Predictive value of unshielded magnetocardiographic mapping to differentiate atrial fibrillation patients from healthy subjects

Coronary artery disease severity and location detection using deep-mining-based magnetocardiography pattern features

BACKGROUND AND OBJECTIVE

The objective of this study was to develop an automated, accurate method of assessing coronary artery disease (CAD), including its severity and location, using deep-mining-based magnetocardiography (MCG) pattern features.

METHODS

The pattern information of MCG was mined deeply, and features were extracted from multiple perspectives. The curl, gradient, and divergence fields were extended based on the current field to visualize hidden pattern information before the singular value decomposition, main field, and image class features were proposed. Finally, the statistical parameters of fine granularity and compound features were introduced. To estimate the CAD severity, stenosis was classified as none, mild, moderate, or severe, and a suitable subset of features for machine learning (ML) modeling was presented. To localize CAD, it was categorized according to the stenosis location, including the left anterior descending (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and the selected subsets of features appropriate for each localization ML model.

RESULTS

The test set exhibited an accuracy, precision, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve of 85.1 %, 77.8 %, 75.9 %, 95.6 %, 75.9 %, and 0.853, respectively, for CAD severity. The model test sets to detect the LAD, LCX, and RCA locations exhibited accuracies of 97.6 %, 81.2 %, and 85.9 %, respectively.

CONCLUSIONS

Deep-mining-based MCG features can effectively reflect the severity and location of CAD. The proposed ML method can serve as an automated, accurate diagnostic tool for clinicians to improve the interpretation and application of MCG technology in clinical settings.

An advanced vision of magnetocardiography as an unrivalled method for a more comprehensive non-invasive clinical electrophysiological assessment

Decades of experimental and clinical studies, along with the most recent clinical trials, have demonstrated the diagnostic potential of magnetocardiography, particularly for the non-invasive early diagnosis of myocardial ischemia. It has also proven to be a valuable clinical tool for monitoring fetal well-being, normal growth, prenatal arrhythmias, and risk markers for sudden death. Such applications have recently received official recognition from Health Canada and the American Heart Association. This unquestionable success, and the additional evidence of magnetocardiography's high sensitivity in diagnosing infiltrative and inflammatory cardiomyopathies, has sparked renewed interest among clinicians. However, while these aforementioned applications are likely to significantly influence the broader clinical adoption of magnetocardiography, the general focus on these areas has shifted attention away from what we have always regarded as the fundamental strength of contactless cardiac magnetic field mapping: its unique ability to bridge the gap between experimental electrophysiology at the cellular level and non-invasive clinical assessments of human electrophysiology. This review aims to engage readers by sharing our vision, experience, and several key research milestones, emphasizing the lesser-explored yet significant potential of magnetocardiography. Specifically, it highlights its unique capability to detect electrically silent phenomena that may be critical for the timely and accurate identification of arrhythmogenic focal electrotonic and vortex currents, which can trigger or sustain life-threatening arrhythmias.

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.

Cardiac Conduction Velocity, Remodeling and Arrhythmogenesis

Cardiac electrophysiological disorders, in particular arrhythmias, are a key cause of morbidity and mortality throughout the world. There are two basic requirements for arrhythmogenesis: an underlying substrate and a trigger. Altered conduction velocity (CV) provides a key substrate for arrhythmogenesis, with slowed CV increasing the probability of re-entrant arrhythmias by reducing the length scale over which re-entry can occur. In this review, we examine methods to measure cardiac CV in vivo and ex vivo, discuss underlying determinants of CV, and address how pathological variations alter CV, potentially increasing arrhythmogenic risk. Finally, we will highlight future directions both for methodologies to measure CV and for possible treatments to restore normal CV.

Predictive value of unshielded magnetocardiographic mapping to differentiate atrial fibrillation patients from healthy subjects

BACKGROUND

P-wave duration, its dispersion and signal-averaged ECG, are currently used markers of vulnerability to atrial fibrillation (AF). However, since tangential atrial currents are better detectable at the body surface as magnetic than electric signals, we investigated the accuracy of magnetocardiographic mapping (MCG), recorded in unshielded clinical environments, as predictor of AF occurrence.

METHODS

MCG recordings, in sinus rhythm (SR), of 71 AF patients and 75 controls were retrospectively analyzed. Beside electric and magnetic P-wave and PR interval duration, two MCG P-wave subintervals, defined P-dep and P-rep, were measured, basing on the point of inversion of atrial magnetic field (MF). Eight parameters were calculated from inverse solution with "Effective Magnetic Dipole (EMD) model" and 5 from "MF Extrema" analysis. Discriminant analysis (DA) was used to assess MCG predictive accuracy to differentiate AF patients from controls.

RESULTS

All but one (P-rep) intervals were significantly longer in AF patients. At univariate analysis, three EMD parameters differed significantly: in AF patients, the dipole-angle-elevation angular speed was lower during P-dep (p < 0.05) and higher during P-rep (p < 0.001) intervals. The space-trajectory during P-rep and the angle-dynamics during P-dep were higher (p < 0.05), whereas ratio-dynamics P-dep was lower (p < 0.01), in AF. At DA, with a combination of MCG and clinical parameters, 81.5% accuracy in differentiating AF patients from controls was achieved. At Cox-regression, the angle-dynamics P-dep was an independent predictor of AF recurrences (p = 0.037).

CONCLUSIONS

Quantitative analysis of atrial MF dynamics in SR and the solution of the inverse problem provide new sensitive markers of vulnerability to AF.