Body Surface Potential Research Articles

Supplemented standard 12-lead electrocardiogram for optimal diagnosis and reconstruction of significant body surface map patterns

In this study, based on 120-lead body surface potential maps (BSPMs), we explored the improvement in electrocardiogram (ECG) diagnosis obtained by adding additional leads and using estimation of unmeasured leads. We found that adding a few leads observed to be optimal for diagnosis or signal capture combined with the existing 12-lead ECG improves diagnostic performance. Separately, using reconstruction (estimation) of BSPMs and using diagnostic criteria derived for maps also improve diagnostic performance over that provided by the recorded 12-lead ECG alone. Combining these 2 ideas, namely, addition of optimal leads and estimation of BSPMs improves performance even more.

Selection of optimal recording sites for limited lead body surface potential mapping in myocardial infarction and left ventricular hypertrophy

A lead selection algorithm was applied to find optimal recording sites for limited lead body surface potential maps. The studied population consisted of a set of 117 lead body surface potential maps recorded from 744 subjects (229, normal; 278, with myocardial infraction [MI]; and 237, with left ventricular hypertrophy [LVH]). One generic lead set derived from all disease groups was found. Also found were 3 disease-specific lead sets (normal, MI, and LVH) and one specific to abnormal subjects (MI and LVH combined). The performance of each lead set in estimating data from other disease groups was largely similar. This was with the exception of leads specific to LVH in the estimation of normal data and normal leads in the estimation of LVH data. Here, the difference was found to be significant ( P < .001). The top 6 recording sites in each lead set did not occupy the same positions as the 6 precordial leads. Although disease-specific lead sets are of limited practical use, this study has illustrated that, largely, there is little difference between the performance of different lead sets. The suboptimality of the 6 precordial leads has also been illustrated.

Truncated Total Least Squares: A New Regularization Method for the Solution of ECG Inverse Problems

The reconstruction of epicardial potentials (EPs) from body surface potentials (BSPs) can be characterized as an ill-posed inverse problem which generally requires a regularized numerical solution. Two kinds of errors/noise: geometric errors and measurement errors exist in the ECG inverse problem and make the solution of such problem more difficulty. In particular, geometric errors will directly affect the calculation of transfer matrix A in the linear system equation AX = B. In this paper, we have applied the truncated total least squares (TTLS) method to reconstruct EPs from BSPs. This method accounts for the noise/errors on both sides of the system equation and treats geometric errors in a new fashion. The algorithm is tested using a realistically shaped heart-lung-torso model with inhomogeneous conductivities. The h-adaptive boundary element method [h-BEM, a BEM mesh adaptation scheme which starts from preset meshes and then refines (adds/removes) grid with fixed order of interpolation function and prescribed numerical accuracy] is used for the forward modeling and the TTLS is applied for inverse solutions and its performance is also compared with conventional regularization approaches such as Tikhonov and truncated single value decomposition (TSVD) with zeroth-, first-, and second-order. The simulation results demonstrate that TTLS can obtain similar results in the situation of measurement noise only but performs better than Tikhonov and TSVD methods where geometric errors are involved, and that the zeroth-order regularization is the optimal choice for the ECG inverse problem. This investigation suggests that TTLS is able to robustly reconstruct EPs from BSPs and is a promising alternative method for the solution of ECG inverse problems.

Mirror image electrocardiograms and additional electrocardiographic leads: new wine in old wineskins?

Background Mirror image electrocardiograms (ECGs), obtained by inverting the original signals, and additional precordial leads have been proposed as means to improve ECG diagnosis. The theoretical backgrounds of these proposals are discussed. Methods In 746 body surface potential maps, the mirror areas of the 6 precordial leads, V 3R, and 2 more leads higher up and 1 lower down the thorax have been determined. The similarity between the original signal and its mirror image was expressed by a similarity index. This was done separately for QRS and ST-T; for the first and second parts of QRS; and for the categories normal, left ventricular hypertrophy, and infarct. Results In general, high similarity scores were obtained. The mirror images of V 1 and V 2 are almost diametrically located on the back. Inverting these leads could render the V 8 and V 9 leads. The other mirror areas may deviate considerably from where generally expected. Conclusion Mirror images can be obtained consistently from all locations, supporting the dipole representation of cardiac electrical activity. Neither mirror image ECGs nor additional chest leads contribute essentially to ECG diagnosis.

Noninvasive electrocardiographic imaging (ECGI) of epicardial activation before and after catheter ablation of the accessory pathway in a patient with Ebstein anomaly

Ebstein’s anomaly (1) is characterized by abnormal development of the tricuspid valve with the septal (and often posterior) leaflets of the valve displaced into the right ventricle (RV). The abnormal development of the tricuspid valve is often associated with several conduction abnormalities, including delayed intra-atrial conduction, right bundle branch block (RBBB) (2, 3), and ventricular pre-excitation (4). Absence of a RBBB pattern during sinus rhythm on a baseline ECG suggests the presence of an atrio-ventricular accessory pathway (AP) in patients with Ebstein’s anomaly. Often, successful catheter ablation of an AP results in a complete or partial RBBB pattern on the post-ablation 12-lead ECG in 94% of cases (5). However, changes in the activation of the heart following a successful catheter ablation of AP in a patient with Ebstein’s anomaly have never been studied with epicardial activation imaging techniques. Electrocardiographic imaging (ECGI) (6, 7) is a novel noninvasive imaging modality for cardiac electrophysiology. ECGI can image cardiac activity on the epicardial surface of the heart from body-surface potentials measured with 250 electrodes together with heart-torso anatomic information obtained from a thoracic ECG-gated CT. It has been validated with intra-operative mapping data in humans (8). It has also been applied in humans to image the electrophysiologic substrate and cardiac excitation under normal and various pathophysiologic conditions (6–11).

Activation patterns during selective pacing of the left ventricle can be characterized using noninvasive electrocardiographic imaging

Background Noncontact endocardial mapping allows accurate beat-to-beat reconstruction of the reentrant pathway of ventricular tachycardia and improves outcomes after ablation. Several studies support electrocardiographic imaging (ECGI) as a means of noninvasively outlining epicardial activation despite constraints of internal geometry. However, few have explored its clinical application. This study aims to evaluate ECGI during selective left ventricular (LV) pacing, relative to an invasive approach. Methods Multisite pacing was performed within the left ventricles of 3 patients undergoing invasive procedures. Simultaneous recording of endocardial potentials using a noncontact multielectrode array and body surface potentials (BSP) using an 80-electrode torso vest was performed. A total of 16 recordings were made. The inverse solution was applied to BSP to reconstruct epicardial activation. Single-paced beats from real and virtual electrograms were used to construct 3-dimensional isochronal and isopotential maps. Endocardial and epicardial data were then superimposed onto a single geometry to allow quantitative comparison of activation foci. Results Good correlation was observed between endocardial activation patterns and those reconstructed from BSP using ECGI. This was repeatedly demonstrated in all LV regions except for the septum (3 recordings). Epicardial isochronal maps were able to locate early and late activation to mean distances of 13.8 ± 4.7 and 12.5 ± 3.7 mm from endocardial data. Isopotential maps localized pacing sites with comparable accuracy (14 ± 5.3 mm). Conclusions Body surface potentials and reconstructed epicardial activation patterns during LV pacing correlate well with endocardial data acquired invasively. The exception was during pacing of the septum. Although early results are encouraging, further quantitative data are required to fully validate and apply this noninvasive tool in the clinical arena.

Spatial dynamics of atrial activity assessed by the vectorcardiogram: from sinus rhythm to atrial fibrillation

This study aims at developing methods for extracting spatiotemporal information about the electric activity of the atria from electrocardiographic signals, in particular during atrial fibrillation. A biophysical model of the atria and a volume conductor model of the thorax were used to simulate the atrial electrical activity as expressed on the atrial surface as well as on the thorax surface. In all, 22 different types of atrial electric activity were generated, 20 of which related to atrial fibrillation (AF). The spatiotemporal behaviour of the 'true' equivalent dipole expression of these activities was documented as well as those of their estimation based on body surface potentials, the vectorcardiogram. Measures were developed for describing the spatial complexity of atrial signals as observed in the 'atrial' vectorcardiogram. Coherence between time course of the vectorcardiogram and the electrical atrial activity of the simulated sinus rhythm and typical atrial flutter has been observed. Identification of the local extremes of the distribution of instantaneous vector orientations revealed the location of stable and single atrial activity sources. Moreover, the spatial complexity of the vectorcardiogram can be quantified in a very natural way by the proposed features and their visualization. The proposed analysis extracts spatial information that has hitherto remained unnoticed in non-invasive studies on atrial fibrillation (AF).

Estimated body surface potential maps in emergency department patients with unrecognized transient myocardial ischemia

Background We report on 5 patients who presented to the emergency department (ED) with chest pain, had negative serum troponin levels, and were discharged with a presumed noncardiac diagnosis. Thereafter, retrospective analysis of Holter monitoring data recorded for a clinical trial revealed ST events indicative of transient myocardial ischemia that was unrecognized clinically. Study Aim The purpose of this analysis was to determine whether initial body surface potential maps estimated from optimal ischemia electrode sites estimated body surface potential map (EBSPM) showed signs of ischemia in the missed ischemia group that could have prevented misdiagnosis. Methods This is a secondary analysis of data from a prospective clinical trial in which patients were attached to 2 Holter monitor devices for simultaneous recordings. One Holter device recorded a standard Mason-Likar 12-lead electrocardiogram (ECG) and the other recorded a 10-electrode lead set considered optimal for ischemia detection. A body surface potential map was then estimated from the optimal lead set. Results At 1 year, 2 of the 5 patients with missed ischemia died and a third had an acute myocardial infarction (MI) (40% mortality, 60% death/nonfatal MI). In comparison, 1-year mortality was 5.7% in 159 similar patients treated for unstable angina at the same institution over the same period ( P = .037). The initial standard ECG showed no abnormalities in 3 patients and showed left ventricular hypertrophy in 1. The fifth patient with a history of recent MI had slight ST elevation in leads III and aVF and Q waves that were considered indicative of recent (not acute) MI. EBSPM data recorded at the time of ED presentation matched the standard ECG (normal in 3, left ventricular hypertrophy or inconclusive in 2). During transient ischemia, all 5 EBSPMs showed areas of ischemia overlapping with standard electrode sites. Conclusion Patients evaluated in the ED for chest pain are at high risk for death or nonfatal MI if they have ischemic events with continuous ST-segment monitoring that are unrecognized clinically. In this small cohort with unrecognized ischemia, the initial body surface potential maps estimated from optimal ischemia electrode sites did not improve on 12-lead ST-segment monitoring to identify this high-risk group.

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

In this study, several methods for optimal lead selection from multilead electrocardiographic recordings are analyzed. Two different lead selection methods have been implemented. For their evaluation, a linear transformation that reconstructs nonselected leads from selected leads is computed according to the least squares optimization, and the performance is evaluated in terms of the mean square error of the derived potentials and correlation. The algorithms were tested on a database of 72 body surface potential recordings: 18 controls, 18 bundle-branch block, 18 myocardial infarction, and 18 ventricular hypertrophy. Each data set was divided into a study and test subsets. Two experiments were carried out: (1) The lead selection, transformation matrix, and performance evaluation is carried out over the test data set (ideal case), and (2) the lead selection and transformation matrix is carried out over the study data set, but the performance is evaluated over the test data set (real case). Our results show important reconstruction errors with either lead selection methods, and only increasing the number of leads reduces the error in reconstruction. However, if a reduced number of leads are to be selected outside the standard 12-lead electrocardiogram, the method proposed by Lux has been shown to be the best option.

A training whole-heart model for simulating propagation and ECG patterns

The forward problem of electrocardiography describes the spatio-temporal source–field relationship generating the body surface potential (BSP) and, thus, the electrocardiogram (ECG). The paper presents a ventricular and atrial model for simulating cardiac de- and repolarization and the P-, QRS- and T-wave. The atria and the ventricles are coupled, so that electroanatomical function can be simulated at ones. Movement and contraction are not taken into account while an individual geometry, fibre architecture and ECG sensor arrangement including the Wilson central terminal (WCT) as common reference were considered. This in silico whole-heart model can be used for detailed investigations of the nature of the ECG for the normal beat, arrhythmias, ischemia and infarction. In addition, this model was used as a reference tool for developing and testing different electrocardiographic inverse approaches.

On the possibility for computing the transmembrane potential in the heart with a one shot method: An inverse problem

We analyze the possibility for using body surface potential maps (BSPMs), a priori information about the voltage distribution in the heart and the bidomain equations to compute the transmembrane potential throughout the myocardium. Our approach is defined in terms of an inverse problem for elliptic partial differential equations (PDEs). More precisely, we formulate it in terms of an output least squares framework in which a goal functional is minimized subject to suitable PDE constraints. The problem is highly unstable and, even under optimal recording conditions, it does not have a unique solution. We propose a methodology for stabilizing and enforcing uniqueness for this inverse problem. Moreover, a fully implicit method for solving the involved minimization problem is presented. In other words, we show how one may solve it in terms of a system consisting of three linear elliptic PDEs, i.e. we derive a so-called one shot method (also commonly referred to as an all-at-once method). Finally, our theoretical findings are illuminated by a series of numerical experiments. These examples indicate that, in the presence of regional ischemia, it might be possible to approximately recover the transmembrane potential during the resting and plateau phases of the heart cycle. This is probably due to the fact that rather accurate a priori information is available during these time intervals. The problem of computing the transmembrane potential at an arbitrary time instance during a heart beat is still an open problem.

Spatial frequency characteristics of body surface potentials during atrial fibrillation

Spatial frequency characteristics of body surface potentials during atrial fibrillation

Focal atrial tachycardia after pulmonary vein isolation: Noninvasive mapping with electrocardiographic imaging (ECGI)

Electrocardiographic imaging (ECGI) is a novel, noninvasive tool for imaging cardiac arrhythmia and defining electrophysiologic properties.1,2 ECGI combines multi-electrode body surface ECG recordings with three-dimensional anatomical heart-torso imaging to reconstruct an epicardial electroanatomical map (Figure 1). ECGI-reconstructed data can be presented as epicardial potential maps, electrograms, or isochrones during activation and repolarization. The ECGI procedure has been extensively tested and validated in experimental preparations with normal and abnormal canine hearts3–10. Recently, ECGI has been validated in humans1,2,11–13. To date, we have presented human ECGI studies of normal activation and repolarization 1,2, right and left bundle branch block1,11, various pacing protocols1,11,13, atrial flutter1, native sinus rhythm and bi-ventricular pacing for cardiac resynchronization (CRT) in heart failure patients11, and focal ventricular tachycardia12. Figure 1 The ECGI procedure. Body surface potential maps (BSPM) are recorded using a multi-channel (256-electrode) mapping system. Non-contrast CT images with the body surface ECGI electrodes applied, simultaneously record the locations of the electrodes (shining ... This report describes the first case in which ECGI was applied in a patient with a focal atrial tachycardia. In particular, ECGI accurately located the earliest site of activation in an atrium which had previously undergone two percutaneous pulmonary vein isolation procedures. The tachyarrhythmia was successfully terminated with radio frequency (RF) ablation in the ECGI-determined location.

Optimizing the 12-lead electrocardiogram: a data driven approach to locating alternative recording sites

Background Despite its widespread use, the limitations of the 12-lead electrocardiogram (ECG) are undisputed. The main deficiency is that just a small area of the precordium is interrogated and for some abnormalities information may be transmitted to a region of the body surface where information is not recorded. In this study, we attempted to optimize the 12-lead ECG by using a data-driven approach to suggest alternate recording sites. Methods A sequential lead selection algorithm was applied to a set of 744 body surface potential maps (BSPMs), consisting of recordings from subjects with myocardial infarction, left ventricular hypertrophy, and no apparent disease. A number of scenarios were investigated in which pairs of precordial leads were repositioned; these pairs were V 3 and V 5, V 4 and V 5, and V 4 and V 6. The algorithm was also used to find optimal positions for all 6 precordial leads. Result Through estimation of entire surface potential distributions it was found that each of the scenarios, with 2 leads repositioned, captured more information than the standard 12-lead ECG. The scenario with V 4 and V 6 repositioned performed best with a root mean square error of 22.3 microvolts and a correlation coefficient of 0.967. This configuration also fared favorably when compared to the scenario where all 6 precordial leads were repositioned as optimizing all 6 leads offered no significant improvement. Conclusion This study demonstrated the use of a lead selection algorithm in enhancing the 12-lead ECG. The results also indicated that repositioning just 2 precordial leads can provide the same level of information capture as that observed when all precordial leads are optimally placed.

Principal Component Analysis in ECG Signal Processing

This paper reviews the current status of principal component analysis in the area of ECG signal processing. The fundamentals of PCA are briefly described and the relationship between PCA and Karhunen-Loève transform is explained. Aspects on PCA related to data with temporal and spatial correlations are considered as adaptive estimation of principal components is. Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrial fibrillation, and analysis of body surface potential maps.

Combination of the LSQR method and a genetic algorithm for solving the electrocardiography inverse problem

Computing epicardial potentials from body surface potentials constitutes one form of ill-posed inverse problem of electrocardiography (ECG). To solve this ECG inverse problem, the Tikhonov regularization and truncated singular-value decomposition (TSVD) methods have been commonly used to overcome the ill-posed property by imposing constraints on the magnitudes or derivatives of the computed epicardial potentials. Such direct regularization methods, however, are impractical when the transfer matrix is large. The least-squares QR (LSQR) method, one of the iterative regularization methods based on Lanczos bidiagonalization and QR factorization, has been shown to be numerically more reliable in various circumstances than the other methods considered. This LSQR method, however, to our knowledge, has not been introduced and investigated for the ECG inverse problem. In this paper, the regularization properties of the Krylov subspace iterative method of LSQR for solving the ECG inverse problem were investigated. Due to the ‘semi-convergence’ property of the LSQR method, the L-curve method was used to determine the stopping iteration number. The performance of the LSQR method for solving the ECG inverse problem was also evaluated based on a realistic heart–torso model simulation protocol. The results show that the inverse solutions recovered by the LSQR method were more accurate than those recovered by the Tikhonov and TSVD methods. In addition, by combing the LSQR with genetic algorithms (GA), the performance can be improved further. It suggests that their combination may provide a good scheme for solving the ECG inverse problem.

Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals

A three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.

Classification of Body Surface Potential Maps: A Comparison of Isointegral Measurements in the Diagnosis of Old Myocardial Infarction

The electrocardiogram (ECG) is one of the most common ways to record, in an non-invasive manner, a patient’s cardiac activity. Once recorded the information can be pre-processed and subsequently analyzed to assess if the patient is suffering from any forms of cardiac abnormality which may require clinical intervention. In the current study we investigate ways in which more can be obtained from the ECG through analysis of the diagnostic properties of body surface potential maps (BSPM). A set of 192 lead BSPMs recorded from a mixture of 116 normal and abnormal subjects (59 normal vs 57 old myocardial infarction) were analyzed. For each patient, diagnostic features were obtained by calculating isointegral measurements from the QRS, STT, and entire QRST segments. These isointegrals provide a measure of the mean distribution of potential during ventricular depolarization, repolarisation, and a combination of both, respectively. For each isointegral type, 192 discrete measurements, and hence 192 features, were obtained; these correspond with the 192 leads recorded. Subsequent to this a signal-to-noise ratio-based feature ranking methodology was applied to select subsets of the best three, six and ten measurements (features) from the 192 available for each isointegral. These subsets of features were then applied to four different classifiers Naive Bayes (NB), support vector machine (SVM), multi-layer perceptron (MLP) and random forest (RF) and in each application ten-fold cross validation was employed. It was found that when using the subsets of features obtained from the STT or QRST isointegrals, classification results in excess of 80% were attainable. This was in contrast to the results obtained using the QRS isointegral features where poorer performance (between 62.9% and 74.1%) was observed. The results from this study have illustrated that, for the studied dataset, the mean distribution of potentials during ventricular depolarization, and during ventricular repolarization and depolarization combined possessed greater diagnostic information. Overall it was concluded that this approach to BSPM analysis does provide a useful means for illustrating the usefulness of various features in diagnostic classification.

Noninvasive assessment of local myocardium repolarization changes using high-resolution surface ECG mapping

A method using body surface potential maps for assessment of myocardium lesions with changed repolarization is presented and suitable mapping system is introduced. Differences between normal and altered QRST integral maps together with torso volume conductor model were used to determine the equivalent dipole representing the lesion. Performance of the method was studied on simulated data. Changed repolarization was modeled by shortening of myocyte action potentials in regions typical for stenosis of the main coronary arteries. The equivalent dipole estimated the positions of small lesions with a mean error of 9+/-4 mm (17+/-14 mm for larger transmural lesions). The subepicardial or subendocardial character of the lesions was reflected in the dipole orientation. Tests of the method on patients after myocardial infarction that underwent coronary intervention on a single coronary vessel showed that in 7 of 8 successfully treated patients the dipole position matched well with the treated vessel. A small dipole moment in another patient indicated unsuccessful treatment. The method was implemented in a new 128-channel mapping system. Its active electrodes, battery powered measuring unit and optical computer interface help to minimize noise in ECG and guarantee patient's safety. The results suggest that the method and mapping system offer useful tools for noninvasive identification of local repolarization changes in the myocardium.

Model-based inferences for clinical applications of the ECG

Doctor Macchi reported on the progress of an animal model study of electric propagation initiated by electric stimuli. Doctor Oostendorp first gave an introduction to the inverse problem of cardiac activation time mapping (ATM), the determination of the depolarization times at the myocardial surface as computed from the equivalent double layer (EDL) source model, and a biophysical model of the volume conductor involved: the passive conductive tissues inside the thorax. Doctor van Oosterom presented some results from an ongoing study aimed at extracting more information about the atrial electric activity from potentials observed on the body surface: the ECG. Doctor Zabel discussed the potential of using a standard 12-lead ECG device for estimating body surface potential maps.