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

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.

Real-Time Magnetocardiography with Passive Miniaturized Coil Array in Earth Ambient Field

We demonstrate a magnetocardiography (MCG) sensor that operates in non-shielded environments, in real-time, and without the need for an accompanying device to identify the cardiac cycles for averaging. We further validate the sensor's performance on human subjects. Our approach integrates seven (7) coils, previously optimized for maximum sensitivity, into a coil array. Based on Faraday's law, magnetic flux from the heart is translated into voltage across the coils. By leveraging digital signal processing (DSP), namely, bandpass filtering and averaging across coils, MCG can be retrieved in real-time. Our coil array can monitor real-time human MCG with clear QRS complexes in non-shielded environments. Intra- and inter-subject variability tests confirm repeatability and accuracy comparable to gold-standard electrocardiography (ECG), viz., a cardiac cycle detection accuracy of >99.13% and averaged R-R interval accuracy of <5.8 ms. Our results confirm the feasibility of real-time R-peak detection using the MCG sensor, as well as the ability to retrieve the full MCG spectrum as based upon the averaging of cycles identified via the MCG sensor itself. This work provides new insights into the development of accessible, miniaturized, safe, and low-cost MCG tools.

Identification of malignant early repolarization pattern by late QRS activity in high-resolution magnetocardiography

Background

The early repolarization pattern (ERP) in electrocardiography (ECG) has been considered as a risk for ventricular fibrillation (VF), but effective methods for identification of malignant ERP are still required. We investigated whether high spatiotemporal resolution 64‐channel magnetocardiography (MCG) would enable distinction between benign and malignant ERPs.

Methods

Among all 2,636 subjects who received MCG in our facility, we identified 116 subjects (43 ± 18 years old, 54% male) with inferior and/or lateral ERP in ECG and without structural heart disease, including 13 survivors of VF (ERP‐VF(+)) and 103 with no history of VF (ERP‐VF(−)). We measured the following MCG parameters in a time‐domain waveform of relative current magnitude: (a) QRS duration (MCG‐QRSD), (b) root‐mean‐square of the last 40 ms (MCG‐RMS40), and (c) low amplitude (<10% of maximal) signal duration (MCG‐LAS).

Results

Compared to ERP‐VF(−), ERP‐VF(+) subjects presented a significantly longer MCG‐QRS (108 ± 24 vs. 91 ± 23 ms, p = .02) and lower MCG‐RMS40 (0.10 ± 0.08 vs. 0.25 ± 0.20, p = .01) but no difference in MCG‐LAS (38 ± 22 vs. 29 ± 23 ms, p = .17). MCG‐QRSD and MCG‐RMS40 showed significantly larger area under the ROC curve compared to J‐peak amplitude in ECG (0.72 and 0.71 vs. 0.50; p = .04 and 0.03). The sensitivity, specificity, and odds ratio for identifying VF(+) based on MCG‐QRSD ≥ 100 ms and MCG‐RMS40 ≤ 0.24 were 69%, 74%, and 6.33 (95% CI, 1.80–22.3), and 92%, 48%, and 10.9 (95% CI, 1.37–86.8), respectively.

Conclusion

Magnetocardiography is an effective tool to distinguish malignant and benign ERPs.

Signal Space Separation Method for a Biomagnetic Sensor Array Arranged on a Flat Plane for Magnetocardiographic Applications: A Computer Simulation Study

Although the signal space separation (SSS) method can successfully suppress interference/artifacts overlapped onto magnetoencephalography (MEG) signals, the method is considered inapplicable to data from nonhelmet-type sensor arrays, such as the flat sensor arrays typically used in magnetocardiographic (MCG) applications. This paper shows that the SSS method is still effective for data measured from a (nonhelmet-type) array of sensors arranged on a flat plane. By using computer simulations, it is shown that the optimum location of the origin can be determined by assessing the dependence of signal and noise gains of the SSS extractor on the origin location. The optimum values of the parameters L_C and L_D, which, respectively, indicate the truncation values of the multipole-order ℓ of the internal and external subspaces, are also determined by evaluating dependences of the signal, noise, and interference gains (i.e., the shield factor) on these parameters. The shield factor exceeds 10⁴ for interferences originating from fairly distant sources. However, the shield factor drops to approximately 100 when calibration errors of 0.1% exist and to 30 when calibration errors of 1% exist. The shielding capability can be significantly improved using vector sensors, which measure the x, y, and z components of the magnetic field. With 1% calibration errors, a vector sensor array still maintains a shield factor of approximately 500. It is found that the SSS application to data from flat sensor arrays causes a distortion in the signal magnetic field, but it is shown that the distortion can be corrected by using an SSS-modified sensor lead field in the voxel space analysis.

A portable prototype magnetometer to differentiate ischemic and non-ischemic heart disease in patients with chest pain

BACKGROUND

Magnetocardiography (MCG) is a non-invasive technique used to measure and map cardiac magnetic fields. We describe the predictive performance of a portable prototype magnetometer designed for use in acute and routine clinical settings. We assessed the predictive ability of the measurements derived from the magnetometer for the ruling-out of healthy subjects and patients whose chest pain has a non-ischemic origin from those with ischemic heart disease (IHD).

METHODS

MCG data were analyzed from a technical performance study, a pilot clinical study, and a young healthy reference group. Participants were grouped to enable differentiation of those with IHD versus non-IHD versus controls: Group A (70 IHD patients); Group B (69 controls); Group C (37 young healthy volunteers). Scans were recorded in an unshielded room. Between-group differences were explored using analysis of variance. The ability of 10 candidate MCG predictors to predict normal/abnormal cases was analyzed using logistic regression. Predictive performance was internally validated using repeated five-fold cross-validation.

RESULTS

Three MCG predictors showed a significant difference between patients and age-matched controls (P<0.001); eight predictors showed a significant difference between patients and young healthy volunteers (P<0.001). Logistic regression comparing patients with controls yielded a specificity of 35.0%, sensitivity of 95.4%, and negative predictive value for the ruling-out of IHD of 97.8% (area under the curve 0.78).

CONCLUSION

This analysis represents a preliminary indication that the portable magnetometer can help rule-out healthy subjects and patients whose chest pain has a non-ischemic origin from those with IHD.

Isolated Late Activation Detected by Magnetocardiography Predicts Future Lethal Ventricular Arrhythmic Events in Patients With Arrhythmogenic Right Ventricular Cardiomyopathy

BACKGROUND

Risk stratification of ventricular arrhythmias is vital to the optimal management in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC). We hypothesized that 64-channel magnetocardiography (MCG) would be useful to detect isolated late activation (ILA) by overcoming the limitations of conventional noninvasive predictors of ventricular tachyarrhythmias, including epsilon waves, late potential (LP), and right ventricular ejection fraction (RVEF), in ARVC patients.Methods and Results:We evaluated ILA on MCG, defined as discrete activations re-emerging after the decay of main RV activation (%magnitude >5%), and conventional noninvasive predictors of ventricular tachyarrhythmias (epsilon waves, LP, and RVEF) in 40 patients with ARVC. ILA was noted in 24 (60%) patients. Most ILAs were found in RV lateral or inferior areas (17/24, 71%). We defined "delayed ILA" as ILA in which the conduction delay exceeded its median (50 ms). During a median follow-up of 42.5 months, major arrhythmic events (MAEs: 1 sudden cardiac death, 3 sustained ventricular tachycardias, and 4 appropriate implantable cardioverter defibrillator discharges) occurred more frequently in patients with delayed ILA (6/12) than in those without (2/28; log-rank: P=0.004). Cox regression analysis identified delayed ILA as the only independent predictor of MAEs (hazard ratio 7.63, 95% confidence interval 1.72-52.6, P=0.007), and other noninvasive parameters were not significant predictors.

CONCLUSIONS

MCG is useful to identify ARVC patients at high risk of future lethal ventricular arrhythmias.

Unshielded magnetocardiography: Repeatability and reproducibility of automatically estimated ventricular repolarization parameters in 204 healthy subjects

BACKGROUND

Magnetocardiographic mapping (MCG) provides quantitative assessment of the magnetic field (MF) induced by cardiac ionic currents, is more sensitive to tangential currents, and measures vortex currents undetectable by ECG, with higher reported sensitivity of MCG ventricular repolarization (VR) parameters for earlier detection of acute myocardial ischemia. Aims of this study were to validate the feasibility of in-hospital unshielded MCG and to assess repeatability and reproducibility of quantitative VR parameters, considering also possible gender- and age-related variability.

METHODS

MCG of 204 healthy subjects [114 males-mean age 43.4 ± 17.3 and 90 females-mean age 40.2 ± 15.7] was retrospectively analyzed, with a patented proprietary software automatically estimating twelve VR parameters derived from the analysis of the dynamics of the T-wave MF extrema (five parameters) and from the inverse solution with the effective magnetic dipole model giving the effective magnetic vector components (seven parameters). MCG repeatability was calculated as coefficient of variation (CV) ±standard error of the mean (SEM). Reproducibility was assessed as intraclass correlation coefficient (ICC).

RESULTS

The repeatability of all MCG parameters was 16 ± 1.2 (%) (average CV ± SEM). Optimal (ICC > 0.7) reproducibility was found for 11/12 parameters (mean values) and in 8/12 parameters (single values). No significant gender-related difference was observed; six parameters showed a strong/moderate correlation with age.

CONCLUSION

Reliable MCG can be performed into an unshielded hospital ambulatory, with repeatability and reproducibility of quantitative assessment of VR adequate for clinical purposes. Wider clinical use is foreseen with the development of multichannel optical magnetometry.

Utility of High-Resolution Magnetocardiography to Predict Later Cardiac Events in Nonischemic Cardiomyopathy Patients With Normal QRS Duration

BACKGROUND

Nonischemic dilated cardiomyopathy (NIDCM) patients, even those with a narrow QRS, are at increased risk for major adverse cardiac events (MACE). We hypothesized that 64-channel magnetocardiography (MCG) would be useful to detect prognostic left intraventricular disorganized conduction (LiDC) by overcoming the limitations of fragmented QRS (fQRS, qualitative definitions, low specificity) and late potential (abnormality undetectable in earlier QRS).Methods and Results:We evaluated LiDC on MCG, defined as significant deviation from a global clockwise left ventricular (LV) activation pattern, and conventional noninvasive predictors of MACE, including fQRS and late potential, in 51 NIDCM patients with narrow QRS (LV ejection fraction, 22±7%; QRS duration, 99±11 ms). MACE was defined as cardiac death, lethal ventricular arrhythmias, or LV assist device (LVAD) implantation. LiDC was present in 22 patients. Baseline characteristics were comparable between patients with and without LiDC, except for the ratio of positive late potential. During a mean follow-up of 2.9 years, MACE developed in 16 NIDCM patients (3 cardiac deaths, 9 lethal ventricular arrhythmias, and 4 LVAD). MACE was more incident in patients with LiDC (13/22) than in those without (3/29, P<0.001). Multivariate analysis revealed LiDC, but not fQRS or late potential, as the strongest independent predictor of MACE (hazard ratio 4.28, 95% confidence interval 1.30-19.39, P=0.015).

CONCLUSIONS

MCG accurately depicts LiDC, a promising noninvasive predictor of MACE in patients with NIDCM and normal QRS.

Comparison of Electric- and Magnetic-Cardiograms Produced by Myocardial Ischemia in Models of the Human Ventricle and Torso

Myocardial ventricular ischemia arises from a lack of blood supply to the heart, which may cause abnormal repolarization and excitation wave conduction patterns in the tissue, leading to cardiac arrhythmias and even sudden death. Current diagnosis of cardiac ischemia by the 12-lead electrocardiogram (ECG) has limitations as they are insensitive in many cases and may show unnoticeable differences to normal patterns. As the magnetic field provides extra information on cardiac excitation and is more sensitive to tangential currents to the surface of the chest, whereas the electric field is more sensitive to flux currents, it has been hypothesized that the magnetocardiogram (MCG) may provide a complementary method to the ECG in ischemic diagnosis. However, it is unclear yet about the differences in sensitivity regions of body surface ECG and MCG signals to ischemic conditions. The aim of this study was to investigate such differences by using 12-, 36- ECG and 36-MCG computed from multi-scale biophysically detailed computational models of the human ventricles and torso in both control and ischemic conditions. It was shown that ischemia produced changes in the ECG and MCG signals in the QRS complex, T-wave and ST-segment, with greater relative differences seen in the 36-lead ECG and MCG as compared to the 12-leads ECG (34% and 37% vs 26%, respectively). The 36-lead ECG showed more averaged sensitivity than the MCG in the change of T-wave due to ischemia (37% vs 32%, respectively), whereas the MCG showed greater sensitivity than the ECG in the change of the ST-segment (50% vs 40%, respectively). In addition, both MCG and ECG showed regional-dependent changes to ischemia, but with MCG showing a stronger correlation between ischemic region in the heart. In conclusion, MCG shows more sensitivity than ECG in response to ischemia, which may provide an alternative method for the diagnosis of ischemia.

Subtraction magnetocardiogram for detecting coronary heart disease

BACKGROUND

A large-scale magnetocardiogram (MCG) database was produced, and standard MCG waveforms of healthy patients were calculated by using this database. It was clarified that the standard MCG waveforms are formed with the same shape and current distribution in healthy patients. A new subtraction method for detecting abnormal ST-T waveforms in coronary heart disease (CHD) patients by using the standard MCG waveform was developed.

METHODS

We used MCGs of 56 CHD patients (63 ± 3 years old) and 101 age-matched normal control patients (65 ± 5 years old). To construct a subtracted ST-T waveform, we used standard MCG waveforms produced from 464 normal MCGs (male: 268, female: 196). The standard MCG waveforms were subtracted from each subject's measured MCGs, which were shortened or lengthened and normalized to adjust to the data length and magnitude of the standard waveform. We evaluated the maximum amplitude and maximum current-arrow magnitude of the subtracted ST-T waveform.

RESULTS

The maximum magnetic field, maximum magnitude of current arrows, and maximum magnitude of total current vector increased according to the number of coronary artery lesions. The sensitivity and specificity of detecting CHD and normal control patients were 74.6% and 84.1%, respectively.

CONCLUSIONS

The subtraction MCG method can be used to detect CHD with high accuracy, namely, sensitivity of 74.6% and specificity of 84.1% (in the case of maximum amplitude of total current vector). Furthermore, the subtraction MCG magnitude and its current distribution can reflect the expanse of the ischemic lesion area and the progress from ischemia to myocardial infarction.

Standard template of adult magnetocardiogram

BACKGROUND

We need to know the magnetocardiogram (MCG) features regarding waveform and two-dimensional current distribution in normal subjects in order to classify the abnormal waveform in patients with heart disease. However, a standard MCG waveform has not been produced yet, therefore, we have first made the standard template MCG waveform.

METHODS AND RESULTS

We used data from 464 normal control subjects' 64-channel MCGs (268 males, 196 females) to produce a template MCG waveform. The measured data were averaged after shortening or lengthening and normalization. The time interval and amplitude of the averaged data were adjusted to mean values obtained from a database. Furthermore, the current distributions (current arrow maps [CAMs]) were calculated from the produced templates to determine the current distribution pattern. The produced template of the QRS complex had a typical shape in six regions that we defined (M1, M2, M3, M4, M5, and M6). In the P wave, the main current arrow in CAMs pointing in a lower-left direction appeared in M1. In the QRS complex, the typical wave appeared in each region, and there were two main current arrows in M2 and M5. There were negative T waves in M1, M4, and M5, and positive T waves in M3 and M6, and the main current arrow pointing in a lower-left direction appeared in M2.

CONCLUSION

Template MCG waveforms were produced. These morphologic features were classified into six regions, and the current distribution was characterized in each region. Consequently, the templates and classifications enable understanding MCG features and writing clinical reports.