Correlation of fetal heart rate dynamics to inflammatory markers and brain-derived neurotrophic factor during pregnancy

OBJECTIVES

This study aims to show the relation between biomarkers in maternal and cord-blood samples and fetal heart rate variability (fHRV) metrics through a non-invasive fetal magnetocardiography (fMCG) technique.

METHODS

Twenty-three women were enrolled for collection of maternal serum and fMCG tracings immediately prior to their scheduled cesarean delivery. The umbilical cord blood was collected for measurement of biomarker levels. The fMCG metrics were then correlated to the biomarker levels from the maternal serum and cord blood.

RESULTS

Brain-derived neurotrophic factor (BDNF) had a moderate correlation with fetal parasympathetic activity (0.416) and fetal sympathovagal ratios (-0.309; -0.356). Interleukin (IL)-6 also had moderate-sized correlations but with an inverse relationship as compared to BDNF. These correlations were primarily in cord-blood samples and not in the maternal blood.

CONCLUSIONS

In this small sample-sized exploratory study, we observed a moderate correlation between fHRV and cord-blood BDNF and IL-6 immediately preceding scheduled cesarean delivery at term. These findings need to be validated in a larger population.

The role of beat-by-beat cardiac features in machine learning classification of ischemic heart disease (IHD) in magnetocardiogram (MCG)

Cardiac electrical changes associated with ischemic heart disease (IHD) are subtle and could be detected even in rest condition in magnetocardiography (MCG) which measures weak cardiac magnetic fields. Cardiac features that are derived from MCG recorded from multiple locations on the chest of subjects and some conventional time domain indices are widely used in Machine learning (ML) classifiers to objectively distinguish IHD and control subjects. Most of the earlier studies have employed features that are derived from signal-averaged cardiac beats and have ignored inter-beat information. The present study demonstrates the utility of beat-by-beat features to be useful in classifying IHD subjects (n = 23) and healthy controls (n = 75) in 37-channel MCG data taken under rest condition of subjects. The study reveals the importance of three features (out of eight measured features) namely, the field map angle (FMA) computed from magnetic field map, beat-by-beat variations of alpha angle in the ST-T region and T wave magnitude variations in yielding a better classification accuracy (92.7 %) against that achieved by conventional features (81 %). Further, beat-by-beat features are also found to augment the accuracy in classifying myocardial infarction (MI) Versus control subjects in two public ECG databases (92 % from 88 % and 94 % from 77 %). These demonstrations summarily suggest the importance of beat-by-beat features in clinical diagnosis of ischemia.

Exploring the Influence of Fetal Sex on Heart Rate Dynamics Using Fetal Magnetocardiographic Recordings

Fetal sex has been associated with different development trajectories that cause structural and functional differences between the sexes throughout gestation. Fetal magnetocardiography (fMCG) recordings from 123 participants (64 females and 59 males; one recording/participant) from a database consisting of low-risk pregnant women were analyzed to explore and compare fetal development trajectories of both sexes. The gestational age of the recordings ranged from 28 to 38 weeks. Linear metrics in both the time and frequency domains were applied to study fetal heart rate variability (fHRV) measures that reveal the dynamics of short- and long-term variability. Rates of linear change with GA in these metrics were analyzed using general linear model regressions with assessments for significantly different variances and GA regression slopes between the sexes. The fetal sexes were well balanced for GA and sleep state. None of the fHRV measures analyzed exhibited significant variance heterogeneity between the sexes, and none of them exhibited a significant sex-by-GA interaction. The absence of a statistically significant sex-by-GA interaction on all parameters resulted in none of the regression slope estimates being significantly different between the sexes. With high-precision fMCG recordings, we were able to explore the variation in fHRV parameters as it relates to fetal sex. The fMCG-based fHRV parameters did not show any significant difference in rates of change with gestational age between sexes. This study provides a framework for understanding normal development of the fetal autonomic nervous system, especially in the context of fetal sex.

Enhancing the efficiency and cost-effectiveness of magnetocardiography by optimal channel selection for cardiac diagnosis

Background. Magnetocardiography (MCG) is a non-invasive and non-contact technique that measures weak magnetic fields generated by the heart. It is highly effective in the diagnosis of heart abnormalities. Multichannel MCG provides detailed spatio-temporal information of the measured magnetic fields. While multichannel MCG systems are costly, usage of the optimal number of measurement channels to characterize cardiac magnetic fields without any appreciable loss of signal information would be economically beneficial and promote the widespread use of MCG technology.Methods. An optimization method based on the sequential selection approach is used to choose channels containing the maximum signal information while avoiding redundancy. The study comprised 40 healthy individuals, along with two subjects having ischemic heart disease and one subject with premature ventricular contraction. MCG measured using a 37 channel MCG system. After revisiting the existing methods of optimization, the mean error and correlation of the optimal set of measurement channels with those of all 37 channels are evaluated for different sets, and it has been found that 18 channels are adequate.Results. The chosen 18 optimal channels exhibited a strong correlation (0.99 ± 0.006) between the original and reconstructed magnetic field maps for a cardiac cycle in healthy subjects. The root mean square error is 0.295 pT, indicating minimal deviation.Conclusion. This selection method provides an efficient approach for choosing MCG, which could be used for minimizing the number of channels as well as in practical unforeseen measurement conditions where few channels are noisy during the measurement.

Magnetocardiography-based coronary artery disease severity assessment and localization using spatiotemporal features

Objective.This study aimed to develop an automatic and accurate method for severity assessment and localization of coronary artery disease (CAD) based on an optically pumped magnetometer magnetocardiography (MCG) system.Approach.We proposed spatiotemporal features based on the MCG one-dimensional signals, including amplitude, correlation, local binary pattern, and shape features. To estimate the severity of CAD, we classified the stenosis as absence or mild, moderate, or severe cases and extracted a subset of features suitable for assessment. To localize CAD, we classified CAD groups according to the location of the stenosis, including the left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA), and separately extracted a subset of features suitable for determining the three CAD locations.Main results.For CAD severity assessment, a support vector machine (SVM) achieved the best result, with an accuracy of 75.1%, precision of 73.9%, sensitivity of 67.0%, specificity of 88.8%, F1-score of 69.8%, and area under the curve of 0.876. The highest accuracy and corresponding model for determining locations LAD, LCX, and RCA were 94.3% for the SVM, 84.4% for a discriminant analysis model, and 84.9% for the discriminant analysis model.Significance. The developed method enables the implementation of an automated system for severity assessment and localization of CAD. The amplitude and correlation features were key factors for severity assessment and localization. The proposed machine learning method can provide clinicians with an automatic and accurate diagnostic tool for interpreting MCG data related to CAD, possibly promoting clinical acceptance.

A movable unshielded magnetocardiography system

Magnetocardiography (MCG), which uses high-sensitivity magnetometers to record magnetic field signals generated by electrical activity in the heart, is a noninvasive method for evaluating heart diseases such as arrhythmia and ischemia. The MCG measurements usually require the participant keeping still in a magnetically shielded room due to the immovable sensor and noisy external environments. These requirements limit MCG applications, such as exercise MCG tests and long-term MCG observations, which are useful for early detections of heart diseases. Here, we introduce a movable MCG system that can clearly record MCG signals of freely behaving participants in an unshielded environment. On the basis of optically pumped magnetometers with a sensitivity of 140 fT/Hz1/2, we successfully demonstrated the resting MCG and the exercise MCG tests. Our method is promising to realize a practical movable multichannel unshielded MCG system that nearly sets no limits to participants and brings another kind of insight into the medical diagnosis of heart disease.

Assessment of atrioventricular conduction by echocardiography and magnetocardiography in normal and anti-Ro/SSA-antibody-positive pregnancies

OBJECTIVES

The objectives of this study were, first, to evaluate the association between fetal echocardiographic atrioventricular (AV) and magnetocardiographic (fMCG) PR intervals at different gestational ages (GAs) in normal and anti-Ro/SSA-antibody-positive pregnancies; second, to determine if PR interval could be predicted by AV interval; and third, to assess the neonatal outcome of fetuses with prolonged AV and PR intervals, with the goal of developing criteria for fetal first-degree AV block (AVB-I).

METHODS

This was a retrospective study of anti-Ro/SSA-antibody-positive pregnancies (cases) and controls that underwent fMCG and fetal echocardiography at the same recording session. Cardiac cycle length, GA and AV (by mitral inflow/aortic outflow Doppler) and PR (by fMCG) intervals were measured. We tested for significant differences between AV and PR intervals using generalized estimating equations to account for repeat measurements, and assessed whether PR interval could be predicted reliably by AV interval. After delivery, infants with fetal AV or PR interval Z-score ≥ 3 underwent 12-lead electrocardiography.

RESULTS

Thirty-nine controls and 31 cases underwent 46 and 36 simultaneous fMCG and echocardiographic examinations, respectively; 101 controls and nine cases underwent fMCG only. AV and PR intervals increased with GA (P < 0.05 for both). Overall, AV and PR intervals were significantly different from each other (P < 0.001); this difference was not significant when compared between cases and controls (P = 0.222). PR interval could not be predicted accurately from AV interval and GA alone. Three of four cases with AV and PR interval Z-scores > + 3 had postnatal AVB-I despite treatment. The fourth fetus, which had predominately second-degree AVB and rare periods of AVB-I, progressed to third-degree AVB despite treatment with dexamethasone.

CONCLUSIONS

The diagnostic threshold for AVB-I, defined by AV interval Z-score, is GA dependent. Based on the observed data, an AV interval Z-score threshold of 3 (AV interval, 151-167 ms) may be appropriate. Echocardiographic AV interval was not predictive of fMCG-PR interval. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Coupling Analysis of Fetal and Maternal Heart Rates via Transfer Entropy Using Magnetocardiography

Recent studies have shown that occasional short term coupling between fetal and maternal cardiac systems occurs. Fetal magnetocardiography (fMCG) is a non-invasive technique that records the magnetic fields associated with the electrical activity of the fetal heart through sensors placed over the maternal abdomen. The fMCG allows accurate estimation of fetal heart rates (fHR) due to its high signal-to-noise ratio (SNR) and temporal resolution. In this study, we analyzed couplingbetween fHR and maternal heart rates (mHR) using Transfer Entropy (TE). TE determines coupling between two variables by quantifying the information transferred between them in both directions. In this work, we used 74 fMCG recordings to compute TE in both directions over 1-minute disjoint time windows (TW). We examined the effect of fetal movement (FM) as a factor of influence on the TE analysis. We identified 21 subjects with FM during the recording and separated them into two gestational age (GA) groups (GA1<32 and GA2≥32 weeks). Next, TE values were compared between TWs containing non- FM with TWs containing FM using Wilcoxon Signed-Rank test. In addition, we compared TE calculations for non-FM segments obtained from the 74 subjects using Rank-Sum test in the two GA groups. Our results showed that TE values from TWs containing FM are not significantly different than those computed for TWs of non-FM. In both directions, we found that TE values obtained from the 74 subjects did not show any significant difference between GA1 and GA2 which is consistent with previous studies. Our study suggests that FM does not affect the TE computations.

Magnetocardiography-Based Ischemic Heart Disease Detection and Localization Using Machine Learning Methods

OBJECTIVE

This study focused on developing a fast and accurate automatic ischemic heart disease detection/localization methodology.

METHODS

T wave was segmented from averaged Magnetocardiography (MCG) recordings and 164 features were subsequently extracted. These features were categorized into three groups: time domain features, frequency domain features, and information theory features. Next, we compared different machine learning classifiers including: k-nearest neighbor, decision tree, support vector machine (SVM), and XGBoost. To identify ischemia heart disease (IHD) case, we selected three classifiers with best performance and applied model ensemble to average results. All 164 features were used in this stage. To localize ischemia, we classified IHD group according to stenosis locations, including left anterior descending (LAD), left circumflex artery (LCX), and right coronary artery (RCA). For this task, we used XGBoost classifier and 18 time domain features.

RESULTS

For IHD detection, the SVM-XGBoost model achieved best results with accuracy = 94.03%, precision = 86.56%, recall = 97.78%, F-score = 92.79%, AUC = 0.98, and average precision = 0.98. For ischemia localization, XGBoost model achieved accuracy = 0.74, 0.68, and 0.65, for LAD, LCX, and RCA, respectively.

CONCLUSION

we have developed an automatic IHD detection and localization system. We find that 1. T wave repolarization synchronicity is an important factor to distinguish IHD from normal subjects 2. Magnetic field pattern is associated with stenosis location.

SIGNIFICANCE

The proposed machine learning method provides the clinicians a fast and accurate diagnosis tool to interpret MCG data, boosting its acceptance into clinics. Furthermore, the magnetic pole characteristics revealed by the method shows to be related to ischemia location, presenting the opportunity to noninvasively locate ischemia.

Tracking Fetal Movement Through Source Localization From Multisensor Magnetocardiographic Recordings

Due to its high spatial and temporal resolution, fetal magnetocardiography (fMCG) measurements have been used for fetal movement (FM) detection in several studies, which considered the changes in the amplitude and/or morphology of measured fMCG signals. Using source localization for fMCG measurements, we propose a novel method to fit a magnetic dipole moment to fetal heart signals and investigate the positional changes of magnetic dipole in order to detect FMs. We first split each fMCG recording into 6-s time windows. Then, the magnetic dipole location and orientation for each time window are estimated using our inverse solution model. Finally, the distance between magnetic dipole positions in adjacent time windows is computed. Also, we calculate the dot products of the normalized magnetic dipoles to monitor the orientational changes. We analyzed 28 fMCG measurements from 23 subjects to investigate accuracy of the dipole fitting results. For each dipole fit, our model described the measured data with a goodness-of-fit value over 97% and with a fitting error of less than 2%. We observed that magnetic dipole positions significantly moved for some time windows. The time points at which the significant movement was observed were correlated with the heart rate acceleration as well. In addition to identifying the time points of the movement, our method is capable of observing rotational movement checking orientation of the dipoles.

Separation of Physiological Signals Using Minimum Norm Projection Operators

OBJECTIVE

This paper presents the development of a fast and robust method which can be applied to multichannel physiologic signals for the purpose of either removing a selected interfering signal or separating signals that arise from temporally correlated and spatially distributed signals such as maternal or fetal cardiac waveform recordings.

METHODS

Projection operators based upon both the weighted and un-weighted minimum norm equations are presented. The weighted formulation uses models based on signal covariance and the un-weighted formulation requires that a statistical model be built using time-locked averaging.

RESULTS

We present examples that demonstrate the utility of our projection operators when applied to maternal and fetal magneto-cardiograms. In addition, we demonstrate the ability to separate fetal breathing signals from both maternal and fetal cardiac signals.

CONCLUSION

The method is effective, robust, fast, and does not require significant input from a user.

SIGNIFICANCE

Although we demonstrate the utility of our projection operators applied to biomagnetic signals, the method can easily be adapted to other applications were the goal is to either separate or suppress selected signal components.

Genetic algorithms for dipole location of fetal magnetocardiography

In this paper, we explore the use of Maximum Likelihood (ML) method with Genetic Algorithms (GA) as global optimization procedure for source reconstruction in fetal magnetocardiography (fMCG) data. A multiple equivalent current dipole (ECD) model was used for sources active in different time samples. Inverse solutions across time were obtained for a single-dipole approximation to estimate the trajectory of the dipole position. We compared the GA and SIMPLEX methods in a simulation environment under noise conditions. Methods are applied on a real fMCG data. Results show robust estimators of the cardiac sources when GA is used as optimization technique.

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.

Evaluation of standardized, computerized Dawes/Redman heart-rate analysis based on different recording methods and in relation to fetal beat-to-beat heart rate variability

Dawes and Redman (DR) based their definition of short-term variation (STV) on the successive differences of mean inter-beat intervals dividing 1 min of cardiotocography recordings in 16 epochs of 3.75 s each. In contrast, heart rate variability (HRV) is based on the inter-beat intervals of discrete R peaks, also referred to as normal-to-normal (NN) intervals. Despite the historical achievements of DR in providing a robust method with the equipment available at the time to encourage the widespread use and creation of large databases, one must ask whether the STV (DR) parameter is reproducible using a different method of recording, and how much temporal information is actually lost by applying the averaging algorithm sketched above. We simultaneously performed both standard Oxford cardiotocography and transabdominal fetal electrocardiography recordings in 26 patients with low-risk singletons. In addition, we revisited our database of 418 standard fetal magnetocardiographic recordings, applying the DR algorithm to the fetal NN data and compared them to standard HRV parameters. The correlation between STV (DR) from cardiotocography and fetal electrocardiography was stronger that of either with short term fHRV from NN intervals. The methodological trade-off to gain STV as a robust parameter from heart rate traces of limited temporal resolution is accompanied by a loss of temporal information that, at the moment, only fetal magnetocardiography and, to a lesser extent, fetal electrocardiography may provide.

Optimal Magnetic Sensor Vests for Cardiac Source Imaging

Magnetocardiography (MCG) non-invasively provides functional information about the heart. New room-temperature magnetic field sensors, specifically magnetoresistive and optically pumped magnetometers, have reached sensitivities in the ultra-low range of cardiac fields while allowing for free placement around the human torso. Our aim is to optimize positions and orientations of such magnetic sensors in a vest-like arrangement for robust reconstruction of the electric current distributions in the heart. We optimized a set of 32 sensors on the surface of a torso model with respect to a 13-dipole cardiac source model under noise-free conditions. The reconstruction robustness was estimated by the condition of the lead field matrix. Optimization improved the condition of the lead field matrix by approximately two orders of magnitude compared to a regular array at the front of the torso. Optimized setups exhibited distributions of sensors over the whole torso with denser sampling above the heart at the front and back of the torso. Sensors close to the heart were arranged predominantly tangential to the body surface. The optimized sensor setup could facilitate the definition of a standard for sensor placement in MCG and the development of a wearable MCG vest for clinical diagnostics.

[Fetal magnetocardiography: a promising way to diagnose fetal arrhytmia and to study fetal heart rate variability?]

OBJECTIVE

An overwiev of the new diagnostic method of fetal wellbeing - fetal magnetocardiography (fMCG).

DESIGN

A review article.

SETTING

Department of Gynecology and Obstetrics, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Slovak Republic.

METHODS

An analysis of the literature using database search engines PubMed, and SCOPE in field of fMCG.

RESULTS

Fetal magnetocardiography is a non-invasive technique able to monitor the spontaneous electrophysiological activity of the fetal heart. Compared to cardiotocography and fetal electrocardiography, this is a more effective method with a higher resolution. The signal obtained from the fetal heart is sufficiently precise and the quality allows an assessment of PQRST complex alterations, and to detect fetal arrhythmia. Thanks to early diagnosis of fetal arrhythmia, there is the possibility for appropriate therapeutic intervention and the reduction of unexplained fetal death in late gestation. fMCG with high temporal resolution also increases the level of clinical trials which record fetal heart rate (FHR) variability. According to the latest theories, FHR variability is a possible indicator of fetal status and enables the study of the fetal autonomic nervous system indirectly. fMCG is an experimental method that requires expensive equipment. It is yet to be shown in the future, if this method will get any application in clinical practice.

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.

Development and application of an automated extraction algorithm for fetal magnetocardiography - normal data and arrhythmia detection

INTRODUCTION

Current standard methods of monitoring fetal heart function are mainly based on echocardiography, which provides indirect information (through mechanical assessment) of the fetal heart rhythm. Fetal magnetocardiography (fMCG) allows a reliable quantification of the temporal structure of fetal heart signals. However, its application in clinical studies is difficult because extracting the fetal heart signal for most current applications requires user intervention. To overcome this limitation, we developed a completely automated extraction algorithm.

PATIENTS AND METHODS

The fMCG recordings were acquired using a 156-channel biomagnetic system. To perform an automated analysis, a combination of orthogonal projection and independent component analysis was used. fMCG recordings from 69 healthy uncomplicated singleton pregnancies with normally developing fetuses were included in the study.

RESULTS

The normal values achieved by the automated algorithm were comparable to previously published data. The majority of the cardiac time intervals were positively correlated with gestational age (GA). The ST segment, T wave and QT interval did not show any correlation.

CONCLUSIONS

The automated detection of fetal heart signals was possible beginning at a GA of 19 weeks. This automated analysis of fMCG recordings might be an objective and easily applicable approach for clinicians to analyze fetal heart signals.

The effect of applying orthogonal projection technique in short window segments to obtain fetal magnetocardiogram

Non-invasive recordings of fetal heart and brain have been possible for almost a decade with the advancement in biomagnetic sensors using the SQUID (Superconducting Quantum Interference Device) technology. Techniques such as orthogonal projection and ICA have been applied to attenuate interference from other biological sources such as maternal heart. Successful application of such techniques among other factors depend on the non-stationary characteristics of the signals. To minimize the effect of non-stationarity due to maternal and/or fetal movement in long duration datasets, we proposed to investigate the minimal time window that is needed to obtain averaging with good SNR to apply the orthogonal projection technique to attenuate maternal magnetocardiogram (MCG) and obtain fetal MCG. The quantifying measure is based on spectral power of signals from 151-channel SQUID array system.

Noninvasive diagnosis of coronary artery disease using two parameters extracted in an extrema circle of magnetocardiogram

Magnetocardiography (MCG) is a complementary or alternative tool for noninvasive detection of coronary artery disease (CAD). The effectiveness of the tool for CAD diagnosis is generally evaluated by statistical analysis. In this study, we present a new method for screening CAD, in which two parameters including the curvature of magnetic field zero line and the area ratio of the extrema circle are extracted in magnetic field maps. 50 normal and 28 CAD subjects, whose signals were recorded by a 4-channel superconducting quantum interference device system, are analyzed with this method. The statistical results show a sensitivity and specificity of 71.4% and 72.0% respectively.

Magnetocardiography with a modular spin-exchange relaxation-free atomic magnetometer array

We present a portable four-channel atomic magnetometer array operating in the spin-exchange relaxation-free regime. The magnetometer array has several design features intended to maximize its suitability for biomagnetic measurement, specifically foetal magnetocardiography, such as a compact modular design and fibre-coupled lasers. The modular design allows the independent positioning and orientation of each magnetometer. Using this array in a magnetically shielded room, we acquire adult magnetocadiograms. These measurements were taken with a 6-11 fT Hz(-1/2) single-channel baseline sensitivity that is consistent with the independently measured noise level of the magnetically shielded room.

The effect of volume conductor modeling on the estimation of cardiac vectors in fetal magnetocardiography

Previous studies based on fetal magnetocardiographic (fMCG) recordings used simplified volume conductor models to estimate the fetal cardiac vector as an unequivocal measure of the cardiac source strength. However, the effect of simplified volume conductor modeling on the accuracy of the fMCG inverse solution remains largely unknown. Aiming to determine the sensitivity of the source estimators to the details of the volume conductor model, we performed simulations using fetal-maternal anatomical information from ultrasound images obtained in 20 pregnant women in various stages of pregnancy. The magnetic field produced by a cardiac source model was computed using the boundary-element method for a piecewise homogeneous volume conductor with three nested compartments (fetal body, amniotic fluid and maternal abdomen) of different electrical conductivities. For late gestation, we also considered the case of a fourth highly insulating layer of vernix caseosa covering the fetus. The errors introduced for simplified volume conductors were assessed by comparing the reconstruction results obtained with realistic versus spherically symmetric models. Our study demonstrates the significant effect of simplified volume conductor modeling, resulting mainly in an underestimation of the cardiac vector magnitude and low goodness-of-fit. These findings are confirmed by the analysis of real fMCG data recorded in mid-gestation.

[Magnetocardiography in clinical practice: algorithms and technologies for data analysis]

This methodological work is the first part of series of papers dedicated to the modern perspective method of non-invasive diagnostics in cardiology--magnetocardiography. Definition of magnetocardiography method is given, levels of magnetocardiography data analysis as well as electrophysiological models are described. The most informative biomarkers and technologies of qualitative and quantitative interpretation of current density distribution maps and curves of total current magnitude are presented. The step-by-step algorithm, which was used for the MCG-data analysis, is proposed.

Clinical application of magnetic mapping

Noninvasive screening technique to identify cardiac disease in its early phase is developed. Magnetic imaging of cardiac action currents is a new and an ideally suited technology for testing the level of local electric heterogeneities of myocardium. Magnetocardiography has the potential to make a valuable contribution in basic examination and analysis of biosignals of a heart. in particular whilst all vector components are used, vast spatial coverage and excellent signal quality.

A comparison of two-dimensional techniques for converting magnetocardiogram maps into effective current source distributions

The aim of this study was to develop a method for converting the pseudo two-dimensional current given by a current-arrow map (CAM) into the physical current. The physical current distribution is obtained by the optimal solution in a least mean square sense with Tikhonov regularization (LMSTR). In the current dipole simulation, the current pattern differences (ΔJ) between the results of the CAM and the LMSTR with several regularization parameters (α = 10(-1)-10(-15)) are calculated. In magnetocardiographic (MCG) analysis, the depth (z(d)) of a reconstruction plane is chosen by using the coordinates of the sinus node, which is estimated from MCG signals at the early p-wave. The ΔJs at p-wave peaks, QRS-complex peaks, and T-wave peaks of MCG signals for healthy subjects are calculated. Furthermore, correlation coefficients and regression lines are also calculated from the current values of the CAM and the LMSTR during p-waves, QRS-complex, and T-waves of MCG signals. In the simulation, the ΔJs (α ≈ 10(-10)) had a minimal value. The ΔJs (α = 10(-10)) at p-wave peaks, QRS-complex peaks, and T-wave peaks of MCG signals for healthy subjects also had minimal value. The correlation coefficients of the current values given by the CAM and the LMSTR (α = 10(-10)) were greater than 0.9. Furthermore, slopes (y) of the regression lines are correlated with the depth (z(d)) (r = -0.93). Consequently, the CAM value can be transformed into the LMSTR current value by multiplying it by the slope (y) obtained from the depth (z(d)). In conclusion, the result given by the CAM can be converted into an effective physical current distribution by using the depth (z(d)).

[Development of three-dimensional analysis of current density distribution by 64-ch magentocardiography and clinical application]

Magnetocardiography (MCG) using a SQUID sensor is characterized by three dimensional cardiac electrical phenomena from magnetic fields, because it is hard to be affected by organ constitution of lungs and torso configuration. We have developed three-dimensional (3D) electric current density distribution analysis by a spatial filter method. At this symposium, we report clinical utility of 64-channel (64-ch) MCG. Subjects consisted of 20 normal volunteers, 10 cases with old myocardial infarction, 13 cases with atrial fibrillation (AFIB) who received surgical pulmonary (PV) isolation, and representative case with fetus premature ventricular complex (PVC). We recorded 10-min MCG data of magnetic field composition (a Bz ingredient) which was perpendicular to body surface in a magnetism shield, using 64-ch SQUID sensors (17.5 x 17.5 cm) built-in in MCG instrumentation(sampling; 500ms, total frequency characteristic; 0.1-200 Hz). We conducted 3D heart outline from electric current density calculated by magnetic field distribution. We also generated 3D functional images of the RT (activation recovery time) dispersion and spatial spectral distribution of a fibrillation wave. Increased fluctuation on RT dispersion map corresponded with space location of myocardial infarction. The mean frequency of 3D spectral map in persistent AFIB showed a higher value than that with restored a sinus rhythm (7.7 +/- 0.5 Hz vs. 6.5 +/- 0.7 Hz). We also demonstrated a fetus PVC. We concluded that 64-ch MCG can evaluate 3D spatial location of myocardial injury, 3D spectral map and characteristic frequency, and fetus arrhythmia. In future, further technical development in the fields of MCG measurement would be necessary for avoiding the used of unshielded room or liquid He.

Topography-time-frequency atomic decomposition for event-related M/EEG signals

We present a method for decomposing MEG or EEG data (channel x time x trials) into a set of atoms with fixed spatial and time-frequency signatures. The spatial part (i.e., topography) is obtained by independent component analysis (ICA). We propose a frequency prewhitening procedure as a pre-processing step before ICA, which gives access to high frequency activity. The time-frequency part is obtained with a novel iterative procedure, which is an extension of the matching pursuit procedure. The method is evaluated on a simulated dataset presenting both low-frequency evoked potentials and high-frequency oscillatory activity. We show that the method is able to recover well both low-frequency and high-frequency simulated activities. There was however cross-talk across some recovered components due to the correlation introduced in the simulation.

Unshielded fetal magnetocardiography system using two-dimensional gradiometers

We developed a fetal magnetocardiography (fMCG) system that uses a pair of two-dimensional gradiometers to achieve high signal-to-noise ratio. The gradiometer, which is based on a low-Tc superconducting quantum interference device, detects the gradient of a magnetic field in two orthogonal directions. Gradiometer position is easy to adjust by operating the gantry to drive the cryostat in both the swinging and axial directions. As a result, a fMCG waveform for 25 weeks' gestation was measured under an unshielded environment in real time. Moreover, the P and T waves for 25 and 34 weeks' gestation, respectively, were obtained by averaging. These results indicate that this two-dimensional gradiometer is one of the most promising techniques for measuring fetal heart rate and diagnosing fetal arrhythmia.

Diagnostic value of magnetocardiography in patients with coronary heart disease and in-stent restenosis

BACKGROUND

In-stent restenosis (ISR) has become one of the most challenging problems in patients with coronary heart disease. At present, using non-invasive methods to assess ISR is a hot topic. In this investigation we attempted to explore the potential of magnetocardiography (MCG) in diagnosis of in-stent restenosis.

METHODS

MCG was analyzed in 52 patients with coronary artery disease for three times: before stenting, one month and 7 months after successful intracoronary stenting.

RESULTS

The average classification of total maps (ACTM) and the ratio of abnormal maps (RAM) were lower in 1 month after intracoronary stenting compared with that obtained before stent planting (2.91 vs 2.52, 65.74% vs 42.80%, P < 0.01), while complex ventricular excitation index (CVEI) increased from -42.63 to -20.05 (P < 0.01). In ISR subgroup (n = 16), RAM decreased in 1 month after intracoronary stenting compared to it before stenting (68.99% vs 45.26%, P < 0.05). ACTM increased in 7 months compared to that obtained in 1 month after stenting (3.15 vs 2.51, P < 0.05). According to the ROC curve, ACTM showed its unique diagnostic value in restenosis patients. The sensitivity and specificity of ACTM were 80.0%, 69.40%, respectively. Its positive predictive value and negative predictive value were 54.6% and 88.5%, respectively.

CONCLUSIONS

After successful intracoronary stenting, most parameters of MCG were improved. ACTM was of prognostic value in diagnosing ISR.

Dobutamine stress magnetocardiography for the detection of significant coronary artery stenoses - a prospective study in comparison with simultaneous 12-lead electrocardiography

BACKGROUND

Exercise electrocardiography is an imperfect test for the detection of coronary artery disease (CAD). Magnetocardiography detects cardiac electrical disturbances associated with myocardial ischemia. We prospectively investigated the accuracy of high-dose dobutamine stress magnetocardiography (DS-MCG) and simultaneous electrocardiography (DS-ECG) for the detection of significant CAD.

METHODS

100 patients with an intermediate pre-test probability for CAD underwent DS-MCG using a multichannel magnetometer prior to invasive coronary angiography. Patients were examined at rest and during a standard dobutamine-atropine scheme. Significant reduction of epicardial current strength/density during stress, reconstructed from the magnetic field map and superposed on a virtual heart model indicates myocardial ischemia. A 12-lead DS-ECG was recorded simultaneously. Significant coronary artery stenosis was defined as > or = 70% of lumen reduction.

RESULTS

Without beta-blocker all 100 patients reached the targeted heart rate. The image quality of DS-MCG and DS-ECG was sufficient for analysis in all patients. In 19 patients CAD was ruled out angiographically. Thirty two or seven patients revealed coronary artery stenoses of 30-49% or of 50-69%, respectively. In 42 patients we found significant stenoses of > or = 70%. In 41 of these patients DS-MCG revealed myocardial ischemia. The sensitivity of DS-MCG and DS-ECG for the detection of significant coronary artery stenosis was 97.6% and 26.2%, the specificity of DS-MCG and DS-ECG 82.8% and 82.8%, respectively.

CONCLUSIONS

DS-MCG can be performed with a standard dobutamine/atropine stress protocol. DS-MCG yields a significantly higher accuracy for the detection of significant coronary artery stenosis than DS-ECG.

Slow Brain Potential and Oscillatory EEG Manifestations of Impaired Temporal Preparation in Parkinson's Disease

Performance in behavioral tasks is influenced by temporal expectations shaped by the temporal structure of the task. Such implicit temporal preparation is reflected in slow brain potentials and electroencephalographic oscillations and is attributed to interval timing mechanisms that probably depend on intact basal ganglia function. We investigated implicit timing in Parkinson's disease using a choice reaction task with two temporally regular stimulus presentation regimes, both including occasional deviant interstimulus intervals. Control subjects, but not patients, demonstrated temporal preparation in the form of an adjustment in time course of slow brain potentials to the duration of the interstimulus interval. However, in both groups, timing perturbations were accompanied by a slow brain potential amplitude drop at the time of expected stimulus occurrence, demonstrating intact representation of time in patients. In patients, oscillatory activity in beta and alpha bands showed attenuated preparatory desynchronization and reduced postmovement event-related synchronization, reflecting abnormal engagement and disengagement of sensorimotor and parietal areas. The results demonstrate profoundly deficient temporal preparation with preserved encoding of temporal information, a dissociation that may be explained by impaired dopamine-dependent motor learning. The results are discussed in the context of recent work on oscillatory activity in the basal ganglia.

Detection of patients with coronary artery disease using cardiac magnetic field mapping at rest

We studied the use of cardiac magnetic field mapping to detect patients with CAD without subjecting them to stress. Fifty-nine healthy control subjects and 101 patients with CAD without previous MI were included. The optimal positions for detecting CAD were located in the left superior parasternal and in the inferior midsternal area. Values for ST slope, ST shift, T peak amplitude, ST-T integral, and magnetic field map orientation differed significantly between the 2 groups. Three parameters together in a multivariate analysis yielded a sensitivity of 84% and a specificity of 83% in distinguishing patients with CAD from control subjects. We suggest that cardiac magnetic field mapping is a promising technique to identify patients with CAD.

Atrial and ventricular rate response and patterns of heart rate acceleration during maternal-fetal terbutaline treatment of fetal complete heart block

Terbutaline is used to treat fetal bradycardia in the setting of complete heart block (CHB); however, little is known of its effects on atrial and ventricular beat rates or patterns of heart rate (HR) acceleration. Fetal atrial and ventricular beat rates were compared before and after transplacental terbutaline treatment (10 to 30 mg/day) by fetal echocardiography in 17 fetuses with CHB caused by immune-mediated damage to a normal conduction system (isoimmune, n = 8) or a congenitally malformed conduction system associated with left atrial isomerism (LAI, n = 9). While receiving terbutaline, 9 of the 17 fetuses underwent fetal magnetocardiography (fMCG) to assess maternal HR and rhythm, patterns of fetal HR acceleration, and correlation between fetal atrial and ventricular accelerations (i.e., AV correlation). Maternal HR and fetal atrial and ventricular beat rates increased with terbutaline. However, terbutaline's effects were greater on the atrial pacemaker(s) in fetuses with isoimmune CHB and greater on the ventricular pacemaker(s) in those with LAI-associated CHB. Patterns of fetal HR acceleration also differed between isoimmune and LAI CHB. Finally, despite increasing HR, terbutaline did not restore the normal coordinated response between atrial and ventricular accelerations in isoimmune or LAI CHB. In conclusion, the pathophysiologic heterogeneity of CHB is reflected in the differing effect of terbutaline on the atrial and ventricular pacemaker(s) and varying patterns of HR acceleration. However, regardless of the cause of CHB, terbutaline augments HR but not AV correlation, suggesting that its effects are determined by the conduction system defect rather than the autonomic control of the developing heart.

Longitudinal study of cardiac electrical activity in anesthetized guinea pigs by contactless magnetocardiography

Guinea pigs (GPs) are used for preclinical evaluation of electrophysiologic effects of new drugs, because their myocytes have human-like action potentials and ventricular repolarization's (VR) ion currents. This study was aimed to assess the reliability of magnetocardiographic (MCG) mapping for longitudinal studies of GP cardiac electrical activity. Eighteen anesthetized GPs were investigated with an unshielded 36-channel MCG instrumentation, at the age of 5 months (268.1 +/- 19 g). Twelve GPs survived and were restudied when 14 months old (595.6 +/- 90.5 g). RR, PR, QRS, QT(peak), QT(end), JT(peak), JT(end) and T(peak-end) intervals were measured from MCG waveforms. Magnetic field (MF) maps, equivalent current dipole (ECD) parameters and current density imaging were also analyzed. A significant prolongation of the PR (p < 0.05) and QRS (p < 0.001) intervals was found at 14 months. Gender-related differences of VR intervals were not significant. P(peak) and QRS(peak) MFs were similar in all animals, while T(peak) MF varied interindividually at 5 months and showed a rotation in some animals, at 14 months. The ECD strengths, measured at the P(peak), QRS(peak) and T(peak) were stronger (p < 0.01) at the age of 14 months than at 5 months. In contrast to findings in Wistar rats, age-related and gender-related differences of MCG VR parameters were not significant in GPs. Further work is necessary to clarify the variability of VR MF observed in healthy GPs.

Simultaneous fetal magnetocardiography and ultrasound/Doppler imaging

The difficulty of utilizing multimodality diagnostic imaging techniques for fetal surveillance remains one of the greatest challenges in providing enhanced prenatal care. In this Letter we demonstrate the feasibility of performing fetal magnetocardiography (fMCG) and ultrasound/Doppler imaging simultaneously, using a multichannel SQUID magnetometer and a portable ultrasound scanner. Despite large magnetic interference from the scanner, the implementation of simple noise reduction procedures and appropriate signal processing techniques yielded fMCG recordings of sufficient quality for assessment of fetal heart rate and rhythm. A variation of reference channel filtering, referred to here as synthetic reference channel filtering, was used to reduce nonstationary low-frequency interference. The combination of fMCG and/or fMEG with ultrasound/Doppler offers new possibilities for assessment of fetal well-being and fetal cardiac function.

Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a common primary inherited cardiac muscle disorder, defined clinically by the presence of unexplained left ventricular hypertrophy. The detection of affected patients remains challenging. Genetic testing is limited because only in 50%-60% of all HCM diagnoses an underlying mutation can be found. Furthermore, the disease has a varied clinical course and outcome, with many patients having little or no discernible cardiovascular symptoms, whereas others develop profound exercise limitation and recurrent arrhythmias or sudden cardiac death. Therefore prospective screening of HCM family members is strongly recommended. According to the current guidelines this includes serial echocardiographic and electrocardiographic examinations. In this study we investigated the capability of cardiac magnetic field mapping (CMFM) to detect patients suffering from HCM. We introduce for the first time a combined diagnostic approach based on map topology quantification using Kullback-Leibler (KL) entropy and regional magnetic field strength parameters. The cardiac magnetic field was recorded over the anterior chest wall using a multichannel-LT-SQUID system. CMFM was calculated based on a regular 36 point grid. We analyzed CMFM in patients with confirmed diagnosis of HCM (HCM, n=33, 43.8+/-13 years, 13 women, 20 men), a control group of healthy subjects (NORMAL, n=57, 39.6+/-8.9 years; 22 women and 35 men), and patients with confirmed cardiac hypertrophy due to arterial hypertension (HYP, n=42, 49.7+/-7.9 years, 15 women and 27 men). A subgroup analysis was performed between HCM patients suffering from the obstructive (HOCM, n=19) and nonobstructive (HNCM, n=14) form of the disease. KL entropy based map topology quantification alone identified HCM patients with a sensitivity of 78.8% and specificity of 86.9% (overall classification rate 84.8%). The combination of the KL parameters with a regional field strength parameter improved the overall classification rate to 87.9% (sensitivity: 84.8%, specificity: 88.9%, area under ROC curve: 0.94). KL measures applied to discriminate between HOCM and HNCM patients showed a correct classification of 78.8%. The combination of one KL and one regional parameter again improved the overall classification rate to 97%. A preliminary prospective analysis in two HCM families showed the feasibility of this diagnostic approach with a correct diagnosis of all 22 screened family members (1 HOCM, 4 HNCM, 17 normal). In conclusion, Cardiac Magnetic Field Mapping including KL entropy based topology quantifications is a suitable tool for HCM screening.

Detection of atrial arrhythmia in superconducting quantum interference device magnetocardiography; preliminary result of a totally-noninvasive localization method for atrial current mapping

Map-guided surgery is the goal for treatment of atrial fibrillation (AF), because it minimizes unnecessary incisions or procedures. We propose a totally-noninvasive and even non-contact method to detect atrial arrhythmia with a superconducting quantum interference device magnetocardiography (MCG) system, and report the first clinical application case of MCG map-guided AF surgery. To detect weak atrial excitation, we utilized a high sensitive 64-channel MCG system measuring tangential magnetic field components, which is known to be more sensitive to a deeper current source. We measured the MCG signals from eight patients with chronic AF. Then, we separated the f-wave from the other components by using independent component analysis. The extracted f-wave caused by reentrant myocardial excitation was three-dimensionally localized on the mesh model of a human heart by a novel beamformer technique having a surface action potential activity as its filter output. We localized the abnormal stimulation source of an atrial arrhythmia non-invasively and visualized the current source distribution corresponding to the atrial excitation successfully on the three-dimensional atrial surface, which was separated from the ventricular excitation. Using this atrial mapping, we underwent minimal AF surgery in three patients and converted their AF to sinus rhythm successfully.

Application of decorrelation-independent component analysis to biomagnetic multi-channel measurements

Biomagnetic multi-channel recordings are typically a superposition of signals from several biological sources of interest and from biological and technical noise sources. Besides averaging, source localization, and spectral analysis to name only a few methods, independent component analysis is an established tool to resolve the superposition present in raw biomagnetic data on a purely statistical basis. Here the time-delayed decorrelation-independent component analysis algorithm is applied to exemplary magnetocardiographic and magnetoencephalographic data and the successful signal separation is demonstrated.

Heart rate variability in the fetus: a comparison of measures

BACKGROUND

In fetal surveillance, fetal heart rate changes are assessed using cardiotocography (CTG). Standard procedures used in the quantification of heart rate variability (HRV) are seldom applied as CTG does not deliver beat interval durations with the same accuracy as the electrocardiogram (ECG). Thus little is known about the interdependency of standard HRV measures prenatally.

MATERIALS AND METHODS

Using fetal magnetocardiography (FMCG: the magnetic equivalent of the fetal ECG), we investigated standard HRV measures in a homogenous group of 20 healthy fetuses. Ten HRV measures were analyzed in 60 five-minute RR interval time series derived from FMCG acquisitions (16th-40th week of gestation).

RESULTS

Using regression analysis, we found a clear dependency on gestational age and mean RR interval for measures from the time and frequency domains as well as for a measure for complexity. Correlation analysis revealed a strong interdependency of the measures, in particular within the specific domains. An adequate description of fetal HRV may be achieved using the standard deviation from the time domain, the high frequency band (0.15-0.40 Hz) from the frequency domain and approximate entropy as a complexity measure.

CONCLUSION

The results indicate that different characteristics of fetal HRV are embedded in the different domains.

Entropy-based automated classification of independent components separated from fMCG

Fetal magnetocardiography (fMCG) is a noninvasive technique suitable for the prenatal diagnosis of the fetal heart function. Reliable fetal cardiac signals can be reconstructed from multi-channel fMCG recordings by means of independent component analysis (ICA). However, the identification of the separated components is usually accomplished by visual inspection. This paper discusses a novel automated system based on entropy estimators, namely approximate entropy (ApEn) and sample entropy (SampEn), for the classification of independent components (ICs). The system was validated on 40 fMCG datasets of normal fetuses with the gestational age ranging from 22 to 37 weeks. Both ApEn and SampEn were able to measure the stability and predictability of the physiological signals separated with ICA, and the entropy values of the three categories were significantly different at p <0.01. The system performances were compared with those of a method based on the analysis of the time and frequency content of the components. The outcomes of this study showed a superior performance of the entropy-based system, in particular for early gestation, with an overall ICs detection rate of 98.75% and 97.92% for ApEn and SampEn respectively, as against a value of 94.50% obtained with the time-frequency-based system.

Noninvasive Classification of Ventricular Preexcitation with Unshielded Magnetocardiography and Transesophageal Atrial Pacing and Follow-Up

BACKGROUND

Ventricular preexcitation (VPx) is usually localized noninvasively by means of electrocardiogram (ECG) algorithms, which vary in their concordance levels. Contactless magnetocardiography (MCG) has been used as an alternate 3-dimensional (3D) method of accessory pathways (AP) localization. The sensitivity of MCG can be increased for preoperative evaluations and planning of ablation procedures by combining it with transesophageal pacing (TEP) and electrophysiological (EP) studies. This study compared the accuracy of VPx localization with MCG with ECG algorithms, and examined the increment in diagnostic accuracy achievable with TEP.

METHODS

Multisite mapping from the anterior chest wall was performed with a 36-channel MCG system. TEP allowed the evaluation of anterograde conduction properties and inducibility of arrhythmias. The reproducibility of the test and follow-up was examined in 88 patients with Wolff-Parkinson-White (WPW) syndrome. The accuracy of MCG localization was reevaluated during pacing-induced maximal VPx in 36 patients in whom, during MCG, the degree of VPx was highest during TEP. The gold standard for validation was effective ablation of the AP.

RESULTS

The MCG classification of VPx was accurate in 94% of AP, versus 64% and 67% with ECG, during sinus rhythm and during pacing-induced maximal VPx, respectively. In 4.5% of cases with unclear ECG localization, MCG suggested a complex septal VPx. In all patients with successful ablations, the 3D MCG localization of the AP corresponded to the ablation site.

CONCLUSIONS

MCG was more accurate than ECG for the classification of VPx and provided additional information in the non-invasive EP assessment of patients with WPW syndrome.

Biomagnetism in perinatal medicine. Our experience in Greece

This is a report on our experience in the application of biomagnetism in perinatal medicine. We provide a brief description of our research work in fetal magnetoencephalography and fetal magnetocardiography in normal, preeclamptic and IUGR pregnancies, together with hemodynamics of the umbilical cord and uterine arteries, providing a new approach to biomagnetism as a non invasive imaging modality in the investigation of perinatal complications.

Magnetocardiography Study on Ventricular Depolarization-Current Pattern in Patients with Brugada Syndrome and Complete Right-Bundle Branch Blocks

BACKGROUND

The objective of this study is to use magnetocardiography to determine the existence of a small abnormal current during ventricular depolarization in patients with Brugada syndrome. To understand this small difference in abnormal current during ventricular depolarization, we compared abnormal currents of patients with cases of complete right-bundle-branch block (CRBBB).

METHODS AND RESULTS

We developed a whole-heart electrical bull's eye map (WHEBEM) that uses magnetocardiograms (MCGs) to visualize the current distribution in a circular map. MCGs of Brugada syndrome patients (n = 16), CRBBB patients (n = 10), and controls (n = 12) at rest were recorded. In the WHEBEMs of Brugada syndrome patients, the magnitude of the S-wave current in the upper-right direction of the anterior side is larger than that of the controls. In addition, the R-wave current direction is similar to that of the controls, and the R-wave vector is distributed over a larger area than that of the controls. On the other hand, the CRBBB patients have a distribution of R-wave currents over a larger area in the left anteromedian region and the left posteromedian region. Moreover, in all CRBBB patients, S-wave currents with a large magnitude have the same direction distributed over a small area.

CONCLUSIONS

The WHEBEM findings suggest that there is an abnormal current in the direction to the upper right (in the S-wave) in the anterosuperior region of Brugada syndrome patients. We thus conclude that a WHEBEM has the potential to detect characteristics of heart disease.

Reconstruction of Fetal Cardiac Vectors From Multichannel fMCG Data Using Recursively Applied and Projected Multiple Signal Classification

Previous attempts at unequivocal specification of signal strength in fetal magnetocardiographic (fMCG) recordings have used an equivalent current dipole (ECD) to estimate the cardiac vector at the peak of the averaged QRS complex. However, even though the magnitude of fetal cardiac currents are anticipated to be relatively stable, ECD-based estimates of signal strength show substantial and unrealistic variation when comparing results from different time windows of the same recording session. The present study highlights the limitations of the ECD model, and proposes a new methodology for fetal cardiac source reconstruction. The proposed strategy relies on recursive subspace projections to estimate multiple dipoles that account for the distributed myocardial currents. The dipoles are reconstructed from spatio-temporal fMCG data, and are subsequently used to derive estimators of the cardiac vector over the entire QRS. The new method is evaluated with respect to simulated data derived from a model of ventricular depolarization, which was designed to account for the complexity of the fetal cardiac source configuration on the QRS interval. The results show that the present methodology overcomes the drawbacks of conventional ECD fitting, by providing robust estimators of the cardiac vector. Additional evaluation with real fMCG data show fetal cardiac vectors whose morphology closely resembles that obtained in adult MCG.

Fetal cardiac time intervals estimated on fetal magnetocardiograms: single cycle analysis versus average beat inspection

Fetal cardiac time intervals (fCTI) are dependent on fetal growth and development, and may reveal useful information for fetuses affected by growth retardation, structural cardiac defects or long QT syndrome. Fetal cardiac signals with a signal-to-noise ratio (SNR) of at least 15 dB were retrieved from fetal magnetocardiography (fMCG) datasets with a system based on independent component analysis (ICA). An automatic method was used to detect the onset and offset of the cardiac waves on single cardiac cycles of each signal, and the fCTI were quantified for each heartbeat; long rhythm strips were used to calculate average fCTI and their variability for single fetal cardiac signals. The aim of this work was to compare the outcomes of this system with the estimates of fCTI obtained with a classical method based on the visual inspection of averaged beats. No fCTI variability can be measured from averaged beats. A total of 25 fMCG datasets (fetal age from 22 to 37 weeks) were evaluated, and 1768 cardiac cycles were used to compute fCTI. The real differences between the values obtained with a single cycle analysis and visual inspection of averaged beats were very small for all fCTI. They were comparable with signal resolution (+/-1 ms) for QRS complex and QT interval, and always <5 ms for the PR interval, ST segment and T wave. The coefficients of determination between the fCTI estimated with the two methods ranged between 0.743 and 0.917. Conversely, inter-observer differences were larger, and the related coefficients of determination ranged between 0.463 and 0.807, assessing the high performance of the automated single cycle analysis, which is also rapid and unaffected by observer-dependent bias.

Non-Invasive Resting Magnetocardiographic Imaging for the Rapid Detection of Ischemia in Subjects Presenting with Chest Pain

BACKGROUND

Early diagnosis of ischemia is complicated by the poor sensitivity of standard tests and contraindication for stress testing in unstable angina patients. Magnetocardiography (MCG) imaging can be used for the rapid, non-invasive detection of ischemia at rest.

METHODS

We studied 125 patients with presumed ischemic chest pain. All were chest pain free at the time of scanning. A 6-minute resting MCG scan (CardioMag Imaging, Inc., New York, 9-channel system) was performed. Following the MCG scan, automated software data analysis was performed, and quantitative scores were automatically calculated for each subject. The presence of ischemia was determined after testing with serial troponins, stress testing, and/or coronary angiography.

RESULTS

The mean age was 59.4 +/- 13.6 years. Most patients (86.4%) had non-ischemic 12-lead ECG and normal troponin (86.2%). Fifty-five patients (44.0%) were determined to be ischemic. The MCG sensitivity, specificity, positive and negative predictive value was 76.4, 74.3, 70.0 and 80.0%, respectively, for the detection of ischemia (p < 0.0001).

CONCLUSIONS

MCG is a new rapid, non-invasive imaging tool able to detect repolarization abnormalities at rest consistent with ischemia in patients presenting with chest pain syndrome and normal or non-specific 12-lead ECG and normal troponin.