Assessment of ventricular electrical heterogeneity in left bundle branch pacing and left ventricular septal pacing by using various electrophysiological methods.

INTRODUCTION: Left bundle branch area pacing (LBBAP) comprises pacing at the left ventricular septum (LVSP) or left bundle branch (LBBP). The aim of the present study was to investigate the differences in ventricular electrical heterogeneity between LVSP, LBBP, right ventricular pacing (RVP) and intrinsic conduction with different dyssynchrony measures using the ECG, vectorcardiograpy, ECG belt, and Ultrahigh frequency (UHF-)ECG. METHODS: Thirty-seven patients with a pacemaker indication for bradycardia or cardiac resynchronization therapy underwent LBBAP implantation. ECG, vectorcardiogram, ECG belt and UHF-ECG signals were recorded during RVP, LVSP and LBBP, and intrinsic activation. QRS duration (QRSd) was measured from the ECG, QRS area was calculated from the vectorcardiogram, LV activation time (LVAT) and standard deviation of activation time (SDAT) from ECG belt and electrical dyssynchrony (e-DYS16) from UHF-ECG. RESULTS: Both LVSP and LBBP significantly reduced ventricular electrical heterogeneity as compared to underlying LBBB and RV pacing in terms of QRS area (p < .001), SDAT (p < .001), LVAT (p < .001) and e-DYS16 (p < .001). QRSd was only reduced as compared to RV pacing(p < .001). QRS area was similar during LBBP and normal intrinsic conduction, e-DYS16 was similar during LVSP and normal intrinsic conduction, whereas SDAT was similar for LVSP, LBBP and normal intrinsic conduction. For all these variables there was no significant difference between LVSP and LBBP. CONCLUSION: Both LVSP and LBBP resulted in a more synchronous LV activation than LBBB and RVP. Especially LBBP resulted in levels of LV synchrony comparable to normal intrinsic conduction.

Quantification of left ventricular myocardial strain: Comparison between MRI tagging, MRI feature tracking, and ultrasound speckle tracking.

Ultrasound speckle tracking is frequently used to quantify myocardial strain, and magnetic resonance imaging (MRI) feature tracking is rapidly gaining interest. Our aim is to validate cardiac MRI feature tracking by comparing it with the gold standard method (i.e., MRI tagging) in healthy subjects and patients. Furthermore, we aim to perform an indirect validation by comparing ultrasound speckle tracking with MRI feature tracking. Forty-two subjects (17 formerly preeclamptic women, three healthy women, and 22 left bundle branch block patients of both sexes) received 3-T cardiac MRI and echocardiography. Cine and tagged MRI, and B-mode ultrasound images, were acquired. Intrapatient global and segmental left ventricular circumferential (MRI tagging vs. MRI feature tracking) and longitudinal (MRI feature tracking vs. ultrasound speckle tracking) peak strain and time to peak strain were compared between the three techniques. Intraclass correlation coefficient (ICC) (< 0.50 = poor, 0.50-0.75 = moderate, > 0.75-0.90 = good, > 0.90 = excellent) and Bland-Altman analysis were used to assess correlation and bias; p less than 0.05 indicates a significant ICC or bias. Global peak strain parameters showed moderate-to-good correlations between methods (ICC = 0.71-0.83, p < 0.01) with no significant biases. Global time to peak strain parameters showed moderate-to-good correlations (ICC = 0.56-0.82, p < 0.01) with no significant biases. Segmental peak strains showed significant biases in all parameters and moderate-to-good correlation (ICC = 0.62-0.77, p < 0.01), except for lateral longitudinal peak strain (ICC = 0.23, p = 0.22). Segmental time to peak strain parameters showed moderate-to-good correlation (ICC = 0.58-0.74, p < 0.01) with no significant biases. MRI feature tracking is a valid method to examine myocardial strain, but there is bias in absolute segmental strain values between imaging techniques. MRI feature tracking shows adequate comparability with ultrasound speckle tracking.

Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy.

AIMS: This study aims to identify and visualize electrocardiogram (ECG) features using an explainable deep learning-based algorithm to predict cardiac resynchronization therapy (CRT) outcome. Its performance is compared with current guideline ECG criteria and QRSAREA. METHODS AND RESULTS: A deep learning algorithm, trained on 1.1 million ECGs from 251 473 patients, was used to compress the median beat ECG, thereby summarizing most ECG features into only 21 explainable factors (FactorECG). Pre-implantation ECGs of 1306 CRT patients from three academic centres were converted into their respective FactorECG. FactorECG predicted the combined clinical endpoint of death, left ventricular assist device, or heart transplantation [c-statistic 0.69, 95% confidence interval (CI) 0.66-0.72], significantly outperforming QRSAREA and guideline ECG criteria [c-statistic 0.61 (95% CI 0.58-0.64) and 0.57 (95% CI 0.54-0.60), P < 0.001 for both]. The addition of 13 clinical variables was of limited added value for the FactorECG model when compared with QRSAREA (Δ c-statistic 0.03 vs. 0.10). FactorECG identified inferolateral T-wave inversion, smaller right precordial S- and T-wave amplitude, ventricular rate, and increased PR interval and P-wave duration to be important predictors for poor outcome. An online visualization tool was created to provide interactive visualizations (https://crt.ecgx.ai). CONCLUSION: Requiring only a standard 12-lead ECG, FactorECG held superior discriminative ability for the prediction of clinical outcome when compared with guideline criteria and QRSAREA, without requiring additional clinical variables. End-to-end automated visualization of ECG features allows for an explainable algorithm, which may facilitate rapid uptake of this personalized decision-making tool in CRT.

Comparison of the relation of the ESC 2021 and ESC 2013 definitions of left bundle branch block with clinical and echocardiographic outcome in cardiac resynchronization therapy.

INTRODUCTION: We aimed to investigate the impact of the 2021 European Society of Cardiology (ESC) guideline changes in left bundle branch block (LBBB) definition on cardiac resynchronization therapy (CRT) patient selection and outcomes. METHODS: The MUG (Maastricht, Utrecht, Groningen) registry, consisting of consecutive patients implanted with a CRT device between 2001 and 2015 was studied. For this study, patients with baseline sinus rhythm and QRS duration ≥ 130ms were eligible. Patients were classified according to ESC 2013 and 2021 guideline LBBB definitions and QRS duration. Endpoints were heart transplantation, LVAD implantation or mortality (HTx/LVAD/mortality) and echocardiographic response (LVESV reduction ≥15%). RESULTS: The analyses included 1.202, typical CRT patients. The ESC 2021 definition resulted in considerably less LBBB diagnoses compared to the 2013 definition (31.6% vs. 80.9%, respectively). Applying the 2013 definition resulted in significant separation of the Kaplan-Meier curves of HTx/LVAD/mortality (p < .0001). A significantly higher echocardiographic response rate was found in the LBBB compared to the non-LBBB group using the 2013 definition. These differences in HTx/LVAD/mortality and echocardiographic response were not found when applying the 2021 definition. CONCLUSION: The ESC 2021 LBBB definition leads to a considerably lower percentage of patients with baseline LBBB then the ESC 2013 definition. This does not lead to better differentiation of CRT responders, nor does this lead to a stronger association with clinical outcomes after CRT. In fact, stratification according to the 2021 definition is not associated with a difference in clinical or echocardiographic outcome, implying that the guideline changes may negatively influence CRT implantation practice with a weakened recommendation in patients that will benefit from CRT.

Comparison of novel ventricular pacing strategies using an electro-mechanical simulation platform.

AIMS: Focus of pacemaker therapy is shifting from right ventricular (RV) apex pacing (RVAP) and biventricular pacing (BiVP) to conduction system pacing. Direct comparison between the different pacing modalities and their consequences to cardiac pump function is difficult, due to the practical implications and confounding variables. Computational modelling and simulation provide the opportunity to compare electrical, mechanical, and haemodynamic consequences in the same virtual heart. METHODS AND RESULTS: Using the same single cardiac geometry, electrical activation maps following the different pacing strategies were calculated using an Eikonal model on a three-dimensional geometry, which were then used as input for a lumped mechanical and haemodynamic model (CircAdapt). We then compared simulated strain, regional myocardial work, and haemodynamic function for each pacing strategy. Selective His-bundle pacing (HBP) best replicated physiological electrical activation and led to the most homogeneous mechanical behaviour. Selective left bundle branch (LBB) pacing led to good left ventricular (LV) function but significantly increased RV load. RV activation times were reduced in non-selective LBB pacing (nsLBBP), reducing RV load but increasing heterogeneity in LV contraction. LV septal pacing led to a slower LV and more heterogeneous LV activation than nsLBBP, while RV activation was similar. BiVP led to a synchronous LV-RV, but resulted in a heterogeneous contraction. RVAP led to the slowest and most heterogeneous contraction. Haemodynamic differences were small compared to differences in local wall behaviour. CONCLUSION: Using a computational modelling framework, we investigated the mechanical and haemodynamic outcome of the prevailing pacing strategies in hearts with normal electrical and mechanical function. For this class of patients, nsLBBP was the best compromise between LV and RV function if HBP is not possible.

Electromechanical factors associated with favourable outcome in cardiac resynchronization therapy.

AIMS: Electromechanical coupling in patients receiving cardiac resynchronization therapy (CRT) is not fully understood. Our aim was to determine the best combination of electrical and mechanical substrates associated with effective CRT. METHODS AND RESULTS: Sixty-two patients were prospectively enrolled from two centres. Patients underwent 12-lead electrocardiogram (ECG), cardiovascular magnetic resonance (CMR), echocardiography, and anatomo-electromechanical mapping (AEMM). Remodelling was measured as the end-systolic volume (ΔESV) decrease at 6 months. CRT was defined effective with ΔESV ≤ -15%. QRS duration (QRSd) was measured from ECG. Area strain was obtained from AEMM and used to derive systolic stretch index (SSI) and total left-ventricular mechanical time. Total left-ventricular activation time (TLVAT) and transeptal time (TST) were derived from AEMM and ECG. Scar was measured from CMR. Significant correlations were observed between ΔESV and TST [rho = 0.42; responder: 50 (20-58) vs. non-responder: 33 (8-44) ms], TLVAT [-0.68; 81 (73-97) vs. 112 (96-127) ms], scar [-0.27; 0.0 (0.0-1.2) vs. 8.7 (0.0-19.1)%], and SSI [0.41; 10.7 (7.1-16.8) vs. 4.2 (2.9-5.5)], but not QRSd [-0.13; 155 (140-176) vs. 167 (155-177) ms]. TLVAT and SSI were highly accurate in identifying CRT response [area under the curve (AUC) > 0.80], followed by scar (AUC > 0.70). Total left-ventricular activation time (odds ratio = 0.91), scar (0.94), and SSI (1.29) were independent factors associated with effective CRT. Subjects with SSI >7.9% and TLVAT <91 ms all responded to CRT with a median ΔESV ≈ -50%, while low SSI and prolonged TLVAT were more common in non-responders (ΔESV ≈ -5%). CONCLUSION: Electromechanical measurements are better associated with CRT response than conventional ECG variables. The absence of scar combined with high SSI and low TLVAT ensures effectiveness of CRT.

Virtual pacing of a patient's digital twin to predict left ventricular reverse remodelling after cardiac resynchronization therapy.

AIMS: Identifying heart failure (HF) patients who will benefit from cardiac resynchronization therapy (CRT) remains challenging. We evaluated whether virtual pacing in a digital twin (DT) of the patient's heart could be used to predict the degree of left ventricular (LV) reverse remodelling post-CRT. METHODS AND RESULTS: Forty-five HF patients with wide QRS complex (≥130 ms) and reduced LV ejection fraction (≤35%) receiving CRT were retrospectively enrolled. Echocardiography was performed before (baseline) and 6 months after CRT implantation to obtain LV volumes and 18-segment longitudinal strain. A previously developed algorithm was used to generate 45 DTs by personalizing the CircAdapt model to each patient's baseline measurements. From each DT, baseline septal-to-lateral myocardial work difference (MWLW-S,DT) and maximum rate of LV systolic pressure rise (dP/dtmax,DT) were derived. Biventricular pacing was then simulated using patient-specific atrioventricular delay and lead location. Virtual pacing-induced changes ΔMWLW-S,DT and ΔdP/dtmax,DT were correlated with real-world LV end-systolic volume change at 6-month follow-up (ΔLVESV). The DT's baseline MWLW-S,DT and virtual pacing-induced ΔMWLW-S,DT were both significantly associated with the real patient's reverse remodelling ΔLVESV (r = -0.60, P < 0.001 and r = 0.62, P < 0.001, respectively), while correlation between ΔdP/dtmax,DT and ΔLVESV was considerably weaker (r = -0.34, P = 0.02). CONCLUSION: Our results suggest that the reduction of septal-to-lateral work imbalance by virtual pacing in the DT can predict real-world post-CRT LV reverse remodelling. This DT approach could prove to be an additional tool in selecting HF patients for CRT and has the potential to provide valuable insights in optimization of CRT delivery.

Association of vectorcardiographic T-wave area with clinical and echocardiographic outcomes in cardiac resynchronization therapy.

AIMS: Data on repolarization parameters in cardiac resynchronization therapy (CRT) are scarce. We investigated the association of baseline T-wave area, with both clinical and echocardiographic outcomes of CRT in a large, multi-centre cohort of CRT recipients. Also, we evaluated the association between the baseline T-wave area and QRS area. METHODS AND RESULTS: In this retrospective study, 1355 consecutive CRT recipients were evaluated. Pre-implantation T-wave and QRS area were calculated from vectorcardiograms. Echocardiographic response was defined as a reduction of ≥15% in left ventricular end-systolic volume between 3 and 12 months after implantation. The clinical outcome was a combination of all-cause mortality, heart transplantation, and left ventricular assist device implantation. Left ventricular end-systolic volume reduction was largest in patients with QRS area ≥ 109 µVs and T-wave area ≥ 66 µVs compared with QRS area ≥ 109 µVs and T-wave area < 66 µVs (P = 0.004), QRS area < 109 µVs and T-wave area ≥ 66 µVs (P < 0.001) and QRS area < 109 µVs and T-wave area < 66 µVs (P < 0.001). Event-free survival rate was higher in the subgroup of patients with QRS area ≥ 109 µVs and T-wave area ≥ 66 µVs (n = 616, P < 0.001) and QRS area ≥ 109 µVs and T-wave area < 66 µVs (n = 100, P < 0.001) than the other subgroups. In the multivariate analysis, T-wave area remained associated with echocardiographic response (P = 0.008), but not with the clinical outcome (P = 0.143), when QRS area was included in the model. CONCLUSION: Baseline T-wave area has a significant association with both clinical and echocardiographic outcomes after CRT. The association of T-wave area with echocardiographic response is independent from QRS area; the association with clinical outcome, however, is not.

Electrical management of heart failure: from pathophysiology to treatment.

Electrical disturbances, such as atrial fibrillation (AF), dyssynchrony, tachycardia, and premature ventricular contractions (PVCs), are present in most patients with heart failure (HF). While these disturbances may be the consequence of HF, increasing evidence suggests that they may also cause or aggravate HF. Animal studies show that longer-lasting left bundle branch block, tachycardia, AF, and PVCs lead to functional derangements at the organ, cellular, and molecular level. Conversely, electrical treatment may reverse or mitigate HF. Clinical studies have shown the superiority of atrial and pulmonary vein ablation for rhythm control and AV nodal ablation for rate control in AF patients when compared with medical treatment. Ablation of PVCs can also improve left ventricular function. Cardiac resynchronization therapy (CRT) is an established adjunct therapy currently undergoing several interesting innovations. The current guideline recommendations reflect the safety and efficacy of these ablation therapies and CRT, but currently, these therapies are heavily underutilized. This review focuses on the electrical treatment of HF with reduced ejection fraction (HFrEF). We believe that the team of specialists treating an HF patient should incorporate an electrophysiologist in order to achieve a more widespread use of electrical therapies in the management of HFrEF and should also include individual conditions of the patient, such as body size and gender in therapy fine-tuning.

Synchronization of repolarization after cardiac resynchronization therapy: A combined clinical and modeling study.

INTRODUCTION: The changes in ventricular repolarization after cardiac resynchronization therapy (CRT) are poorly understood. This knowledge gap is addressed using a multimodality approach including electrocardiographic and echocardiographic measurements in patients and using patient-specific computational modeling. METHODS: In 33 patients electrocardiographic and echocardiographic measurements were performed before and at various intervals after CRT, both during CRT-ON and temporary CRT-OFF. T-wave area was calculated from vectorcardiograms, and reconstructed from the 12-lead electrocardiography (ECG). Computer simulations were performed using a patient-specific eikonal model of cardiac activation with spatially varying action potential duration (APD) and repolarization rate, fit to a patient's ECG. RESULTS: During CRT-ON T-wave area diminished within a day and remained stable thereafter, whereas QT-interval did not change significantly. During CRT-OFF T-wave area doubled within 5 days of CRT, while QT-interval and peak-to-end T-wave interval hardly changed. Left ventricular (LV) ejection fraction only increased significantly increased after 1 month of CRT. Computer simulations indicated that the increase in T-wave area during CRT-OFF can be explained by changes in APD following chronic CRT that are opposite to the change in CRT-induced activation time. These APD changes were associated with a reduction in LV dispersion in repolarization during chronic CRT. CONCLUSION: T-wave area during CRT-OFF is a sensitive marker for adaptations in ventricular repolarization during chronic CRT that may include a reduction in LV dispersion of repolarization.

Histopathological Validation of Dark-Blood Late Gadolinium Enhancement MRI Without Additional Magnetization Preparation.

BACKGROUND: Conventional bright-blood late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (MRI) often suffers from poor scar-to-blood contrast due to the bright blood pool adjacent to the enhanced scar tissue. Recently, a dark-blood LGE method was developed which increases scar-to-blood contrast without using additional magnetization preparation. PURPOSE: We aim to histopathologically validate this dark-blood LGE method in a porcine animal model with induced myocardial infarction (MI). STUDY TYPE: Prospective. ANIMAL MODEL: Thirteen female Yorkshire pigs. FIELD STRENGTH/SEQUENCE: 1.5 T, two-dimensional phase-sensitive inversion-recovery radiofrequency-spoiled turbo field-echo. ASSESSMENT: MI was experimentally induced by transient coronary artery occlusion. At 1-week and 7-week post-infarction, in-vivo cardiac MRI was performed including conventional bright-blood and novel dark-blood LGE. Following the second MRI examination, the animals were sacrificed, and histopathology was obtained. Matching LGE slices and histopathology samples were selected based on anatomical landmarks. Independent observers, while blinded to other data, manually delineated the endocardial, epicardial, and infarct borders on either LGE images or histopathology samples. The percentage of infarcted left-ventricular myocardium was calculated for both LGE methods on a per-slice basis, and compared with histopathology as reference standard. Contrast-to-noise ratios were calculated for both LGE methods at 1-week and 7-week post-infarction. STATISTICAL TESTS: Pearson's correlation coefficient and paired-sample t-tests were used. Significance was set at P < 0.05. RESULTS: A combined total of 24 matched LGE and histopathology slices were available for histopathological validation. Dark-blood LGE demonstrated a high level of agreement compared to histopathology with no significant bias (-0.03%, P = 0.75). In contrast, bright-blood LGE showed a significant bias of -1.57% (P = 0.03) with larger 95% limits of agreement than dark-blood LGE. Image analysis demonstrated significantly higher scar-to-blood contrast for dark-blood LGE compared to bright-blood LGE, at both 1-week and 7-weeks post-infarction. DATA CONCLUSION: Dark-blood LGE without additional magnetization preparation provides superior visualization and quantification of ischemic scar compared to the current in vivo reference standard. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Hemodynamics-driven mathematical model of first and second heart sound generation.

NEW & NOTEWORTHY: To the best of our knowledge, this is the first hemodynamic-based heart sound generation model embedded in a complete real-time computational model of the cardiovascular system. Simulated heart sounds are similar to experimental and clinical measurements, both quantitatively and qualitatively. Our model can be used to investigate the relationships between heart sound acoustic features and hemodynamic factors/anatomical parameters.

Pacing therapy for atrioventricular dromotropathy: a combined computational-experimental-clinical study.

AIMS: Investigate haemodynamic effects, and their mechanisms, of restoring atrioventricular (AV)-coupling using pacemaker therapy in normal and failing hearts in a combined computational-experimental-clinical study. METHODS AND RESULTS: Computer simulations were performed in the CircAdapt model of the normal and failing human heart and circulation. Experiments were performed in a porcine model of AV dromotropathy. In a proof-of-principle clinical study, left ventricular (LV) pressure and volume were measured in 22 heart failure (HF) patients (LV ejection fraction <35%) with prolonged PR interval (>230 ms) and narrow or non-left bundle branch block QRS complex. Computer simulations and animal studies in normal hearts showed that restoring of AV-coupling with unchanged ventricular activation sequence significantly increased LV filling, mean arterial pressure, and cardiac output by 10-15%. In computer simulations of failing hearts and in HF patients, reducing PR interval by biventricular (BiV) pacing (patients: from 300 ± 61 to 137 ± 30 ms) resulted in significant increases in LV stroke volume and stroke work (patients: 34 ± 40% and 26 ± 31%, respectively). However, worsening of ventricular dyssynchrony by using right ventricular (RV) pacing abrogated the benefit of restoring AV-coupling. In model simulations, animals and patients, the increase of LV filling and associated improvement of LV pump function coincided with both larger mitral inflow (E- and A-wave area) and reduction of diastolic mitral regurgitation. CONCLUSION: Restoration of AV-coupling by BiV pacing in normal and failing hearts with prolonged AV conduction leads to considerable haemodynamic improvement. These results indicate that BiV or physiological pacing, but not RV pacing, may improve cardiac function in patients with HF and prolonged PR interval.

Reduction in the QRS area after cardiac resynchronization therapy is associated with survival and echocardiographic response.

INTRODUCTION: Recent studies have shown that the baseline QRS area is associated with the clinical response after cardiac resynchronization therapy (CRT). In this study, we investigated the association of QRS area reduction (∆QRS area) after CRT with the outcome. We hypothesize that a larger ∆QRS area is associated with a better survival and echocardiographic response. METHODS AND RESULTS: Electrocardiograms (ECG) obtained before and 2-12 months after CRT from 1299 patients in a multi-center CRT-registry were analyzed. The QRS area was calculated from vectorcardiograms that were synthesized from 12-lead ECGs. The primary endpoint was a combination of all-cause mortality, heart transplantation, and left ventricular (LV) assist device implantation. The secondary endpoint was the echocardiographic response, defined as LV end-systolic volume reduction ≥ of 15%. Patients with ∆QRS area above the optimal cut-off value (62 µVs) had a lower risk of reaching the primary endpoint (hazard ratio: 0.43; confidence interval [CI] 0.33-0.56, p < .001), and a higher chance of echocardiographic response (odds ratio [OR] 3.3;CI 2.4-4.6, p < .0001). In multivariable analysis, ∆QRS area was independently associated with both endpoints. In patients with baseline QRS area ≥109 µVs, survival, and echocardiographic response were better when the ∆QRS area was ≥62 µVs (p < .0001). Logistic regression showed that in patients with baseline QRS area ≥109 µVs, ∆QRS area was the only significant predictor of survival (OR: 0.981; CI: 0.967-0.994, p = .006). CONCLUSION: ∆QRS area is an independent determinant of CRT response, especially in patients with a large baseline QRS area. Failure to achieve a large QRS area reduction with CRT is associated with a poor clinical outcome.

To what extent are perfusion defects seen by myocardial perfusion SPECT in patients with left bundle branch block related to myocardial infarction, ECG characteristics, and myocardial wall motion?

INTRODUCTION: We investigated if uptake pattern on myocardial perfusion SPECT (MPS) in patients with left bundle branch block (LBBB) is related to myocardial fibrosis, myocardial wall motion, and electrocardiography (ECG) characteristics. METHODS: Twenty-three patients (9 women) with LBBB, examined with MPS and cardiac magnetic resonance (CMR), were included. Tracer uptake on MPS was classified by visual interpretation as typical LBBB pattern (Defect+, n = 13) or not (Defect-, n = 10) and quantitatively. CMR images were evaluated for wall thickness and for myocardial wall motion both by visual assessment and by regional myocardial radial strain from feature tracking, and for presence and location of myocardial fibrosis. ECGs were analyzed regarding QRS duration and the presence of strict criteria for LBBB. RESULTS: Wall thickness was slightly lower in the septum compared to the lateral wall in Defect+ patients (5.6 ± 1.1 vs 6.0 ± 1.3 mm, P = 0.03) but not in Defect- patients (5.6 ± 1.0 vs 5.6 ± 0.9 mm, P = 0.84). Defect+ patients showed a larger proportion of dyskinetic segments in the septum and hyperkinetic segments in the lateral wall compared to Defect- patients (P = 0.006 and P = 0.004, respectively). Decreased myocardial radial strain was associated with decreased tracer uptake by MPS (R = 0.37, P < 0.001). Areas of fibrosis did not match areas with uptake defect on MPS. No differences in ECG variables were seen. CONCLUSION: The heterogeneous regional tracer uptake in some patients with LBBB is related to underlying regional myocardial dyskinesia, wall thickening, and wall thickness rather than stress-induced ischemia, myocardial fibrosis, or specific ECG characteristics.

Exploring the cause of conduction delays in patients with repaired Tetralogy of Fallot.

AIMS: Cardiac dyssynchrony in patients with repaired Tetralogy of Fallot (rToF) has been attributed to right bundle branch block (RBBB), fibrosis and/or the patches that are inserted during repair surgery. We aimed to investigate the basis of abnormal activation in rToF patients by mapping the electrical activation sequence during sinus rhythm (SR) and right ventricular (RV) pacing. METHODS AND RESULTS: A total of 17 patients were studied [13 with rToF, 2 with left bundle branch block (LBBB), and 2 without RBBB or LBBB (non-BBB)] during medically indicated cardiac surgery. During SR and RV pacing, measurements were performed using 112-electrode RV endocardial balloons (rToF only) and biventricular epicardial sock arrays (four of the rToF and all non-rToF patients). During SR, functional lines of block occurred in five rToF patients, while RV pacing caused functional blocks in four rToF patients. The line of block persisted during both SR and RV pacing in only 2 out of 13 rToF patients. Compared to SR, RV pacing increased dispersion of septal activation, but not dispersion of endocardial and epicardial activation of the RV free wall. During pacing, RV and left ventricular activation dispersion in rToF patients were comparable to that of the non-rToF patients. CONCLUSION: The results of the present study indicate that the delayed activation in the right ventricle of rToF patients is predominantly due to block(s) in the Purkinje system and that conduction in RV tissue is fairly normal.

Reconstruction of three-dimensional biventricular activation based on the 12-lead electrocardiogram via patient-specific modelling.

AIMS: Non-invasive imaging of electrical activation requires high-density body surface potential mapping. The nine electrodes of the 12-lead electrocardiogram (ECG) are insufficient for a reliable reconstruction with standard inverse methods. Patient-specific modelling may offer an alternative route to physiologically constraint the reconstruction. The aim of the study was to assess the feasibility of reconstructing the fully 3D electrical activation map of the ventricles from the 12-lead ECG and cardiovascular magnetic resonance (CMR). METHODS AND RESULTS: Ventricular activation was estimated by iteratively optimizing the parameters (conduction velocity and sites of earliest activation) of a patient-specific model to fit the simulated to the recorded ECG. Chest and cardiac anatomy of 11 patients (QRS duration 126-180 ms, documented scar in two) were segmented from CMR images. Scar presence was assessed by magnetic resonance (MR) contrast enhancement. Activation sequences were modelled with a physiologically based propagation model and ECGs with lead field theory. Validation was performed by comparing reconstructed activation maps with those acquired by invasive electroanatomical mapping of coronary sinus/veins (CS) and right ventricular (RV) and left ventricular (LV) endocardium. The QRS complex was correctly reproduced by the model (Pearson's correlation r = 0.923). Reconstructions accurately located the earliest and latest activated LV regions (median barycentre distance 8.2 mm, IQR 8.8 mm). Correlation of simulated with recorded activation time was very good at LV endocardium (r = 0.83) and good at CS (r = 0.68) and RV endocardium (r = 0.58). CONCLUSION: Non-invasive assessment of biventricular 3D activation using the 12-lead ECG and MR imaging is feasible. Potential applications include patient-specific modelling and pre-/per-procedural evaluation of ventricular activation.

A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation.

Computer models of cardiac electro-mechanics (EM) show promise as an effective means for the quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. To realize such advanced applications methodological key challenges must be addressed. Enhanced computational efficiency and robustness is crucial to facilitate, within tractable time frames, model personalization, the simulation of prolonged observation periods under a broad range of conditions, and physiological completeness encompassing therapy-relevant mechanisms is needed to endow models with predictive capabilities beyond the mere replication of observations. Here, we introduce a universal feature-complete cardiac EM modeling framework that builds on a flexible method for coupling a 3D model of bi-ventricular EM to the physiologically comprehensive 0D CircAdapt model representing atrial mechanics and closed-loop circulation. A detailed mathematical description is given and efficiency, robustness, and accuracy of numerical scheme and solver implementation are evaluated. After parameterization and stabilization of the coupled 3D-0D model to a limit cycle under baseline conditions, the model's ability to replicate physiological behaviors is demonstrated, by simulating the transient response to alterations in loading conditions and contractility, as induced by experimental protocols used for assessing systolic and diastolic ventricular properties. Mechanistic completeness and computational efficiency of this novel model render advanced applications geared towards predicting acute outcomes of EM therapies feasible.

Occurrence and Persistency of Conduction Disturbances during Transcatheter Aortic Valve Implantation.

Background and Objectives: Conduction disturbances such as left bundle branch block (LBBB) and complete atrio-ventricular block (cAVB) are relatively frequent complications following trans-catheter aortic valve implantation (TAVI). We investigated the dynamics of these conduction blocks to further understand luxating factors and predictors for their persistency. Materials and Methods: We prospectively included 157 consecutive patients who underwent a TAVI procedure. Electrocardiograms (ECGs) were obtained at specific time points during the TAVI procedure and at follow-up until at least six months post-procedure. Results: Of the 106 patients with a narrow QRS complex (nQRS) before TAVI, ~70% developed LBBB; 28 (26.4%) being classified as super-transient (ST-LBBB), 20 (18.9%) as transient (T-LBBB) and 24 (22.6%) as persistent (P-LBBB). Risk of LBBB was higher for self-expandable (SE) than for balloon-expandable (BE) prostheses and increased with larger implant depth. During the TAVI procedure conduction disturbances showed a dynamic behavior, as illustrated by alternating kinds of blocks in 18 cases. Most LBBBs developed during balloon aortic valvuloplasty (BAV) and at positioning and deployment of the TAVI prosthesis. The incidence of LBBB was not significantly different between patients who did and did not undergo BAV prior to TAVI implantation (65.3% and 74.2%, respectively (p = 0.494)). Progression to cAVB was most frequent for patients with preexisting conduction abnormalities (5/34) patients) and in patients showing ST-LBBB (6/28). Conclusions: During the TAVI procedure, conduction disturbances showed a dynamic behavior with alternating types of block in 18 cases. After a dynamic period of often alternating types of block, most BBBs are reversible while one third persist. Patients with ST-LBBB are most prone to progressing into cAVB. The observation that the incidence of developing LBBB after TAVI is similar with and without BAV suggests that a subgroup of patients has a substrate to develop LBBB regardless of the procedure.

Effective Distance between Aortic Valve and Conduction System Is an Independent Predictor of Persistent Left Bundle Branch Block during Transcatheter Aortic Valve Implantation.

Background and objectives: Persistent left bundle branch block (P-LBBB) has been associated with poor clinical outcomes of transcatheter aortic valve implantation (TAVI) procedures. We hypothesized that the distance from the aortic valve to the proximal conduction system, expressed as the effective distance between the aortic valve and conduction system (EDACS), can predict the occurrence of P-LBBB in patients undergoing a TAVI procedure. Materials and methods: In a retrospective study, data from 269 patients were analyzed. EDACS was determined using two longitudinal CT sections. Results: Sixty-four of the patients developed P-LBBB. EDACS ranged between -3 and +18 mm. EDACS was significantly smaller in P-LBBB than in non-P-LBBB patients (4.6 (2.2-7.1) vs. 8.0 (5.8-10.2) mm, median values (interquartile range); p < 0.05). Receiver operating characteristic analysis showed an area under the curve of 0.78 for predicting P-LBBB based on EDACS. In patients with EDACS of ≤3 mm and >10 mm, the chance of developing P-LBBB was ≥50% and <10%, respectively. Conclusions: A small EDACS increases the risk for the development of P-LBBB during TAVI by a factor of >25. As EDACS can be measured pre-procedurally, it may be a valuable additional factor to weigh the risks of transcatheter and surgical aortic valve replacement.