Kim Simelius

Magnetocardiographic and Electrocardiographic Exercise Mapping in Healthy Subjects

AbstractIn 12-lead electrocardiography (ECG), detection of myocardial ischemia is based on ST-segment changes in exercise testing. Magnetocardiography (MCG) is a complementary method to the ECG for a noninvasive study of the electric activity of the heart. In the MCG, ST-segment changes due to stress have also been found in healthy subjects. To further study the normal response to exercise, we performed MCG mappings in 12 healthy volunteers during supine bicycle ergometry. We also recorded body surface potential mappings (BSPM) with 123 channels using the same protocol. In this paper we compare, for the first time, multichannel MCG recorded in bicycle exercise testing with BSPM over the whole thorax in middle-aged healthy subjects. We quantified changes induced by the exercise in the MCG and BSPM with parameters based on signal amplitude, and correlation between signal distributions at rest and after exercise. At the ST-segment and T-wave apex, the exercise induced a magnetic field component outward the precordium and the minimum value of the MCG signal over the mapped area was found to be amplified. The response to exercise was smaller in the BSPM than in the MCG. A negative component in the MCG signal at the repolarization period of the cardiac cycle should be considered as a normal response to exercise. Therefore, maximum ST-segment depression over the mapped area in the MCG may not be an eligible parameter when evaluating the presence of ischemia.

ST-segment level and slope in exercise-induced myocardial ischemia evaluated with body surface potential mapping.

Body surface potential mapping (BSPM) is superior to 12-lead electrocardiography for detection of acute and old myocardial infarctions (MIs). We used BSPM to examine electrocardiographic criteria for acute reversible myocardial ischemia. BSPM with 123 channels was performed in 45 patients with coronary artery disease (CAD) and 25 healthy controls during supine bicycle exercise testing. Of the 45 patients, 18 patients had anterior, 14 had posterior, and 13 had inferior ischemia documented by coronary angiography and thallium scintigraphy. The ST amplitude was measured 60 ms after the J-point and the ST slope calculated by fitting a regression line from the J-point to 60 ms after it. The optimal locations for detecting ST depression and ST-slope decrease were identified. In the pooled CAD patient group, the optimal location for ST depression was 5 cm below standard lead V(5) (CAD group: -70 +/- 70 microV; controls: 70 +/- 80 microV, p <0.001). Using a cut-off value of -10 microV, the ST depression separated the patients with CAD from controls with a sensitivity of 84% and a specificity of 96%. The ST slope became more horizontal in the patient group than in the control group. The optimal location for ST-slope decrease was over the left side (CAD group: 20 +/- 20 microV/s; controls: 720 +/- 320 microV/s, p <0.001). Using a cut-off value of 320 microV/s, the ST slope separated patients with CAD from controls with a sensitivity of 93% at a specificity level of 88%. The area under the receiver operating characteristic curve of ST slope tended to be higher than the one of ST depression (97% vs 93%; p = 0.097). In conclusion, regions sensitive for ST depression and for ST-slope decrease could be identified in BSPM, despite variation in the location of ischemia and the presence or absence of a history of MI. ST slope is a sensitive and specific marker of transient myocardial ischemia, and might perform even better than ST depression.

Arrhythmia localization using body surface potential mapping during catheterization

The authors describe the use of a new body surface potential mapping (BSPM) system for arrhythmia treatment in Helsinki University Central Hospital. First, the implementation of the mapping system is presented. Then, the methods clinical use is described and finally, the benefits for radiofrequency ablation therapy are considered.

Non-invasive arrhythmia risk evaluation in clinical environment

Summary We have applied various methods to extract parameters from high-resolution magnetocardiographic (MCG) and electrocardiographic (ECG) recordings for characterizing the risk of life-threatening arrhythmias. The methods include detection of late fields and late potentials at the end of the QRS, abnormalities in spectral variability and signal fragmentation during the QRS, and variability in the heart rate. In addition, we have developed methods to convert MCG signals measured with any sensor configurations to a common presentation form. The signal processing methods have been implemented on a user-friendly interface which allows fast and easy use in a clinical environment.

Self-organizing maps in arrhythmia localization from body surface potential mapping

The authors have developed a novel method for ventricular tachycardia (VT) source localization using body surface potential mapping (BSPM). Kohonen self-organizing maps (SOM) are utilized for the classification of different types of VTs. The method is a two-step process. First, a large number of potential patterns from VT QRS complexes are presented to the SOM. Second, QRS time traces on this SOM are created to find the representative patterns for different types of VT. The localization can be performed using these time traces as a reference. The presented method utilizes both spatial and temporal aspects of the recorded VT to create a representative pattern of the tachycardia. The data was obtained from 27 patients with ventricular tachycardia; 21 were used for the teaching set and 6 for the test set. Results comparable to the well-documented integral map method were obtained in this study.

Simulation of Anisotropic Propagation in the Myocardium with a Hybrid Bidomain Model

We describe simulations of propagated electrical excitation in three-dimensional anisotropic myocardial muscle. According to the bidomain theory, anisotropic electrical conductivities are presented as tensors in the intracellular and interstitial domains (Di and De, respectively). Under the assumption of equal anisotropy ratio (Di = kDe), subthreshold behaviour of the excitable elements is governed by a parabolic reaction-diffusion equation for the membrane potential, solvable even on a desktop computer. In the case of more general anisotropies (Di ? kDe), also the interstitial potential needs to be solved simultaneously from an elliptic partial differential equation, requiring a supercomputer for large arrays of excitable elements. In both cases, the elements obey cellular automata rules in the suprathreshold state. We present preliminary results of the propagated excitation for different anisotropy ratios in a three-dimensional slab geometry.

Late QRS Activity in Signal‐Averaged Magnetocardiography, Body Surface Potential Mapping, and Orthogonal ECG in Postinfarction Ventricular Tachycardia Patients

Background: Delayed electrical activity necessary for re‐entrant ventricular tachycardia (VT) is detectable noninvasively with high resolution techniques. We compared high resolution signalaveraged analysis of magnetocardiography (MCG), body surface potential mapping (BSPM), and orthogonal three‐lead ECG (SA‐ECG) in the identification of patients prone to VT after myocardial infarction (Ml).

Baseline reconstruction for localization of rapid ventricular tachycardia from body surface potential maps

Determination of an accurate electrocardiographic (ECG) baseline is generally needed for localization of ventricular arrhythmias with body surface potential mapping (BSPM). We suggest a novel signal processing method for ECG baseline reconstruction during monomorphic ventricular tachycardias (VT). The method is based on an assumption that VT consists of similar ventricular extrasystolic beats with overlapping depolarization and repolarization. The sequential reconstruction algorithm utilizes information of small variations in the heart rate and yields a non-overlapping QRST-signal, provided that the measurement set-up has a high enough temporal resolution to avoid distortions due to sampling differences and misalignment of individual beats. The reconstructed QRST-signal is utilized to subtract overlapping T-waves from the QRS complexes during VT. The use of the method is demonstrated with clinically measured BSPM data.

Spatiotemporal characterization of paced cardiac activation with body surface potential mapping and self-organizing maps

In this study self-organizing maps (SOM) were utilized for spatiotemporal analysis and classification of body surface potential mapping (BSPM) data. Altogether 86 cardiac depolarization (QRS) sequences paced by a catheter in 18 patients were included. Spatial BSPM distributions at every 5 ms over the QRS complex were first presented to an untrained SOM. The learning process of the SOM units organized the maps in such a way that similar BSPMs are represented in particular areas of the SOM network. Thereafter, time trajectories and distance maps were created on the trained SOM from sequential maps in a selected paced QRS. The trajectories and distance maps can be applied as such for the localization of abnormal ventricular activation, as well as quantitative input for statistical classification. The results indicate that the method has potential for locating endocardial sites of abnormal ventricular activation, despite the patient material being too limited to provide a reliable statistical evaluation of the source localization accuracy.

Classification of body surface potential map sequences during ventricular activation using Kohonen networks

The authors present a new method based on Kohonen networks for the analysis and classification of body surface potential map (BSPM) sequences. First, BSPM sequences obtained from a time interval of the cardiac cycle (e.g. QRS, ST) are presented to an untrained Self-Organizing Map (SOM). During the learning process the SOM units organize in such a way that similar BSPMs are represented in particular areas of the SOM. Time traces from the cardiac activation are then created on the trained SOM and forwarded to a Learning Vector Quantization network for final classification. In this paper the method was applied to BSPM sequences obtained during catheter pace mappings with the aim to noninvasively localize sources of ventricular tachycardia.