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Magnetocardiography (MCG) provides a non-invasive, contactless technique for evaluating the magnetic fields generated by cardiac electrical activity, offering unique spatial insights into cardiac electrophysiology. However, conventional MCG systems depend on superconducting quantum interference devices that require cryogenic cooling and magnetic shielded environments, posing considerable impediments to widespread clinical adoption. In this study, we present a novel MCG system utilizing a high-sensitivity, wide-dynamic-range magnetoresistive sensor array operating at room temperature. To mitigate environmental interference, identical sensors were deployed as reference channels, enabling adaptive noise cancellation (ANC) without the need for traditional magnetic shielding. MCG recordings were obtained from 40 healthy participants, with signals processed using ANC, R-peak-synchronized averaging, and Bayesian spatial signal separation. This approach enabled the reliable detection of key cardiac components, including P, QRS, and T waves, from the unshielded MCG recordings. Our findings underscore the feasibility of a cost-effective, portable MCG system suitable for clinical settings, presenting new opportunities for noninvasive cardiac diagnostics and monitoring.

Despite cognitive workload (CW) being a critical metric in several applications, no technology exists to seamlessly and reliably quantify CW. Previously, we demonstrated the feasibility of a wearable MagnetoCardioGraphy (MCG) sensor to classify high vs. low CW based on MCG-derived heart rate variability (mHRV). However, our sensor was unable to address certain critical operational requirements, resulting in noisy signals, often to the point of being unusable. In addition, test conditions for the participants were not decoupled from motion (i.e., physical activity (PA)), raising questions as to whether the noted changes in mHRV were attributed to CW, PA, or both. This study reports software and hardware advancements to optimize the MCG data quality, and investigates whether changes in CW (in the absence of PA) can be reliably detected. Performance is validated for healthy adults (n = 10) performing three types of CW tasks (one for low CW and two for high CW to eliminate the memory effect). Results demonstrate the ability to retrieve MCG R-peaks throughout the recordings, as well as the ability to differentiate high vs. low CW in all cases, confirming that CW does modulate the mHRV. A paired Bonferroni t-test with significance α=0.01 confirms the hypothesis that an increase in CW decreases mHRV. Our findings lay the groundwork toward a seamless, practical, and low-cost sensor for monitoring CW.

Fetal magnetocardiography (fMCG) is a non-invasive technique that measures the magnetic fields associated with fetal heart electrical activity outside of the maternal abdomen. fMCG has high temporal precision for measuring fetal heart rate and its variability which reflects fetal neurodevelopment. Free of cryogenics and low-cost sensors called microfabricated optically pumped magnetometers (OPMs) have emerged as an alternate to cryogenic SQUID (Superconducting Quantum Interference Device) systems to record fMCG. Previous research has demonstrated the ability of the OPMs to measure the fMCG at different maternal positions by taking the advantage of the conformal and geometric flexibility of the sensors. In this work, we designed and configured a bed-based stand-alone array of OPMs to obtain serial recordings of fMCG. 72 combined OPM-SQUID recordings were conducted at different gestational ages in 22 pregnant women. We were able to obtain fMCG with similar detectability as the gold standard SQUID from OPM sensors mounted on a novel belly-shape patient interface design with movable sensor holders. While additional translational research is needed, the outcome of this study can further facilitate the development of a non-cryogenic low-cost smaller footprint device to increase the use of OPMs for fetal research and clinical applications.

Magnetocardiography has received regulatory recognition as a contactless, sensitive aid for physicians to diagnose or exclude myocardial ischemia in chest pain patients, with or without coronary obstruction. Such success, however, might not equate to guideline endorsement or proven clinical effectiveness. Moreover, despite its intrinsic advantages, including unrivalled contactless functional imaging of cardiac electrophysiology and a strong potential for multimodal integration with other imaging methods, its clinical adoption remains limited by the lack of internationally recognized standards and guidelines. This Perspective Review article, highlighting the viewpoints of clinical end users, is a call for urgent action to establish an interdisciplinary expert commission. This is essential for defining consensus-based standards and recommendations for the clinical use of MCG.

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 pTrms 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 pTrms 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.

Background Fetal magnetocardiography (fMCG) is the most accurate method to assess fetal heart rhythm and conduction. New quantum sensor technology makes it possible to use less expensive devices. The aim of the study is to measure cardiac time intervals of healthy fetuses with a new technology, optically pumped magnetometry (OPM), and compare these results with conventional SQUID-based fMCG and postnatal ECGs. Methods The recordings were made using an OPM-based fMCG system and a person-sized magnetic shield, established at German Heart Center,TUM University, Munich, Germany. The subjects were 57 healthy women with uncomplicated singleton pregnancies, studied at a mean gestational age of 32 ± 3.7 weeks with an overall range of 25–40 weeks. The P, PR, QRS, QT, QTc, and RR intervals were measured and compared with published data from previous fMCG devices and postnatal ECG. Results The P, PR, and QRS intervals increased with gestational age, but the QT and QTc intervals did not. The measured values of the OPM device were consistent with those from previously published data SQUID values. U-waves were seen in 17.3% of subjects. Eleven subjects were studied by fMCG after 30 weeks’ gestation and by ECG within 17 weeks of birth. In this cohort, the P-wave duration, QRS duration, and QTc increased after birth, but the PR and QT intervals did not. Conclusion The results obtained with our innovative OPM-based fMCG system are comparable to previously available measurements obtained by other technologies. The data establish prediction intervals for OPM-based fMCG waveforms in normal fetuses, which is essential for future clinical application. The technology can be used to recognize fetuses with rhythm or conduction abnormalities that might not be evident by echocardiography. To our knowledge, this is the first report comparing fetal cardiac time intervals measured by OPM-based fMCG with postnatal ECG. Lengthening of cardiac intervals consistent with increased chamber size was seen postnatally.

Letter to the Editor

An extremely low magnetic field environment is required for magnetocardiography (MCG) based on SERF atomic magnetometers. This environment is typically achieved using a magnetic shielding cylinder (MSC) in conjunction with active magnetic compensation (AMC). However, to facilitate patient access, the MSC is designed with a single-ended opening, which compromises its shielding efficiency and leads to a nonlinear gradient distribution of magnetic disturbance within the MSC. This paper proposes an asymmetric toroidal coil configuration for the AMC system. The characteristics of the coil were studied, and the coil parameters were optimized. Experimental results demonstrate that the proposed method effectively reduces the spatial gradient of magnetic disturbance across the MCG measurement panel, thereby enhancing MCG imaging performance.

The human heart produces electrical signals to contract and relax its muscles that helps in its blood pumping activities. These electrical impulses give rise to electric potentials on the body surface and tiny magnetic field around the thorax. These functional activities can be investigated using Electro/Magnetocardiogram (E/MCG). The more challenging task in the E/MCG research is to image the cardiac dysfunctions in three dimensions not at the surface level but at the source level and this is called the inverse problem. To solve this, one has to model a generic structure of the discretised heart enclosed in the thorax mesh and their spatial relation with location of the MCG detectors, called forward problem. In this current research, sources in a homogeneous volume conductor model is used in the construction of forward problem. A novel algorithm is implemented that uses Vectocardiography (VCG) signals in the forward problem of MCG. Another objective of this paper includes the utilization of dynamic lead field based on VCG orientations in the inverse problem. In this study, the ill-posed problems are solved using Bayesian approach and the results are compared with the deterministic approach for measurements on noise signals. The analysis revealed that the proposed algorithms with VCG priors (that are extracted from the VCG signals) in the Bayesian framework significantly improved MCG source localization in cases of Myocardial Ischemia. Analysis from the study showed that the proposed algorithms with VCG priors in probabilistic methods significantly captured a good region of spread of the reconstructed borders of inverse solutions. The average spread for deterministic methods was around 3.5 - 4.3cm in the diseased cases with simulated true ruptured region of spread being 2.5cm. In contrast, Bayesian methods and total variation methods with VCG priors reduced the spread to 2.9 to 3.03cm, respectively. The introduction of VCG signals in the forward problem of MCG not only increases the accuracy of cardiomagnetic imaging but also provides a path for more reliable diagnostic tools in cardiology.

Early diagnosis and localization of myocardial ischemia (MS) and coronary artery stenosis (CAS) play a crucial role in the effective prevention and management of ischemic heart disease (IHD). Magnetocardiography (MCG) has emerged as a promising approach for non-invasive, non-contact, and high-sensitivity assessment of cardiac dysfunction. This study presents a multi-center, AI-enabled diagnosis and localization of myocardial ischemia and coronary artery stenosis from MCG data. To this end, we collected a large-scale dataset consisting of 2,158 MCG recordings from eight clinical centers. We then proposed a multiscale vision transformer-based network for extracting spatio-temporal information from multichannel MCG recordings. Anatomical prior knowledge of the coronary artery and the irrigated left ventricular regions was incorporated by a carefully designed graph convolutional network (GCN)-based feature fusion module. The proposed approach achieved an accuracy of 84.7%, a sensitivity of 83.8%, and a specificity of 85.6% in diagnosing IHD, an average accuracy of 78.4% in localization of five MS regions, and an average accuracy of 65.3% in localization of stenosis in three coronary arteries. Subsequent validation on an independent validation dataset consisting of 268 MCG recordings collected from four clinical centers demonstrated an accuracy of 82.3%, a sensitivity of 83.8%, and a specificity of 81.3% in diagnosing IHD, an average accuracy of 77.3% in localization of five myocardial ischemic regions, and an average accuracy of 65.6% in localization of stenosis in three coronary arteries. The proposed approach can be used as a fast and accurate diagnosis tool, boosting the integration of MCG examination into clinical routine.