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

Fetal magnetocardiogram waveform characteristics

BACKGROUND

Fetal magnetocardiography (fMCG) is the most direct and precise method of assessing fetal rhythm and conduction. Although the utility of fMCG for evaluation of fetuses with serious arrhythmia is generally acknowledged, many aspects of fetal rhythm and conduction are relatively unstudied.

OBJECTIVE

To record fMCG in a large group of normal fetuses in order to provide a more comprehensive evaluation of fMCG waveform characteristics, including waveform intervals, amplitudes, and morphology.

METHODS

The subjects were 132 healthy women with uncomplicated singleton pregnancies, studied at 15.7-39.9 (mean 28.9) weeks' gestation in 259 sessions. The P, PR, QRS, QT, QTc, and RR intervals and the P/QRS and T/QRS amplitude ratios were measured.

MAIN RESULTS

The P, PR, QRS, and RR intervals increased with gestational age, but QT and QTc did not. U-waves were seen in 11% of fetuses. The T-waves were often flat with low T/QRS amplitude ratios. Equiphasic QRS complexes were associated with tall P-waves. The PR, QRS, and QT intervals showed a power law dependence on RR interval with power law exponents 0.445, 0.363, and 0.381, respectively.

SIGNIFICANCE

The data establish prediction intervals for fMCG waveform intervals and amplitudes in normal fetuses. This is critical for identification of fetuses with abnormal rhythm. Our study is the first to document the incidence of U-waves and flat T-waves in the fetus, both of which are uncommon postnatally. The association of tall P-waves with equiphasic QRS complexes provides a useful means of improving the resolution of fetal P-waves.

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.

De-noising the abdominal phonogram for foetal heart rate extraction: blind source separation versus empirical filtering

This work explored the suitability of using the foetal phonocardiogram (FPCG) blindly separated from the abdominal phonogram as a source for foetal heart rate (FHR) measuring in antenatal surveillance. To this end, and working on a dataset of 15 abdominal phonograms, the FPCG was estimated by using two de-noising approaches (1) single-channel independent component analysis (SCICA) to produce FPCG(e) and (2) empirical filtering to produce FPCG(g). Next, the FPCGs were further processed to collect the beat-to-beat FHR and the resulting time-series (FCTG(e) and FCTG(g) were compared to the reference signal given by the abdominal ECG (FCTG(r)). Results are promising, the FPCG(e) gives rise to a FCTG(e) that resembles FCTG(r) and, most importantly, whose mean FHR value is statistically equivalent to that given by FCTG(r) (p > 0.05). Thus, the mean FHR value obtained from the FPCG(e), is likely to be equivalent to the value given by the abdominal ECG, which is especially significant since the FPCG(e) is retrieved from the noisy abdominal phonogram. Hence, as far as this study has gone, it can be said that, when using SCICA to de-noise the abdominal phonogram, the resulting FPCG is likely to become a useful source for FHR collection in antenatal surveillance.

Antenatal architecture and activity of the human heart

We construct the components for a family of computational models of the electrophysiology of the human foetal heart from 60 days gestational age (DGA) to full term. This requires both cell excitation models that reconstruct the myocyte action potentials, and datasets of cardiac geometry and architecture. Fast low-angle shot and diffusion tensor magnetic resonance imaging (DT-MRI) of foetal hearts provides cardiac geometry with voxel resolution of approximately 100 µm. DT-MRI measures the relative diffusion of protons and provides a measure of the average intravoxel myocyte orientation, and the orientation of any higher order orthotropic organization of the tissue. Such orthotropic organization in the adult mammalian heart has been identified with myocardial sheets and cleavage planes between them. During gestation, the architecture of the human ventricular wall changes from being irregular and isotropic at 100 DGA to an anisotropic and orthotropic architecture by 140 DGA, when it has the smooth, approximately 120° transmural change in myocyte orientation that is characteristic of the adult mammalian ventricle. The DT obtained from DT-MRI provides the conductivity tensor that determines the spread of potential within computational models of cardiac tissue electrophysiology. The foetal electrocardiogram (fECG) can be recorded from approximately 60 DGA, and RR, PR and QT intervals between the P, R, Q and T waves of the fECG can be extracted by averaging from approximately 90 DGA. The RR intervals provide a measure of the pacemaker rate, the QT intervals an index of ventricular action potential duration, and its rate-dependence, and so these intervals constrain and inform models of cell electrophysiology. The parameters of models of adult human sinostrial node and ventricular cells that are based on adult cell electrophysiology and tissue molecular mapping have been modified to construct preliminary models of foetal cell electrophysiology, which reproduce these intervals from fECG recordings. The PR and QR intervals provide an index of conduction times, and hence propagation velocities (approx. 1-10 cm s(-1), increasing during gestation) and so inform models of tissue electrophysiology. Although the developing foetal heart is small and the cells are weakly coupled, it can support potentially lethal re-entrant arrhythmia.

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.

Antenatal surveillance through estimates of the sources underlying the abdominal phonogram: a preliminary study

Today, it is generally accepted that current methods for biophysical antenatal surveillance do not facilitate a comprehensive and reliable assessment of foetal well-being and that continuing research into alternative methods is necessary to improve antenatal monitoring procedures. In our research, attention has been paid to the abdominal phonogram, a signal that is recorded by positioning an acoustic sensor on the maternal womb and contains valuable information about foetal status, but which is hidden by maternal and environmental sources. To recover such information, previous work has used single-channel independent component analysis (SCICA) on the abdominal phonogram and successfully retrieved estimates of the foetal phonocardiogram, the maternal phonocardiogram, the maternal respirogram and noise. The availability of these estimates made it possible for the current study to focus on their evaluation as sources for antenatal surveillance purposes. To this end, the foetal heart rate (FHR), the foetal heart sounds morphology, the maternal heart rate (MHR) and the maternal breathing rate (MBR) were collected from the estimates retrieved from a dataset of 25 abdominal phonograms. Next, these parameters were compared with reference values to quantify the significance of the physiological information extracted from the estimates. As a result, it has been seen that the instantaneous FHR, the instantaneous MHR and the MBR collected from the estimates consistently followed the trends given by the reference signals, which is a promising outcome for this preliminary study. Thus, as far as this study has gone, it can be said that the independent traces retrieved by SCICA from the abdominal phonogram are likely to become valuable sources of information for well-being surveillance, both foetal and maternal.

On the interpretation of the independent components underlying the abdominal phonogram: a study of their physiological relevance

Recorded by positioning a sensitive acoustic sensor over the maternal womb, the abdominal phonogram is a signal that contains valuable information for foetal surveillance (e.g. heart rate), which is hidden by maternal and environmental sources. To recover such information, previous work used single-channel independent component analysis (SCICA) to separate the abdominal phonogram into statistically independent components (ICs) that, once acquired, must be objectively associated with the real sources underlying the abdominal phonogram-either physiological or environmental. This is a typical challenge for blind source separation methodologies and requires further research on the signals of interest to find a suitable solution. Here, we have conducted a joint study on 75 sets of ICs by means of statistical, spectral, complexity and time-structure analysis methods. As a result, valuable and consistent characteristics of the components separated from the abdominal phonogram by SCICA have been revealed: (1) the ICs are spectrally disjoint and sorted according to their frequency content, (2) only the ICs with lower frequency content present strong regular patterns and (3) such regular patterns are driven by well-known physiological processes given by the maternal breathing rate, the maternal heart rate and the foetal heart rate. This information was so promising that it has been used in current work for automatic classification of ICs and recovery of the traces of the physiological sources underlying the abdominal phonogram. Future work will look for the extraction of information useful for surveillance (e.g. heart rate), not only about foetal well-being, but also about maternal condition.

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.

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.