Repolarization Heterogeneity of Magnetocardiography Predicts Long-Term Prognosis in Patients with Acute Myocardial Infarction

Accurate diagnosis of severe coronary stenosis based on resting magnetocardiography: a prospective, single-center, cross-sectional analysis

OBJECTIVE

To evaluate the role of resting magnetocardiography in identifying severe coronary artery stenosis in patients with suspected coronary artery disease.

METHODS

A total of 513 patients with angina symptoms were included and divided into two groups based on the extent of coronary artery disease determined by angiography: the non-severe coronary stenosis group (< 70% stenosis) and the severe coronary stenosis group (≥ 70% stenosis). The diagnostic model was constructed using magnetic field map (MFM) parameters, either individually or in combination with clinical indicators. The performance of the models was evaluated using receiver operating characteristic curves, accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Calibration plots and decision curve analysis were performed to investigate the clinical utility and performance of the models, respectively.

RESULTS

In the severe coronary stenosis group, QR_MCTDd, S_MDp, and TT_MAC50 were significantly higher than those in the non-severe coronary stenosis group (10.46 ± 10.66 vs. 5.11 ± 6.07, P < 0.001; 7.2 ± 8.64 vs. 4.68 ± 6.95, P = 0.003; 0.32 ± 57.29 vs. 0.26 ± 57.29, P < 0.001). While, QR_MVamp, R_MA, and T_MA in the severe coronary stenosis group were lower (0.23 ± 0.16 vs. 0.28 ± 0.16, P < 0.001; 55.06 ± 48.68 vs. 59.24 ± 53.01, P < 0.001; 51.67 ± 39.32 vs. 60.45 ± 51.33, P < 0.001). Seven MFM parameters were integrated into the model, resulting in an area under the curve of 0.810 (95% CI: 0.765-0.855). The sensitivity, specificity, PPV, NPV, and accuracy were 71.7%, 80.4%, 93.3%, 42.8%, and 73.5%; respectively. The combined model exhibited an area under the curve of 0.845 (95% CI: 0.798-0.892). The sensitivity, specificity, PPV, NPV, and accuracy were 84.3%, 73.8%, 92.6%, 54.6%, and 82.1%; respectively. Calibration curves demonstrated excellent agreement between the nomogram prediction and actual observation. The decision curve analysis showed that the combined model provided greater net benefit compared to the magnetocardiography model.

CONCLUSIONS

The novel quantitative MFM parameters, whether used individually or in combination with clinical indicators, have been shown to effectively predict the risk of severe coronary stenosis in patients presenting with angina-like symptoms. Magnetocardiography, an emerging non-invasive diagnostic tool, warrants further exploration for its potential in diagnosing coronary heart disease.

Clinical magnetocardiography: the unshielded bet-past, present, and future

Magnetocardiography (MCG), which is nowadays 60 years old, has not yet been fully accepted as a clinical tool. Nevertheless, a large body of research and several clinical trials have demonstrated its reliability in providing additional diagnostic electrophysiological information if compared with conventional non-invasive electrocardiographic methods. Since the beginning, one major objective difficulty has been the need to clean the weak cardiac magnetic signals from the much higher environmental noise, especially that of urban and hospital environments. The obvious solution to record the magnetocardiogram in highly performant magnetically shielded rooms has provided the ideal setup for decades of research demonstrating the diagnostic potential of this technology. However, only a few clinical institutions have had the resources to install and run routinely such highly expensive and technically demanding systems. Therefore, increasing attempts have been made to develop cheaper alternatives to improve the magnetic signal-to-noise ratio allowing MCG in unshielded hospital environments. In this article, the most relevant milestones in the MCG's journey are reviewed, addressing the possible reasons beyond the currently long-lasting difficulty to reach a clinical breakthrough and leveraging the authors' personal experience since the early 1980s attempting to finally bring MCG to the patient's bedside for many years thus far. Their nearly four decades of foundational experimental and clinical research between shielded and unshielded solutions are summarized and referenced, following the original vision that MCG had to be intended as an unrivaled method for contactless assessment of the cardiac electrophysiology and as an advanced method for non-invasive electroanatomical imaging, through multimodal integration with other non-fluoroscopic imaging techniques. Whereas all the above accounts for the past, with the available innovative sensors and more affordable active shielding technologies, the present demonstrates that several novel systems have been developed and tested in multicenter clinical trials adopting both shielded and unshielded MCG built-in hospital environments. The future of MCG will mostly be dependent on the results from the ongoing progress in novel sensor technology, which is relatively soon foreseen to provide multiple alternatives for the construction of more compact, affordable, portable, and even wearable devices for unshielded MCG inside hospital environments and perhaps also for ambulatory patients.

A movable unshielded magnetocardiography system

Magnetocardiography (MCG), which uses high-sensitivity magnetometers to record magnetic field signals generated by electrical activity in the heart, is a noninvasive method for evaluating heart diseases such as arrhythmia and ischemia. The MCG measurements usually require the participant keeping still in a magnetically shielded room due to the immovable sensor and noisy external environments. These requirements limit MCG applications, such as exercise MCG tests and long-term MCG observations, which are useful for early detections of heart diseases. Here, we introduce a movable MCG system that can clearly record MCG signals of freely behaving participants in an unshielded environment. On the basis of optically pumped magnetometers with a sensitivity of 140 fT/Hz1/2, we successfully demonstrated the resting MCG and the exercise MCG tests. Our method is promising to realize a practical movable multichannel unshielded MCG system that nearly sets no limits to participants and brings another kind of insight into the medical diagnosis of heart disease.

Effectiveness of magnetocardiography to identify patients in need of coronary artery revascularization: a cross-sectional study

BACKGROUND

Patients with angina-like symptoms need invasive or non-invasive angiography to determine whether revascularization is necessary. For patients in need of revascularization, undergoing coronary computed tomography angiography (CCTA) may delay the treatment of revascularization and increase exposure to contrast agents and radiation. The aim of this cross-sectional study was to accessed the effectiveness of magnetocardiography (MCG) to identify patients who should undergo coronary revascularization.

METHODS

A total of 203 patients who were suffering from angina-like symptoms and underwent percutaneous coronary angiography (PCA) between July 27, 2015 and April 10, 2017 at the 8th Medical Center of Chinese PLA General Hospital, were enrolled in this cross-sectional study. In all patients, 12-lead electrocardiography (ECG) and MCG test were performed before PCA. For each subject. The value at every single sampling point was extracted from T wave of each MCG channel in time sequence. Pearson's correlation coefficients were calculated for each two T-waves. A binary logistic regression diagnosis model of these coefficients was established to identify patients in need of revascularization.

RESULTS

Ten pairings of coefficients were entered into diagnostic regression model as covariates. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.747 (95% CI: 0.680-0.815), and the asymptotic P value was less than 0.001. At the cut-off value of 0.55, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 72.9%, 65.9%, 74.8%, 63.6% and 69.9%, and the positive and negative post-test probabilities were 65.9% and 25.7%. The accuracy, sensitivity, specificity, PPV and NPV for 12-lead ECG were 67.0%, 62.7%, 63.5%, 70.5% and 55.1%, respectively. However, when those acute myocardial infarction (AMI) patients were ruled out from both groups, the MCG model had an accuracy of 68.2%, a sensitivity of 70.1%, a specificity of 66.3%, a PPV of 68.5% and an NPV of 67.9%. But, the accuracy, sensitivity, specificity, PPV and NPV for 12-lead ECG were 60.0%, 55.2%, 65.1%, 62.3% and 58.1%, respectively.

CONCLUSIONS

Patients suffering from angina-like symptoms, with a logistic regression model value over 0.55, should be recommended for PCA.

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.

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.