Magnetocardiography Research Articles

Sub-pT magnetic field detection by tunnel magneto-resistive sensors

We developed tunnel magneto-resistive (TMR) sensors based on magnetic tunnel junctions (MTJs) that are able to detect a weak, sub-pT, magnetic field at a low frequency. Small detectivities of 0.94 pT/Hz1/2 at 1 Hz and 0.05 pT/Hz1/2 at 1 kHz were achieved by lowering the resistance of MTJs and enhancement of the signal using a thick CoFeSiB layer and magnetic flux concentrators. We demonstrated real-time measurement of magnetocardiography (MCG) and nuclear magnetic resonance (NMR) of protons using developed sensors. This result shows that both MCG and NMR can be measured by the same measurement system with ultra-sensitive TMR sensors.

Abstract 10642: A Novel Way to Predict Obstructive Coronary Artery Disease Requiring Revascularization: The Use of Magnetocardiography

Introduction: Coronary artery disease (CAD) causes one-third of total deaths in people over the age of 35. The evaluation of suspected obstructive CAD includes H&P, ECG, and cardiac enzymes. These tests can often lead to diagnostic uncertainty which can then lead to unnecessary testing such as stress tests and/or coronary angiography. Magnetocardiography (MCG) has been proposed as a noninvasive, radiation free, rapid adjunctive test in predicting coronary ischemia requiring revascularization. MCG measures the magnetic fields produced by electrical currents in the heart with unique and distinct advantages over traditional electrocardiographic approaches. Methods: One hundred patients (62% male, 69% white, age 60.9 years), suspected of having obstructive CAD, were evaluated at a large urban community hospital. All patients underwent MCG prior to coronary angiography which was interpreted by readers blinded to clinical data. MCG was considered positive if the scan displayed findings of “RT angle”, “multipolar”, or “island”. Of the 100 patients, 72 MCG studies were interpretable. Results: Of the 72 MCG studies, 25 were considered positive. Of the 25, 17 revealed obstructive CAD on angiography and underwent PCI with balloon or stent. Of the 47 negative, 35 revealed no obstructive CAD on angiography. Sensitivity was 58.6% and specificity was 81.4%. Removing patients with “island” MCG features resulted in 65 studies which improved specificity to 92.1% at a slight penalty in sensitivity at 55.6%. There were 11 patients where stress testing and MCG could be compared to angiography revealing a diagnostic accuracy of 54.5% and 81.8%, respectively. Discussion: MCG was able to predict obstructive CAD leading to PCI with a specificity of 81.4%. Refining interpretation criteria improved specificity to 92.1% plus better diagnostic accuracy than stress testing. MCG shows promise as an adjunctive test for patients with suspected CAD who may require revascularization with PCI.

Optically pumped magnetometer with dynamic common mode magnetic field compensation

Optically pumped magnetometer (OPM) working in spin-exchange relaxation-free (SERF) region is extremely sensitive to magnetic field. However, it is desired to operate in zero magnetic field environment. Relative strong common mode magnetic field limits the sensitivity of the sensor and may even make the sensor work outside of SERF range. To reduce the common mode magnetic field in real time, this paper proposes an optically pumped magnetometer with dynamic magnetic feedback. Two similar OPMs work simultaneously with one measuring the target signal and the other one monitoring the common mode magnetic field. With a close loop feedback through a proportional integral derivative (PID) controller, the common mode magnetic field signal is compensated dynamically. Comparative experiments show that the proposed scheme reduces the common mode inference about 30 dB. To validate the feasibility of using the proposed probe for ultra-weak biomagnetism measurement, an artificial magnetocardiography (MCG) signal with peak-to-peak amplitude 60 pT and a 5 pT, 10 Hz sinusoid signal are measured by the prototype sensor. The experiment results show that the signals can be clearly observed after signal processing.

Unshielded magnetocardiography contributes to non-invasively rule-out ischemic heart disease in patients with chest pain of uncertain origin

Abstract Background Out of millions of patients (pts) screened every year for chest pain in emergency departments (EDs) only 10% to 20% are affected by an acute coronary syndrome (ACS) or angina due to ischemic heart disease (IHD). Unless ECG recording and serum markers are clearly positive, most of them must undergo complete clinical workout to exclude IHD prior to discharge. Moreover, since even effort-ECG and echocardiography don't exhaustively rule-out IHD, second-level exams are frequently needed, enhancing hospitalization time and related costs. Magnetocardiography (MCG) is increasingly reported as a sensitive, non-invasive, radiation-free method with high negative predictive value (PV) to rule out IHD. Purpose Retrospective cohort study to evaluate the reliability likelihood of unshielded MCG (uMCG) as a tool for rapid rule-out of IHD. Method Rest uMCG data of 263 patients (pts), all chest-pain free at the moment of MCG scan, were retrospectively analyzed. uMCG was recorded with a 36-channel SQUID system (intrinsic sensitivity 30 fT/√Hz, above 1Hz), for 90 seconds. With proprietary software, 13 MCG parameters were automatically calculated from T-wave magnetic field (T-MF): 5 parameters quantifying the dynamics of the MF extrema and eight, obtained from inverse solution with the equivalent magnetic dipole (EMD) model, quantifying the spatial dynamics of the T-wave effective magnetic vector (T-EMV). Pts were stratified as follows: – Group A, chest pain pts, with IHD confirmed by subsequent SPECT and coronary angiography (mean age 66±11 years, 36.7% female); – Group B, chest pain pts, with IHD excluded by subsequent SPECT or coronary angiography (mean age 59±10 years, 28.8% female); – Group C, healthy control subjects (mean age 25±7 years, 48.6% female). Only 60 pts in each group were randomly selected for the analysis. Non-parametric Kruskal-Wallis tests were used to compare the 13 MCG predictors among groups. Linear discriminant analysis was employed to assess likelihood ratios (LHR) and PVs, considering a mean IHD prevalence of 13% (range 10–20%) in chest-pain pts. Results Positive LHR was 9, while the negative LHR was 0.3, resulting in a helpful reduction of the pre-test probability of IHD. Whereas positive PV ranges from 51 to 70%, hardly confirming IHD diagnosis, negative PV ranges from 92 to 96%, giving confidence for a safe IHD rule-out. Conclusions Automatic analysis of T-MF and of T-EMV dynamics from rest MCG provided impressive negative LHR and PV values that, if confirmed in prospective multicenter trials, would rank MCG as a useful tool for quick and early triage of pts with acute chest pain and still non-diagnostic ECG and enzyme patterns, to rule-out those whose symptoms are of non-ischemic origin. Interestingly, a similar high negative PV has been recently reported using MCG QRS predictors. Thus, even better results could be expected by combining algorithms for automatic assessment of both T-wave and QRS predictors. Funding Acknowledgement Type of funding sources: None.

Value of magnetocardiography in chronic coronary disease detection: results of multicenter trial

Abstract Background Diagnostic management of patients with chest pain remains a clinical challenge. Magnetocardiography (MCG) is non-invasive evaluation of the magnetic field of the heart that is produced by the electric activity of the myocardium. Previous studies have clearly demonstrated the potential of MCG in coronary artery disease (CAD) detection. The objective of this multicenter trial is the investigation of value of MCG in diagnosis of mild and severe coronary artery disease using novel approach of magnetocardiographic current density vectors (CDV) maps evaluation. Methods This clinical trial was conducted in three GCP accredited institutions under the leadership of a General Hospital in China. The trials were designed for paired experiments with multi-center blind interpretation. Coronary angiography and coronary flow reserve fraction were used as a “gold standard”. In total 133 persons (mean age 59±3,1 years), divided into 3 groups, were examined. The first group (61 subjects) was identified for patients with severe myocardial ischemia and met the criteria for revascularization: degree of coronary artery stenosis is ≥80% or coronary blood flow reserve score ≤0,8. The second group (13 subjects) is patients whose myocardial ischemia is confirmed but has not yet reached the criteria for revascularization: coronary artery stenosis is between 50% and 80%, coronary blood flow reserve score >0,8. The third group (59 subjects) is whom the “gold standard” confirmed that there is no coronary artery disease. This group is called the negative control group. The MCG examination was performed using a 7-channel MCG system located in an unshielded room. Magnetocardiography recordings were taken from 36 positions at rest Based on the magnetic field distribution, set of subsequent current vectors maps were reconstructed with equidistant time step (10 ms) within the ST-T interval. Each of these maps was classified into two categories: normal map or pathological map. This classification is based on the analysis of the of the largest current density vectors direction and dipole or non-dipole structure of the map. Then, portion of pathological CDV maps within the ST-T interval was defined. Based of this portion, each MCG examination was was assigned to one of 3 groups: mild CAD, severe CAD or no CAD. Results The coincidence rate of each group was as follows: coincidence rate of severe CAD – 85,45%, coincidence rate of mild CAD – 77,78%, coincidence rate of control group was 87,10%. Sensitivity 93,75% and specificity 87,10% were achieved, PPS was 88,24%, NPV 93,10%. In terms of likelhood ratio results were as follows: a positive likelhood ratio of 7.27, negative likelhood ratio – 0.07. Conclusion MCG-examination seems to be a reliable method in the diagnosis of chronic severe and mild CAD. Further large-scale studies needed to confirm these findings. Funding Acknowledgement Type of funding sources: None.

102 Detection of Acute Coronary Syndrome by Magnetocardiography

To evaluate the use of magnetocardiography (MCG) for early identification or rule out of acute coronary syndromes (ACS) in emergency department (ED) patients with chest pain. Magnetocardiography is a noninvasive imaging method that measures the electromagnetic fields generated by the heart’s activity. MCG is rapid, easy to perform, and provides a radiation-free imaging assessment for patients with suspected ACS. This is a prospective, observational, multicenter trial comparing the accuracy and time to disposition of ED standard of care (SOC) vs. MCG. Patients were enrolled at 3 sites from January to May 2021. Inclusion criteria were ED patients with chest pain, age ≥ 18 years, modified heart score > 2, and signs/symptoms of ACS in the ED. Exclusion criteria were STEMI, unable to fit into the device, non-ambulatory, hemodynamically unstable, and unable to lie supine for up to 5 minutes. Additional exclusion criteria were patients with pacemakers, AICD, other active devices, or any ferromagnetic metal above the costal margins. Patients underwent a MCG scan in addition to ED SOC. MCG was performed within 4 hours of ED triage. We hypothesize that the use of MCG will lead to shorter ED length of stay (LOS), with equal or improved diagnosis of suspected ACS patients. Of 58 scans, 32 were available for evaluation. 26 were unevaluable due to either insufficient data or uninterpretable. Patients with any artifacts were considered unevaluable. With technical improvements, the arttifact on current scans may be decreased which will result in fewer unevaluable scans. Mean age was 51.3 (SD± 1 .9) years, 50% female, 59.4% Black, 37.5% White, 3.1% other. Mean HEART score was 4.2 (SD± 1.1). Mean number of cardiovascular risk factors was 3.0 (SD± 1.6). Mean LOS (minutes) for MCG was 187 (SD ± 122) vs. SOC 812 (SD ± 73) (P < 0.0001 by paired t-test) (95% CI difference: -882.0, - 368.1). Thus, when compared with standard of care evaluation alone, the mean length-of-stay could have been reduced by 10.6 hours without any significant change in diagnostic accuracy. MCG and SOC based on troponins were both negative in 28 patients.There were 2 false positives by SOC (6.2%, 2/32). In these two patients presumed to have ACS by SOC, both went to cardiac catheterization, which revealed no ACS. MCG correctly identified the patients to have no ACS. There were two false negatives by MCG. In these two patients, MCG was positive and SOC rule out by troponins was negative. No stress test or cardiac catheterization was done in these two patients. Eleven patients (34%) were placed in the observation unit (OU). The MCG done in the ED and the rule out in the OU were both negative for ACS. Furthermore, early MCG done in the ED as compared with standard of care evaluation alone, would potentially eliminate overnight observation unit stays in 34% of the study population. Magnetocardiography results in a significantly lower LOS for chest pain in the ED which could lead to decreased ED LOS, improved ED turnaround times and better ED efficiency. MCG may avoid an OU stay with resultant cost savings in about one-third of ED chest pain patients. More importantly, MCG detected patients who were false positive by SOC and could have avoided a cardiac catheterization. MCG had two false positives which were negative by troponins but no cardiac catheterization or stress test were done in these two patients.

Coherent detection stochastic resonance assisted biomagnetometer for measuring magnetocardiography at room temperature

A method of magnetocardiography (MCG) measurement using an overdamped bistable model based stochastic resonance (SR) technique for advancing biomagnetic sensors is proposed. To determine the system parameters for SR, an evolutionary algorithm combined with the coherent detection (CD) method is applied. We acquire and process an animal MCG at room temperature, detected by a commercially available optically pumped magnetometer. A comparison with a lowpass filter and the traditional CD method verified the ability of the proposed method to obtain a higher signal-to-noise ratio and peak value of the MCG, whilst retaining sufficient dynamic information.

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

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. 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. 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. 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. 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.

A method for magnetocardiography functional localization based on boundary element method and Nelder-Mead simplex algorithm.

BackgroundThe magnetocardiography (MCG) functional localization can transfer the biomagnetic signal to the electrical activity information inside the heart. The electrical activity is directly related to the physiological function of the heart.MethodsThis study proposes a practical method for MCG functional localization based on the boundary element method (BEM) and the Nelder–Mead (NM) simplex algorithm. Single equivalent moving current dipole (SEMCD) is served as the equivalent cardiac source. The parameters of SEMCD are adapted using the NM simplex algorithm by fitting the measured MCG with the calculated MCG obtained based on BEM. The SEMCD parameters are solved in the sense that the difference between measured and calculated MCG is minimized.ResultsThe factors affecting the localization accuracy of this BEM–NM method were first explored with synthetic signals. Then, the results with real MCG signals show a good agreement between the SEMCD location and the region where ventricle depolarization starts, demonstrating the feasibility of this idea.ConclusionsThis is the first three‐dimensional localization of the onset of ventricular depolarization with the BEM–NM method. The method is promising in the noninvasive localization of lesions for heart diseases.

Sparse Representation for Cardiac Electrical Activity Imaging in Magnetocardiography

Signal sparsity has been widely discussed in communication system, cloud computing, multimedia processing and computational biology. Reconstructing the sparsely distributed current sources of the heart by means of non-invasive magnetocardiography (MCG) measurement and various optimization methods provides a new way to solve the inverse problem of the cardiac magnetic field. The problem of sparse source location of MCG is in the time series of MCG measurement caused by active sparse current source, can the spatiotemporal source be reconstructed accurately and effectively? For the above problem, the scientific contributions of the paper include: (1) A modified focal underdetermined system solver algorithm is proposed for a sparse solution, by combing with dynamic regularization factor and smoothed sparse constraint; (2) Lead field matrix is reduced by prior information of cardiac magnetic field map to reduce under-determination; (3) Spatiotemporal sources are reconstructed for non-invasive cardiac electrical activity imaging. The results of real MCG data demonstrate the effectiveness of this method for cardiac electrical activity imaging. The temporal and spatial changes of the current sources are similar to the depolarization and repolarization process of the ventricle.

Evaluation of Sensor and Analysis Area in the Signal Source Estimation by Spatial Filter for Magnetocardiography

Magnetocardiography (MCG) has been extensively investigated and evaluated in various clinical studies for its potential in detecting the early stages of cardiac diseases. In particular, the establishment of a technology that can provide detailed information on the lesion parts of the heart is expected. The estimation result of the current spatial filter method, such as the exact low-resolution brain electromagnetic tomography (eLORETA), contains errors and has insufficient estimation accuracy for clinical applications. The information of sensors located at the ends cannot be utilized, and the amount of information that affects the estimation result is different for each sensor, which causes the derivation of a biased estimated solution. Therefore, in this study, we considered that the amount of information of each sensor can be used equally by setting an analysis area larger than the sensor area and proposed a method focusing on the relationship between the analysis area of signal source estimation and the sensor plane. We simulated the most efficient and optimized analysis area to be used and performed the source signal estimation by eLORETA using the QRS-complex peak data of the actual MCGs used in adjusting the 51ch sensor directly above the xiphoid process. We compared the following three sizes of the analysis area: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x =120$ </tex-math></inline-formula> mm, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y =120$ </tex-math></inline-formula> mm, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z =100$ </tex-math></inline-formula> mm (a); <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x =180$ </tex-math></inline-formula> mm, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y =180$ </tex-math></inline-formula> mm, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z =100$ </tex-math></inline-formula> mm (b); and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$x =240$ </tex-math></inline-formula> mm, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$y =240$ </tex-math></inline-formula> mm, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z =100$ </tex-math></inline-formula> mm (c). Thus, because the signals from the heart are originally considered to be a single block, the estimated solution is also expected to be a single block. The solution was estimated as a single block, except case with analysis area (a), which corresponds to the conventional method. In addition, the position and size of the estimated solution are similar to those of the heart obtained from the computed tomography (CT) images. The goodness of fit of each analysis area was approximately 0.99 or more, which indicated that there was no significant difference. Thus, we demonstrated that it is possible to visualize the movement of the myocardium by estimating the time-series waveform of the MCG.

High-sensitivity operation of a single-beam atomic magnetometer for three-axis magnetic field measurement.

We demonstrate a single-beam atomic magnetometer (AM) capable of measuring a three-axis magnetic field with high-sensitivity, achieved by applying a small DC offset field and a high frequency modulation field. To satisfy the miniaturization demand of AMs, an elliptically polarized light detuned by 50 GHz from the resonance transition center is employed. The circularly polarized component is used to polarize the alkali-metal atoms, while the linearly polarized light is used to detect the dynamics of the polarized spin under a magnetic field. Based on theoretical analysis, parameters that significantly affect the performance are optimized, and a sensitivity of 20 fT/Hz1/2 in x-axis, 25 fT/Hz1/2 in y-axis, 30 fT/Hz1/2 in z-axis is achieved with a miniature 4 × 4 × 4 mm 87Rb vapor cell. Moreover, we also verify that the operation principle of AMs can be used to null background magnetic fields in-situ with isotropic compensation resolution of 6.7 pT, which provides an effectively precise method for zeroing ambient magnetic field. The high-sensitivity operating of an elliptically-polarized-laser-based magnetometer provides prospective futures for constructing a compact, low-cost AM, which is particularly applicable for non-invasive bio-magnetic imaging such as array-based magnetoencephalography (MEG) and magnetocardiography (MCG).

Measurement, processing and analysis of stress magnetocardiograms

Magnetocardiography (MCG) measures weak magnetic fields originating due to the electrical activity of the heart. MCG offers distinct diagnostic information on the cardiac electrophysiology in a variety of dysfunctions. This list includes myocardial ischemia, which is associated with reduced blood supply to the heart, electrically manifested as changes in the ST segment of the cardiac cycle. As opposed to the conventional measurement of electrocardiogram (ECG) on subjects undergoing physical stress test to investigate these ST changes, rest MCG itself has been demonstrated to be more sensitive. Considerable interest exists among researchers to investigate MCG signals measured during physical exertion as well to explore the possibilities of improvements in its sensitivity. This paper portrays the MCG measurements of a few subjects under rest and during moderate cycling in supine posture using a non-magnetic bicycle ergometer. The work details the signal processing steps followed in processing MCG to refine the signal quality in computing the parameter, ST fluctuation score in an automated manner. Significant changes are seen on the ST fluctuation scores measured on a few healthy subjects across rest and stress conditions. These results persuade its possible use on MCG measured on subjects with ischemic heart diseases by treating this analysis as baseline measurements.

An epoch based methodology to denoise magnetocardiogram (MCG) signals and its application to measurements on subjects with implanted devices

Magnetocardiograms (MCG) provide clinically useful diagnostic information in a variety of cardiac dysfunctions. Low frequency baseline drifts and high frequency noise are inevitably present in routine MCG even for those measured inside magnetically shielded rooms. These interferences sometimes exceed subtle cardiac features in MCG recorded on subjects with implanted devices like cardiac pacemakers; this makes interpretation of cardiac magnetic fields difficult. The present study proposes a correlation-based beat-by-beat approach and principal component analysis to eliminate drifts and high frequency noise respectively; the approach is suitable for denoising both single and multi-channel MCG data. The methodology is critically evaluated on simulated noisy measurements using a 37 channel MCG system, when objects such as implantable permanent pacemaker and stainless-steel wire are sequentially kept externally on the chests of five healthy subjects. By characterizing the noise introduced by each of these objects, the deterioration in the quality of MCG and its subsequent restoration by using the proposed method is assessed. The performance of the proposed method is also compared with other conventional denoising techniques namely, bandpass filters, wavelets and ensemble empirical mode decomposition. The proposed method not only exhibits least distortion, but also preserves the beat-by-beat dynamics of cardiac time series. The method has also been illustrated on actual MCG measurements on two subjects with implanted pacemaker which highlight the ability of the proposed method for denoising MCG in general and during extremely noisy measurement situations.

A new wearable multichannel magnetocardiogram system with a SERF atomic magnetometer array

In this study, a wearable multichannel human magnetocardiogram (MCG) system based on a spin exchange relaxation-free regime (SERF) magnetometer array is developed. The MCG system consists of a magnetically shielded device, a wearable SERF magnetometer array, and a computer for data acquisition and processing. Multichannel MCG signals from a healthy human are successfully recorded simultaneously. Independent component analysis (ICA) and empirical mode decomposition (EMD) are used to denoise MCG data. MCG imaging is realized to visualize the magnetic and current distribution around the heart. The validity of the MCG signals detected by the system is verified by electrocardiogram (ECG) signals obtained at the same position, and similar features and intervals of cardiac signal waveform appear on both MCG and ECG. Experiments show that our wearable MCG system is reliable for detecting MCG signals and can provide cardiac electromagnetic activity imaging.

Solving the Magnetocardiography Forward Problem in a Realistic Three-Dimensional Heart-Torso Model

The forward problem in magnetocardiography (MCG) is important for understanding the relationship between the electric activity of the heart and the body surface magnetic field (BSM), and providing insight into the clinical application of MCG. In this paper, we proposed a computational framework based on the finite element method (FEM) to solve the MCG forward problem. For the subject-specific heart-torso geometry established from the medical image, the modified FitzHugh-Nagumo (FHN) equation was used to describe the volumetric myocardial dynamic transmembrane potential (TMP), then the quasi-static Maxwell equations was applied to simulate the propagation of cardiac magnetic field produced by TMP. The two parts were validated on the simplified one-dimensional FHN equation and the source model of the straight wire respectively, in which the analytical solutions exist. Further, under a realistic geometry heart-torso model, the distribution of the body surface magnetic vector field was presented, the component in the direction perpendicular to the body surface ( B <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y</sub> ) of which was in very good agreement with the actual observations from the same subject on a pulse-pumped Rb atomic magnetometer.

The latest trend in magnetocardiogram measurement system technology

Heart consists of myocardium cells and the electrophysiological activity of the cells generate magnetic fields. By measuring this magnetic field, magnetocardiogram (MCG), functional diagnosis of the heart diseases is possible. Since the strength of the MCG signals is weak, typically in the range of 1-10 pT, we need sensitive magnetic sensors. Conventionally, superconducting quantum interference devices (SQUID)s were used for the detection of MCG signals due to its superior sensitivity to other magnetic sensors. However, drawback of the SQUID is the need for regular refill of a cryogenic liquid, typically liquid helium for cooling lowtemperature SQUIDs. Efforts to eliminate the need for the refill in the SQUID system have been done by using cryocooler-based conduction cooling or use of non-cryogenic sensors, or room-temperature sensors. Each sensor has advantage and disadvantage, in terms of magnetic field sensitivity and complexity of the system, and we review the recent trend of MCG technology.

Novel Non-Invasive Index for Prediction of Responders in Cardiac Resynchronization Therapy Using High-Resolution Magnetocardiography.

Approximately one-third of patients with advanced heart failure (HF) do not respond to cardiac resynchronization therapy (CRT). We investigated whether the left ventricular (LV) conduction pattern on magnetocardiography (MCG) can predict CRT responders.Methods and Results:This retrospective study enrolled 56 patients with advanced HF (mean [±SD] LV ejection fraction [LVEF] 23±8%; QRS duration 145±19 ms) and MCG recorded before CRT. MCG-QRS current arrow maps were classified as multidirectional (MDC; n=28) or unidirectional (UDC; n=28) conduction based on a change of either ≥35° or <35°, respectively, in the direction of the maximal current arrow after the QRS peak. Baseline New York Heart Association functional class and LVEF were comparable between the 2 groups, but QRS duration was longer and the presence of complete left bundle branch block and LV dyssynchrony was higher in the UDC than MDC group. Six months after CRT, 30 patients were defined as responders, with significantly more in the UDC than MDC group (89% vs. 14%, respectively; P<0.001). Over a 5-year follow-up, Kaplan-Meyer analysis showed that adverse cardiac events (death or implantation of an LV assist device) were less frequently observed in the UDC than MDC group (6/28 vs. 15/28, respectively; P=0.027). Multivariate analysis revealed that UDC on MCG was the most significant predictor of CRT response (odds ratio 69.8; 95% confidence interval 13.14-669.32; P<0.001). Preoperative non-invasive MCG may predict the CRT response and long-term outcome after CRT.

Construction of Dynamic Lead Fields from Vectorcardiography to Solve the Forward and the Inverse Problems in Magnetocardiography

The muscles of the heart are associated with the flow of currents on tissue in the volume conductor formed inside the human body. The electrical currents of the human heart generate a tiny magnetic field beyond the thorax surface. The functional waves generated in terms of the field are detected using Magnetocardiogram (MCG) at the detector level. One of the challenging tasks in the research area is to compute algorithms which help in visualizing/localizing the cardiac anomalies non-invasively at the heart level. In order to localize, a generic model based on prior assumptions is designed which is known as a forward problem. This model depicts the spatial relation between the heart locations and the detectors.In this paper, a novel method is proposed in the construction of the forward matrix; where the prior heart vectors are constrained with vectorcardiography (VCG) signals. The spatial matrix is subsequently used to estimate the desired position on the myocardium in an inverse way. To evaluate the model, several true prior dipoles are placed on desired positions of the heart each at a time and the inverse problem is solved using multi-start downhill simplex search. The spatial matrices are updated based on VCG during each movement of the test dipoles' positions in the inverse search. The inverse studies are computed and compared between the proposed and the existed methods for the entire cardiac cycle. The performance of the inverse model with unit VCG orientations exhibited an improvement of 3.027±0.17 mm average localization error than the conventional one.

Miniature Coil Array for Passive Magnetocardiography in Non-Shielded Environments

Existing practices for monitoring heart activity rely heavily on electrocardiography (ECG) approaches, which suffer from low accuracy (as electric fields get impacted by biological tissues); extensive diagnostic times; and lack of comfort (as electrodes are in direct contact with the human body). Though magnetocardiography (MCG) provides more accurate and localized signals while also being non-contact, state-of-the-art equipment for capturing such weak magnetic fields (i.e., SQUIDs) requires extensive shielding and is very expensive. MCG sensing devices that do not require shielding have been reported, but they are sbulky, heavy, and cumbersome to use. In this work, we take a major step forward and propose a novel, miniature, and low-cost MCG sensor for operation in non-shielded environments that breaks the state-of-the-art boundaries in terms of size and weight. Our sensor relies on novel coil design principles and Digital Signal Processing (DSP) algorithms to achieve: (a) 4.67 times smaller diameter, (b) 4.5 times smaller height, and (c) at least 216 times lighter weight than previous passive implementations. In vitro measurements demonstrate that a 4-coil sensor array with 15 minutes of recoding time is sufficient to capture human MCG signals. Discussions indicate that higher number of coils and longer recording times can be employed to improve the signal clarity and fit diverse clinical needs. The proposed coil sensor array provides a convenient method to diagnose several cardiac conditions, such as myocardial ischemia, arrhythmia, right atrial hypertrophy, right ventricular hypertrophy, and the Brugada syndrome.