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Introduction: Identifying the origin of nonpulmonary vein atrial fibrillation (AF) triggers (NPVTs) after pulmonary vein isolation (PVI) can be challenging. We aimed to determine if noninvasive electrocardiographic imaging (ECGi) could localize pacing from common NPVT sites. ECGi combines measured body surface potentials with heart‐torso geometry acquired from computed tomography (CT) to generate an activation map. Methods: In 12 patients with AF undergoing first time ablation, the ECGi vest was fitted for preprocedural CT scan and worn during the procedure. After PVI, we performed steady‐state pacing from 15 typical anatomic NPVT sites at a cycle length of 700–800 ms. We co‐registered the invasive anatomic map with the CT‐based ECGi epicardial activation map to compare ECGi predicted to true pacing origin. Results: In the study cohort (67% male, 58% persistent AF, and 67% with left atrial dilation), 148 (82%) pacing sites had both capture and adequate anatomy acquired from the three‐dimensional mapping system to co‐register with ECGi activation map. Median distance between true pacing sites and point of earliest epicardial activation derived from the ECGi maps for all sites was 17 mm (interquartile range, 10–22 mm). Assuming paced sites treated as regions with a radius of 2.5 cm, the earliest activation site on ECGi map falls within the region with 94% accuracy. Conclusion: ECGi can approximate the origin of paced beats from common NPVT sites to within a median distance of 17 mm. A rapidly identified region may then be the focus of more detailed catheter‐based mapping techniques to facilitate successful localization and ablation of NPVTs. [ABSTRACT FROM AUTHOR]

Background: Leadless cardiac resynchronization therapy (CRT) is an emerging heart failure treatment. An implanted electrode delivers lateral or septal endocardial left ventricular (LV) pacing (LVP) upon detection of a right ventricular (RV) pacing stimulus from a coimplanted device, thus generating biventricular pacing (BiVP). Electrical efficacy data regarding this therapy, particularly leadless LV septal pacing (LVSP) for potential conduction system capture, are limited. Objectives: The purpose of this study was to evaluate the acute performance of leadless CRT using electrocardiographic imaging (ECGi) and assess the optimal pacing modality (OPM) of LVSP on the basis of RV and LV activation. Methods: Ten WiSE-CRT recipients underwent an ECGi study testing: RV pacing, BiVP, LVP only, and LVP with an optimized atrioventricular delay (LV-OPT). BiV, LV, and RV activation times (shortest time taken to activate 90% of the ventricles [BIVAT-90], shortest time taken to activate 95% of the LV, and shortest time taken to activate 90% of the RV) plus LV and BiV dyssynchrony index (standard deviation of LV activation times and standard deviation of all activation times) were calculated from reconstructed epicardial electrograms. The individual OPM yielding the greatest improvement from baseline was determined. Results: BiVP generated a 23.7% improvement in BiVAT-90 (P = .002). An improvement of 43.3% was observed at the OPM (P = .0001), primarily through reductions in shortest time taken to activate 90% of the RV. At the OPM, BiVAT-90 improved in patients with lateral (43.3%; P = .0001; n = 5) and septal (42.4%; P = .009; n = 5) LV implants. The OPM varied by individual. LVP and LV-OPT were mostly superior in patients with LVSP, and in those with sinus rhythm and left bundle branch block (n = 4). Conclusion: Leadless CRT significantly improves acute ECGi-derived activation and dyssynchrony metrics. Using an individualized OPM improves efficacy in selected patients. Effective LVSP is feasible, with fusion pacing at LV-OPT mitigating the potential deleterious effects on RV activation.

Introduction: Patients with hypertrophic cardiomyopathy (HCM) are at risk for lethal ventricular arrhythmia, but the electrophysiological substrate behind this is not well-understood. We used non-invasive electrocardiographic imaging to characterize patients with HCM, including cardiac arrest survivors. Methods: HCM patients surviving ventricular fibrillation or hemodynamically unstable ventricular tachycardia (n = 17) were compared to HCM patients without a personal history of potentially lethal arrhythmia (n = 20) and a pooled control group with structurally normal hearts. Subjects underwent exercise testing by non-invasive electrocardiographic imaging to estimate epicardial electrophysiology. Results: Visual inspection of reconstructed epicardial HCM maps revealed isolated patches of late activation time (AT), prolonged activation-recovery intervals (ARIs), as well as reversal of apico-basal trends in T-wave inversion and ARI compared to controls (p < 0.005 for all). AT and ARI were compared between groups. The pooled HCM group had longer mean AT (60.1 ms vs. 52.2 ms, p < 0.001), activation dispersion (55.2 ms vs. 48.6 ms, p = 0.026), and mean ARI (227 ms vs. 217 ms, p = 0.016) than structurally normal heart controls. HCM ventricular arrhythmia survivors could be differentiated from HCM patients without a personal history of life-threatening arrhythmia by longer mean AT (63.2 ms vs. 57.4 ms, p = 0.007), steeper activation gradients (0.45 ms/mm vs. 0.36 ms/mm, p = 0.011), and longer mean ARI (234.0 ms vs. 221.4 ms, p = 0.026). A logistic regression model including whole heart mean activation time and activation recovery interval could identify ventricular arrhythmia survivors from the HCM cohort, producing a C statistic of 0.76 (95% confidence interval 0.72-0.81), with an optimal sensitivity of 78.6% and a specificity of 79.8%. Discussion: The HCM epicardial electrotype is characterized by delayed, dispersed conduction and prolonged, dispersed activation-recovery intervals. Combination of electrophysiologic measures with logistic regression can improve differentiation over single variables. Future studies could test such models prospectively for risk stratification of sudden death due to HCM. [ABSTRACT FROM AUTHOR]

Patients with heart failure and a non–left bundle branch block (non-LBBB) QRS pattern have a limited response to biventricular pacing (BVP). A personalized cardiac resynchronization therapy (CRT) implantation approach guided by real-time electrocardiographic imaging (ECGi) was studied. Twenty patients with left ventricular ejection fraction (LVEF) ≤ 35%, QRS duration ≥ 120 ms, and non-LBBB [13 (65%) with right bundle branch block and 7 (35%) with intraventricular conduction delay] were recruited. During CRT implantation, right atrial, right ventricular, coronary sinus, His-bundle, and/or left bundle leads were inserted. The total activation time (TAT) with different pacing combinations were measured in real time during implantation by ECGi. The configuration producing the shortest TAT was chosen. Clinical response was defined as ≥1 New York Heart Association class improvement. Echocardiographic response was defined as left ventricular end-systolic volume reduction ≥ 15% and/or LVEF improvement ≥ 10% at 6 months. After ECGi-guided CRT implantation, LVEF improved from 26% ± 6% to 34% ± 11% (P <.01) and New York Heart Association class improved from 3.0 ± 0.5 to 2.0 ± 0.6 (P <.01). Both clinical and echocardiographic response rates were 70%. The ECGi approach resulted in better acute electrical resynchronization over BVP as measured by TAT reduction (40% vs 14%; P <.01). The percentage of TAT reduction was found to be a strong predictor for echocardiographic response (area under the curve for the receiver operating characteristic curve 0.91; 95% confidence interval 0.78–1.00). A strong positive correlation between percentage TAT reduction and percentage LVEF improvement (Pearson R = 0.70; P =.001) was found. ECGi-guided CRT implantation in patients with non-LBBB generates superior acute electrical resynchronization compared with BVP and is associated with favorable clinical and echocardiographic outcomes. [Display omitted] [ABSTRACT FROM AUTHOR]

Introduction: Biventricular pacing (BiVp) improves outcomes in systolic heart failure patients with electrical dyssynchrony. BiVp is delivered from epicardial left ventricular (LV) and endocardial right ventricular (RV) electrodes. Acute electrical activation changes with different LV‐RV stimulation offsets can help guide individually optimized BiVp programming. We sought to study the BiVp ventricular activation with different LV‐RV offsets and compare with 12‐lead ECG. Methods: In five patients with BiVp (63 ± 17‐year‐old, 80% male, LV ejection fraction 27 ± 6%), we evaluated acute ventricular epicardial activation, varying LV‐RV offsets in 20 ms increments from −40 to 80 ms, using electrocardiographic imaging (ECGI) to obtain absolute ventricular electrical uncoupling (VEUabs, absolute difference in average LV and average RV activation time) and total activation time (TAT). For each patient, we calculated the correlation between ECGI and corresponding ECG (3D‐QRS‐area and QRS duration) with different LV‐RV offsets. Results: The LV‐RV offset to attain minimum VEUabs in individual patients ranged 20–60 ms. In all patients, a larger LV‐RV offset was required to achieve minimum VEUabs (36 ± 17 ms) or 3D‐QRS‐area (40 ± 14 ms) than that for minimum TAT (−4 ± 9 ms) or QRS duration (−8 ± 11 ms). In individual patients, 3D‐QRS‐area correlated with VEUabs (r 0.65 ± 0.24) and QRS duration correlated with TAT (r 0.95 ± 0.02). Minimum VEUabs and minimum 3D‐QRS‐area were obtained by LV‐RV offset within 20 ms of each other in all five patients. Conclusions: LV‐RV electrical uncoupling, as assessed by ECGI, can be minimized by optimizing LV‐RV stimulation offset. 3D‐QRS‐area is a surrogate to identify LV‐RV offset that minimizes LV‐RV uncoupling. [ABSTRACT FROM AUTHOR]

Sudden cardiac death causes multiple deaths annually, and T-wave alternans are a reliable predictor of this fatal event. Detecting alternans is crucial for reducing disease incidence, and electrocardiographic imaging is a promising tool, providing spatial-temporal insights. The absence of references and segmentation methods specific to these data may complicate progress in the field. Therefore, this work aimed to develop a reference for evaluating estimation methods. Initially, a novel T-wave segmentation procedure specific to these data was introduced and compared with a commonly used method. Subsequently, a reference for assessing alternans estimation methods was created by integrating alternans into epicardial signals through a spatial-temporal Gaussian function. Finally, a bootstrap-based classifier for detecting alternans was developed. Results underscored the superiority of the novel T-wave segmentation procedure, with the lowest 95% confidence interval being $[16.57~\mu V, 18.80~\mu V]$ , indicating significant disparities between the two segmentation methodologies. Furthermore, the generated reference demonstrated the distinguishability of T-wave alternans with an amplitude of approximately $55~\mu V$ from noise. Additionally, the classifier exhibited consistency with previous findings, demonstrating its ability to detect alternans with amplitudes around $50~\mu V$ . In conclusion, this study provides a spatial-temporal reference for proper evaluation of estimation methods, contributing to establishing a gold standard.

Background Electrical activity underlying the T-wave is less well understood than the QRS-complex. This study investigated the relationship between normal T-wave morphology and the underlying ventricular repolarization gradients using the equivalent dipole layer (EDL). Methods Body-surface-potential-maps (BSPM, 67‑leads) were obtained in nine normal cases. Subject specific MRI-based anatomical heart/torso-models with electrode positions were created. The boundary element method was used to account for the volume conductor effects. To simulate the measured T-waves, the EDL was used to apply different ventricular repolarization gradients: a) transmural, b) interventricular c) apico-basal and d) all three gradients (a-c) combined. The combined gradient (d) was optimized using an inverse procedure (Levenberg-Marquardt). Correspondence between simulated and measured T-waves was assessed using correlation coefficient (CC) and relative difference (RD). Results Realistic T-waves were simulated if repolarization times of: (a) the epicardium were smaller than the endocardium; (b) the left ventricle were smaller than the right ventricle and (c) the apex increased towards the base. The apico-basal gradient resulted in the highest correspondence between measured and simulated T-waves (CC = 0.84(0.81–0.91);RD = 0.68(0.60–0.71)) compared to a transmural gradient (CC = 0.77(0.71–0.80);RD = 1.46(0.82–1.75)) and an interventricular gradient (CC = 0.71(0.67–0.80);RD = 0.85(0.75–0.87)). All three gradients combined further improved the correspondence between measured and simulated T-waves (CC = 0.83(0.82–0.89);RD = 0.60(0.51–0.63)), especially after optimization (CC = 0.96(0.94–0.98);RD = 0.27(0.22–0.34)). Conclusion The application of all repolarization gradients combined resulted in the largest agreement between simulated and measured T-waves, followed by the apico-basal repolarization gradient. With these findings, we will optimize our EDL-based inverse procedure to assess repolarization abnormalities. [ABSTRACT FROM AUTHOR]

Background: Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo. Methods: CMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests. Results: 77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively). Conclusion: Our high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification. Clinical trial registration: Title: Multimorbidity Life-Course Approach to Myocardial Health—A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1 [ABSTRACT FROM AUTHOR]

Biventricular endocardial pacing (BiV-endo) and left bundle branch area pacing (LBBAP) are novel methods of delivering cardiac resynchronization therapy. These techniques are associated with improved activation times and acute hemodynamic response compared with conventional biventricular epicardial pacing (BiV-epi); however, the effects on repolarization and arrhythmic risk are unknown. The purpose of this study was to compare the effects of temporary BiV-epi, BiV-endo, and LBBAP on epicardial left ventricular (LV) repolarization using electrocardiographic imaging (ECGi). Eleven patients indicated for cardiac resynchronization therapy underwent a temporary pacing protocol with ECGi. BiV-endo was delivered via endocardial stimulation of the LV lateral wall. LBBAP was delivered by pacing the LV septum. Epicardial LV repolarization time (LVRT-95; time taken for 95% of the LV to repolarize), LV RT dispersion, mean LV activation recovery interval (ARI), LV ARI dispersion, and RT gradients were calculated. The protocol was completed in 10 patients. During LBBAP, there were significant reductions in LVRT-95 (94.9 ± 17.4 ms vs 125.0 ± 29.4 ms; P =.03) and LV RT dispersion (29.4 ± 6.3 ms vs 40.8 ± 11.4 ms; P =.015) compared with BiV-epi. In contrast, there were no significant differences between baseline, BiV-epi, or BiV-endo. There was a nonsignificant reduction in mean RT gradients between LBBAP and baseline rhythm (0.74 ± 0.22 ms/mm vs 1.01 ± 0.31 ms/mm; P =.07). There were no significant differences in mean LV ARI or LV ARI dispersion between groups. Temporary LBBAP reduces epicardial dispersion of repolarization compared with conventional BiV-epi. Further study is required to determine whether these repolarization changes on ECGi translate into a reduced risk of ventricular arrhythmia in clinical practice. [Display omitted] [ABSTRACT FROM AUTHOR]

The body surface electrocardiogram (ECG) is a direct result of electrical activity generated by the myocardium. Using the body surface ECGs to reconstruct cardiac electrical activity is called the inverse problem of electrocardiography. The method to solve the inverse problem depends on the chosen cardiac source model to describe cardiac electrical activity. In this paper, we describe the theoretical basis of two inverse methods based on the most commonly used cardiac source models: the epicardial potential model and the equivalent dipole layer model. We discuss similarities and differences in applicability, strengths and weaknesses and sketch a road towards improved inverse solutions by targeted use, sequential application or a combination of the two methods.

Aims To define a stepwise application of left bundle branch pacing (LBBP) criteria that will simplify implantation and guarantee electrical resynchronization. Left bundle branch pacing has emerged as an alternative to biventricular pacing. However, a systematic stepwise criterion to ensure electrical resynchronization is lacking. Methods and results A cohort of 24 patients from the LEVEL-AT trial (NCT04054895) who received LBBP and had electrocardiographic imaging (ECGI) at 45 days post-implant were included. The usefulness of ECG- and electrogram-based criteria to predict accurate electrical resynchronization with LBBP were analyzed. A two-step approach was developed. The gold standard used to confirm resynchronization was the change in ventricular activation pattern and shortening in left ventricular activation time, assessed by ECGI. Twenty-two (91.6%) patients showed electrical resynchronization on ECGI. All patients fulfilled pre-screwing requisites: lead in septal position in left-oblique projection and W paced morphology in V1. In the first step, presence of either right bundle branch conduction delay pattern (qR or rSR in V1) or left bundle branch capture Plus (QRS ≤120 ms) resulted in 95% sensitivity and 100% specificity to predict LBBP resynchronization, with an accuracy of 95.8%. In the second step, the presence of selective capture (100% specificity, only 41% sensitivity) or a spike-R <80 ms in non-selective capture (100% specificity, sensitivity 46%) ensured 100% accuracy to predict resynchronization with LBBP. Conclusion Stepwise application of ECG and electrogram criteria may provide an accurate assessment of electrical resynchronization with LBBP (Graphical abstract). [ABSTRACT FROM AUTHOR]

The inverse problem of electrocardiography or electrocardiographic imaging (ECGI) is a technique for reconstructing electrical information about cardiac surfaces from noninvasive or non-contact recordings. ECGI has been used to characterize atrial and ventricular arrhythmias. Although it is a technology with years of progress, its development to characterize atrial arrhythmias is challenging. Complications can arise when trying to describe the atrial mechanisms that lead to abnormal propagation patterns, premature or tachycardic beats, and reentrant arrhythmias. This review addresses the various ECGI methodologies, regularization methods, and post-processing techniques used in the atria, as well as the context in which they are used. The current advantages and limitations of ECGI in the fields of research and clinical diagnosis of atrial arrhythmias are outlined. In addition, areas where ECGI efforts should be concentrated to address the associated unsatisfied needs from the atrial perspective are discussed. [ABSTRACT FROM AUTHOR]

Background: Patients with ischemic cardiomyopathy, non-left bundle branch block (LBBB), or QRS duration <150msec have a lower response rate to CRT than other indicated patients. The EBS is a novel surface mapping system designed to measure electrical dyssynchrony via the standard deviation of the activation times (SDAT) of the left ventricle.Objective: To evaluate the efficacy of the ECG Belt System (EBS) in patients less likely to respond to cardiac resynchronization therapy (CRT) and determine whether EBS use in lead placement guidance and device programming was superior compared with standard CRT care.Methods: This was a prospective, randomized trial of heart failure patients with EBS-guided CRT implant and programming vs. standard CRT care. The primary endpoint was relative change in LV end-systolic volume from baseline to 6 months post-implant.Results: A total of 408 subjects from centers in Europe and North America were randomized. Although both EBS and control patients had a mean improvement in LVESV, there was no significant difference in relative change from baseline (p=0.26). While patients with a higher baseline SDAT derived greater LV reverse remodeling, improvement in electrical dyssynchrony did not correlate with the extent of reverse remodeling.Conclusion: The findings of the present study do not support EBS-guided therapy for CRT management of heart failure with reduced ejection fraction. [ABSTRACT FROM AUTHOR]

Aims Pacing remote from the latest electrically activated site (LEAS) in the left ventricle (LV) may diminish response to cardiac resynchronization therapy (CRT). We tested whether proximity of LV pacing site (LVPS) to LEAS, determined by non-invasive three-dimensional electrical activation mapping [electrocardiographic Imaging (ECGI)], increased likelihood of CRT response. Methods and results Consecutive CRT patients underwent ECGI and chest/heart computed tomography 6–24 months of post-implant. Latest electrically activated site and the distance to LVPS (dp) were assessed. Left ventricular end-systolic volume (LVESV) reduction of ≥15% at clinical follow-up defined response. Logistic regression probabilistically modelled non-response; variables included demographics, heart failure classification, left bundle branch block (LBBB), ischaemic heart disease (IHD), atrial fibrillation, QRS duration, baseline ejection fraction (EF) and LVESV, comorbidities, use of CRT optimization algorithm, angiotensin-converting enzyme inhibitor(ACE)/angiotensin-receptor blocker (ARB), beta-blocker, diuretics, and dp. Of 111 studied patients [64 ± 11 years, EF 28 ± 6%, implant duration 12 ± 5 months (mean ± SD), 98% had LBBB, 38% IHD], 67% responded at 10 ± 3 months post CRT-implant. Latest electrically activated sites were outside the mid-to-basal lateral segments in 35% of the patients. dp was 42 ± 23 mm [31 ± 14 mm for responders vs. 63 ± 24 mm non-responders (P < 0.001)]. Longer dp and the lack of use of CRT optimization algorithm were the only independent predictors of non-response [area under the curve (AUC) 0.906]. dp of 47 mm delineated responders and non-responders (AUC 0.931). Conclusion The distance between LV pacing site and latest electrical activation is a strong independent predictor for CRT response. Non-invasive electrical evaluation to characterize intrinsic activation and guide LV lead deployment may improve CRT efficacy. [ABSTRACT FROM AUTHOR]

Electrocardiographic Imaging is a non-invasive technique that requires cardiac Imaging for the reconstruction of cardiac electrical activity. In this study, we explored imageless ECGI by quantifying the errors of using heart meshes with either an inaccurate location inside the thorax or an inaccurate geometry. Multiple‑lead body surface recordings of 25 atrial fibrillation (AF) patients were recorded. Cardiac atrial meshes were obtained by segmentation of medical images obtained for each patient. ECGI was computed with each patient's segmented atrial mesh and compared with the ECGI obtained under errors in the atrial mesh used for ECGI estimation. We modeled both the uncertainty in the location of the atria inside the thorax by artificially translating the atria inside the thorax and the geometry of the atrial mesh by using an atrial mesh in a reference database. ECGI signals obtained with the actual meshes and the translated or estimated meshes were compared in terms of their correlation coefficients, relative difference measurement star, and errors in the dominant frequency (DF) estimation in epicardial nodes. CC between ECGI signals obtained after translating the actual atrial meshes from the original position by 1 cm was above 0.97. CC between ECGIs obtained with patient specific atrial geometry and estimated atrial geometries was 0.93 ± 0.11. Mean errors in DF estimation using an estimated atrial mesh were 7.6 ± 5.9%. Imageless ECGI can provide a robust estimation of cardiac electrophysiological parameters such as activation rates even during complex arrhythmias. Furthermore, it can allow more widespread use of ECGI in clinical practice. [ABSTRACT FROM AUTHOR]

The electrocardiogram (ECG) is the standard method in clinical practice to non-invasively analyze the electrical activity of the heart, from electrodes placed on the body's surface. The ECG can provide a cardiologist with relevant information to assess the condition of the heart and the possible presence of cardiac pathology. Nonetheless, the global view of the heart's electrical activity given by the ECG cannot provide fully detailed and localized information about abnormal electrical propagation patterns and corresponding substrates on the surface of the heart. Electrocardiographic imaging, also known as the inverse problem in electrocardiography, tries to overcome these limitations by non-invasively reconstructing the heart surface potentials, starting from the corresponding body surface potentials, and the geometry of the torso and the heart. This problem is ill-posed, and regularization techniques are needed to achieve a stable and accurate solution. The standard approach is to use zero-order Tikhonov regularization and the L-curve approach to choose the optimal value for the regularization parameter. However, different methods have been proposed for computing the optimal value of the regularization parameter. Moreover, regardless of the estimation method used, this may still lead to over-regularization or under-regularization. In order to gain a better understanding of the effects of the choice of regularization parameter value, in this study, we first focused on the regularization parameter itself, and investigated its influence on the accuracy of the reconstruction of heart surface potentials, by assessing the reconstruction accuracy with high-precision simultaneous heart and torso recordings from four dogs. For this, we analyzed a sufficiently large range of parameter values. Secondly, we evaluated the performance of five different methods for the estimation of the regularization parameter, also in view of the results of the first analysis. Thirdly, we investigated the effect of using a fixed value of the regularization parameter across all reconstructed beats. Accuracy was measured in terms of the quality of reconstruction of the heart surface potentials and estimation of the activation and recovery times, when compared with ground truth recordings from the experimental dog data. Results show that values of the regularization parameter in the range (0.01–0.03) provide the best accuracy, and that the three best-performing estimation methods (L-Curve, Zero-Crossing, and CRESO) give values in this range. Moreover, a fixed value of the regularization parameter could achieve very similar performance to the beat-specific parameter values calculated by the different estimation methods. These findings are relevant as they suggest that regularization parameter estimation methods may provide the accurate reconstruction of heart surface potentials only for specific ranges of regularization parameter values, and that using a fixed value of the regularization parameter may represent a valid alternative, especially when computational efficiency or consistency across time is required. [ABSTRACT FROM AUTHOR]

Biventricular endocardial pacing (BiV-endo) has demonstrated superior cardiac resynchronization compared to conventional biventricular epicardial pacing (BiV-epi). Left bundle branch area pacing (LBBAP) may also achieve effective cardiac resynchronization therapy (CRT). The purpose of this study was to compare the acute electrical and hemodynamic effects of BiV-epi, BiV-endo, and LBBAP delivered from the LV endocardium and to assess how myocardial scar affects response. Eleven patients with heart failure and indications for CRT underwent a temporary pacing study with electrocardiographic imaging (ECGi) and hemodynamic assessment. BiV-endo was delivered by stimulation of the left ventricular (LV) lateral wall, and LBBAP was delivered by stimulation of the LV septum, at the site of a Purkinje potential. LV activation time (LVAT-95), LV dyssynchrony index (LVDI), biventricular activation time (BIVAT-90), and biventricular dyssynchrony index (BIVDI) were calculated. Myocardial scar was assessed using magnetic resonance imaging (MRI). The protocol was completed in 10 patients. Compared to BiV-epi (LVAT-95: 79.2 ± 13.1 ms; LVDI: 26.6 ± 3.4 ms) LV resynchronization was superior during BiV-endo (LVAT-95: 48.5 ± 14.9 ms; P =.001; LVDI: 16.6 ± 6.4 ms; P =.002) and LBBAP (LVAT-95: 48.9 ± 12.5 ms; P =.001; LVDI: 15.3 ± 3.4 ms; P =.001). Biventricular resynchronization was similarly superior during BiV-endo and LBBAP vs BiV-epi (BIVAT-90 and BIVDI; P <.05). The rate of acute hemodynamic responders was higher during BiV-endo (90%) and LBBAP (70%) vs BiV-epi (50%). The benefits of LBBAP (but not BiV-endo) on LV resynchronization were attenuated when septal scar was present in a subset of 8 patients who underwent MRI. Our findings suggest superior electrical resynchronization and a higher proportion of acute hemodynamic responders during BiV-endo and LBBAP compared to BiV-epi. Electrical resynchronization was similar between BiV-endo and LBBAP; however, septal scar seemed to attenuate response to LBBAP. [Display omitted] [ABSTRACT FROM AUTHOR]

Aims Cardiac resynchronization therapy programmed to dynamically fuse pacing with intrinsic conduction using atrioventricular (AV) timing algorithms (e.g. SyncAV) has shown promise; however, mechanistic data are lacking. This study assessed the impact of SyncAV on electrical dyssynchrony across various pacing modalities using non-invasive epicardial electrocardiographic imaging (ECGi). Methods and results Twenty-five patients with left bundle-branch block (median QRS duration (QRSd) 162.7 ms) and intact AV conduction (PR interval 174.0 ms) were prospectively enrolled. ECGi was performed acutely during biventricular pacing with fixed nominal AV delays (BiV) and using SyncAV (optimized for the narrowest QRSd) during: BiV + SyncAV, LV-only single-site (LVSS + SyncAV), MultiPoint pacing (MPP + SyncAV), and LV-only MPP (LVMPP + SyncAV). Dyssynchrony was quantified via ECGi (LV activation time, LVAT; RV activation time, RVAT; LV electrical dispersion index, LVEDi; ventricular electrical uncoupling index, VEU; and biventricular total activation time, VVtat). Intrinsic conduction LVAT (124 ms) was significantly reduced by BiV pacing (109 ms) (P = 0.001) and further reduced by LVSS + SyncAV (103 ms), BiV + SyncAV (103 ms), LVMPP + SyncAV (95 ms), and MPP + SyncAV (90 ms). Intrinsic RVAT (93 ms), VVtat (130 ms), LVEDi (36 ms), VEU (50 ms), and QRSd (163 ms) were reduced by SyncAV across all pacing modes. More patients exhibited minimal LVAT, VVtat, LVEDi, and QRSd with MPP + SyncAV than any other modality. Conclusion Dynamic AV delay programming targeting fusion with intrinsic conduction significantly reduced dyssynchrony, as quantified by ECGi and QRSd for all evaluated pacing modes. MPP + SyncAV achieved the greatest synchrony overall but not for all patients, highlighting the value of pacing mode individualization during fusion optimization. [ABSTRACT FROM AUTHOR]

Abstract Background The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world’s longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46–the cardiac sub-study of the NSHD. Methods We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium. Discussion By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR–ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age. Trial registration: Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD).

Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECGI. [ABSTRACT FROM AUTHOR]

Background: In electrocardiographic imaging (ECGI), selecting an optimal regularization parameter (λ) is crucial for obtaining accurate inverse electrograms. The effects of signal and geometry uncertainties on the inverse problem regularization have not been thoroughly quantified, and there is no established methodology to identify when λ is sub-optimal due to these uncertainties. This study introduces a novel approach to λ selection using Tikhonov regularization and L-curve optimization, specifically addressing the impact of electrical noise in body surface potential map (BSPM) signals and geometrical inaccuracies in the cardiac mesh., Methods: Nineteen atrial simulations (5 of regular rhythms and 14 of atrial fibrillation) ensuring variability in substrate complexity and activation patterns were used for computing the ECGI with added white Gaussian noise from 40 dB to -3dB. Cardiac mesh displacements (1-3 cm) were applied to simulate the uncertainty of atrial positioning and study its impact on the L-curve shape. The regularization parameter, the maximum curvature, and the most horizontal angle of the L-curve (β) were quantified. In addition, BSPM signals from real patients were used to validate our findings., Results: The maximum curvature of the L-curve was found to be inversely related to signal-to-noise ratio and atrial positioning errors. In contrast, the β angle is directly related to electrical noise and remains unaffected by geometrical errors. Our proposed adjustment of λ, based on the β angle, provides a more reliable ECGI solution than traditional corner-based methods. Our findings have been validated with simulations and real patient data, demonstrating practical applicability., Conclusion: Adjusting λ based on the amount of noise in the data (or on the β angle) allows finding optimal ECGI solutions than a λ purely found at the corner of the L-curve. It was observed that the relevant information in ECGI activation maps is preserved even under the presence of uncertainties when the regularization parameter is correctly selected. The proposed criteria for regularization parameter selection have the potential to enhance the accuracy and reliability of ECGI solutions., Competing Interests: Declaration of competing interest M.S. Guillem. A.M. Climent. Are co-founders of Corify Care SL. R. Molero, J. Reventós-Presmanes, A.M. Climent. And M.S. Guillem get honorary from Corify Care SL. M.S. Guillem, L. Mont is shareholders of Corify Care SL. L. Mont reports honoraria as consultant, lecturer, and Advisory Board from Boston Scientific, Abbott Medical, Johnson & Johnson, and Medtronic. He is a shareholder of Galgo Medical SL. I. Roca-Luque has received honoraria as a lecturer and consultant from Abbott and Biosense Webster., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Obesity confers higher risks of cardiac arrhythmias. The extent to which weight loss reverses subclinical proarrhythmic adaptations in arrhythmia-free obese individuals is unknown., Objective: The purpose of this study was to study structural, electrophysiological, and autonomic remodeling in arrhythmia-free obese patients and their reversibility with bariatric surgery using electrocardiographic imaging (ECGi)., Methods: Sixteen arrhythmia-free obese patients (mean age 43 ± 12 years; 13 (81%) female participants; BMI 46.7 ± 5.5 kg/m 2 ) had ECGi pre-bariatric surgery, of whom 12 (75%) had ECGi postsurgery (BMI 36.8 ± 6.5 kg/m 2 ). Sixteen age- and sex-matched lean healthy individuals (mean age 42 ± 11 years; BMI 22.8 ± 2.6 kg/m 2 ) acted as controls and had ECGi only once., Results: Obesity was associated with structural (increased epicardial fat volumes and left ventricular mass), autonomic (blunted heart rate variability), and electrophysiological (slower atrial conduction and steeper ventricular repolarization time gradients) remodeling. After bariatric surgery, there was partial structural reverse remodeling, with a reduction in epicardial fat volumes (68.7 cm 3 vs 64.5 cm 3 ; P = .0010) and left ventricular mass (33 g/m 2.7 vs 25 g/m 2.7 ; P < .0005). There was also partial electrophysiological reverse remodeling with a reduction in mean spatial ventricular repolarization gradients (26 mm/ms vs 19 mm/ms; P = .0009), although atrial activation remained prolonged. Heart rate variability, quantified by standard deviation of successive differences in R-R intervals, was also partially improved after bariatric surgery (18.7 ms vs 25.9 ms; P = .017). Computational modeling showed that presurgical obese hearts had a larger window of vulnerability to unidirectional block and had an earlier spiral-wave breakup with more complex reentry patterns than did postsurgery counterparts., Conclusion: Obesity is associated with adverse electrophysiological, structural, and autonomic remodeling that is partially reversed after bariatric surgery. These data have important implications for bariatric surgery weight thresholds and weight loss strategies., Competing Interests: Disclosures The authors have no conflicts to disclose., (Copyright © 2024 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Objective. This study aims to assess the sensitivity of epicardial potential-based electrocardiographic imaging (ECGI) to the removal or interpolation of bad leads. Approach. We utilized experimental data from two distinct centers. Langendorff-perfused pig ( n = 2) and dog ( n = 2) hearts were suspended in a human torso-shaped tank and paced from the ventricles. Six different bad lead configurations were designed based on clinical experience. Five interpolation methods were applied to estimate the missing data. Zero-order Tikhonov regularization was used to solve the inverse problem for complete data, data with removed bad leads, and interpolated data. We assessed the quality of interpolated ECG signals and ECGI reconstructions using several metrics, comparing the performance of interpolation methods and the impact of bad lead removal versus interpolation on ECGI. Main results. The performance of ECG interpolation strongly correlated with ECGI reconstruction. The hybrid method exhibited the best performance among interpolation techniques, followed closely by the inverse-forward and Kriging methods. Bad leads located over high amplitude/high gradient areas on the torso significantly impacted ECGI reconstructions, even with minor interpolation errors. The choice between removing or interpolating bad leads depends on the location of missing leads and confidence in interpolation performance. If uncertainty exists, removing bad leads is the safer option, particularly when they are positioned in high amplitude/high gradient regions. In instances where interpolation is necessary, the inverse-forward and Kriging methods, which do not require training, are recommended. Significance. This study represents the first comprehensive evaluation of the advantages and drawbacks of interpolating versus removing bad leads in the context of ECGI, providing valuable insights into ECGI performance., (Creative Commons Attribution license.)

Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.

Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF). Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh. Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients. Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm. [ABSTRACT FROM AUTHOR]

Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sudden cardiac arrest survivors undergo extensive clinical testing, with a growing role for multimodality imaging, before diagnosing "idiopathic" ventricular fibrillation. Multimodality imaging, considered as using multiple imaging modalities as diagnostics, is important for revealing structural myocardial abnormalities in patients with cardiac arrest. This review focuses on combining imaging modalities (echocardiography, cardiac magnetic resonance and computed tomography) and the electrocardiographic characterization of sudden cardiac arrest survivors and discusses the surplus value of multimodality imaging in the diagnostic routing of these patients. We focus on novel insights obtained through electrostructural and/or electromechanical imaging in apparently idiopathic ventricular fibrillation patients, with special attention to non-invasive electrocardiographic imaging. [ABSTRACT FROM AUTHOR]

Background: Brugada syndrome (BrS) is caused by mutations in SCN5A gene in 15%-20% of cases. Previous studies showed worse prognosis in SCN5A mutation carriers (SCN5A+). To date, there are no data on genotype-phenotype correlation with electrocardiographic (ECG) imaging (ECGI) and high-density epicardial electroanatomic map.Objective: This study aimed to correlate SCN5A mutation with substrate severity in BrS assessed by ECGI and high-density electroanatomic map.Methods: All consecutive BrS patients undergoing ECGI and high-density epicardial electroanatomic map with HD Grid Mapping Catheter were retrospectively analyzed. On ECGI, the following parameters were analyzed before and after ajmaline administration: right ventricular outflow tract (RVOT) activation time (RVOT-AT) and RVOT recovery time (RVOT-RT). On electroanatomic map, the parameters analyzed before and after ajmaline were high-frequency potential activation time (HFPat), high-frequency potential duration (HFPd), high-frequency potential amplitude (HFPa), low-frequency potential activation time (LFPat), low-frequency potential duration (LFPd), and low-frequency potential amplitude (LFPa).Results: Thirty-nine BrS patients with ECGI were included. Eight patients (20.5%) were SCN5A+. At baseline ECGI map, mean RVOT-RT was longer in SCN5A+ (P = .024). After ajmaline administration, SCN5A+ patients showed longer RVOT-AT (125.6 vs 100.8 ms; P = .045) and longer RVOT-RT (426.4 vs 397 ms; P = .033). After ajmaline administration, SCN5A+ showed longer HFPat (164.1 vs 119.5 ms; P = .041); longer LFPat (272.7 vs 200.5 ms; P = .018); and longer LFPd (211.9 vs 151.2 ms; P = .033).Conclusion: In BrS, SCN5A+ patients compared with SCN5A- patients exhibit marked depolarization and repolarization abnormalities as assessed by ECGI and epicardial high-density electroanatomic map. [ABSTRACT FROM AUTHOR]

Background: Adaptive cardiac resynchronization therapy (aCRT) is known to have clinical benefits over conventional CRT, but the mechanisms are unclear. Objective: Compare effects of aCRT and conventional CRT on electrical dyssynchrony. Methods: A prospective, double-blind, 1:1 parallel-group assignment randomized controlled trial in patients receiving CRT for routine clinical indications. Participants underwent cardiac computed tomography and 128-electrode body surface mapping. The primary outcome was change in electrical dyssynchrony measured on the epicardial surface using noninvasive electrocardiographic imaging before and 6 months post-CRT. Ventricular electrical uncoupling (VEU) was calculated as the difference between the mean left ventricular (LV) and right ventricular (RV) activation times. An electrical dyssynchrony index (EDI) was computed as the standard deviation of local epicardial activation times. Results: We randomized 27 participants (aged 64 ± 12 years; 34% female; 53% ischemic cardiomyopathy; LV ejection fraction 28% ± 8%; QRS duration 155 ± 21 ms; typical left bundle branch block [LBBB] in 13%) to conventional CRT (n = 15) vs aCRT (n = 12). In atypical LBBB (n = 11; 41%) with S waves in V5-V6, conduction block occurred in the anterior RV, as opposed to the interventricular groove in strict LBBB. As compared to baseline, VEU reduced post-CRT in the aCRT (median reduction 18.9 [interquartile range 4.3–29.2 ms; P = .034]), but not in the conventional CRT (21.4 [-30.0 to 49.9 ms; P = .525]) group. There were no differences in the degree of change in VEU and EDI indices between treatment groups. Conclusion: The effect of aCRT and conventional CRT on electrical dyssynchrony is largely similar, but only aCRT harmoniously reduced interventricular dyssynchrony by reducing RV uncoupling.

The article argues on the non-consistent benefit from conduction system pacing over cardiac resynchronization therapy (CRT) in restoring myocardium conduction through the His-Purkinje system pacing and suggests the need to personalize therapy. It recognizes the usefulness of computational modeling and suggests personalization of CRT strategy using the presence of left ventricular (LV) scar and its location assessed with late gadolinium enhancement magnetic resonance imaging.

Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF).Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh.Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients.Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm.

Purpose: Cardiac resynchronization therapy (CRT) reduces ventricular activation times and electrical dyssynchrony, however the effect on repolarization is unclear. In this study, we sought to investigate the effect of CRT and left ventricular (LV) remodeling on dispersion of repolarization using electrocardiographic imaging (ECGi).Methods: 11 patients with heart failure and electrical dyssynchrony underwent ECGi 1-day and 6-months post CRT. Reconstructed epicardial electrograms were used to create maps of activation time, repolarization time (RT) and activation recovery intervals (ARI) and calculate measures of RT, ARI and their dispersion. ARI was corrected for heart rate (cARI).Results: Compared to baseline rhythm, LV cARI dispersion was significantly higher at 6 months (28.2 ± 7.7 vs 36.4 ± 7.2 ms; P = 0.03) but not after 1 day (28.2 ± 7.7 vs 34.4 ± 6.8 ms; P = 0.12). There were no significant differences from baseline to CRT for mean LV cARI or RT metrics. Significant LV remodeling (>15% reduction in end-systolic volume) was an independent predictor of increase in LV cARI dispersion (P = 0.04) and there was a moderate correlation between the degree of LV remodeling and the relative increase in LV cARI dispersion (R = -0.49) though this was not statistically significant (P = 0.12).Conclusion: CRT increases LV cARI dispersion, but this change was not fully apparent until 6 months post implant. The effects of CRT on LV cARI dispersion appeared to be dependent on LV reverse remodeling, which is in keeping with evidence that the risk of ventricular arrhythmia after CRT is higher in non-responders compared to responders. [ABSTRACT FROM AUTHOR]

Background: The life course accumulation of overt and subclinical myocardial dysfunction contributes to older age mortality, frailty, disability and loss of independence. The Medical Research Council National Survey of Health and Development (NSHD) is the world's longest running continued surveillance birth cohort providing a unique opportunity to understand life course determinants of myocardial dysfunction as part of MyoFit46-the cardiac sub-study of the NSHD.Methods: We aim to recruit 550 NSHD participants of approximately 75 years+ to undertake high-density surface electrocardiographic imaging (ECGI) and stress perfusion cardiovascular magnetic resonance (CMR). Through comprehensive myocardial tissue characterization and 4-dimensional flow we hope to better understand the burden of clinical and subclinical cardiovascular disease. Supercomputers will be used to combine the multi-scale ECGI and CMR datasets per participant. Rarely available, prospectively collected whole-of-life data on exposures, traditional risk factors and multimorbidity will be studied to identify risk trajectories, critical change periods, mediators and cumulative impacts on the myocardium.Discussion: By combining well curated, prospectively acquired longitudinal data of the NSHD with novel CMR-ECGI data and sharing these results and associated pipelines with the CMR community, MyoFit46 seeks to transform our understanding of how early, mid and later-life risk factor trajectories interact to determine the state of cardiovascular health in older age.Trial Registration: Prospectively registered on ClinicalTrials.gov with trial ID: 19/LO/1774 Multimorbidity Life-Course Approach to Myocardial Health- A Cardiac Sub-Study of the MCRC National Survey of Health and Development (NSHD). [ABSTRACT FROM AUTHOR]

Background: The pathogenesis of Brugada syndrome (BrS) and consequently of abnormal electrograms (aEGMs) found in the epicardium of the right ventricular outflow tract (RVOT-EPI) is controversial.Objective: The purpose of this study was to analyze aEGM from high-density RVOT-EPI electroanatomic mapping (EAM).Methods: All patients undergoing RVOT-EPI EAM with the HD-Grid catheter for BrS were retrospectively included. Maps were acquired before and after ajmaline, and all patients had concomitant noninvasive electrocardiographic imaging with annotation of RVOT-EPI latest activation time (RVOTat). High-frequency potentials (HFPs) were defined as ventricular potentials occurring during or after the far-field ventricular EGM showing a local activation time (HFPat). Low-frequency potentials (LFPs) were defined as aEGMs occurring after near-field ventricular activation showing fractionation or delayed components. Their activation time from surface ECG was defined as LFPat.Results: Fifteen consecutive patients were included in the study. At EAM before ajmaline, 7 patients (46.7%) showed LFPs. All patients showed HFPs before and after ajmaline and LFPs after ajmaline. Mean HFPat (134.4 vs 65.3 ms, P <.001), mean LFPat (224.6 vs 113.6 ms, P <.001), and mean RVOTat (124.8 vs 55.9 ms, P <.001) increased after ajmaline. RVOTat correlated with HFPat before (ρ = 0.76) and after ajmaline (ρ = 0.82), while RVOTat was shorter than LFPat before (P <.001) and after ajmaline (P <.001). BrS patients with history of aborted sudden cardiac death had longer aEGMs after ajmaline.Conclusion: Two different types of aEGMs are described from BrS high-density epicardial mapping. This might correlate with depolarization and repolarization abnormalities. [ABSTRACT FROM AUTHOR]

Inverse electrocardiography (iECG) estimates epi- and endocardial electrical activity from body surface potentials maps (BSPM). In individuals at risk for cardiomyopathy, non-invasive estimation of normal ventricular activation may provide valuable information to aid risk stratification to prevent sudden cardiac death. However, multiple simultaneous activation wavefronts initiated by the His-Purkinje system, severely complicate iECG. To improve the estimation of normal ventricular activation, the iECG method should accurately mimic the effect of the His-Purkinje system, which is not taken into account in the previously published multi-focal iECG. Therefore, we introduce the novel multi-wave iECG method and report on its performance. Multi-wave iECG and multi-focal iECG were tested in four patients undergoing invasive electro-anatomical mapping during normal ventricular activation. In each subject, 67-electrode BSPM were recorded and used as input for both iECG methods. The iECG and invasive local activation timing (LAT) maps were compared. Median epicardial inter-map correlation coefficient (CC) between invasive LAT maps and estimated multi-wave iECG versus multi-focal iECG was 0.61 versus 0.31. Endocardial inter-map CC was 0.54 respectively 0.22. Modeling the His-Purkinje system resulted in a physiologically realistic and robust non-invasive estimation of normal ventricular activation, which might enable the early detection of cardiac disease during normal sinus rhythm. [ABSTRACT FROM AUTHOR]

Objective: To promote the effectiveness in measuring high-density body surface potentials (BSPs) and optimize the clinical application of electrocardiographic imaging (ECGI) to identify atrial fibrillation (AF) drivers, it is essential to identify a minimal electrode number., Methods: This study included 24 participants with paroxysmal or persistent AF. We compared the reconstructed entropy maps and epicardial potential maps using 10 different electrode counts, ranging from 12 to 128, to determine the minimum necessary number of electrodes. A novel atrial activity extraction method and an improved spectral clustering technique were designed to intelligently identify electrode locations from the 128 evenly distributed electrodes., Results: For patients with persistent AF, the correlation coefficient (CC) of the reconstructed potential maps ranged from 0.72 to 0.99, and the structural similarity index (SSIM) >0.90 when the number of electrodes was ≥64. For patients with paroxysmal AF, the CC ranged from 0.85 to 0.99 and the SSIM≥0.90 when the number of electrodes was ≥48. Across all 24 AF patients, when electrode numbers were ≥64, the mean ± standard deviation of the CC between pairwise potential maps was >0.93 ± 0.06. Electrode placement on the upper anterior and posterior regions of the torso, above the sixth intercostal septum, was found to be advantageous for capturing atrial electrical activity conducive to identifying AF drivers., Conclusion: For patients with persistent AF, ≥64 electrodes are recommended. For patients with paroxysmal AF, ≥48 electrodes are recommended., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The electrocardiogram (ECG) is the standard method in clinical practice to non-invasively analyze the electrical activity of the heart, from electrodes placed on the body’s surface. The ECG can provide a cardiologist with relevant information to assess the condition of the heart and the possible presence of cardiac pathology. Nonetheless, the global view of the heart’s electrical activity given by the ECG cannot provide fully detailed and localized information about abnormal electrical propagation patterns and corresponding substrates on the surface of the heart. Electrocardiographic imaging, also known as the inverse problem in electrocardiography, tries to overcome these limitations by non-invasively reconstructing the heart surface potentials, starting from the corresponding body surface potentials, and the geometry of the torso and the heart. This problem is ill-posed, and regularization techniques are needed to achieve a stable and accurate solution. The standard approach is to use zero-order Tikhonov regularization and the L-curve approach to choose the optimal value for the regularization parameter. However, different methods have been proposed for computing the optimal value of the regularization parameter. Moreover, regardless of the estimation method used, this may still lead to over-regularization or under-regularization. In order to gain a better understanding of the effects of the choice of regularization parameter value, in this study, we first focused on the regularization parameter itself, and investigated its influence on the accuracy of the reconstruction of heart surface potentials, by assessing the reconstruction accuracy with high-precision simultaneous heart and torso recordings from four dogs. For this, we analyzed a sufficiently large range of parameter values. Secondly, we evaluated the performance of five different methods for the estimation of the regularization parameter, also in view of the results of the first analysis. Thirdly, we investigated the effect of using a fixed value of the regularization parameter across all reconstructed beats. Accuracy was measured in terms of the quality of reconstruction of the heart surface potentials and estimation of the activation and recovery times, when compared with ground truth recordings from the experimental dog data. Results show that values of the regularization parameter in the range (0.01–0.03) provide the best accuracy, and that the three best-performing estimation methods (L-Curve, Zero-Crossing, and CRESO) give values in this range. Moreover, a fixed value of the regularization parameter could achieve very similar performance to the beat-specific parameter values calculated by the different estimation methods. These findings are relevant as they suggest that regularization parameter estimation methods may provide the accurate reconstruction of heart surface potentials only for specific ranges of regularization parameter values, and that using a fixed value of the regularization parameter may represent a valid alternative, especially when computational efficiency or consistency across time is required.

Introduction: Patients with hypertrophic cardiomyopathy (HCM) are at risk for lethal ventricular arrhythmia, but the electrophysiological substrate behind this is not well-understood. We used non-invasive electrocardiographic imaging to characterize patients with HCM, including cardiac arrest survivors. Methods: HCM patients surviving ventricular fibrillation or hemodynamically unstable ventricular tachycardia (n = 17) were compared to HCM patients without a personal history of potentially lethal arrhythmia (n = 20) and a pooled control group with structurally normal hearts. Subjects underwent exercise testing by non-invasive electrocardiographic imaging to estimate epicardial electrophysiology. Results: Visual inspection of reconstructed epicardial HCM maps revealed isolated patches of late activation time (AT), prolonged activation-recovery intervals (ARIs), as well as reversal of apico-basal trends in T-wave inversion and ARI compared to controls ( p < 0.005 for all). AT and ARI were compared between groups. The pooled HCM group had longer mean AT (60.1 ms vs. 52.2 ms, p < 0.001), activation dispersion (55.2 ms vs. 48.6 ms, p = 0.026), and mean ARI (227 ms vs. 217 ms, p = 0.016) than structurally normal heart controls. HCM ventricular arrhythmia survivors could be differentiated from HCM patients without a personal history of life-threatening arrhythmia by longer mean AT (63.2 ms vs. 57.4 ms, p = 0.007), steeper activation gradients (0.45 ms/mm vs. 0.36 ms/mm, p = 0.011), and longer mean ARI (234.0 ms vs. 221.4 ms, p = 0.026). A logistic regression model including whole heart mean activation time and activation recovery interval could identify ventricular arrhythmia survivors from the HCM cohort, producing a C statistic of 0.76 (95% confidence interval 0.72-0.81), with an optimal sensitivity of 78.6% and a specificity of 79.8%. Discussion: The HCM epicardial electrotype is characterized by delayed, dispersed conduction and prolonged, dispersed activation-recovery intervals. Combination of electrophysiologic measures with logistic regression can improve differentiation over single variables. Future studies could test such models prospectively for risk stratification of sudden death due to HCM., Competing Interests: Medtronic has not influenced or sponsored any of the research here but has provided speaker fees to PK for a topic unrelated to this work. Imperial Innovations holds the patent for the intellectual property of the Ventricular Conduction Stability algorithm on behalf of the authors MS-S, KL, FN, AV, DF, and PK. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationship that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Chow, Leong, Shun-Shin, Jones, Guttmann, Mohiddin, Lambiase, Elliott, Ormerod, Koa-Wing, Lefroy, Lim, Linton, Ng, Qureshi, Whinnett, Peters, Francis, Varnava and Kanagaratnam.)

Background: Leadless cardiac resynchronization therapy (CRT) is an emerging heart failure treatment. An implanted electrode delivers lateral or septal endocardial left ventricular (LV) pacing (LVP) upon detection of a right ventricular (RV) pacing stimulus from a coimplanted device, thus generating biventricular pacing (BiVP). Electrical efficacy data regarding this therapy, particularly leadless LV septal pacing (LVSP) for potential conduction system capture, are limited., Objectives: The purpose of this study was to evaluate the acute performance of leadless CRT using electrocardiographic imaging (ECGi) and assess the optimal pacing modality (OPM) of LVSP on the basis of RV and LV activation., Methods: Ten WiSE-CRT recipients underwent an ECGi study testing: RV pacing, BiVP, LVP only, and LVP with an optimized atrioventricular delay (LV-OPT). BiV, LV, and RV activation times (shortest time taken to activate 90% of the ventricles [BIVAT-90], shortest time taken to activate 95% of the LV, and shortest time taken to activate 90% of the RV) plus LV and BiV dyssynchrony index (standard deviation of LV activation times and standard deviation of all activation times) were calculated from reconstructed epicardial electrograms. The individual OPM yielding the greatest improvement from baseline was determined., Results: BiVP generated a 23.7% improvement in BiVAT-90 ( P  = .002). An improvement of 43.3% was observed at the OPM ( P = .0001), primarily through reductions in shortest time taken to activate 90% of the RV. At the OPM, BiVAT-90 improved in patients with lateral (43.3%; P = .0001; n = 5) and septal (42.4%; P = .009; n = 5) LV implants. The OPM varied by individual. LVP and LV-OPT were mostly superior in patients with LVSP, and in those with sinus rhythm and left bundle branch block (n = 4)., Conclusion: Leadless CRT significantly improves acute ECGi-derived activation and dyssynchrony metrics. Using an individualized OPM improves efficacy in selected patients. Effective LVSP is feasible, with fusion pacing at LV-OPT mitigating the potential deleterious effects on RV activation., (© 2024 Heart Rhythm Society. Published by Elsevier Inc.)

Aims: Electrocardiographic imaging (ECGi) and the ECG belt are body surface potential mapping systems which can assess electrical dyssynchrony in patients undergoing cardiac resynchronization therapy (CRT). ECGi-derived dyssynchrony metrics are calculated from reconstructed epicardial potentials based on body surface potentials combined with a thoracic CT scan, while the ECG belt relies on body surface potentials alone. The relationship between dyssynchrony metrics from these two systems is unknown. In this study we aim to compare intra-ventricular and inter-ventricular dyssynchrony metrics between ECGi and the ECG belt.Methods: Seventeen patients underwent ECGi after CRT. A subsample of 40 body surface potentials was used to simulate the ECG belt. ECGi dyssynchrony metrics, calculated from reconstructed epicardial potentials, and ECG belt dyssynchrony metrics, calculated from the sampled body surface potentials were compared.Results: There was a strong positive correlation between ECGi left ventricular activation time (LVAT) and ECG belt left thorax activation time (LTAT) (R = 0.88 ; P < 0.001) and between ECGi standard deviation of activation times (SDAT) and ECG belt-SDAT (R = 0.76; P < 0.001) during intrinsic rhythm. The correlation for both pairs was also strong during biventricular pacing. Ventricular electrical uncoupling, a well validated ECGi inter-ventricular dyssynchrony metric, correlated strongly with ECG belt-SDAT during intrinsic rhythm (R = 0.76; P < 0.001) but not biventricular pacing (R = 0.29; P = 0.26). Cranial or caudal displacement of the simulated ECG belt did not affect LTAT or SDAT.Conclusion: ECGi- and ECG belt-derived intra-ventricular and inter-ventricular dyssynchrony metrics were strongly correlated. The ECG belt may offer comparable dyssynchrony assessment to ECGi, with associated practical and cost advantages. [ABSTRACT FROM AUTHOR]

The article presents a case study of a 24-years-old man with a family history of sudden death was scheduled for sudden cardiac death screening at our Center after an episode of syncope. Topics include the alterations related to generation and/or conduction of action potentials in the cardiac tissue can result in the origin and propagation of cardiac arrhythmias, and the heritable mutations in genes that encode heart ion channels are the underlying cause of arrhythmias.

Background Dispersion and gradients in repolarization have been associated with life‐threatening arrhythmias, but are difficult to quantify precisely from surface electrocardiography. The objective of this study was to evaluate electrocardiographic imaging (ECGI) to noninvasively detect repolarization‐based abnormalities. Methods and Results Ex vivo data were obtained from Langendorff‐perfused pig hearts (n=8) and a human donor heart. Unipolar electrograms were recorded simultaneously during sinus rhythm from an epicardial sock and the torso‐shaped tank within which the heart was suspended. Regional repolarization heterogeneities were introduced through perfusion of dofetilide and pinacidil into separate perfusion beds. In vivo data included torso and epicardial potentials recorded simultaneously in anesthetized, closed‐chest pigs (n=5), during sinus rhythm, and ventricular pacing. For both data sets, ECGI accurately reconstructed T‐wave electrogram morphologies when compared with those recorded by the sock (ex vivo: correlation coefficient, 0.85 [0.52–0.96], in vivo: correlation coefficient, 0.86 [0.52–0.96]) and repolarization time maps (ex‐vivo: correlation coefficient, 0.73 [0.63–0.83], in vivo: correlation coefficient, 0.76 [0.67–0.82]). ECGI‐reconstructed repolarization time distributions were strongly correlated to those measured by the sock (both data sets, R2 ≥0.92). Although the position of the gradient was slightly shifted by 8.3 (0–13.9) mm, the mean, max, and SD between ECGI and recorded gradient values were highly correlated (R2=0.87, 0.75, and 0.86 respectively). There was no significant difference in ECGI accuracy between ex vivo and in vivo data. Conclusions ECGI reliably and accurately maps potentially critical repolarization abnormalities. This noninvasive approach allows imaging and quantifying individual parameters of abnormal repolarization‐based substrates in patients with arrhythmogenesis, to improve diagnosis and risk stratification.

Electrocardiographic imaging (ECGI) is a technique to reconstruct non-invasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regarding atrial fibrillation (AF), the characterization of the electrical propagation and the underlying substrate favoring AF is inherently more challenging than for ventricular arrhythmias, due to the progressive and heterogeneous nature of the disease and its manifestation, the small volume and wall thickness of the atria, and the relatively large role of microstructural abnormalities in AF. At the same time, ECGI has the advantage over other mapping technologies of allowing a global characterization of atrial electrical activity at every atrial beat and non-invasively. However, since ECGI is time-consuming and costly and the use of electrical mapping to guide AF ablation is still not fully established, the clinical value of ECGI for AF is still under assessment. Nonetheless, AF is known to be the manifestation of a complex interaction between electrical and structural abnormalities and therefore, true electro-anatomical-structural imaging may elucidate important key factors of AF development, progression, and treatment. Therefore, it is paramount to identify which clinical questions could be successfully addressed by ECGI when it comes to AF characterization and treatment, and which questions may be beyond its technical limitations. In this manuscript we review the questions that researchers have tried to address on the use of ECGI for AF characterization and treatment guidance (for example, localization of AF triggers and sustaining mechanisms), and we discuss the technological requirements and validation. We address experimental and clinical results, limitations, and future challenges for fruitful application of ECGI for AF understanding and management. We pay attention to existing techniques and clinical application, to computer models and (animal or human) experiments, to challenges of methodological and clinical validation. The overall objective of the study is to provide a consensus on valuable directions that ECGI research may take to provide future improvements in AF characterization and treatment guidance.