Magnetocardiographic localization of ventricular pre-excitation in a child with a congenital heart defect

The magnetocardiogram

The magnetic field produced by the heart's electrical activity is called the magnetocardiogram (MCG). The first 20 years of MCG research established most of the concepts, instrumentation, and computational algorithms in the field. Additional insights into fundamental mechanisms of biomagnetism were gained by studying isolated hearts or even isolated pieces of cardiac tissue. Much effort has gone into calculating the MCG using computer models, including solving the inverse problem of deducing the bioelectric sources from biomagnetic measurements. Recently, most magnetocardiographic research has focused on clinical applications, driven in part by new technologies to measure weak biomagnetic fields.

Space-time database for standardization of adult magnetocardiogram-making standard MCG parameters

BACKGROUND

The magnetocardiogram (MCG) is a promising medical tool for detecting and visualizing abnormal cardiac electrical activation in heart-disease patients. However, there is no large-scale MCG database of healthy subjects, and there is little knowledge of gender- and age-related influences on MCG data.

METHODS AND RESULTS

We obtained MCG data from 869 subjects (554 men, 315 women) using a conventional 64-channel MCG system, which covers the whole heart. Electrocardiogram (ECG) data were also obtained; 464 people (268 men, 196 women) were identified as a normal group using ECG data. Time intervals (PQ, QRS, QT, and QTc), current distributions (maximum current vector (MCV), and the total current vector (TCV)) of MCG data of the 464 normal subjects were analyzed to obtain basic MCG parameters. Although mean values of PQ and QRS intervals of the male subjects were slightly longer than those of the female subjects, no intervals were correlated with gender or age. The correlation between PQ intervals of ECG and those of MCG was better than the correlation between QRS and QT intervals of ECG and those of MCG. Both MCV and TCV angles were much smaller than the electrical-axis angle in ECG. Although TCVs of the QRS and T waves were stable, the women's mean T-wave-TCV angles significantly increased with age. The maximum amplitude of the P wave was about 1.7 pT, and the value of the QRS complex was about 20-25 pT. Moreover, the T-wave amplitude decreases with age.

CONCLUSION

The MCG standard space-time parameters determined here provide a normal range for MCG parameters.

Classifying cases of fetal Wolff-Parkinson-White syndrome by estimating the accessory pathway from fetal magnetocardiograms

The paper presents an evaluation of the possibility of using fetal magnetocardiogram (FMCG) signals to estimate and classify the accessory pathway in fetal Wolff-Parkinson-White (WPW) syndrome. The FMCG signals of two fetuses with WPW syndrome (type A) were detected using a 64-channel superconducting quantum-interference device system. An average across the cycles of these signals was taken to obtain clear WPW signals. To determine the direction and position of the accessory pathway in a fetal heart accurately, the accessory pathway and activated pathway at the peak of the QRS complex thus obtained were estimated for each fetus, using a single-dipole model. The phase angle (about 90 degrees) between the equivalent current dipoles (ECDs) was the same for both fetuses. This angle suggested that the accessory pathway is in the left side of the heart, i.e. that the pathway exists in the left ventricle, which indicates type A WPW syndrome. Identification of the position of the accessory pathway in a fetus with WPW syndrome from the angle between the ECD of the accessory pathway and the ECD of the peak in the QRS complex was thus demonstrated.

Magnetocardiographic localization of arrhythmia substrates: a methodology study with accessory pathway ablation as reference

In magnetocardiographic (MCG) localization of arrhythmia substrates, a model of the thorax as volume conductor is a crucial component of the calculations. In this study, we investigated different models of the thorax, to determine the most suitable to use in the computations. Our methods and results are as follows. We studied 11 patients with overt Wolff-Parkinson-White syndrome, scheduled for catheter ablation. The MCG registrations were made with a 37-channel "superconducting quantum interference device" system. The underlying equivalent current dipole was computed for the delta-wave. Three models of the thorax were used: the infinite halfspace, a sphere and a box. For anatomical correlation and to define the suitable sphere and box, magnetic resonance images were obtained. As reference we used the position of the tip of the catheter, at successful radio-frequency-ablation, documented by cine-fluoroscopy. Nine patients could be evaluated. The mean errors (range) when using the infinite halfspace, the sphere and the box were 96 (49-125), 21 (5-39), and 36 mm (20-58 mm), respectively (p < 0.0001). In conclusion, the sphere was significantly better suited than the other models tested in this study, but even with this model the accuracy of MCG localization must further improve to be clinically useful. More realistic models of the thorax are probably required to achieve this goal.

Transformation of multichannel magnetocardiographic signals to standard grid form

Multichannel magnetocardiographic (MCG) recordings with fixed sensor arrays are not directly comparable with single-channel measurements carried out at standard grid locations. In addition, comparison of data obtained with different types of magnetometers is difficult. We present a method for transforming multichannel measurements to the standard-grid format. The minimum-norm estimate (MNE) of the source current distribution in the body is calculated, and the desired field components in standard grid points are then computed from the MNE. We measured three subjects with both a 24-channel and a single-channel instrument. The signals extrapolated from the multichannel measurements corresponded quite well to the single-channel data registered at the standard grid locations, especially in those grid points that were covered by the 24-channel device. The signal-amplitude-weighted correlations between the extrapolated and directly measured signals were 0.73-0.87. In simulations with ideal measurement geometry but with a realistic amount of random noise in the signals, we obtained a 0.99 correlation. It was also found that the method is relatively tolerant to errors in the location and orientation of the multichannel magnetometer. For example, a simulated 20-mm displacement in the location of the sensor array caused only a 3% decrease in the correlation, and when it was rotated and tilted by 10 degrees C, the correlation decreased by 5%. The basic advantage of our extrapolation method is its physiologic nature: the method is based on the mathematical modeling of the source current distribution, rather than on direct constraints applied to the magnetic field.