with the ROC curve analysis. Agreement between methods was done with Pearson correlation test and Bland-Altman plot.Results: PVCs originated from the RVOT in 11 (61%) patients. The stronger predictor of PVC origin was the AD. The median AD in PVCs from RVOT was significantly longer than from outside the RVOT, both with ECGI and invasively, respectively 62 (58-73) vs 37 (33-40) ms, p < 0.0001 and 68 (60-75) vs 35 (29-41) ms, p < 0.0001. Agreement between the two methods was good (r = 0.864, p < 0.0001). The cut-off value of 43 ms for AD measured with ECGI predicted the origin of the PVCs with a sensitivity and specificity of 100%.Conclusions: We found good agreement between ECGI and invasive map. The AD measured with ECGI was the best predictor of the origin of the PVCs. [ABSTRACT FROM AUTHOR]

Aims: Assess the minimal number of ECGI leads needed to obtain a good spatial resolution.Methods: We enrolled 20 patients that underwent ablation of premature ventricular or atrial contractions using Carto and ECGI with AMYCARD. We evaluated the agreement regarding the site of origin of the arrhythmia between the ECGI and Carto, the area and diameter of the earliest activation site obtained with the ECGI (EASa and EASd). Based on previous studies with pacemapping, we considered a good spatial resolution of the ECGI when the EASd measured on the isopotential map was less than 18 mm. In presence of agreement the ECGI was reprocessed: a) with half the number of electrode bands (8 leads per electrode band) and b) with 6 electrode bands.Results: The initial map was obtained with 23 (22-23) electrode bands per patient, corresponding to 143 (130-170) leads. Agreement rate was 85%, the median EASa and EASd were: 0.7 (0.5-1.3) cm2 and 9 (8-13) mm. With half the number of electrode bands including 73 (60-79) leads, agreement rate was 80%, the EASa and EASd were: 2.1 (1.5-6.2) cm2 and 16 (14 -28) mm. With only six electrode bands using 38 (30-42) leads, agreement rate was 55%, EASa and EASd were: 4.0 (3.3-5.0) cm2 and 23 (21-25) mm. The number of leads was a predictor of agreement with a good spatial resolution, OR (95% CI) of 1.138 (1.050-1.234), p = .002. According to the ROC curve, the minimal number of leads was 74 (AUC 0.981; 95% CI: 0.949-1.00, p < .0001).Conclusion: Reducing the number of leads was associated with a lower agreement rate and a significant reduction of spatial resolution. However, the number of leads needed to achieve a good spatial resolution was less than the maximal available. [ABSTRACT FROM AUTHOR]

Background: His bundle pacing is a new method for delivering cardiac resynchronization therapy (CRT).Objectives: The authors performed a head-to-head, high-precision, acute crossover comparison between His bundle pacing and conventional biventricular CRT, measuring effects on ventricular activation and acute hemodynamic function.Methods: Patients with heart failure and left bundle branch block referred for conventional biventricular CRT were recruited. Using noninvasive epicardial electrocardiographic imaging, the authors identified patients in whom His bundle pacing shortened left ventricular activation time. In these patients, the authors compared the hemodynamic effects of His bundle pacing against biventricular pacing using a high-multiple repeated alternation protocol to minimize the effect of noise, as well as comparing effects on ventricular activation.Results: In 18 of 23 patients, left ventricular activation time was significantly shortened by His bundle pacing. Seventeen patients had a complete electromechanical dataset. In them, His bundle pacing was more effective at delivering ventricular resynchronization than biventricular pacing: greater reduction in QRS duration (-18.6 ms; 95% confidence interval [CI]: -31.6 to -5.7 ms; p = 0.007), left ventricular activation time (-26 ms; 95% CI: -41 to -21 ms; p = 0.002), and left ventricular dyssynchrony index (-11.2 ms; 95% CI: -16.8 to -5.6 ms; p < 0.001). His bundle pacing also produced a greater acute hemodynamic response (4.6 mm Hg; 95% CI: 0.2 to 9.1 mm Hg; p = 0.04). The incremental activation time reduction with His bundle pacing over biventricular pacing correlated with the incremental hemodynamic improvement with His bundle pacing over biventricular pacing (R = 0.70; p = 0.04).Conclusions: His resynchronization delivers better ventricular resynchronization, and greater improvement in hemodynamic parameters, than biventricular pacing. [ABSTRACT FROM AUTHOR]

Background Poor identification of electrical dyssynchrony is postulated to be a major factor contributing to the low success rate for cardiac resynchronization therapy. Objective The purpose of this study was to evaluate the sensitivity of body surface mapping and electrocardiographic imaging (ECGi) to detect electrical dyssynchrony noninvasively. Methods Langendorff-perfused pig hearts (n = 11) were suspended in a human torso-shaped tank, with left bundle branch block (LBBB) induced through ablation. Recordings were taken simultaneously from a 108-electrode epicardial sock and 128 electrodes embedded in the tank surface during sinus rhythm and ventricular pacing. Computed tomography provided electrode and heart positions in the tank. Epicardial unipolar electrograms were reconstructed from torso potentials using ECGi. Dyssynchrony markers from torso potentials (eg, QRS duration) or ECGi (total activation time, interventricular delay [D-LR], and intraventricular markers) were correlated with those recorded from the sock. Results LBBB was induced (n = 8), and sock-derived activation maps demonstrated interventricular dyssynchrony (D-LR and total activation time) in all cases ( P < .05) and intraventricular dyssynchrony for complete LBBB ( P < .05) compared to normal sinus rhythm. Only D-LR returned to normal with biventricular pacing ( P = .1). Torso markers increased with large degrees of dyssynchrony, and no reduction was seen during biventricular pacing ( P > .05). Although ECGi-derived markers were significantly lower than recorded ( P < .05), there was a significant strong linear relationship between ECGi and recorded values. ECGi correctly diagnosed electrical dyssynchrony and interventricular resynchronization in all cases. The latest site of activation was identified to 9.1 ± 0.6 mm by ECGi. Conclusion ECGi reliably and accurately detects electrical dyssynchrony, resynchronization by biventricular pacing, and the site of latest activation, providing more information than do body surface potentials. [ABSTRACT FROM AUTHOR]

Aims: Electromechanical de-coupling is hypothesized to explain non-response of dyssynchrony patient to cardiac resynchronization therapy (CRT). In this pilot study, we investigated regional electromechanical uncoupling in 10 patients referred for CRT using two non-invasive electrical and mechanical imaging techniques (CMR tissue tracking and ECGI).Methods and Results: Reconstructed regional electrical and mechanical activation captured delayed LBBB propagation direction from septal to anterior/inferior and finally to lateral walls as well as from LV apical to basal. All 5 responders demonstrated significantly delayed mechanical and electrical activation on the lateral LV wall at baseline compared to the non-responders (P<.05). On follow-up ECGI, baseline electrical activation patterns were preserved in native rhythm and global LV activation time was reduced with biventricular pacing.Conclusions: The combination of novel imaging techniques of ECGI and CMR tissue tracking can be used to assess spatial concordance of LV electrical and mechanical activation to gain insight into electromechanical coupling. [ABSTRACT FROM AUTHOR]

Ten years ago, electrocardiographic imaging (ECGI) started to demonstrate its efficiency in clinical settings. The initial application to localize focal ventricular arrhythmias such as ventricular premature beats was probably the easiest to challenge and validates the concept. Our clinical experience in using this non-invasive mapping technique to identify the sources of electrical disorders and guide catheter ablation of atrial arrhythmias (premature atrial beat, atrial tachycardia, atrial fibrillation), ventricular arrhythmias (premature ventricular beats) and ventricular pre-excitation (Wolff-Parkinson-White syndrome) is described here. [ABSTRACT FROM AUTHOR]

Non-invasive electrocardiographic imaging (ECGI) of the cardiac muscle can help the pre-procedure planning of the ablation of ventricular arrhythmias by reducing the time to localize the origin. Our non-invasive ECGI system, the cardiac isochrone positioning system (CIPS), requires non-intersecting meshes of the heart, lungs and torso. However, software to reconstruct the meshes of the heart, lungs and torso with the capability to check and prevent these intersections is currently lacking. Consequently the reconstruction of a patient specific model with realistic atrial and ventricular wall thickness and incorporating blood cavities, lungs and torso usually requires additional several days of manual work. Therefore new software was developed that checks and prevents any intersections, and thus enables the use of accurate reconstructed anatomical models within CIPS. In this preliminary study we investigated the accuracy of the created patient specific anatomical models from MRI or CT. During the manual segmentation of the MRI data the boundaries of the relevant tissues are determined. The resulting contour lines are used to automatically morph reference meshes of the heart, lungs or torso to match the boundaries of the morphed tissue. Five patients were included in the study; models of the heart, lungs and torso were reconstructed from standard cardiac MRI images. The accuracy was determined by computing the distance between the segmentation contours and the morphed meshes. The average accuracy of the reconstructed cardiac geometry was within 2mm with respect to the manual segmentation contours on the MRI images. Derived wall volumes and left ventricular wall thickness were within the range reported in literature. For each reconstructed heart model the anatomical heart axis was computed using the automatically determined anatomical landmarks of the left apex and the mitral valve. The accuracy of the reconstructed heart models was well within the accuracy of the used medical image data (pixel size <1.5mm). For the lungs and torso the number of triangles in the mesh was reduced, thus decreasing the accuracy of the reconstructed mesh. A novel software tool has been introduced, which is able to reconstruct accurate cardiac anatomical models from MRI or CT within only a few hours. This new anatomical reconstruction tool might reduce the modeling errors within the cardiac isochrone positioning system and thus enable the clinical application of CIPS to localize the PVC/VT focus to the ventricular myocardium from only the standard 12 lead ECG. [ABSTRACT FROM AUTHOR]

• A more precise and robust solution to locate the atrial fibrillation lesion. • An improvement for the inverse solution in electrocardiographic imaging. • A multi-scale solution based on uniform phase empirical mode decomposition. • Better reconstructed cardiac potential, even for disturbed body surface ECG signals. Current techniques used for solving the inverse problem in Electrocardiographic imaging (ECGI) to locate atrial fibrillation (AF) drivers are far from dependable and accurate. Given that body surface electrocardiographic signals (ECGs) are composed of numerous components, separation promises to be a powerful solution for the inverse operation, extracting sections with more specific components from the whole and processing them in a unique way. Therefore, this work proposes a multi-scale time–frequency domain solution based on uniform phase empirical mode decomposition (UPEMD_MSTFDS). We first utilize UPEMD to decompose the complete ECGs. Then we obtain the final solution by applying the second-order Tikhonov algorithms (Tikhonov) and truncated singular value decomposition (TSVD) to the different decomposed signal parts. To evaluate the accuracy and robustness of UPEMD_MSTFDS, two simulated datasets with or without random respiratory interference, namely baseline wander (BW), are employed. Quantitative results show that the detection accuracy of UPEMD_MSTFDS is improved by more than 10% on the first dataset including simple AF (SAF) and complex AF (CAF) when compared to popular inverse algorithms except for Bayesian maximum a posteriori estimation (Bayes). In the same condition but with BW, the weighted under-estimation indicator of UPEMD_MSTFDS drops by more than 70%, and the weighted over-estimation indicator corresponding to SAF with BW and CAF with BW drop to 39.99% and 57.03%, respectively. Moreover, both the driver and domain frequency maps computed by UPEMD_MSTFDS are most similar to the real ones of the other dataset, demonstrating that UPEMD_MSTFDS is apparently superior to existing algorithms. [ABSTRACT FROM AUTHOR]

Abstract: This is the first reported study of ventricular activation patterns after cardiac transplantation, using electrocardiographic imaging (ECGI), a noninvasive method for electrophysiologic mapping. This study of ten patients reveals that transplanted hearts have unique ventricular activation patterns in sinus rhythm, activating early in the epicardial aspect of the anterior or inferior septum, with intact right and left bundle branch conduction. They have late activation with slowing of conduction near the right ventricular (RV) basal free wall, causing a mild QRS prolongation and an rSr’ pattern in lead V1 of the ECG. PVCs arise from both endocardial and epicardial locations in both ventricles. [Copyright &y& Elsevier]

Objectives: The aim of this study was to noninvasively image the electrophysiological (EP) substrate of human ventricles after myocardial infarction and define its characteristics. Background: Ventricular infarct border zone is characterized by abnormal cellular electrophysiology and altered structural architecture and is a key contributor to arrhythmogenesis. The ability to noninvasively image its electrical characteristics could contribute to understanding of mechanisms and to risk-stratification for ventricular arrhythmia. Methods: Electrocardiographic imaging, a noninvasive functional EP imaging modality, was performed during sinus rhythm (SR) in 24 subjects with infarct-related myocardial scar. The abnormal EP substrate on the epicardial aspect of the scar was identified, and its location, size, and morphology were compared with the anatomic scar imaged by other noninvasive modalities. Results: Electrocardiographic imaging constructs epicardial electrograms that have characteristics of reduced amplitude (low voltage) and fractionation. Electrocardiographic imaging colocalizes the epicardial electrical scar to the anatomic scar with a high degree of accuracy (sensitivity 89%, specificity 85%). In nearly all subjects, SR activation patterns were affected by the presence of myocardial scar. Late potentials could be identified and were almost always within ventricular scar. Conclusions: Electrocardiographic imaging accurately identifies areas of anatomic scar and complements standard anatomic imaging by providing scar-related EP characteristics of low voltages, altered SR activation, electrogram fragmentation, and presence of late potentials. [Copyright &y& Elsevier]