Modeling ventricular repolarization gradients in normal cases using the equivalent dipole layer.

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, 67­leads) 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.

Body surface potential mapping detects early disease onset in plakophilin-2-pathogenic variant carriers.

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a progressive inherited cardiac disease. Early detection of disease and risk stratification remain challenging due to heterogeneous phenotypic expression. The standard configuration of the 12 lead electrocardiogram (ECG) might be insensitive to identify subtle ECG abnormalities. We hypothesized that body surface potential mapping (BSPM) may be more sensitive to detect subtle ECG abnormalities. METHODS AND RESULTS: We obtained 67 electrode BSPM in plakophilin-2 (PKP2)-pathogenic variant carriers and control subjects. Subject-specific computed tomography/magnetic resonance imaging based models of the heart/torso and electrode positions were created. Cardiac activation and recovery patterns were visualized with QRS- and STT-isopotential map series on subject-specific geometries to relate QRS-/STT-patterns to cardiac anatomy and electrode positions. To detect early signs of functional/structural heart disease, we also obtained right ventricular (RV) echocardiographic deformation imaging. Body surface potential mapping was obtained in 25 controls and 42 PKP2-pathogenic variant carriers. We identified five distinct abnormal QRS-patterns and four distinct abnormal STT-patterns in the isopotential map series of 31/42 variant carriers. Of these 31 variant carriers, 17 showed no depolarization or repolarization abnormalities in the 12 lead ECG. Of the 19 pre-clinical variant carriers, 12 had normal RV-deformation patterns, while 7/12 showed abnormal QRS- and/or STT-patterns. CONCLUSION: Assessing depolarization and repolarization by BSPM may help in the quest for early detection of disease in variant carriers since abnormal QRS- and/or STT-patterns were found in variant carriers with a normal 12 lead ECG. Because electrical abnormalities were observed in subjects with normal RV-deformation patterns, we hypothesize that electrical abnormalities develop prior to functional/structural abnormalities in ARVC.

Assessment of electrical dyssynchrony in cardiac resynchronization therapy: 12-lead electrocardiogram vs. 96-lead body surface map.

AIMS: The standard deviation of activation time (SDAT) derived from body surface maps (BSMs) has been proposed as an optimal measure of electrical dyssynchrony in patients with cardiac resynchronization therapy (CRT). The goal of this study was two-fold: (i) to compare the values of SDAT in individual CRT patients with reconstructed myocardial metrics of depolarization heterogeneity using an inverse solution algorithm and (ii) to compare SDAT calculated from 96-lead BSM with a clinically easily applicable 12-lead electrocardiogram (ECG). METHODS AND RESULTS: Cardiac resynchronization therapy patients with sinus rhythm and left bundle branch block at baseline (n = 19, 58% males, age 60 ± 11 years, New York Heart Association Classes II and III, QRS 167 ± 16) were studied using a 96-lead BSM. The activation time (AT) was automatically detected for each ECG lead, and SDAT was calculated using either 96 leads or standard 12 leads. Standard deviation of activation time was assessed in sinus rhythm and during six different pacing modes, including atrial pacing, sequential left or right ventricular, and biventricular pacing. Changes in SDAT calculated both from BSM and from 12-lead ECG corresponded to changes in reconstructed myocardial ATs. A high degree of reliability was found between SDAT values obtained from 12-lead ECG and BSM for different pacing modes, and the intraclass correlation coefficient varied between 0.78 and 0.96 (P < 0.001). CONCLUSION: Standard deviation of activation time measurement from BSM correlated with reconstructed myocardial ATs, supporting its utility in the assessment of electrical dyssynchrony in CRT. Importantly, 12-lead ECG provided similar information as BSM. Further prospective studies are necessary to verify the clinical utility of SDAT from 12-lead ECG in larger patient cohorts, including those with ischaemic cardiomyopathy.

Comparison of electrical dyssynchrony parameters between electrocardiographic imaging and a simulated ECG belt.

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.

Localization of ventricular activation origin using patient-specific geometry: Preliminary results.

BACKGROUND AND OBJECTIVES: Catheter ablation of ventricular tachycardia (VT) may include induction of VT and localization of VT-exit site. Our aim was to assess localization performance of a novel statistical pace-mapping method and compare it with performance of an electrocardiographic inverse solution. METHODS: Seven patients undergoing ablation of VT (4 with epicardial, 3 with endocardial exit) aided by electroanatomic mapping underwent intraprocedural 120-lead body-surface potential mapping (BSPM). Two approaches to localization of activation origin were tested: (1) A statistical method, based on multiple linear regression (MLR), which required only the conventional 12-lead ECG for a sufficient number of pacing sites with known origin together with patient-specific geometry of the endocardial/epicardial surface obtained by electroanatomic mapping; and (2) a classical deterministic inverse solution for recovering heart-surface potentials, which required BSPM and patient-specific geometry of the heart and torso obtained via computed tomography (CT). RESULTS: For the MLR method, at least 10-15 pacing sites with known coordinates, together with their corresponding 12-lead ECGs, were required to derive reliable patient-specific regression equations, which then enabled accurate localization of ventricular activation with unknown origin. For 4 patients who underwent epicardial mapping, the median of localization error for the MLR was significantly lower than that for the inverse solution (10.6 vs. 27.3 mm, P  =  0.034); a similar result held for 3 patients who underwent endocardial mapping (7.7 vs. 17.1 mm, P  =  0.017). The pooled localization error for all epicardial and endocardial sites was also significantly smaller for the MLR compared with the inverse solution (P  =  0.005). CONCLUSIONS: The novel pace-mapping approach to localizing the origin of ventricular activation offers an easily implementable supplement and/or alternative to the preprocedure inverse solution; its simplicity makes it suitable for real-time applications during clinical catheter-ablation procedures.

[Rhythm analysis of body surface potential mapping recordings from atrial fibrillation patients based on autocorrelation function].

The study of atrial fibrillation (AF) has been known as a hot topic of clinical concern. Body surface potential mapping (BSPM), a noninvasive electrical mapping technology, has been widely used in the study of AF. This study adopted 10 AF patients' preoperative and postoperative BSPM data (each patient's data contained 128 channels), and applied the autocorrelation function method to obtain the activation interval of the BSPM signals. The activation interval results were compared with that of manual counting method and the applicability of the autocorrelation function method was verified. Furthermore, we compared the autocorrelation function method with the commonly used fast Fourier transform (FFT) method. It was found that the autocorrelation function method was more accurate. Finally, to find a simple rule to predict the recurrence of atrial fibrillation, the autocorrelation function method was used to analyze the preoperative BSPM signals of 10 patients with persistent AF. Consequently, we found that if the patient's proportion of channels with dominant frequency larger than 2.5 Hz in the anterior left region is greater than the other three regions (the anterior right region, the posterior left region, and the posterior right region), he or she might have a higher possibility of AF recurrence. This study verified the rationality of the autocorrelation function method for rhythm analysis and concluded a simple rule of AF recurrence prediction based on this method.

Minimal configuration of body surface potential mapping for discrimination of left versus right dominant frequencies during atrial fibrillation.

BACKGROUND: Ablation of drivers maintaining atrial fibrillation (AF) has been demonstrated as an effective therapy. Drivers in the form of rapidly activated atrial regions can be noninvasively localized to either left or right atria (LA, RA) with body surface potential mapping (BSPM) systems. This study quantifies the accuracy of dominant frequency (DF) measurements from reduced-leads BSPM systems and assesses the minimal configuration required for ablation guidance. METHODS: Nine uniformly distributed lead sets of eight to 66 electrodes were evaluated. BSPM signals were registered simultaneously with intracardiac electrocardiograms (EGMs) in 16 AF patients. DF activity was analyzed on the surface potentials for the nine leads configurations, and the noninvasive measures were compared with the EGM recordings. RESULTS: Surface DF measurements presented similar values than panoramic invasive EGM recordings, showing the highest DF regions in corresponding locations. The noninvasive DFs measures had a high correlation with the invasive discrete recordings; they presented a deviation of <0.5 Hz for the highest DF and a correlation coefficient of >0.8 for leads configurations with 12 or more electrodes. CONCLUSIONS: Reduced-leads BSPM systems enable noninvasive discrimination between LA versus RA DFs with similar results as higher-resolution 66-leads system. Our findings demonstrate the possible incorporation of simplified BSPM systems into clinical planning procedures for AF ablation.

Noninvasive Estimation of Epicardial Dominant High-Frequency Regions During Atrial Fibrillation.

INTRODUCTION: Ablation of high dominant frequency (DF) sources in patients with atrial fibrillation (AF) is an effective treatment option for paroxysmal AF. The aim of this study was to evaluate the accuracy of noninvasive estimation of DF and electrical patterns determination by solving the inverse problem of the electrocardiography. METHODS: Four representative AF patients with left-to-right and right-to-left atrial DF patterns were included in the study. For each patient, intracardiac electrograms from both atria were recorded simultaneously together with 67-lead body surface recordings. In addition to clinical recordings, realistic mathematical models of atria and torso anatomy with different DF patterns of AF were used. For both mathematical models and clinical recordings, inverse-computed electrograms were compared to intracardiac electrograms in terms of voltage, phase, and frequency spectrum relative errors. RESULTS: Comparison between intracardiac and inverse computed electrograms for AF patients showed 8.8 ± 4.4% errors for DF, 32 ± 4% for voltage, and 65 ± 4% for phase determination. These results were corroborated by mathematical simulations showing that the inverse problem solution was able to reconstruct the frequency spectrum and the DF maps with relative errors of 5.5 ± 4.1%, whereas the reconstruction of the electrograms or the instantaneous phase presented larger relative errors (i.e., 38 ± 15% and 48 ± 14 % respectively, P < 0.01). CONCLUSIONS: Noninvasive reconstruction of atrial frequency maps can be achieved by solving the inverse problem of electrocardiography with a higher accuracy than temporal distribution patterns.

Spatiotemporal Characteristics of QRS Complexes Enable the Diagnosis of Brugada Syndrome Regardless of the Appearance of a Type 1 ECG.

INTRODUCTION: The diagnosis of Brugada syndrome based on the ECG is hampered by the dynamic nature of its ECG manifestations. Brugada syndrome patients are only 25% likely to present a type 1 ECG. The objective of this study is to provide an ECG diagnostic criterion for Brugada syndrome patients that can be applied consistently even in the absence of a type 1 ECG. METHODS AND RESULTS: We recorded 67-lead body surface potential maps from 94 Brugada syndrome patients and 82 controls (including right bundle branch block patients and healthy individuals). The spatial propagation direction during the last r' wave and the slope at the end of the QRS complex were measured and compared between patients groups. Receiver-operating characteristic curves were constructed for half of the database to identify optimal cutoff values; sensitivity and specificity for these cutoff values were measured in the other half of the database. A spontaneous type 1 ECG was present in only 30% of BrS patients. An orientation in the sagittal plane < 101º during the last r' wave and a descending slope < 9.65 mV/s enables the diagnosis of the syndrome with a sensitivity of 69% and a specificity of 97% in non-type 1 Brugada syndrome patients. CONCLUSION: Spatiotemporal characteristics of surface ECG recordings can enable a robust identification of BrS even without the presence of a type 1 ECG.

Comparison of the spatial QRS-T angle derived from digital ECGs recorded using conventional electrode placement with that derived from Mason-Likar electrode position.

BACKGROUND: The spatial QRS-T angle is ideally derived from orthogonal leads. We compared the spatial QRS-T angle derived from orthogonal leads reconstructed from digital 12-lead ECGs and from digital Holter ECGs recorded with the Mason-Likar (M-L) electrode positions. METHODS AND RESULTS: Orthogonal leads were constructed by the inverse Dower method and used to calculate spatial QRS-T angle by (1) a vector method and (2) a net amplitude method, in 100 volunteers. Spatial QRS-T angles from standard and M-L ECGs differed significantly (57°±18° vs 48°±20° respectively using net amplitude method and 53°±28° vs 48°±23° respectively by vector method; p<0.001). Difference in amplitudes in leads V4-V6 was also observed between Holter and standard ECGs, probably due to a difference in electrical potential at the central terminal. CONCLUSION: Mean spatial QRS-T angles derived from standard and M-L lead systems differed by 5°-9°. Though statistically significant, these differences may not be clinically significant.

Cardiac Body Surface Potentials in Rats with Experimental Pulmonary Hypertension during Ventricular Depolarization.

The spatial and the amplitude-temporal parameters of cardiac body surface potentials were examined in female Wistar rats with experimental pulmonary hypertension during ventricular depolarization. The cardiac body surface potentials have been led from 64 subcutaneous electrodes evenly distributed across the chest surface prior to and 4 weeks after subcutaneous injection of a single dose of monocrotaline (60 mg/kg). Right ventricular hypertrophy and electrophysiological remodeling of the heart developed in rats with experimental pulmonary hypertension in 4 weeks after monocrotaline injection; these changes led to a significant increase in amplitude and temporal characteristics of the cardioelectric field on the body surface in comparison with the initial state.

Assessment of myocardial infarct size with body surface potential mapping: validation against contrast-enhanced cardiac magnetic resonance imaging.

BACKGROUND: Assessment of myocardial infarct (MI) size is important for therapeutic and prognostic reasons. We used body surface potential mapping (BSPM) to evaluate whether single-lead electrocardiographic variables can assess MI size. METHODS: We performed BSPM with 120 leads covering the front and back chest (plus limb leads) on 57 patients at different phases of MI: acutely, during healing, and in the chronic phase. Final MI size was determined by contrast-enhanced cardiac magnetic resonance imaging (DE-CMR) and correlated with various computed depolarization- and repolarization-phase BSPM variables. We also calculated correlations between BSPM variables and enzymatic MI size (peak CK-MBm). RESULTS: BSPM variables reflecting the Q- and R wave showed strong correlations with MI size at all stages of MI. R width performed the best, showing its strongest correlation with MI size on the upper right back, there representing the width of the "reciprocal Q wave" (r = 0.64-0.71 for DE-CMR, r = 0.57-0.64 for CK-MBm, P < 0.0001). Repolarization-phase variables showed only weak correlations with MI size in the acute phase, but these correlations improved during MI healing. T-wave variables and the QRSSTT integral showed their best correlations with DE-CMR defined MI size on the precordial area, at best r = -0.57, P < 0.0001 in the chronic phase. The best performing BSPM variables could differentiate between large and small infarcts at all stages of MI. CONCLUSIONS: Computed, single-lead electrocardiographic variables can estimate the final infarct size at all stages of MI, and differentiate large infarcts from small.

Noninvasive imaging of cardiac excitation: current status and future perspective.

Noninvasive imaging of cardiac excitation using body surface potential mapping (BSPM) data and inverse procedures is an emerging technique that enables estimation of myocardial depolarization and repolarization. Despite numerous reports on the possible advantages of this imaging technique, it has not yet advanced into daily clinical practice. This is mainly due to the time consuming nature of data acquisition and the complexity of the mathematics underlying the used inverse procedures. However, the popularity of this field of research has increased and noninvasive imaging of cardiac electrophysiology is considered a promising tool to complement conventional invasive electrophysiological studies. Furthermore, the use of appropriately designed electrode vests and more advanced computers has greatly reduced the procedural time. This review provides descriptive overview of the research performed thus far and the possible future directions. The general challenges in routine application of BSPM and inverse procedures are discussed. In addition, individual properties of the biophysical models underlying the inverse procedures are illustrated.

U wave features in body surface potential mapping in post-myocardial infarction patients.

BACKGROUND: The data on U wave features in post-myocardial infarction (MI) remain sparse. We employed 120-lead body surface potential mapping (BSPM) to explore the U wave in patients with remote MI. METHODS: Sixty post-MI patients and 46 healthy controls were examined. After signal averaging, the polarity changes of U wave related to the T wave were analyzed, and the spatial and temporal U wave parameters were computed. RESULTS: Four types of patterns based on T and U polarity were recognized. A pattern with positive T and U waves was related to better ventricular function. The study groups did not differ as regards to Tend-Uapex and Tapex-Uapex intervals whereas Uapex-Uend was significantly longer in MI patients (110 ± 20 ms vs. 100 ± 13 ms, P = 0.004). MI patients had significantly higher U wave maximum amplitude (70 ± 30 µV vs. 50 ± 20 µV, P < 0.001), and U integral area (3.96 ± 1.50 µV·s vs. 3.17 ± 0.99 µV·s, P = 0.002), but lower corresponding T wave parameter values, thus resulting into higher U/T maximum amplitude and area ratios (0.16 ± 0.10 vs. 0.09 ± 0.04, P < 0.001; and 0.13 ± 0.06 vs. 0.09 ± 0.03, P < 0.001). In comparison to 12-lead ECG, BSPM covering the entire thorax enhanced the detection of U waves. CONCLUSION: MI tends to increase the U amplitude and prolong the later part of U wave duration thus augmenting the U wave. The size and location of infarction were associated with specific T and U wave polarity patterns.

An expert review of the inverse problem in electrocardiographic imaging for the non-invasive identification of atrial fibrillation drivers.

BACKGROUND AND OBJECTIVE: Electrocardiographic imaging (ECGI) has emerged as a non-invasive approach to identify atrial fibrillation (AF) driver sources. This paper aims to collect and review the current research literature on the ECGI inverse problem, summarize the research progress, and propose potential research directions for the future. METHODS AND RESULTS: The effectiveness and feasibility of using ECGI to map AF driver sources may be influenced by several factors, such as inaccuracies in the atrial model due to heart movement or deformation, noise interference in high-density body surface potential (BSP), inconvenient and time-consuming BSP acquisition, errors in solving the inverse problem, and incomplete interpretation of the AF driving source information derived from the reconstructed epicardial potential. We review the current research progress on these factors and discuss possible improvement directions. Additionally, we highlight the limitations of ECGI itself, including the lack of a gold standard to validate the accuracy of ECGI technology in locating AF drivers and the challenges associated with guiding AF ablation based on post-processed epicardial potentials due to the intrinsic difference between epicardial and endocardial potentials. CONCLUSIONS: Before performing ablation, ECGI can provide operators with predictive information about the underlying locations of AF driver by non-invasively and globally mapping the biatrial electrical activity. In the future, endocardial catheter mapping technology may benefit from the use of ECGI to enhance the diagnosis and ablation of AF.

A two-step inverse solution for a single dipole cardiac source.

Introduction: The inverse problem of electrocardiography noninvasively localizes the origin of undesired cardiac activity, such as a premature ventricular contraction (PVC), from potential recordings from multiple torso electrodes. However, the optimal number and placement of electrodes for an accurate solution of the inverse problem remain undetermined. This study presents a two-step inverse solution for a single dipole cardiac source, which investigates the significance of the torso electrodes on a patient-specific level. Furthermore, the impact of the significant electrodes on the accuracy of the inverse solution is studied. Methods: Body surface potential recordings from 128 electrodes of 13 patients with PVCs and their corresponding homogeneous and inhomogeneous torso models were used. The inverse problem using a single dipole was solved in two steps: First, using information from all electrodes, and second, using a subset of electrodes sorted in descending order according to their significance estimated by a greedy algorithm. The significance of electrodes was computed for three criteria derived from the singular values of the transfer matrix that correspond to the inversely estimated origin of the PVC computed in the first step. The localization error (LE) was computed as the Euclidean distance between the ground truth and the inversely estimated origin of the PVC. The LE obtained using the 32 and 64 most significant electrodes was compared to the LE obtained when all 128 electrodes were used for the inverse solution. Results: The average LE calculated for both torso models and using all 128 electrodes was 28.8 ± 11.9 mm. For the three tested criteria, the average LEs were 32.6 ± 19.9 mm, 29.6 ± 14.7 mm, and 28.8 ± 14.5 mm when 32 electrodes were used. When 64 electrodes were used, the average LEs were 30.1 ± 16.8 mm, 29.4 ± 12.0 mm, and 29.5 ± 12.6 mm. Conclusion: The study found inter-patient variability in the significance of torso electrodes and demonstrated that an accurate localization by the inverse solution with a single dipole could be achieved using a carefully selected reduced number of electrodes.

First-in-human noninvasive left ventricular ultrasound pacing: A potential screening tool for cardiac resynchronization therapy.

Background: A screening tool to predict response to cardiac resynchronization therapy (CRT) could improve patient selection and outcomes. Objective: The purpose of this study was to investigate the feasibility and safety of noninvasive CRT via transcutaneous ultrasonic left ventricular (LV) pacing applied as a screening test before CRT implants. Methods: P-wave-triggered ultrasound stimuli were delivered during bolus dosing of an echocardiographic contrast agent to simulate CRT noninvasively. Ultrasound pacing was delivered at a variety of LV locations with a range of atrioventricular delays to achieve fusion with intrinsic ventricular activation. Three-dimensional cardiac activation maps were acquired via the Medtronic CardioInsight 252-electrode mapping vest during baseline, ultrasound pacing, and after CRT implantation. A separate control group received only the CRT implants. Results: Ultrasound pacing was achieved in 10 patients with a mean of 81.2 ± 50.8 ultrasound paced beats per patient and up to 20 consecutive beats of ultrasound pacing. QRS width at baseline (168.2 ± 17.8 ms) decreased significantly to 117.3 ± 21.5 ms (P <.001) in the best ultrasound paced beat and to 125.8 ± 13.3 ms (P <.001) in the best CRT beat. Electrical activation patterns were similar between CRT pacing and ultrasound pacing with stimulation from the same area of the LV. Troponin results were similar between the ultrasound pacing and the control groups (P = .96), confirming safety. Conclusion: Noninvasive ultrasound pacing before CRT is safe and feasible, and it estimates the degree of electrical resynchronization achievable with CRT. Further study of this promising technique to guide CRT patient selection is warranted.

Reconstruction of cardiac position using body surface potentials.

Electrocardiographic imaging (ECGI) is a noninvasive technique to assess the bioelectric activity of the heart which has been applied to aid in clinical diagnosis and management of cardiac dysfunction. ECGI is built on mathematical models that take into account several patient specific factors including the position of the heart within the torso. Errors in the localization of the heart within the torso, as might arise due to natural changes in heart position from respiration or changes in body position, contribute to errors in ECGI reconstructions of the cardiac activity, thereby reducing the clinical utility of ECGI. In this study we present a novel method for the reconstruction of cardiac geometry utilizing noninvasively acquired body surface potential measurements. Our geometric correction method simultaneously estimates the cardiac position over a series of heartbeats by leveraging an iterative approach which alternates between estimating the cardiac bioelectric source across all heartbeats and then estimating cardiac positions for each heartbeat. We demonstrate that our geometric correction method is able to reduce geometric error and improve ECGI accuracy in a wide range of testing scenarios. We examine the performance of our geometric correction method using different activation sequences, ranges of cardiac motion, and body surface electrode configurations. We find that after geometric correction resulting ECGI solution accuracy is improved and variability of the ECGI solutions between heartbeats is substantially reduced.

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation.

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiotemporal indices for processing BSPM data and test their clinical applicability through a comparison with the recently proposed non-dipolar component index (NDI) for prediction of single-procedure catheter ablation (CA) success rate in persAF patients. Methods: BSPM recordings were obtained with a 252-lead vest in 13 persAF patients (8 men, 63 ± 8 years, 11 ± 13 months sustained AF duration) before undergoing CA. Each recording was divided into seven 1-min segments of high signal quality. Spatiotemporal ventricular activity (VA) cancellation was applied to each segment to isolate atrial activity (AA). The two novel indices, called error-ratio, normalized root-mean-square error (ERNRMSE) and error-ratio, mean-absolute error (ERABSE), were calculated. These indices quantify the capacity of a subset of BSPM vest electrodes to accurately represent the AA, and AA dominant frequency (DF), respectively, on all BSPM electrodes over time, compared to the optimal principal component analysis (PCA) representation. The NDI, quantifying the fraction of energy retained after removal of the three largest PCs, was also calculated. The two novel indices and the NDI were statistically compared between patient groups based on single-procedure clinical CA outcome. Finally, their predictive power for univariate CA outcome classification was assessed using receiver operating characteristic (ROC) analysis with cross-validation for a logistic regression classifier. Results: Patient clinical outcomes were recorded 6 months following procedures, and those who had an arrhythmia recurrence at least 2 months post-CA were defined as having a negative outcome. Clinical outcome information was available for 11 patients, 6 with arrhythmia recurrence. Therefore, a total of 77 1-min AA-BSPM segments were available for analysis. Significant differences were found in the values of the novel indices and NDI between patients with arrhythmia recurrence post-ablation and those without. ROC analysis showed the best CA outcome predictive performance for ERNRMSE (AUC = 0.77 ± 0.08, sensitivity = 76.2%, specificity = 84.8%). Conclusion: Significant association was found between the novel indices and CA success or failure. The novel index ERNRMSE additionally shows good predictive power for single-procedure CA outcome.

A 3D-CNN with temporal-attention block to predict the recurrence of atrial fibrillation based on body-surface potential mapping signals.

Catheter ablation has become an important treatment for atrial fibrillation (AF), but its recurrence rate is still high. The aim of this study was to predict AF recurrence using a three-dimensional (3D) network model based on body-surface potential mapping signals (BSPMs). BSPMs were recorded with a 128-lead vest in 14 persistent AF patients before undergoing catheter ablation (Maze-IV). The torso geometry was acquired and meshed by point cloud technology, and the BSPM was interpolated into the torso geometry by the inverse distance weighted (IDW) method to generate the isopotential map. Experiments show that the isopotential map of BSPMs can reflect the propagation of the electrical wavefronts. The 3D isopotential sequence map was established by combining the spatial-temporal information of the isopotential map; a 3D convolutional neural network (3D-CNN) model with temporal attention was established to predict AF recurrence. Our study proposes a novel attention block that focuses the characteristics of atrial activations to improve sampling accuracy. In our experiment, accuracy (ACC) in the intra-patient evaluation for predicting the recurrence of AF was 99.38%. In the inter-patient evaluation, ACC of 3D-CNN was 81.48%, and the area under the curve (AUC) was 0.88. It can be concluded that the dynamic rendering of multiple isopotential maps can not only comprehensively display the conduction of cardiac electrical activity on the body surface but also successfully predict the recurrence of AF after CA by using 3D isopotential sequence maps.