Evaluation of lead selection methods for optimal reconstruction of body surface potentials

Enhancing the efficiency and cost-effectiveness of magnetocardiography by optimal channel selection for cardiac diagnosis

Background. Magnetocardiography (MCG) is a non-invasive and non-contact technique that measures weak magnetic fields generated by the heart. It is highly effective in the diagnosis of heart abnormalities. Multichannel MCG provides detailed spatio-temporal information of the measured magnetic fields. While multichannel MCG systems are costly, usage of the optimal number of measurement channels to characterize cardiac magnetic fields without any appreciable loss of signal information would be economically beneficial and promote the widespread use of MCG technology.Methods. An optimization method based on the sequential selection approach is used to choose channels containing the maximum signal information while avoiding redundancy. The study comprised 40 healthy individuals, along with two subjects having ischemic heart disease and one subject with premature ventricular contraction. MCG measured using a 37 channel MCG system. After revisiting the existing methods of optimization, the mean error and correlation of the optimal set of measurement channels with those of all 37 channels are evaluated for different sets, and it has been found that 18 channels are adequate.Results. The chosen 18 optimal channels exhibited a strong correlation (0.99 ± 0.006) between the original and reconstructed magnetic field maps for a cardiac cycle in healthy subjects. The root mean square error is 0.295 pT, indicating minimal deviation.Conclusion. This selection method provides an efficient approach for choosing MCG, which could be used for minimizing the number of channels as well as in practical unforeseen measurement conditions where few channels are noisy during the measurement.

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.

Reduced leadset selection and performance evaluation in the inverse problem of electrocardiography for reconstructing the ventricularly paced electrograms

OBJECTIVE

Noninvasive electrocardiographic imaging (ECGI) is used for obtaining high-resolution images of the electrical activity of the heart, and is a powerful method with the potential to detect certain arrhythmias. However, there is no 'best' lead configuration in the literature to measure the torso potentials. This paper evaluates ECGI reconstructions using various reduced leadset configurations, explores whether one can find a common reduced leadset configuration that can accurately reconstruct the electrograms for datasets with different pacing sites, and compares two activation time estimation methods.

APPROACH

We used 23 ventricularly-paced datasets with pacing sites on different regions of the epicardium. Starting with a full 192‑leadset, we found "optimized" reduced leadsets specific to each dataset; we considered 64‑lead and 32‑lead configurations. Based on the histogram of individual "optimized" lead selections, we found a common reduced leadset. We compared the ECGI reconstructions and activation times of the individually optimized lead configurations with the common lead configurations.

RESULTS

Both 64‑lead configurations had similar performances to the 192‑leadset. 32‑leadset configurations, on the other hand, yielded noisy reconstructions, which affected their performance.

SIGNIFICANCE

There are no statistically significant differences in the performance of the inverse solutions when a 64‑lead common reduced leadset is used to estimate the electrograms and their respective pacing sites compared to using the full leadset. 32‑lead configurations, on the other hand, require a more careful study to improve their performance. The activation time method used significantly affects the pacing site estimation performance, especially with fewer electrodes.

Optimized Electrode Locations for Wearable Single-Lead ECG Monitoring Devices: A Case Study Using WFEES Modules based on the LANS Method

Body surface potential mapping (BSPM) is a valuable tool for research regarding electrocardiograms (ECG). However, the BSPM system is limited by its large number of electrodes and wires, long installation time, and high computational complexity. In this paper, we designed a wearable four-electrode electrocardiogram-sensor (WFEES) module that measures six-channel ECGs simultaneously for ECG investigation. To reduce the testing lead number and the measurement complexity, we further proposed a method, the layered (A, N) square-based (LANS) method, to optimize the ECG acquisition and analysis process using WFEES modules for different applications. Moreover, we presented a case study of electrode location optimization for wearable single-lead ECG monitoring devices using WFEES modules with the LANS method. In this study, 102 sets of single-lead ECG data from 19 healthy subjects were analyzed. The signal-to-noise ratio of ECG, as well as the mean and coefficient of variation of QRS amplitude, was derived among different channels to determine the optimal electrode locations. The results showed that a single-lead electrode pair should be placed on the left chest above the electrode location of standard precordial leads V1 to V4. Additionally, the best orientation was the principal diagonal as the direction of the heart's electrical axis.

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.

Improving the diagnosis of bundle branch block by analysis of body surface potential maps

Bundle branch block (BBB) is a defect on the electrical conduction system of the heart diagnosed by analyzing electrocardiogram (ECG) morphology. Our study aims to determine whether mapping information, specifically QRS duration and observation data from maps obtained using body surface potential mapping (BSPM), can be helpful in BBB diagnosis. We studied 64-lead BSPM recordings of 18 BBB patients and 9 controls with normal ventricular conduction. QRS duration was measured from the BSPM information obtained. The BSPM maps were computed along the QRS complex for each individual and group, and maps for each group were compared with maps for each individual. QRS complexes of the 12 standard leads were computed for each individual and group, and complexes of each group were compared with the complexes of each individual. QRS duration measured for all available leads (64 unipolar leads and 12 standard leads) was 7.4 +/- 3.9 milliseconds longer than QRS duration measured only in the standard 12-lead ECG for left BBB patients (LBBB) and 15.3 +/- 10.8 milliseconds longer for right BBB with left anterior fascicular block patients (RBBB_LAFB). In case of comparisons based on the standard ECG, sensitivity was 76.9% for LBBB patients and 66.6% for control subjects. However, classification based on map comparisons showed a sensitivity of 93% for LBBB patients and 89% for controls. QRS duration measured from BSPM information does not differ significantly from 12-lead standard ECG measurement for LBBB. However, differences are higher for RBBB_LAFB patients. Representative BSPM maps permit an automatic classification of the subjects.