Characterization of Fetal Arrhythmias by Means of Fetal Magnetocardiography in Three Cases of Difficult Ultrasonographic Imaging

The magnetocardiogram

The magnetic field produced by the heart's electrical activity is called the magnetocardiogram (MCG). The first 20 years of MCG research established most of the concepts, instrumentation, and computational algorithms in the field. Additional insights into fundamental mechanisms of biomagnetism were gained by studying isolated hearts or even isolated pieces of cardiac tissue. Much effort has gone into calculating the MCG using computer models, including solving the inverse problem of deducing the bioelectric sources from biomagnetic measurements. Recently, most magnetocardiographic research has focused on clinical applications, driven in part by new technologies to measure weak biomagnetic fields.

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.

Fetal arrhythmias: prenatal evaluation and intrauterine therapeutics

Introduction

Fetal arrhythmias are a common phenomenon with rather complicated etiologies. Debates remain regarding prenatal diagnosis and treatment of fetal arrhythmias.

Methods

The literature reporting on prenatal diagnosis and treatment of fetal arrhythmias published in the recent two decades were retrieved, collected and analyzed.

Results

Both fetal magnetocardiogram and electrocardiogram provide information of cardiac time intervals, including the QRS and QT durations. M-mode ultrasound detects the AV and VA intervals, fetal heart rate, and AV conduction. By using Doppler ultrasound, simultaneous recording of the atrial and ventricular waves can be obtained. Benign fetal arrhythmias, including premature contractions and sinus tachycardia, do not need any treatment before and after birth. Sustained fetal arrhythmias that predispose to the occurrence of hydrops fetalis, cardiac dysfunction or eventual fetal demise require active treatments. Intrauterine therapy of fetal tachyarrhythmias has been carried out by the transplacental route. If maternal transplacental treatment fails, intraumbilical, intraperitoneal, or direct fetal intramuscular injection of antiarrhythmic agents can be attempted.

Conclusions

The outcomes of intrauterine therapy of fetal tachyarrhythmias depend on the types or etiology of fetal arrhythmias and fetal conditions. Most are curable to a transplacental treatment by the first-line antiarrhythmic agents. Fetal cardiac pacings are effective methods to restore sinus rhythm in drug-resistant or hemodynamically compromised cases. Immediate postnatal pacemaker implantation is warranted in refractory cases.

Fetal arrhythmias: Surveillance and management

Fetal arrhythmias warrant sophisticated surveillance and management, especially for the high-risk pregnancies. Clinically, fetal arrhythmias can be categorized into 3 types: premature contractions, tachyarrhythmias, and bradyarrhythmias. Fetal arrhythmias include electrocardiography, cardiotocography, echocardiography and magnetocardiography. Oxygen saturation monitoring can be an effective way of fetal surveillance for congenital complete AV block or SVT during labor. Genetic surveillance of fetal arrhythmias may facilitate the understanding of the mechanisms of the arrhythmias and provide theoretical basis for diagnosis and treatment. For fetal benign arrhythmias, usually no treatment but a close follow-up is need, while persistant fetal arrhythmias with congestive heart dysfunction or hydrops fetalis, intrauterine or postnatal treatments are required. The prognoses of fetal arrhythmias depend on the type and severity of fetal arrhythmias and the associated fetal conditions. Responses of fetal arrhythmias to individual treatments and clinical schemes are heterogeneous, and the prognoses are poor particularly under such circumstances.

Fetal cardiac time intervals in healthy pregnancies - an observational study by fetal ECG (Monica Healthcare System)

BACKGROUND

Fetal electrocardiogram (fECG) can detect QRS signals in fetuses from as early as 17 weeks' gestation; however, the technique is limited by the minute size of the fetal signal relative to noise ratio. The aim of this study was to evaluate precise fetal cardiac time intervals (fCTIs) with the help of a newly developed fetal ECG device (Monica Healthcare System).

METHODS

In a prospective manner we included 15-18 healthy fetuses per gestational week from 32 weeks onwards. The small and wearable Monica AN24 monitoring system uses standard ECG electrodes placed on the maternal abdomen to monitor fECG, maternal ECG and uterine electromyogram (EMG). Fetal CTIs were estimated on 1000 averaged fetal heart beats. Detection was deemed successful if there was a global signal loss of less than 30% and an analysis loss of the Monica AN24 signal separation analysis of less than 50%. Fetal CTIs were determined visually by three independent measurements.

RESULTS

A total of 149 fECGs were performed. After applying the requirements 117 fECGs remained for CTI analysis. While the onset and termination of P-wave and QRS-complex could be easily identified in most ECG patterns (97% for P-wave, PQ and PR interval and 100% for QRS-complex), the T-wave was detectable in only 41% of the datasets. The CTI results were comparable to other available methods such as fetal magnetocardiography (fMCG).

CONCLUSIONS

Although limited and preclinical in its use, fECG (Monica Healthcare System) could be an additional useful tool to detect precise fCTIs from 32 weeks' gestational age onwards.

A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings

Background

EEG may be affected by artefacts hindering the analysis of brain signals. Data-driven methods like independent component analysis (ICA) are successful approaches to remove artefacts from the EEG. However, the ICA-based methods developed so far are often affected by limitations, such as: the need for visual inspection of the separated independent components (subjectivity problem) and, in some cases, for the independent and simultaneous recording of the inspected artefacts to identify the artefactual independent components; a potentially heavy manipulation of the EEG signals; the use of linear classification methods; the use of simulated artefacts to validate the methods; no testing in dry electrode or high-density EEG datasets; applications limited to specific conditions and electrode layouts.

Methods

Our fingerprint method automatically identifies EEG ICs containing eyeblinks, eye movements, myogenic artefacts and cardiac interference by evaluating 14 temporal, spatial, spectral, and statistical features composing the IC fingerprint. Sixty-two real EEG datasets containing cued artefacts are recorded with wet and dry electrodes (128 wet and 97 dry channels). For each artefact, 10 nonlinear SVM classifiers are trained on fingerprints of expert-classified ICs. Training groups include randomly chosen wet and dry datasets decomposed in 80 ICs. The classifiers are tested on the IC-fingerprints of different datasets decomposed into 20, 50, or 80 ICs. The SVM performance is assessed in terms of accuracy, False Omission Rate (FOR), Hit Rate (HR), False Alarm Rate (FAR), and sensitivity (p). For each artefact, the quality of the artefact-free EEG reconstructed using the classification of the best SVM is assessed by visual inspection and SNR.

Results

The best SVM classifier for each artefact type achieved average accuracy of 1 (eyeblink), 0.98 (cardiac interference), and 0.97 (eye movement and myogenic artefact). Average classification sensitivity (p) was 1 (eyeblink), 0.997 (myogenic artefact), 0.98 (eye movement), and 0.48 (cardiac interference). Average artefact reduction ranged from a maximum of 82% for eyeblinks to a minimum of 33% for cardiac interference, depending on the effectiveness of the proposed method and the amplitude of the removed artefact. The performance of the SVM classifiers did not depend on the electrode type, whereas it was better for lower decomposition levels (50 and 20 ICs).

Discussion

Apart from cardiac interference, SVM performance and average artefact reduction indicate that the fingerprint method has an excellent overall performance in the automatic detection of eyeblinks, eye movements and myogenic artefacts, which is comparable to that of existing methods. Being also independent from simultaneous artefact recording, electrode number, type and layout, and decomposition level, the proposed fingerprint method can have useful applications in clinical and experimental EEG settings.

Segmented independent component analysis for improved separation of fetal cardiac signals from nonstationary fetal magnetocardiograms

Fetal magnetocardiograms (fMCGs) have been successfully processed with independent component analysis (ICA) to separate the fetal cardiac signals, but ICA effectiveness can be limited by signal nonstationarities due to fetal movements. We propose an ICA-based method to improve the quality of fetal signals separated from fMCG affected by fetal movements. This technique (SegICA) includes a procedure to detect signal nonstationarities, according to which the fMCG recordings are divided in stationary segments that are then processed with ICA. The first and second statistical moments and the signal polarity reversal were used at different threshold levels to detect signal transients. SegICA effectiveness was assessed in two fMCG datasets (with and without fetal movements) by comparing the signal-to-noise ratio (SNR) of the signals extracted with ICA and with SegICA. Results showed that the SNR of fetal signals affected by fetal movements improved with SegICA, whereas the SNR gain was negligible elsewhere. The best measure to detect signal nonstationarities of physiological origin was signal polarity reversal at threshold level 0.9. The first statistical moment also provided good results at threshold level 0.6. SegICA seems a promising method to separate fetal cardiac signals of improved quality from nonstationary fMCG recordings affected by fetal movements.

A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings

We propose a novel computational approach to automatically identify the fetal heart rate patterns (fHRPs), which are reflective of sleep/awake states. By combining these patterns with presence or absence of movements, a fetal behavioral state (fBS) was determined. The expert scores were used as the gold standard and objective thresholds for the detection procedure were obtained using Receiver Operating Characteristics (ROC) analysis. To assess the performance, intraclass correlation was computed between the proposed approach and the mutually agreed expert scores. The detected fHRPs were then associated to their corresponding fBS based on the fetal movement obtained from fetal magnetocardiogaphic (fMCG) signals. This approach may aid clinicians in objectively assessing the fBS and monitoring fetal wellbeing.

Spatial repolarization heterogeneity detected by magnetocardiography correlates with cardiac iron overload and adverse cardiac events in beta-thalassemia major

Background

Patients with transfusion-dependent beta-thalassemia major (TM) are at risk for myocardial iron overload and cardiac complications. Spatial repolarization heterogeneity is known to be elevated in patients with certain cardiac diseases, but little is known in TM patients. The purpose of this study was to evaluate spatial repolarization heterogeneity in patients with TM, and to investigate the relationships between spatial repolarization heterogeneity, cardiac iron load, and adverse cardiac events.

Methods and Results

Fifty patients with TM and 55 control subjects received 64-channel magnetocardiography (MCG) to determine spatial repolarization heterogeneity, which was evaluated by a smoothness index of QT_c (SI-QT_c), a standard deviation of QT_c (SD-QT_c), and a QT_c dispersion. Left ventricular function and myocardial T2* values were assessed by cardiac magnetic resonance. Patients with TM had significantly greater SI-QT_c, SD-QT_c, and QT_c dispersion compared to the control subjects (all p values<0.001). Spatial repolarization heterogeneity was even more pronounced in patients with significant iron overload (T2*<20 ms, n = 20) compared to those with normal T2* (all p values<0.001). Log_e cardiac T2* correlated with SI-QT_c (r = −0.609, p<0.001), SD-QT_c (r = −0.572, p<0.001), and QT_c dispersion (r = −0.622, p<0.001), while all these indices had no relationship with measurements of the left ventricular geometry or function. At the time of study, 10 patients had either heart failure or arrhythmia. All 3 indices of repolarization heterogeneity were related to the presence of adverse cardiac events, with areas under the receiver operating characteristic curves (ranged between 0.79 and 0.86), similar to that of cardiac T2*.

Conclusions

Multichannel MCG demonstrated that patients with TM had increased spatial repolarization heterogeneity, which is related to myocardial iron load and adverse cardiac events.

Clinical application of magnetocardiography

Magnetocardiography is a noninvasive contactless method to measure the magnetic field generated by the same ionic currents that create the electrocardiogram. The time course of magnetocardiographic and electrocardiographic signals are similar. However, compared with surface potential recordings, multichannel magnetocardiographic mapping (MMCG) is a faster and contactless method for 3D imaging and localization of cardiac electrophysiologic phenomena with higher spatial and temporal resolution. For more than a decade, MMCG has been mostly confined to magnetically shielded rooms and considered to be at most an interesting matter for research activity. Nevertheless, an increasing number of papers have documented that magnetocardiography can also be useful to improve diagnostic accuracy. Most recently, the development of standardized instrumentations for unshielded MMCG, and its ease of use and reliability even in emergency rooms has triggered a new interest from clinicians for magnetocardiography, leading to several new installations of unshielded systems worldwide. In this review, clinical applications of magnetocardiography are summarized, focusing on major milestones, recent results of multicenter clinical trials and indicators of future developments.

Cardiac vectors in the healthy human fetus: developmental changes assessed by magnetocardiography and realistic approximations of the volume conductor

This study sought to characterize the developmental changes of three measures used to describe the morphology of the fetal cardiac vector: QRS peak-amplitude, QRS duration and QRS time-amplitude integral. To achieve this objective, we rely on a recently developed methodology for fetal cardiac vector estimation, using multichannel fetal magnetocardiographic (fMCG) recordings and realistic approximations of the volume conductors obtained from free-hand ultrasound imaging. fMCG recordings and 3D ultrasound images were obtained from 23 healthy, uncomplicated pregnancies for a total of 77 recordings performed at gestational ages between 22 and 37 weeks. We report the developmental changes of the cardiac vector parameters with respect to gestational age and estimated fetal weight, as well as their dependence on the estimated ventricular mass derived from cardiac dimensions measured with M-mode ultrasound. The normative values can be used along with the cardiac time intervals reported by previous fMCG studies to assist future clinical studies investigating conditions that affect fetal cardiac function.

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.

Pulsed-wave tissue Doppler echocardiography for the analysis of fetal cardiac arrhythmias

OBJECTIVES

Rhythm analysis of the fetal heart is hampered by the inability to routinely obtain electrocardiographic recordings of the fetus. Doppler studies of fetal cardiac tissue movements, assessing cardiac movements both qualitatively and quantitatively, have recently been described. We used a conventional high-resolution ultrasound system to obtain rhythm data from pulsed-wave tissue Doppler signals of the fetal heart in normal cardiac rhythm and in a variety of fetal cardiac arrhythmias.

METHODS

Fifty-five fetuses with normal (sinus) rhythm, 45 fetuses with rhythm disturbances and two neonates (one with arrhythmia and one with normal sinus rhythm) were studied. Using a conventional high-resolution ultrasound system equipped for fetal studies, but without specific tissue Doppler hardware or software, we performed pulsed-wave tissue Doppler echocardiography (PW-TDE) of atrioventricular valve ring excursions to study the atrial and ventricular mechanical actions. In the neonates, electrocardiograms were also recorded.

RESULTS

PW-TDE in normal fetuses shows a typical pattern of tissue motion parallel to the long axis of the heart and in the opposite direction to the blood flow, both in systole and diastole. This pattern is easily obtained from the tricuspid valve annulus in normal sinus rhythm and shows characteristic changes in various fetal arrhythmias.

CONCLUSION

PW-TDE of atrioventricular valve annulus movement patterns may prove to be a valuable additional tool for assessing fetal cardiac arrhythmias.

A novel approach to track fetal movement using multi-sensor magnetocardiographic recordings

Changes in fetal magnetocardiographic (fMCG) signals are indicators for fetal body movement. We propose a novel approach to reliably extract fetal body movements based on the field strength of the fMCG signal independent of its frequency. After attenuating the maternal MCG, we use a Hilbert transform approach to identify the R-wave. At each R-wave, we compute the center-of-gravity (cog) of the coordinate positions of MCG sensors, each weighted by the magnitude of the R-wave amplitude recorded at the corresponding sensor. We then define actogram as the distance between the cog computed at each R-wave and the average of the cog from all the R-waves in a 3-min duration. By applying a linear de-trending approach to the actogram we identify the fetal body movement and compare this with the synchronous occurrence of the acceleration in the fetal heart rate. Finally, we apply this approach to the fMCG recorded simultaneously with ultrasound from a single subject and show its improved performance over the QRS-amplitude based approach in the visually verified movements. This technique could be applied to transform the detection of fetal body movement into an objective measure of fetal health and enhance the predictive value of prevalent clinical testing for fetal wellbeing.

Influence of gestational age on the effectiveness of spatial and temporal methods for the reconstruction of the fetal magnetocardiogram

Fetal magnetocardiography (fMCG) has been shown to augment fetal ultrasound evaluation for high-risk conditions, but the clinical utility of fMCG depends on the reliability of the cardiac traces reconstructed. We performed a methodological study to examine the influence of gestational age on the properties of the fetal magnetocardiograms extracted with two methods of signal reconstruction: the template matching technique (TMT), which extracts the maternal components from the signal using only temporal information, and independent component analysis (ICA), which separates the fetal signals by using information on the spatial distribution of the mixed source signals in addition to higher order temporal statistics. Efficiency and accuracy were evaluated in terms of fetal beat detection, signal characteristics, and duration of cardiac time intervals (CTIs) on the averaged traces. ICA outperformed TMT with regard to beat detection and signal-to-noise ratio. The timing of the heartbeats and the duration of the CTIs were essentially the same, whereas some alterations in signal morphology were observed in the ICA traces. We conclude that ICA may be useful in early gestation when the signals are noisy, while TMT may be preferred when accurate beat morphology is required for diagnostic purposes.

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.

Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data

In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction.

Fetal and maternal magnetocardiography during flecainide therapy for supraventricular tachycardia

BACKGROUND

Fetal magnetocardiography is a noninvasive technique capable of identifying fetal arrhythmias and can simultaneously characterize the cardiac rhythm of the mother and fetus.

CASES

Three patients, two singleton pregnancies and one twin pregnancy, were admitted for evidence of fetal supraventricular tachycardia. Fetal magnetocardiography was used to monitor the effects of flecainide therapy on the fetus and mother. Two singleton pregnancy fetuses showed improved heart rate and cardiac rhythm within 1 week of the initial dosing. Maintenance dosages controlled the conditions thereafter. Flecainide slowed the supraventricular tachycardia in the twin subject, but magnetocardiography revealed maternal adverse effects necessitating termination of flecainide therapy.

CONCLUSION

Magnetocardiography is a valuable tool for rhythm diagnosis and for monitoring the maternal and fetal cardiac rhythms in a patient undergoing flecainide therapy for fetal supraventricular tachycardia.

Beat-to-beat estimate of fetal cardiac time intervals using magnetocardiography: longitudinal charts of normality ranges and individual trends

BACKGROUND

Fetal magnetocardiography (fMCG) records fetal cardiac electro-physiological activity during the second half of gestation. We aimed at assessing normality values, related variability, and trends of fetal cardiac time intervals (fCTI) evaluated longitudinally from beat-to-beat fMCG analysis in uncomplicated pregnancies.

MATERIALS AND METHODS

The fMCG were recorded with multi-channel system in shielded room. FCTI were estimated on more than 2600 fetal cardiac cycles from 51 fMCG data sets of uncomplicated pregnancies. Independent component analysis (ICA) allowed reconstructing reliable fetal signals for beat-to-beat identification of fCTI (RR, P wave, PQ, PR, QT, QTc, QRS, ST, and T wave); intra-individual variability analysis and trends were calculated; reference longitudinal charts accounted for intra- and inter-individual variations and were compared with figures estimated on averaged signals.

RESULTS

For each data set, fCTI were calculated beat-to-beat on rhythm strips of more than 50 beats (95% overall detection rate). FCTI values, variability, and trends were in good agreement with available reference figures; intervals related to P and T waves were, respectively, underestimated and overestimated with respect to those estimated on averaged signals or obtained by other research groups. Errors were reduced and individual trends could be drawn.

CONCLUSIONS

ICA permitted the reconstruction of reliable time course of fetal cardiac signals and the beat-to-beat calculation of time intervals, and normality ranges, with smaller errors with respect to previous studies. The retrieval of fetal traces with clear morphology and the longitudinal character of the study allowed estimating individual trends and beat-to-beat characterization, impossible with cross-sectional studies on averaged beats.

Optimal filter design for shielded and unshielded ambient noise reduction in fetal magnetocardiography

The greatest impediment to extracting high-quality fetal signals from fetal magnetocardiography (fMCG) is environmental magnetic noise, which may have peak-to-peak intensity comparable to fetal QRS amplitude. Being an unstructured Gaussian signal with large disturbances at specific frequencies, ambient field noise can be reduced with hardware-based approaches and/or with software algorithms that digitally filter magnetocardiographic recordings. At present, no systematic evaluation of filters' performances on shielded and unshielded fMCG is available. We designed high-pass and low-pass Chebychev II-type filters with zero-phase and stable impulse response; the most commonly used band-pass filters were implemented combining high-pass and low-pass filters. The achieved ambient noise reduction in shielded and unshielded recordings was quantified, and the corresponding signal-to-noise ratio (SNR) and signal-to-distortion ratio (SDR) of the retrieved fetal signals was evaluated. The study regarded 66 fMCG datasets at different gestational ages (22-37 weeks). Since the spectral structures of shielded and unshielded magnetic noise were very similar, we concluded that the same filter setting might be applied to both conditions. Band-pass filters (1.0-100 Hz) and (2.0-100 Hz) provided the best combinations of fetal signal detection rates, SNR and SDR; however, the former should be preferred in the case of arrhythmic fetuses, which might present spectral components below 2 Hz.

A method for the automatic reconstruction of fetal cardiac signals from magnetocardiographic recordings

Fetal magnetocardiography (fMCG) allows monitoring the fetal heart function through algorithms able to retrieve the fetal cardiac signal, but no standardized automatic model has become available so far. In this paper, we describe an automatic method that restores the fetal cardiac trace from fMCG recordings by means of a weighted summation of fetal components separated with independent component analysis (ICA) and identified through dedicated algorithms that analyse the frequency content and temporal structure of each source signal. Multichannel fMCG datasets of 66 healthy and 4 arrhythmic fetuses were used to validate the automatic method with respect to a classical procedure requiring the manual classification of fetal components by an expert investigator. ICA was run with input clusters of different dimensions to simulate various MCG systems. Detection rates, true negative and false positive component categorization, QRS amplitude, standard deviation and signal-to-noise ratio of reconstructed fetal signals, and real and per cent QRS differences between paired fetal traces retrieved automatically and manually were calculated to quantify the performances of the automatic method. Its robustness and reliability, particularly evident with the use of large input clusters, might increase the diagnostic role of fMCG during the prenatal period.

Automatic detection of cardiac waves on fetal magnetocardiographic signals

Fetal magnetocardiography (fMCG) provides fetal cardiac traces useful for the prenatal monitoring of fetal heart function. In this paper, we describe an analytical model (ACWD) for the automatic detection of cardiac waves boundaries that works on fetal signals reconstructed from fMCG by means of independent component analysis. ACWD was validated for 45 healthy and 4 arrhythmic fetuses ranging from 22 to 37 weeks; ACWD outcomes were compared with the estimates of three independent investigators. Descriptive statistics were used to assess correspondence between the outcomes of the automatic and manual approaches. The parametric two-tailed Pearson correlation test (alpha=0.01) was employed to quantify, by means of the coefficients of determination, the amount of common variation between the sequences of intervals quantified automatically and manually. ACWD performances on short and long rhythm strips were investigated. ACWD demonstrated to be a robust tool providing dependable estimates of cardiac intervals and their variability during the third gestational trimester also in case of fetal arrhythmias. SNR and stability of fetal traces were the factors limiting ACWD performances. ACWD computation time, which was approximately 1:600 with respect to the manual procedure, was comparable with the time required for fCTI estimation on averaged beats.

Simultaneous monitoring of separate fetal magnetocardiographic signals in twin pregnancy

Fetal magnetocardiography (fMCG) allows the non-invasive recording of fetal cardiac electrical activity with increasing efficacy as gestation progresses. Many reports on the successful extraction of reliable fetal magnetocardiographic traces in singleton pregnancies exist in the literature, whereas there is only one report on the reconstruction of averaged fetal cardiac signals obtained in a twin pregnancy with the use of a double sensor array system. In this paper, we aimed at assessing the effectiveness of an ICA-based procedure to reconstruct the time course of fetal cardiac signals recorded with a single-shot multi-channel fMCG device in an uncomplicated twin pregnancy at 27 weeks. The evaluation of heart rate and beats synchronicity permitted the differentiation of fetal components; the quality of reconstructed fetal signals allowed visual inspection on single cycles and the simultaneous monitoring of separate fetal heart rate patterns. The proposed technique might be applied in twin pregnancies not only to characterize fetal arrhythmias, but also in all cases of discordant fetal growth, either in the case of intra-uterine growth retardation affecting one fetus, or in the case of twin-twin transfusion syndrome, a life-threatening condition where both fetuses are at risk of heart failure.

Multichannel mapping of fetal magnetocardiogram in an unshielded hospital setting

OBJECTIVES

To evaluate the feasibility of unshielded in-hospital multichannel mapping of fetal magnetocardiogram (FMCG), with a 36-channel system for standard adult magnetocardiographic (MCG) recordings, and its reliability according to the recommended standards for FMCG.

METHODS

FMCG was ambulatory mapped with a 36-channel MCG system, in six normal pregnancies at different gestational ages. MCG analysis included adaptive digital filtering of 50 Hz, signal averaging, reconstruction of magnetic field distribution (MFD) and source localization. Fixed Point Independent Component Analysis algorithm (FastICA) was used to reconstruct the FMCG, separating them from maternal contamination and noise.

RESULTS

The quality of FMCG recorded after the 32nd gestational week and reconstructed with FastICA was close to FMCG obtained in shielded rooms, and good enough to measure cardiac intervals and heart rate variability parameters. In two cases, reconstruction of the MFD during the QRS allowed three-dimensional localization of ventricular sources.

CONCLUSIONS

A first demonstration has been given that multichannel mapping of FMCG can be performed in unshielded clinical environments, with resolution good enough for contactless assessment of fetal cardiac electrophysiology. FastICA processing on unshielded FMCG, recorded after the 32nd week, provided beat-to-beat analysis and heart rate variability assessment. Further work is needed to improve signal reconstruction in early pregnancy.