Changes in dipolar structure of cardiac magnetic field maps after ST elevation myocardial infarction

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.

An Integrated Maximum Current Density Approach for Noninvasive Detection of Myocardial Infarction

We present a new approach of integrated maximum current density (IMCD) for the noninvasive detection of myocardial infarction (MI) using magnetocardiography (MCG) data acquired from a superconducting quantum interference device (SQUID) system. In this paper, we investigated the relationship of the maximum current density (MCD) in the current density map and the underlying equivalent current dipole (ECD) based on a novel method of reconstructing the ECD in the extremum circle of the magnetic field map. The performance of IMCD and the integrated ECD (IECD) approaches were also evaluated by using 61-channel MCG data from 39 healthy subjects and 102 patients with ST elevation myocardial infarction (STEMI). Statistical analysis of the healthy and STEMI groups demonstrate that the IMCD approach obtains sensitivity and specificity up to 91.2% and 84.6%, somewhat higher than that of IECD, respectively. The results indicate that IMCD provides spatiotemporal information regarding cardiac electrical activity during ventricular repolarization. This approach may be helpful to diagnose MI in clinic application. The physical concept of the approach is also explained in this paper.

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

PURPOSE

Magnetocardiography (MCG) has been proposed as a noninvasive, diagnostic tool for risk-stratifying patients with acute myocardial infarction (AMI). This study evaluated whether MCG predicts long-term prognosis in AMI.

MATERIALS AND METHODS

In 124 AMI patients (95 males, mean age 60±11 years), including 39 with ST-elevation myocardial infarction, a 64-channel MCG was performed within 2 days after AMI. During a mean follow-up period of 6.1 years, major adverse cardiac events (MACE) were evaluated.

RESULTS

MACE occurred in 31 (25%) patients, including 20 revascularizations, 8 deaths, and 3 re-infarctions. Non-dipole patterns were observed at the end of the T wave in every patients. However, they were observed at T-peak in 77% (24/31) and 54% (50/93) of patients with and without MACE, respectively (p=0.03). Maximum current, field map angles, and distance dynamics were not different between groups. In the multivariate analysis, patients with non-dipole patterns at T-peak had increased age- and gender-adjusted hazard ratios for MACE (hazard ratio 2.89, 95% confidence interval 1.20-6.97, p=0.02) and lower cumulative MACE-free survival than those with dipole patterns (p=0.02).

CONCLUSION

Non-dipole patterns at T-peak were more frequently observed in patients with MACE and were related to poor long-term prognosis. Thus, repolarization heterogeneity measured by MCG may be a useful predictor for AMI prognosis.

QTc Heterogeneity in Rest Magnetocardiography is Sensitive to Detect Coronary Artery Disease: In Comparison with Stress Myocardial Perfusion Imaging

BACKGROUND

Stress nuclear myocardial perfusion imaging (MPI) is an established method for diagnosis and prognosis of coronary artery disease (CAD). However, radiation exposure limits its clinical application. Magnetocardiography (MCG) has been proposed as a non-contact, rapid and non-radiation technique with high reproducibility. The aim of the study was to evaluate the diagnostic efficacy of rest MCG in CAD comparing to stress MPI.

METHODS

We prospectively enrolled 55 patients with suspected CAD (64 ± 10 years) who were scheduled for coronary angiography (CA). MCG, stress (201)Tl MPI and CA were performed within 3 months. The spatial distribution maps of QTc interval (21 × 21 in resolution) were derived from a 64-channel MCG system (KRISS, Korea). T-wave propagation mapping, repolarization heterogeneity index with QTc dispersion and smoothness index of QTc (SI-QTc) were analyzed, and the diagnostic criteria for CAD were developed based on the receiver operating characteristic (ROC) curve analysis.

RESULTS

Patients with significant CAD (≥ 70% luminal stenosis, n = 36) had higher QTc dispersion and SI-QTc than controls (both p < 0.05). The diagnostic sensitivity and specificity were 0.8330, 0.6842 for QTc dispersion ≥ 79 ms; 0.7778, 0.6842 for SI-QTc ≥ 9.1 ms; and 0.8611, 0.6842 for combination. There was no difference of area under ROC curve by using criteria of QTc dispersion ≥ 79 ms, SI-QTc ≥ 9.1 ms or combination (0.7588, 0.7310, 0.7727, p = NS), and non-inferior to stress MPI (p = NS).

CONCLUSIONS

The QTc heterogeneity parameters of rest MCG yield a good sensitivity and acceptable specificity for detection of CAD, and may provide an alternative to stress MPI without stress and radiation.

KEY WORDS

Coronary artery disease (CAD); Magnetocardiography (MCG); Myocardial perfusion imaging (MPI); Repolarization.

Early detection of coronary artery disease in patients studied with magnetocardiography: an automatic classification system based on signal entropy

We propose an automatic system for the classification of coronary artery disease (CAD) based on entropy measures of MCG recordings. Ten patients with coronary artery narrowing ≥ or ≤ 50% were categorized by a multilayer perceptron (MLP) neural network based on Linear Discriminant Analysis (LDA). Best results were obtained with MCG at rest: 99% sensitivity, 97% specificity, 98% accuracy, 96% and 99% positive and negative predictive values for single heartbeats. At patient level, these results correspond to a correct classification of all patients. The classifier's suitability to detect CAD-induced changes on the MCG at rest was validated with surrogate data.