Magnetocardiography predicts coronary artery disease in patients with acute chest pain

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.

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.

Electromagnetic field and cardiovascular diseases: A state-of-the-art review of diagnostic, therapeutic, and predictive values

Despite encouraging advances in early diagnosis and treatment, cardiovascular diseases (CVDs) remained a leading cause of morbidity and mortality worldwide. Increasing evidence has shown that the electromagnetic field (EMF) influences many biological processes, which has attracted much attention for its potential therapeutic and diagnostic modalities in multiple diseases, such as musculoskeletal disorders and neurodegenerative diseases. Nonionizing EMF has been studied as a therapeutic or diagnostic tool in CVDs. In this review, we summarize the current literature ranging from in vitro to clinical studies focusing on the therapeutic potential (external EMF) and diagnostic potential (internal EMF generated from the heart) of EMF in CVDs. First, we provided an overview of the therapeutic potential of EMF and associated mechanisms in the context of CVDs, including cardiac arrhythmia, myocardial ischemia, atherosclerosis, and hypertension. Furthermore, we investigated the diagnostic and predictive value of magnetocardiography in CVDs. Finally, we discussed the critical steps necessary to translate this promising approach into clinical practice.

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.

Magnetocardiography for the detection of myocardial ischemia

Ischemic heart disease (IHD) continues to be a significant global public health concern and ranks among the leading causes of mortality worldwide. However, the identification of myocardial ischemia in patients suspected of having coronary artery disease (CAD) remains a challenging issue. Functional or stress testing is widely recognized as the gold standard method for diagnosing myocardial ischemia, but it is hindered by low diagnostic accuracy and limitations such as radiation exposure. Magnetocardiography (MCG) is a non-contact, non-invasive method that records magnetic fields produced by the electrical activity of the heart. Unlike electrocardiography (EKG) and other functional or stress testing, MCG offers numerous advantages. It is highly sensitive and can detect early signs of myocardial ischemia that may be missed by other diagnostic tools. This review aims to provide an extensive overview of the available evidence that establishes the utility of MCG as a valuable diagnostic tool for identifying myocardial ischemia, accompanied by a discussion of potential future research directions in this domain.

Development of Magnetocardiograph without Magnetically Shielded Room Using High-Detectivity TMR Sensors

A magnetocardiograph that enables the clear observation of heart magnetic field mappings without magnetically shielded rooms at room temperatures has been successfully manufactured. Compared to widespread electrocardiographs, magnetocardiographs commonly have a higher spatial resolution, which is expected to lead to early diagnoses of ischemic heart disease and high diagnostic accuracy of ventricular arrhythmia, which involves the risk of sudden death. However, as the conventional superconducting quantum interference device (SQUID) magnetocardiographs require large magnetically shielded rooms and huge running costs to cool the SQUID sensors, magnetocardiography is still unfamiliar technology. Here, in order to achieve the heart field detectivity of 1.0 pT without magnetically shielded rooms and enough magnetocardiography accuracy, we aimed to improve the detectivity of tunneling magnetoresistance (TMR) sensors and to decrease the environmental and sensor noises with a mathematical algorithm. The magnetic detectivity of the TMR sensors was confirmed to be 14.1 pT_rms on average in the frequency band between 0.2 and 100 Hz in uncooled states, thanks to the original multilayer structure and the innovative pattern of free layers. By constructing a sensor array using 288 TMR sensors and applying the mathematical magnetic shield technology of signal space separation (SSS), we confirmed that SSS reduces the environmental magnetic noise by -73 dB, which overtakes the general triple magnetically shielded rooms. Moreover, applying digital processing that combined the signal average of heart magnetic fields for one minute and the projection operation, we succeeded in reducing the sensor noise by about -23 dB. The heart magnetic field resolution measured on a subject in a laboratory in an office building was 0.99 pT_rms and obtained magnetocardiograms and current arrow maps as clear as the SQUID magnetocardiograph does in the QRS and ST segments. Upon utilizing its superior spatial resolution, this magnetocardiograph has the potential to be an important tool for the early diagnosis of ischemic heart disease and the risk management of sudden death triggered by ventricular arrhythmia.

Detection of coronary artery disease in patients with chest pain: A machine learning model based on magnetocardiography parameters

BACKGROUD

Patients with chest pain and suspected of coronary artery disease(CAD) need further test to confirm the diagnosis. Magnetocardiography (MCG) is a non-invasive and emission-free technology which can detect and measure the weak magnetic fields created by the electrical activity of the heart.

OBJECTIVE

This study aimed to investigate the usefulness of the 10 MCG parameters to detect CAD in patients with chest pain by means of a machine learning method of multilayer perceptron(MLP) neural network.

METHODS

209 patients who were suffering from chest pain and suspected of CAD were enrolled in this cross-sectional study. In all patients, 12-lead electrocardiography(ECG) and MCG test were performed before percutaneous coronary angiography(PCA). 10 MCG parameters were analyzed by MLP neural networks.

RESULTS

11 diagnostic models(M1 to M11) were established after MLP analysis. The accuracies ranged from 71.2% to 90.5%. Two models(M10 and M11) were further analyzed. The accuracy, sensitivity, specificity, PPV, NPV, PLR and NLR were 89.5%, 89.8%, 88.9%, 92.7%, 84.7%, 11.10 and 0.11, of M10, and were 90.0%, 91.4%, 87.7%, 92.1%, 86.6%, 7.43 and 0.10, of M11.

CONCLUSIONS

By a method of MLP neural network, MCG is applicable in identifying CAD in patients with chest pain, which seems beneficial for detection of CAD.

Assessing heart disease using a novel magnetocardiography device

The aim of this paper is to present the use of a portable, unshielded magnetocardiograph (MCG) and identify key characteristics of MCG scans that could be used in future studies to identify parameters that are sensitive to cardiac pathology. We recruited 50 patients with confirmed myocardial infarction (MI) within the past 12 weeks and 46 volunteers with no history of cardiac disease. A set of 38 parameters were extracted from MCG features including both signals from the sensor array and from magnetic images obtained from the device and principal component analysis was used to concentrate the information contained in these parameters into uncorrelated predictors. Linear fits of these parameters were then used to examine the ability of MCG to distinguish between sub-groups of patients. In the fist instance, the primary aim of this study was to ensure that MCG has a basic ability to separate a highly polarised patient group (young controls from post infarction patients) and to identify parameters that could be used in future studies to build a formal diagnostic tool kit. Parameters that parameterised left ventricular ejection fraction (LVEF) were identified and an example is presented to show differential low and high ejection fractions.

Diagnostic accuracy of the magnetocardiograph for patients with suspected acute coronary syndrome

Background

We aimed to estimate the diagnostic accuracy of the VitalScan magnetocardiograph (MCG) for suspected acute coronary syndrome (ACS).

Methods

We undertook a prospective cohort study evaluating the diagnostic accuracy of the MCG in adults with suspected ACS. The reference standard of ACS was determined by an independent adjudication committee based on 30-day investigations and events. The cohort was split into a training sample, to derive the MCG algorithm and an algorithm combining MCG with a modified Manchester Acute Coronary Syndrome (MACS) clinical probability score, and a validation sample, to estimate diagnostic accuracy.

Results

We recruited 756 participants and analysed data from 680 (293 training, 387 validation), of whom 96 (14%) had ACS. In the training sample, the respective area under the receiver operating characteristic (AUROC) curves were the following: MCG 0.66 (95% CI 0.58 to 0.74), MACS 0.64 (95% CI 0.54 to 0.73) and MCG+MACS 0.70 (95% CI 0.63 to 0.77). MCG specificity was 0.16 (95% CI 0.12 to 0.21) at the threshold achieving acceptable sensitivity for rule-out (>0.98). In the validation sample (n=387), the respective AUROCs were the following: MCG 0.56 (95% CI 0.48 to 0.64), MACS 0.69 (95% CI 0.61 to 0.77) and MCG+MACS 0.64 (95% CI 0.56 to 0.72). MCG sensitivity was 0.89 (95% CI 0.77 to 0.95) and specificity 0.15 (95% CI 0.12 to 0.20) at the rule-out threshold. MCG+MACS sensitivity was 0.85 (95% CI 0.73 to 0.92) and specificity 0.30 (95% CI 0.25 to 0.35).

Conclusion

The VitalScan MCG is currently unable to accurately rule out ACS and is not yet ready for use in clinical practice. Further developmental research is required.

A 90-second magnetocardiogram using a novel analysis system to assess for coronary artery stenosis in Emergency department observation unit chest pain patients

•

Magnetocardiography non-invasively detects coronary artery stenosis.

•

Emergency department chest pain patients are further evaluated in observation unit.

•

Patients underwent 90-second magnetocardiography scan using novel analysis system.

•

Results compared to usual care with stress testing and coronary angiography.

•

Magnetocardiography shows promise as feasible and comparable testing option.

Background

Magnetocardiography (MCG) has been shown to non-invasively detect coronary artery stenosis (CAS). Emergency department (ED) patients with possible acute coronary syndrome (ACS) are commonly placed in an observation unit (OU) for further evaluation. Our objective was to compare a novel MCG analysis system with stress testing (ST) and/or coronary angiography (CA) in non-high risk EDOU chest pain patients.

Methods

This is a prospective pilot study of non-high risk EDOU chest pain patients evaluated with ST and/or CA that underwent a resting 90-second MCG scan between August 2017 and February 2018. A positive MCG scan was defined as having current dipole deviations with dispersion or splitting during the repolarization phase. ST, CA and major adverse cardiac events (MACE) 30 days and 6 months post-discharge assessed.

Results

Of 101 study patients, mean age was 56 years and 53.6% were male. MCG scan sensitivity with 95% CI was 27.3% [7.3%, 60.7%], specificity 77.8% [67.5%, 85.6%], PPV 13.0% [3.4%, 34.7%] and NPV 89.7% [80.3%, 95.2%] compared to ST, and 33.3% [7.5%, 70.7%], 78.3% [68.4%, 86.2%], 13% [5.2%, 29.0%] and 92.3% [88.2%, 95.1%] respectively compared to ST and CA. No patients had positive ST, CA or MACE 30 days and 6 months post-discharge.

Conclusion

This pilot study suggests a resting 90-second MCG scan shows promise in evaluating EDOU chest pain patients for CAS and warrants further study as an alternative testing modality to identify patients safe for discharge. Larger studies are needed to assess accuracy of MCG using this novel analysis system.

Magnetocardiography for identification of coronary ischemia in patients with chest pain and normal resting 12-lead electrocardiogram

Background

Identification of coronary ischemia in patients presenting with chronic chest pain is difficult as resting ECG can be normal. Diagnosis of coronary ischemia requires evaluation during exercise or pharmacological stress. A noninvasive test to identify coronary ischemia at rest without the need for exercise is desirable. We studied the diagnostic accuracy of magnetocardiography (MCG) at rest to detect coronary ischemia in these patients.

Methods

Patients with chronic chest pain and suspected coronary ischemia with a normal ECG were included. Patients underwent treadmill test (TMT) and were divided into TMT positive and TMT negative groups. MCG was recorded in a magnetically shielded room. Iso‐field contour maps generated at the T‐wave peak were compared between the groups. From the magnetic field map (MFM), the magnetic field angle at T‐wave peak was calculated and was also compared across the two groups.

Results

There were a total of 29 patients, 12 with positive TMT and 17 with negative TMT. An abnormal magnetic field angle was more common in the TMT positive group (72% vs. 6%). Abnormal contour maps in the form of nondipole patterns or abnormal orientation were seen in 81.8% (9/11) patients in TMT positive group and 6.8% (1/17) patients in the TMT negative group (p < .001).

Conclusion

Abnormal magnetic field angle and abnormal magnetic field maps in MCG recorded at rest are able to identify the presence of coronary ischemia in patients with chronic chest pain and a normal resting ECG.

Designing a Low-Cost, Single-Supply ECG System for Suppression of Movement Artifact from Contaminated Magnetocardiogram

Measurement of the late potentials and His-bundle activity is crucial for many clinical studies using the noncontact and noninvasive magnetocardiography (MCG) technique; these weak signals are extracted by averaging many cardiac cycles aligned using the R-peak of the cardiac cycle identified using an electrocardiography (ECG) lead. ECG is measured simultaneously with MCG using a conventional dual-supply ECG amplifier, which requires either two separate batteries or a single battery with a switching voltage inverter circuit for its proper operation. The ECG circuitry based on two separate batteries requires a relatively large voltage supply (-18 to +18 V). The single-supply (low voltage: 0-9 V) ECG circuitry may be implemented using a switching voltage inverter; however, this mode of operation introduces switching noise in the system. The objective of the present work is to overcome these problems by carefully designing a low-voltage, single-supply ECG system, which can be used simultaneously with the MCG setup without introducing a significant level of additional noise in the MCG measurement system.

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.

Magnetocardiography measurements with 4He vector optically pumped magnetometers at room temperature

In this paper, we present a proof of concept study which demonstrates for the first time the possibility of recording magnetocardiography (MCG) signals with ⁴He vector optically pumped magnetometers (OPM) operated in a gradiometer mode. Resulting from a compromise between sensitivity, size and operability in a clinical environment, the developed magnetometers are based on the parametric resonance of helium in a zero magnetic field. Sensors are operated at room temperature and provide a tri-axis vector measurement of the magnetic field. Measured sensitivity is around 210 f T (√Hz)^-1 in the bandwidth (2 Hz; 300 Hz). MCG signals from a phantom and two healthy subjects are successfully recorded. Human MCG data obtained with the OPMs are compared to reference electrocardiogram recordings: similar heart rates, shapes of the main patterns of the cardiac cycle (P/T waves, QRS complex) and QRS widths are obtained with both techniques.

Incremental diagnostic value of combined quantitative and qualitative parameters of magnetocardiography to detect coronary artery disease

BACKGROUND/OBJECTIVES

Magnetocardiography (MCG) has been proposed as a non-invasive and functional technique with high accuracy for diagnosis of myocardial ischemia. This study sought to investigate the incremental diagnostic value of combined quantitative and qualitative parameters of MCG to detect coronary artery disease (CAD).

METHODS

Ninety six patients with suspected CAD who underwent coronary angiography were enrolled in the analysis to test the diagnostic accuracy of 2 MCG parameters (a quantitative parameter of the percent change of ST-segment fluctuation score and a qualitative parameter of non-dipole phenomenon).

RESULTS

The best cut-off value for the percent change of ST-segment fluctuation score was -51.0%. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 78.1, 73.9, 82.0, 79.1, and 77.4, in the percent change of ST-segment fluctuation score and 86.5, 84.8, 88.0, 86.7, and 86.3 in non-dipole phenomenon. The area under the curve of receiver-operating characteristics was 0.79 for the percent change of ST-segment fluctuation score and 0.86 for non-dipole phenomenon (p<0.001). However, the incorporation of non-dipole phenomenon into a model with the percent change of ST-segment fluctuation score significantly improved C-statistics, indicating the enhancement of diagnostic performance in the detection of significant CAD (0.790 to 0.930; p<0.001).

CONCLUSIONS

Qualitative assessment of non-dipole phenomenon has a better diagnostic value than the quantitative parameter of percent change of ST-segment fluctuation score in the detection of significant CAD. Furthermore, this study found that the incorporation of non-dipole phenomenon into the percent change of ST-segment fluctuation score significantly improved the diagnostic performance of CAD detection.

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.

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.

Three-dimensional reconstruction of a cardiac outline by magnetocardiography

A 3-D cardiac visualization is significantly helpful toward clinical applications of magnetocardiography (MCG), but the cardiac reconstruction requires a segmentation process using additional image modalities. This paper proposes a 3-D cardiac outline reconstruction method using only MCG measurement data without further imaging techniques. The cardiac outline was reconstructed by a combination of both spatial filtering and coherence mapping method. The strength of cardiac activities was first estimated by the array-gain constraint minimum-norm spatial filter with recursively updated gram matrix (AGMN-RUG). Then, waveforms were reconstructed at whole source grids, and the maximum source points of an atrium and ventricle were selected as a reference, respectively. Next, the coherence between each maximum source point and whole source points was compared by the coherence mapping method. A reconstructed cardiac outline was validated by comparing with an overlapped volume ratio when the reconstructed volume was identically matched with the original volume. The results obtained by the AGMN-RUG were compared to the results by other spatial filters. The accuracy of numerical simulation and phantom experiment by the AGMN-RUG was superior 10% and 8%, respectively, than the accuracy by the standardized low-resolution electromagnetic tomography. This accuracy demonstrated the efficacy of the proposed 3-D cardiac reconstruction method.

Electrochemical growth of Co nanowires in ultra-high aspect ratio InP membranes: FFT-impedance spectroscopy of the growth process and magnetic properties

The electrochemical growth of Co nanowires in ultra-high aspect ratio InP membranes has been investigated by fast Fourier transform-impedance spectroscopy (FFT-IS) in the frequency range from 75 Hz to 18.5 kHz. The impedance data could be fitted very well using an electric circuit equivalent model with a series resistance connected in series to a simple resistor-capacitor (RC) element and a Maxwell element. Based on the impedance data, the Co deposition in ultra-high aspect ratio InP membranes can be divided into two different Co deposition processes. The corresponding share of each process on the overall Co deposition can be determined directly from the transfer resistances of the two processes. The impedance data clearly show the beneficial impact of boric acid on the Co deposition and also indicate a diffusion limitation of boric acid in ultra-high aspect ratio InP membranes. The grown Co nanowires are polycrystalline with a very small grain size. They show a narrow hysteresis loop with a preferential orientation of the easy magnetization direction along the long nanowire axis due to the arising shape anisotropy of the Co nanowires.

Diagnostic value of magnetocardiography in coronary artery disease and cardiac arrhythmias: a review of clinical data

Despite the availability of several advanced non-invasive diagnostic tests such as echocardiography and magnetic resonance imaging, electrocardiography (ECG) remains as the most widely used diagnostic technique in clinical cardiology. ECG detects electrical potentials that are generated by cardiac electrical activity. In addition to electrical potentials, the same electrical activity of the heart also induces magnetic fields. These extremely weak cardiac magnetic signals are detected by a non-invasive, contactless technique called magnetocardiography (MCG), which has been evaluated in a number of clinical studies for its usefulness in diagnosing heart diseases. We reviewed the basic principles, history and clinical data on the diagnostic role of MCG in coronary artery disease and cardiac arrhythmias.

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.

Magnetocardiography for the diagnosis of coronary artery disease: a systematic review and meta-analysis

BACKGROUND

Coronary artery disease (CAD) has a significant disease burden making early diagnosis and management imperative. Magnetocardiography (MCG) is a relatively new noninvasive technique that allows diagnosis of CAD by recording the magnetic fields generated by the electrical activity of the heart.

METHODS

We searched MEDLINE and the Cochrane Central Register of Controlled Trials for prospective studies that evaluated the test characteristics (e.g., sensitivity, specificity, likelihood ratios) of MCG for detection of CAD. Studies were included if they evaluated either patients with stable CAD documented by angiogram or patients presenting initially with acute coronary syndrome and subsequently diagnosed with CAD. The quality of included studies was assessed using an adaptation of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. We performed meta-analyses of sensitivity, specificity and positive and negative likelihood ratios using Meta-DiSc software.

RESULTS

Screening of titles and abstracts followed by full-text review yielded seven studies that met our inclusion criteria. Meta-analyses yielded a pooled sensitivity of 83% (95% confidence interval [CI] 80% to 86%) and a specificity of 77% (95% CI 73% to 81%). The pooled positive likelihood ratio was 3.92 (95% CI 2.30 to 6.66) and negative likelihood ratio was 0.20 (95% CI 0.12 to 0.35). Significant heterogeneity was present in all meta-analyses.

CONCLUSIONS

The pooled test characteristics for MCG are similar to those of existing noninvasive modalities for diagnosing CAD. Our results suggest that MCG is a potential complementary or alternative tool for noninvasive detection of CAD.

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.

Algorithm for quantitative 3 dimensional analysis of ECG signals improves myocardial diagnosis over cardiologists in diabetic patients

Acute myocardial infarction (AMI) diagnosis in type II diabetes (DM2) patients is difficult and ECG findings are often non-diagnostic or inconclusive. We developed computer algorithms to process standard 12-lead ECG input data for quantitative 3-dimensional (3D) analysis (my3KGTM), and hypothesized that use of the my3KGTM's array of over 100 3D-based AMI diagnostic markers may improve diagnostic accuracy for AMI in DM2 patients.

METHODS

We identified 155 consecutive DM2 patients age >25 yrs with chest discomfort or shortness of breath who were evaluated at an urban emergency department (130 patients (pts)) or the cardiac catheterization laboratory (25 pts) for possible AMI. The first digital 12-lead ECG for each patient, obtained within 30 min of presentation, was evaluated by (1) 2 blinded expert cardiologists, and (2) my3KGTM. In each case, the ECG was classified as either likely AMI or likely non-AMI. "Gold standard" was the final clinical diagnosis. Statistical analysis was McNemar's test with continuity correction.

RESULTS

The 155 DM2 patients were 50% male, mean age 56.8 ± 12.0 yrs; 44 pts had a final clinical diagnosis of AMI (17 ST Elevation Myocardial Infarctions (STEMI), 27 Non-ST Elevation Myocardial Infarctions (NSTEMI)) and 111 had no AMI.

CONCLUSIONS

Relative to standard 12L ECG read by cardiologists, quantitative 3D ECG analysis showed significant and substantial gains in sensitivity for AMI diagnosis in DM2 patients, without loss in specificity. Sensitivity gains were particularly high in patients exhibiting NSTEMI, the most common form of AMI in DM2.

Cardiac magnetic field mapping quantified by Kullback-Leibler entropy detects patients with coronary artery disease

Cardiac magnetic field mapping (CMFM) is a noninvasive method to determine cardiac electrical activity. We analysed the utility of CMFM for the detection of patients with coronary artery disease (CAD) without subjecting them to stress. We studied 59 healthy control subjects and 101 patients with CAD without previous myocardial infarction (MI). The heart's magnetic field was recorded over the anterior chest wall using a multichannel magnetic measurement system with axial second-order gradiometers. The evaluation of CMFM was based on comparison of the 'ideal' group mean maps of young healthy subjects and maps of examined individuals. Three measures of similarity were considered: Kullback-Leibler (KL) entropy, normalized residual magnetic field strength and deviations in the magnetic field map orientation. The mean values of these parameters during the depolarization and repolarization were used for further classification with the help of logistic regression. The feature set based on the KL-entropy demonstrated the best classification results (sensitivity/specificity of 85/80%), followed by the residual feature (85/75%) and the magnetic field orientation feature (80/73%) sets. The forward stepwise technique was applied to select the best set of features from the combined feature set. Two parameters were selected, namely the KL-entropy for the repolarization period and the residual parameter for the depolarization period. The classification based on these parameters demonstrated a sensitivity of 88% and a specificity of 88% for the distinction of CAD patients from the control subjects. The area under the receiver operator curve was 94%. Hence, we suggest that CMFM evaluation based on KL-entropy is a promising technique to identify patients with CAD.

Usefulness of magnetocardiogram to detect unstable angina pectoris and non-ST elevation myocardial infarction

Electrophysiologic information as well as anatomic information to detect coronary artery disease is important for accurate diagnosis. A diagnostic tool that can detect patients with unstable angina pectoris (UAP) or non-ST elevation myocardial infarction (NSTEMI) with severe stenosis would be beneficial for patients and clinicians. Magnetocardiography has been recognized as a noncontact, noninvasive, fast tool to detect ischemic coronary artery disease and provide direct electrophysiologic information from the heart. In this study, 10 magnetocardiographic (MCG) parameters from 4 groups, including 185 young controls, 19 age-matched controls (AMCs), 110 patients with UAP, and 83 patients with NSTEMIs, were analyzed. A 64-channel MCG system in a magnetically shielded room was used. All 10 parameters showed significant differences (p <0.001) between controls and patients with NSTEMIs, and 6 parameters showed significant differences (p <0.01) between AMCs and patients with UAP. MCG parameters significantly increased when ischemic heart conditions worsened. Of the 10 parameters, the magnetic field map was among the easiest ways to detect the severity of coronary artery disease. Abnormal magnetic field maps were observed frequently with worsening ischemic coronary artery disease (70% of patients with UAP and 92.5% of those with NSTEMIs had abnormal maps). The combination of the binary boundaries of the 10 parameters had 96.4% sensitivity and 85% specificity to detect NSTEMI. In conclusion, the MCG parameters and magnetic field maps may detect UAP and NSTEMI easily when they are considered together.

Visual 3Dx: algorithms for quantitative 3-dimensional analysis of ECG signals

INTRODUCTION

The 12-lead ECG is useful for cardiac diagnosis but has limited sensitivity and specificity. To address this, we developed the Visual3Dx, a comprehensive method for describing cardiac electrical activity in time and space. The Visual3Dx transforms the ECG input into a time-variable heart vector, and normalizes each lead input to assure equal representation from all cardiac regions.

METHODS

We compared the Visual3Dx to the standard 12-lead ECG for detection of acute myocardial ischemia (AMI) in 2 clinical models. Model 1 was AMI after 90 s of balloon coronary occlusion in 117 cases. Model 2 was 122 consecutive patients who: (1) presented to an urban emergency department with chest pain; (2) were admitted to coronary care and developed elevated cardiac troponin levels; and (3) had coronary arteriography within 6 hrs.

RESULTS

In Model 1, the 12 lead ECG developed ST segment deviation diagnostic of AMI in 78/117 occlusions (67%), whereas using the same input ECG data, the Visual3Dx was diagnostic of AMI in 105/117 occlusions (90%; p<0.001). In Model 2, the first 12 lead ECG was diagnostic of AMI in 80/122 (66%), whereas the Visual3Dx was diagnostic in 103/122 (84%). In both Models, the largest sensitivity gains were seen in left circumflex and right coronary artery occlusions.

CONCLUSIONS

The Visual3Dx is a promising tool for 3D quantitative analysis of cardiac electrical activity that may improve diagnosis of AMI, especially in electrically remote regions of the heart. Additional studies will define diagnostic specificity and further improve 3D biomarkers of AMI.

Detection of non-ST-elevation myocardial infarction using magnetocardiogram: new information from spatiotemporal electrical activation map

BACKGROUND AND AIM

Non-ST-segment elevation myocardial infarction (NSTEMI) cannot be easily detected in the emergency room. We evaluate a method to detect NSTEMI using 64-channel magnetocardiography (MCG).

METHODS

MCG recordings were made in 20 NSTEMI patients (aged 59.7+/-12.4 years), 15 young (aged 26.8+/-3.4 years), and 13 age-matched control subjects (aged 57.3+/-3.6). We evaluated three approaches to analysis, including 1) determination when individual subjects' MCG results fell outside normal ranges for ten MCG parameters, 2) the magnetic field map at the T-wave peak (T-MFM), and 3) a pair of spatiotemporal activation graphs (STAGs) showing two projections of electrical excitation during repolarization.

RESULTS

Significant differences were found between normal controls and patients for all MCG parameters. None of the healthy controls had more than four MCG abnormal parameters, whereas 19 NSTEMI patients (95%) were abnormal in more than four parameters. STAGs and T-MFM also showed clear differences between healthy controls and NSTEMI patients.

CONCLUSIONS

These results suggest that the MCG is sensitive to changes in the cardiac electrical pathway after myocardial infarction as described by these graphs and parameters, and therefore MCG may be a useful tool to detect severe ischemic patients.

Resting magnetocardiography predicts 3-year mortality in patients presenting with acute chest pain without ST segment elevation

OBJECTIVE

Magnetocardiography (MCG) as a noninvasive, noncontact and risk-free diagnostic method predicts ischemic coronary artery disease (CAD) in patients with acute chest pain at admission with high accuracy. However, it remains unclear whether MCG findings can add prognostic information.

METHOD

A cohort of 402 consecutive patients presenting at the intensive care unit (ICU) with acute chest pain without ST segment elevation (NSTEMI) were included in a prospective registry. In order to prove the prognostic value of MCG a head-to-head comparison of the admission MCG, ECG, TnI, and ECHO tests was made.

RESULTS

In 43 patients (10.7%) the MCG could not be analyzed due to insufficient signal-to-noise ratio. Complete follow-up over a period of up to 3 years was obtained in 355 out of the 359 patients (98.9%). Age at admission was 67.2 +/- 10.3 years, 59.7% males. In the group of patients with an abnormal MCG at admission, 43 out of 249 patients (17.3%) died in the follow-up period, while in the group of patients with a normal MCG at admission only 4 out of 106 patients died (3.77%). The relative risk was 4.58 (95% confidence intervals: 1.68-12.42). A multivariate regression analysis revealed the highest mortality risk for patients with diabetes mellitus and an abnormal MCG at admission (RR = 18.0; 95% CI: 2.49-133.3).

CONCLUSION

Resting MCG at hospital admission predicts 3-year mortality in patients presenting with acute chest pain without ST segment elevation in the ECG. MCG seems to be valuable in identifying chest pain patients at highest risk.

Identification of ischemic heart disease via machine learning analysis on magnetocardiograms

Ischemic heart disease (IHD) is predominantly the leading cause of death worldwide. Early detection of IHD may effectively prevent severity and reduce mortality rate. Recently, magnetocardiography (MCG) has been developed for the detection of heart malfunction. Although MCG is capable of monitoring the abnormal patterns of magnetic field as emitted by physiologically defective heart, data interpretation is time-consuming and requires highly trained professional. Hence, we propose an automatic method for the interpretation of IHD pattern of MCG recordings using machine learning approaches. Two types of machine learning techniques, namely back-propagation neural network (BNN) and direct kernel self-organizing map (DK-SOM), were applied to explore the IHD pattern recorded by MCG. Data sets were obtained by sequential measurement of magnetic field emitted by cardiac muscle of 125 individuals. Data were divided into training set and testing set of 74 cases and 51 cases, respectively. Predictive performance was obtained by both machine learning approaches. The BNN exhibited sensitivity of 89.7%, specificity of 54.5% and accuracy of 74.5%, while the DK-SOM provided relatively higher prediction performance with a sensitivity, specificity and accuracy of 86.2%, 72.7% and 80.4%, respectively. This finding suggests a high potential of applying machine learning approaches for high-throughput detection of IHD from MCG data.

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.

Integral Value of JT Interval in Magnetocardiography is Sensitive to Coronary Stenosis and Improves Soon After Coronary Revascularization

BACKGROUND

Magnetocardiography (MCG) is sensitive to minute cardiac electric abnormalities, but its clinical utility in diagnosing ischemic heart disease (IHD) has not been established. The present study examined the usefulness of an integral MCG value of ventricular repolarization in patients with IHD.

METHODS AND RESULTS

MCG was performed at rest in 14 patients with coronary stenosis >75% confirmed by coronary angiography (IHD group) using a 64-channel system, and then the sum of the 64-channel integral values of the QRS or JT intervals (QRSi and JTi, respectively) was calculated. The JTi/QRSi value indicated the total power of currents in JT compared with those in QRS. These measurements were repeated within 2 weeks after coronary revascularization. The Control group comprised 30 healthy volunteers. The baseline value of JTi/QRSi was significantly smaller in the IHD than in the Control group, but after revascularization it increased and did not significantly differ from the Control group. No significant difference in ST deviation was identified by electrocardiography (ECG) before and after coronary revascularization. Analysis of the Control group revealed that JTi/QRSi was not affected by age.

CONCLUSIONS

The JTi/QRSi of the MCG is more sensitive to coronary stenosis than ECG, and this parameter improves soon after coronary revascularization.

Can magnetocardiography detect patients with non-ST-segment elevation myocardial infarction?

BACKGROUND AND AIM

Magnetocardiography (MCG) has been proposed as a noninvasive diagnostic tool to risk-stratify patients with myocardial infarction (MI) and ischemia. The purpose of this study is to find the MCG parameters that are sensitive enough to detect the non-ST-segment elevation myocardial infarction (NSTEMI) patients.

METHODS

MCG data were recorded and analyzed from 165 young controls (mean age = 27.2 +/- 9.0 years), 57 age-matched controls (mean age = 55.9 +/- 10.5 years) and 83 NSTEMI patients (mean age = 59.7 +/- 11.1 years). The MCG recordings were obtained using a 64-channel MCG system in a magnetically shielded room. Statistical analyses were performed for 24 parameters derived from QRS-, R-, T-wave, and ST-T period. Binary boundaries to detect NSTEMI patients out of control subjects were found using the receiver operating characteristic (ROC) curve for each parameter.

RESULTS

Fifteen parameters showed a significant difference (P < 0.05 and P < 0.01) between NSTEMI and both of the control groups. For detection of NSTEMI, the angle of the maximum current and the filed map angle on T-wave peak showed the highest diagnostic performance from 75% to 92% including accuracy, sensitivity, specificity, positive predictive value, and negative predictive value (area under ROC curve = 0.87 approximately 0.93).

CONCLUSIONS

Our study showed that MCG has potential clinical application for detection of NSTEMI and should be further investigated.

Spatiotemporal correlation analyses: a new procedure for standardisation of DC magnetocardiograms

There is a lack of standard methods for the analysis of magnetocardiograms (MCGs). MCG signals have a shape similar to the ECG (P wave, QRS complex, T wave). High-quality multichannel recordings can indicate even slight disturbances of de- and repolarisation. The purpose of our study was to apply a new approach in the analysis of signal-averaged DC-MCGs. DC-MCGs (31-channel) were recorded in 182 subjects: 110 patients after myocardial infarction and 72 controls. Spatiotemporal correlation analysis of the QRS complex and T wave patterns throughout the entire heart cycle was used to analyse homogeneity of de- and repolarisation. These plots were compared to standard ECG analyses (electrical axis, Q wave, ST deviation, T polarity and shape). Spatiotemporal correlation analyses seem to be applicable in assessing the course of electrical repolarisation with respect to homogeneity. MCG provided all diagnostic information contained in common ECG recordings at high significance levels. The ECG patterns were included in 5/8 of our parameters for electrical axis, 6/8 for Q-wave, 7/8 for ST deviation and 5/8 for T-polarity based on two time series of correlation coefficients. We conclude that our spatiotemporal correlation approach provides a new tool for standardised analysis of cardiac mapping data such as MCG.

Contactless magnetocardiographic mapping in anesthetized Wistar rats: evidence of age-related changes of cardiac electrical activity

Magnetocardiography (MCG) is the recording of the magnetic field (MF) generated by cardiac electrophysiological activity. Because it is a contactless method, MCG is ideal for noninvasive cardiac mapping of small experimental animals. The aim of this study was to assess age-related changes of cardiac intervals and ventricular repolarization (VR) maps in intact rats by means of MCG mapping. Twenty-four adult Wistar rats (12 male and 12 female) were studied, under anesthesia, with the same unshielded 36-channel MCG instrumentation used for clinical recordings. Two sets of measurements were obtained from each animal: 1) at 5 mo of age (297.5 ± 21 g body wt) and 2) at 14 mo of age (516.8 ± 180 g body wt). RR and PR intervals, QRS segment, and QTpeak, QTend, JTpeak, JTend, and Tpeak-end were measured from MCG waveforms. MCG imaging was automatically obtained as MF maps and as inverse localization of cardiac sources with equivalent current dipole and effective magnetic dipole models. After 300 s of continuous recording were averaged, the signal-to-noise ratio was adequate for study of atrial and ventricular MF maps and for three-dimensional localization of the underlying cardiac sources. Clear-cut age-related differences in VR duration were demonstrated by significantly longer QTend, JTend, and Tpeak-end in older Wistar rats. Reproducible multisite noninvasive cardiac mapping of anesthetized rats is simpler with MCG methodology than with ECG recording. In addition, MCG mapping provides new information based on quantitative analysis of MF and equivalent sources. In this study, statistically significant age-dependent variations in VR intervals were found.

Using independent component analysis for noise reduction of magnetocardiographic data in case of exercise with an ergometer

In 1992, Brockmeier et al. showed that there is a strong difference in magnetocardiography (MCG)-detected field distribution generated by the heart at rest and under stress. To study the possible clinical applications of this finding, it is convenient to avoid pharmacological stress and to perform stress MCG (SMCG) using conventional physical stress with an ergometer. When using a non-magnetic ergometer, the MCG recordings under physical stress are more noisy due to the unavoidable movement artefacts from the patient and from the residual artefacts of the ergometer. To remove these artefacts a denoising was performed using independent component analysis (ICA) in a new implementation. This work shows that with ICA in this special implementation it is becoming feasible to extract heart signals from SMCG data recorded during ergometer exercise.