Forward-Solution Noninvasive Computational Arrhythmia Mapping: The VMAP Study.

BACKGROUND: The accuracy of noninvasive arrhythmia source localization using a forward-solution computational mapping system has not yet been evaluated in blinded, multicenter analysis. This study tested the hypothesis that a computational mapping system incorporating a comprehensive arrhythmia simulation library would provide accurate localization of the site-of-origin for atrial and ventricular arrhythmias and pacing using 12-lead ECG data when compared with the gold standard of invasive electrophysiology study and ablation. METHODS: The VMAP study (Vectorcardiographic Mapping of Arrhythmogenic Probability) was a blinded, multicenter evaluation with final data analysis performed by an independent core laboratory. Eligible episodes included atrial and ventricular: tachycardia, fibrillation, pacing, premature atrial and ventricular complexes, and orthodromic atrioventricular reentrant tachycardia. Mapping system results were compared with the gold standard site of successful ablation or pacing during electrophysiology study and ablation. Mapping time was assessed from time-stamped logs. Prespecified performance goals were used for statistical comparisons. RESULTS: A total of 255 episodes from 225 patients were enrolled from 4 centers. Regional accuracy for ventricular tachycardia and premature ventricular complexes in patients without significant structural heart disease (n=75, primary end point) was 98.7% (95% CI, 96.0%-100%; P<0.001 to reject predefined H0 <0.80). Regional accuracy for all episodes (secondary end point 1) was 96.9% (95% CI, 94.7%-99.0%; P<0.001 to reject predefined H0 <0.75). Accuracy for the exact or neighboring segment for all episodes (secondary end point 2) was 97.3% (95% CI, 95.2%-99.3%; P<0.001 to reject predefined H0 <0.70). Median spatial accuracy was 15 mm (n=255, interquartile range, 7-25 mm). The mapping process was completed in a median of 0.8 minutes (interquartile range, 0.4-1.4 minutes). CONCLUSIONS: Computational ECG mapping using a forward-solution approach exceeded prespecified accuracy goals for arrhythmia and pacing localization. Spatial accuracy analysis demonstrated clinically actionable results. This rapid, noninvasive mapping technology may facilitate catheter-based and noninvasive targeted arrhythmia therapies. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT04559061.

Computational ECG mapping and respiratory gating to optimize stereotactic ablative radiotherapy workflow for refractory ventricular tachycardia.

BACKGROUND: Stereotactic ablative radiotherapy (SAbR) is an emerging therapy for refractory ventricular tachycardia (VT). However, the current workflow is complicated, and the precision and safety in patients with significant cardiorespiratory motion and VT targets near the stomach may be suboptimal. OBJECTIVE: We hypothesized that automated 12-lead electrocardiogram (ECG) mapping and respiratory-gated therapy may improve the ease and precision of SAbR planning and facilitate safe radiation delivery in patients with refractory VT. METHODS: Consecutive patients with refractory VT were studied at 2 hospitals. VT exit sites were localized using a 3-D computational ECG algorithm noninvasively and compared to available prior invasive mapping. Radiotherapy (25 Gy) was delivered at end-expiration when cardiac respiratory motion was ≥0.6 cm or targets were ≤2 cm from the stomach. RESULTS: In 6 patients (ejection fraction 29% ± 13%), 4.2 ± 2.3 VT morphologies per patient were mapped. Overall, 7 out of 7 computational ECG mappings (100%) colocalized to the identical cardiac segment when prior invasive electrophysiology study was available. Respiratory gating was associated with smaller planning target volumes compared to nongated volumes (71 ± 7 vs 153 ± 35 cc, P < .01). In 2 patients with inferior wall VT targets close to the stomach (6 mm proximity) or significant respiratory motion (22 mm excursion), no GI complications were observed at 9- and 12-month follow-up. Implantable cardioverter-defibrillator shocks decreased from 23 ± 12 shocks/patient to 0.67 ± 1.0 (P < .001) post-SAbR at 6.0 ± 4.9 months follow-up. CONCLUSIONS: A workflow including computational ECG mapping and protocol-guided respiratory gating is feasible, is safe, and may improve the ease of SAbR planning. Studies to validate this workflow in larger populations are required.

Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study.

Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored. Thus, this study aimed to determine the sensitivity of the QRS complex of the ECG to the anatomical location and regional number of PMJs. The QRS complex was simulated using an image-based human torso and biventricular model, and cardiac electrophysiology was simulated using Cardioid. The PMJs were modeled as discrete current injection stimuli, and the location and number of stimuli were varied within initial activation regions based on published experiments. Results indicate that the QRS complex features were most sensitive to the presence or absence of four "seed" stimuli, and adjusting locations of nearby "regional" stimuli provided finer tuning. Decreasing number of regional stimuli by an order of magnitude resulted in virtually no change in the QRS complex. Thus, a minimal 12-stimuli configuration was identified that resulted in physiological excitation, defined by QRS complex feature metrics and ventricular excitation pattern. Overall, the sensitivity results suggest that parameterizing PMJ location, rather than number, be given significantly higher priority in future studies creating personalized ventricular models from patient-derived ECGs.

Rotors exhibit greater surface ECG variation during ventricular fibrillation than focal sources due to wavebreak, secondary rotors, and meander.

INTRODUCTION: Ventricular fibrillation is a common life-threatening arrhythmia. The ECG of VF appears chaotic but may allow identification of sustaining mechanisms to guide therapy. HYPOTHESIS: We hypothesized that rotors and focal sources manifest distinct features on the ECG, and computational modeling may identify mechanisms of such features. METHODS: VF induction was attempted in 31 patients referred for ventricular arrhythmia ablation. Simultaneous surface ECG and intracardiac electrograms were recorded using biventricular basket catheters. Endocardial phase maps were used to mechanistically classify each VF cycle as rotor or focally driven. ECGs were analyzed from patients demonstrating both mechanisms in the primary analysis and from all patients with induced VF in the secondary analysis. The ECG voltage variation during each mechanism was compared. Biventricular computer simulations of VF driven by focal sources or rotors were created and resulting ECGs of each VF mechanism were compared. RESULTS: Rotor-based VF exhibited greater voltage variation than focal source-based VF in both the primary analysis (n = 8, 110 ± 24% vs. 55 ± 32%, P = 0.02) and the secondary analysis (n = 18, 103 ± 30% vs. 67 ± 34%, P = 0.009). Computational VF simulations also revealed greater voltage variation in rotors compared to focal sources (110 ± 19% vs. 33 ± 16%, P = 0.001), and demonstrated that this variation was due to wavebreak, secondary rotor initiation, and rotor meander. CONCLUSION: Clinical and computational studies reveal that quantitative criteria of ECG voltage variation differ significantly between VF-sustaining rotors and focal sources, and provide insight into the mechanisms of such variation. Future studies should prospectively evaluate if these criteria can separate clinical VF mechanisms and guide therapy.

Non-invasive, model-based measures of ventricular electrical dyssynchrony for predicting CRT outcomes.

AIMS: Left ventricular activation delay due to left bundle branch block (LBBB) is an important determinant of the severity of dyssynchronous heart failure (DHF). We investigated whether patient-specific computational models constructed from non-invasive measurements can provide measures of baseline dyssynchrony and its reduction after CRT that may explain the degree of long-term reverse ventricular remodelling. METHODS AND RESULTS: LV end-systolic volume reduction (ΔESVLV) measured by 2D trans-thoracic echocardiography in eight patients following 6 months of CRT was significantly (P < 0.05) greater in responders (26 ± 20%, n = 4) than non-responders (11 ± 16%, n = 4). LV reverse remodelling did not correlate with baseline QRS duration or its change after biventricular pacing, but did correlate with baseline LV endocardial activation measured by electroanatomic mapping (R2 = 0.71, P < 0.01). Patient-specific models of LBBB ventricular activation with parameters obtained by matching model-computed vectorcardiograms (VCG) to those derived from standard patient ECGs yielded LV endocardial activation times that correlated well with those measured from endocardial maps (R2 = 0.90). Model-computed 3D LV activation times correlated strongly with the reduction in LVESV (R2 = 0.93, P < 0.001). Computed decreases due to simulated CRT in the time delay between LV septal and lateral activation correlated strongly with ΔESVLV (R2 = 0.92, P < 0.001). Models also suggested that optimizing VV delays may improve resynchronization by this measure of activation delay. CONCLUSIONS: Patient-specific computational models constructed from non-invasive measurements can compute estimates of LV dyssynchrony and their changes after CRT that may be as good as or better than electroanatomic mapping for predicting long-term reverse remodelling.

Ventricular fibrillation: triggers, mechanisms and therapies.

Ventricular fibrillation (VF) is a common, life-threatening arrhythmia responsible for significant morbidity and mortality. Due to challenges in safely mapping VF, a comprehensive understanding of its mechanisms remains elusive. Recent findings have provided new insights into mechanisms that sustain early VF. Notably, the central role of electrical rotors and catheter-based ablation of VF rotor substrate have been recently reported. In this article, we will review data regarding four stages of VF: initiation, transition, maintenance and evolution. We will discuss the particular mechanisms for each stage and therapies targeting these mechanisms. We also examine inherited arrhythmia syndromes, including the mechanisms and therapies specific to each. We hope that the overview of VF outlined in this work will assist other investigators in designing future therapies to interrupt this life-threatening arrhythmia.

High-order finite element methods for cardiac monodomain simulations.

Computational modeling of tissue-scale cardiac electrophysiology requires numerically converged solutions to avoid spurious artifacts. The steep gradients inherent to cardiac action potential propagation necessitate fine spatial scales and therefore a substantial computational burden. The use of high-order interpolation methods has previously been proposed for these simulations due to their theoretical convergence advantage. In this study, we compare the convergence behavior of linear Lagrange, cubic Hermite, and the newly proposed cubic Hermite-style serendipity interpolation methods for finite element simulations of the cardiac monodomain equation. The high-order methods reach converged solutions with fewer degrees of freedom and longer element edge lengths than traditional linear elements. Additionally, we propose a dimensionless number, the cell Thiele modulus, as a more useful metric for determining solution convergence than element size alone. Finally, we use the cell Thiele modulus to examine convergence criteria for obtaining clinically useful activation patterns for applications such as patient-specific modeling where the total activation time is known a priori.

Patient-specific modeling of ventricular activation pattern using surface ECG-derived vectorcardiogram in bundle branch block.

Patient-specific computational models have promise to improve cardiac disease diagnosis and therapy planning. Here a new method is described to simulate left-bundle branch block (LBBB) and RV-paced ventricular activation patterns in three dimensions from non-invasive, routine clinical measurements. Activation patterns were estimated in three patients using vectorcardiograms (VCG) derived from standard 12-lead electrocardiograms (ECG). Parameters of a monodomain model of biventricular electrophysiology were optimized to minimize differences between the measured and computed VCG. Electroanatomic maps of local activation times measured on the LV and RV endocardial surfaces of the same patients were used to validate the simulated activation patterns. For all patients, the optimal estimated model parameters predicted a time-averaged mean activation dipole orientation within 6.7 ± 0.6° of the derived VCG. The predicted local activation times agreed within 11.5 ± 0.8 ms of the measured electroanatomic maps, on the order of the measurement accuracy.

Patient-Specific Models of Cardiac Biomechanics.

Patient-specific models of cardiac function have the potential to improve diagnosis and management of heart disease by integrating medical images with heterogeneous clinical measurements subject to constraints imposed by physical first principles and prior experimental knowledge. We describe new methods for creating three-dimensional patient-specific models of ventricular biomechanics in the failing heart. Three-dimensional bi-ventricular geometry is segmented from cardiac CT images at end-diastole from patients with heart failure. Human myofiber and sheet architecture is modeled using eigenvectors computed from diffusion tensor MR images from an isolated, fixed human organ-donor heart and transformed to the patient-specific geometric model using large deformation diffeomorphic mapping. Semi-automated methods were developed for optimizing the passive material properties while simultaneously computing the unloaded reference geometry of the ventricles for stress analysis. Material properties of active cardiac muscle contraction were optimized to match ventricular pressures measured by cardiac catheterization, and parameters of a lumped-parameter closed-loop model of the circulation were estimated with a circulatory adaptation algorithm making use of information derived from echocardiography. These components were then integrated to create a multi-scale model of the patient-specific heart. These methods were tested in five heart failure patients from the San Diego Veteran's Affairs Medical Center who gave informed consent. The simulation results showed good agreement with measured echocardiographic and global functional parameters such as ejection fraction and peak cavity pressures.

Myofiber prestretch magnitude determines regional systolic function during ectopic activation in the tachycardia-induced failing canine heart.

Electrical dyssynchrony leads to prestretch in late-activated regions and alters the sequence of mechanical contraction, although prestretch and its mechanisms are not well defined in the failing heart. We hypothesized that in heart failure, fiber prestretch magnitude increases with the amount of early-activated tissue and results in increased end-systolic strains, possibly due to length-dependent muscle properties. In five failing dog hearts with scars, three-dimensional strains were measured at the anterolateral left ventricle (LV). Prestretch magnitude was varied via ventricular pacing at increasing distances from the measurement site and was found to increase with activation time at various wall depths. At the subepicardium, prestretch magnitude positively correlated with the amount of early-activated tissue. At the subendocardium, local end-systolic strains (fiber shortening, radial wall thickening) increased proportionally to prestretch magnitude, resulting in greater mean strain values in late-activated compared with early-activated tissue. Increased fiber strains at end systole were accompanied by increases in preejection fiber strain, shortening duration, and the onset of fiber relengthening, which were all positively correlated with local activation time. In a dog-specific computational failing heart model, removal of length and velocity dependence on active fiber stress generation, both separately and together, alter the correlations between local electrical activation time and timing of fiber strains but do not primarily account for these relationships.

Affine transformation registers small scale lung deformation.

To evaluate the nature of small scale lung deformation between multiple pulmonary magnetic resonance images, two different kinematic intensity based image registration techniques: affine and bicubic Hermite interpolation were tested. The affine method estimates uniformly distributed deformation metrics throughout the lung. The bicubic Hermite method allows the expression of heterogeneously distributed deformation metrics such as Lagrangian strain. A cardiac triggered inversion recovery technique was used to obtain 10 sequential images of pulmonary vessel structure in a sagittal plane in the right lung at FRC in 4 healthy subjects (Age: 28.5(6.2)). One image was used as the reference image, and the remaining images (target images) were warped onto the reference image using both image registration techniques. The normalized correlation between the reference and the transformed target images within the lung domain was used as a cost function for optimization, and the root mean square (RMS) of image intensity difference was used to evaluate the quality of the registration. Both image registration techniques significantly improved the RMS compared with non-registered target images (p= 0.04). The spatial mean (µE) and standard deviation (σ(E)) of Lagrangian strain were computed based on the spatial distribution of lung deformation approximated by the bicubic Hermite method, and were measured on the order of 10(-3) or less, which is virtually negligible. As a result, small scale lung deformation between FRC lung volumes is spatially uniform, and can be simply characterized by affine deformation even though the bicubic Hermite method is capable of expressing complicated spatial patterns of lung deformation.