The effects of intrapartum hypoxia on the fetal QT interval

Feasibility Analysis of ECG-Based pH Estimation for Asphyxia Detection in Neonates

Birth asphyxia is a potential cause of death that is also associated with acute and chronic morbidities. The traditional and immediate approach for monitoring birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative noninvasive approaches such as pulse oximeters can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative noninvasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate the prominent ECG features based on pH estimation that could potentially be used to explore the noninvasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset used contained 274 segments of ECG and pH values recorded simultaneously. After preprocessing the data, principal component analysis and the Pan-Tompkins algorithm were used for each segment to determine the most significant ECG cycle and to compute the ECG features. Descriptive statistics were performed to describe the main properties of the processed dataset. A Kruskal-Wallis nonparametric test was then used to analyze differences between the asphyxiated and non-asphyxiated groups. Finally, a Dunn-Šidák post hoc test was used for individual comparison among the mean ranks of all groups. The findings of this study showed that ECG features (T/QRS, T Amplitude, Tslope, Tslope/T, Tslope/|T|, HR, QT, and QTc) based on pH estimation differed significantly (p < 0.05) in asphyxiated neonates. All these key ECG features were also found to be significantly different between the two groups.

Power-MF: robust fetal QRS detection from non-invasive fetal electrocardiogram recordings

Objective.Perinatal asphyxia poses a significant risk to neonatal health, necessitating accurate fetal heart rate monitoring for effective detection and management. The current gold standard, cardiotocography, has inherent limitations, highlighting the need for alternative approaches. The emerging technology of non-invasive fetal electrocardiography shows promise as a new sensing technology for fetal cardiac activity, offering potential advancements in the detection and management of perinatal asphyxia. Although algorithms for fetal QRS detection have been developed in the past, only a few of them demonstrate accurate performance in the presence of noise and artifacts.Approach.In this work, we proposePower-MF, a new algorithm for fetal QRS detection combining power spectral density and matched filter techniques. We benchmarkPower-MFagainst three open-source algorithms on two recently published datasets (Abdominal and Direct Fetal ECG Database: ADFECG, subsets B1 Pregnancy and B2 Labour; Non-invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research: NInFEA).Main results.Our results show thatPower-MFoutperforms state-of-the-art algorithms on ADFECG (B1 Pregnancy: 99.5% ± 0.5% F1-score, B2 Labour: 98.0% ± 3.0% F1-score) and on NInFEA in three of six electrode configurations by being more robust against noise.Significance.Through this work, we contribute to improving the accuracy and reliability of fetal cardiac monitoring, an essential step toward early detection of perinatal asphyxia with the long-term goal of reducing costs and making prenatal care more accessible.

Chronic maternal hypercortisolemia models stress-induced adverse birth outcome and altered cardiac function in newborn lambs

Maternal stress in pregnancy is thought to be a contributing factor in adverse pregnancy outcome, including stillbirth and prematurity. Previous studies in our laboratory have shown that chronic elevation in maternal cortisol concentration in ewes (by maternal infusion of 1 mg·kg^-1·day^-1) during the late gestion increased the incidence of stillbirth and altered fetal heart rate and blood pressure at birth. We designed the current study to test the effect of chronically elevated maternal cortisol on fetal cardiac adaption from in utero life to ex utero life. The combined risk of stillbirth or prematurity was significantly greater in the pregnancies with maternal hypercortisolemia: in this cohort, 40% of the lambs of cortisol-infused ewes died in utero or at birth compared to 25% of lambs of control ewes, and 24% of lambs of cortisol-infused ewes were born preterm, whereas no lamb was born preterm in the control group. Compared to control lambs, the lambs of cortisol-infused ewes born at full term exhibited a significant increase in mean aortic pressure just prior to birth, and a significant decrease in mean aortic pressure that was evident during the first 9 hours after birth. The QT interval was decreased prior to birth and increased immediately after birth in the newborns of cortisol-treated ewes compared to control lambs. These findings suggest that an excess in utero corticosteroid exposure adversely affects fetal cardiac adaptation to extrauterine life and that chronic maternal stress or hypersecretion of corticosteroids may contribute to adverse obstetric outcomes.

Sodium dichloroacetate stimulates cardiac mitochondrial metabolism and improves cardiac conduction in the ovine fetus during labor

Previous studies in our laboratory have suggested that the increase in stillbirth in pregnancies complicated by chronic maternal stress or hypercortisolemia is associated with cardiac dysfunction in late stages of labor and delivery. Transcriptomics analysis of the overly represented differentially expressed genes in the fetal heart of hypercortisolemic ewes indicated involvement of mitochondrial function. Sodium dichloroacetate (DCA) has been used to improve mitochondrial function in several disease states. We hypothesized that administration of DCA to laboring ewes would improve both cardiac mitochondrial activity and cardiac function in their fetuses. Four groups of ewes and their fetuses were studied: control, cortisol-infused (1 g/kg/day from 115 to term; CORT), DCA-treated (over 24 h), and DCA + CORT-treated; oxytocin was delivered starting 48 h before the DCA treatment. DCA significantly decreased cardiac lactate, alanine, and glucose/glucose-6-phosphate and increased acetylcarnitine/isobutyryl-carnitine. DCA increased mitochondrial activity, increasing oxidative phosphorylation (P_CI, P_CI + II) per tissue weight or per unit of citrate synthase. DCA also decreased the duration of the QRS, attenuating the prolongation of the QRS observed in CORT fetuses. The effect to reduce QRS duration with DCA treatment correlated with increased glycerophosphocholine and serine and decreased phosphorylcholine after DCA treatment. There were negative correlations of acetylcarnitine/isobutyryl-carnitine to both heart rate (HR) and mean arterial pressure (MAP). These results suggest that improvements in mitochondrial respiration with DCA produced changes in the cardiac lipid metabolism that favor improved conduction in the heart. DCA may therefore be an effective treatment of fetal cardiac metabolic disturbances in labor that can contribute to impairments of fetal cardiac conduction.

AECG-DecompNet: abdominal ECG signal decomposition through deep-learning model

Objective.The accurate decomposition of a mother's abdominal electrocardiogram (AECG) to extract the fetal ECG (FECG) is a primary step in evaluating the fetus's health. However, the AECG is often affected by different noises and interferences, such as the maternal ECG (MECG), making it hard to evaluate the FECG signal. In this paper, we propose a deep-learning-based framework, namely 'AECG-DecompNet', to efficiently extract both MECG and FECG from a single-channel abdominal electrode recording.Approach.AECG-DecompNet is based on two series networks to decompose AECG, one for MECG estimation and the other to eliminate interference and noise. Both networks are based on an encoder-decoder architecture with internal and external skip connections to reconstruct the signals better.Main results.Experimental results show that the proposed framework performs much better than utilizing one network for direct FECG extraction. In addition, the comparison of the proposed framework with popular single-channel extraction techniques shows superior results in terms of QRS detection while indicating its ability to preserve morphological information. AECG-DecompNet achieves exceptional accuracy in theprecisionmetric (97.4%), higher accuracy inrecallandF₁metrics (93.52% and 95.42% respectively), and outperforms other state-of-the-art approaches.Significance.The proposed method shows a notable performance in preserving the morphological information when the FECG within the AECG signal is weak.

Model based estimation of QT intervals in non-invasive fetal ECG signals

The end timing of T waves in fetal electrocardiogram (fECG) is important for the evaluation of ST and QT intervals which are vital markers to assess cardiac repolarization patterns. Monitoring malignant fetal arrhythmias in utero is fundamental to care in congenital heart anomalies preventing perinatal death. Currently, reliable detection of end of T waves is possible only by using fetal scalp ECG (fsECG) and fetal magnetocardiography (fMCG). fMCG is expensive and less accessible and fsECG is an invasive technique available only during intrapartum period. Another safer and affordable alternative is the non-invasive fECG (nfECG) which can provide similar assessment provided by fsECG and fMECG but with less accuracy (not beat by beat). Detection of T waves using nfECG is challenging because of their low amplitudes and high noise. In this study, a novel model-based method that estimates the end of T waves in nfECG signals is proposed. The repolarization phase has been modeled as the discharging phase of a capacitor. To test the model, fECG signals were collected from 58 pregnant women (age: (34 ± 6) years old) bearing normal and abnormal fetuses with gestational age (GA) 20-41 weeks. QT and QTc intervals have been calculated to test the level of agreement between the model-based and reference values (fsECG and Doppler Ultrasound (DUS) signals) in normal subjects. The results of the test showed high agreement between model-based and reference values (difference < 5%), which implies that the proposed model could be an alternative method to detect the end of T waves in nfECG signals.

End-to-end trained encoder-decoder convolutional neural network for fetal electrocardiogram signal denoising

OBJECTIVE

Non-invasive fetal electrocardiography has the potential to provide vital information for evaluating the health status of the fetus. However, the low signal-to-noise ratio of the fetal electrocardiogram (ECG) impedes the applicability of the method in clinical practice. Quality improvement of the fetal ECG is of great importance for providing accurate information to enable support in medical decision-making. In this paper we propose the use of artificial intelligence for the task of one-channel fetal ECG enhancement as a post-processing step after maternal ECG suppression.

APPROACH

We propose a deep fully convolutional encoder-decoder framework, learning end-to-end mappings from noise-contaminated fetal ECGs to clean ones. Symmetric skip-layer connections are used between corresponding convolutional and transposed convolutional layers to help recover the signal details.

MAIN RESULTS

Experiments on synthetic data show an average improvement of 7.5 dB in the signal-to-noise ratio (SNR) for input SNRs in the range of  -15 to 15 dB. Application of the method with real signals and subsequent ECG interval analysis demonstrates a root mean square error of 9.9 and 14 ms for the PR and QT intervals, respectively, when compared with simultaneous scalp measurements. The proposed network can achieve substantial noise removal on both synthetic and real data. In cases of highly noise-contaminated signals some morphological features might be unreliably reconstructed.

SIGNIFICANCE

The presented method has the advantage of preserving individual variations in pulse shape and beat-to-beat intervals. Moreover, no prior knowledge on the power spectra of the noise or the pulse locations is required.

QRStree: A prefix tree-based model to fetal QRS complexes detection

Non-invasive fetal electrocardiography (NI-FECG) plays an important role in fetal heart rate (FHR) measurement during the pregnancy. However, despite the large number of methods that have been proposed for adult ECG signal processing, the analysis of NI-FECG remains challenging and largely unexplored. In this study, we propose a prefix tree-based framework, called QRStree, for FHR measurement directly from the abdominal ECG (AECG). The procedure is composed of three stages: Firstly, a preprocessing stage is employed for noise elimination. Secondly, the proposed prefix tree-based method is used for fetal QRS complexes (FQRS) detection. Finally, a correction stage is applied for false positive and false negative correction. The novelty of the framework relies on using the range of FHR to establish the connections between the FQRS. The consecutive FQRS can be considered as strings composed of alphabet items, thus we can use the prefix tree to store them. A vertex of the tree contains an alphabet, thus a path of the tree gives a string. Such that, by storing the connections of the FQRS into the prefix tree structure, the problem of FQRS detection converts to a problem of optimal path selection. Specifically, after selecting the optimal path of the tree, the nodes in the optimal path are collected as detected FQRS. Since the prefix tree can cover every possible combination of the FQRS candidates, it has the potential to reduce the occurrence of miss detections. Results on two different databases show that the proposed method is effective in FHR measurement from single-channel AECG. The focus on single-channel FHR measurement facilitates the long-term monitoring for healthcare at home.

The effects of asymmetric volume conductor modeling on non-invasive fetal ECG extraction

OBJECTIVE

Non-invasive fetal electrocardiography (NI-FECG) shows promise for capturing novel physiological information that may indicate signs of fetal distress. However, significant deterioration in NI-FECG signal quality occurs during the presence of a highly non-conductive layer known as vernix caseosa which forms on the fetal body surface beginning in approximately the 28th week of gestation. This work investigates asymmetric modeling of vernix caseosa and other maternal-fetal tissues in accordance with clinical observations and assesses their impacts for NI-FECG signal processing.

APPROACH

We develop a process for simulating dynamic maternal-fetal abdominal ECG mixtures using a synthetic cardiac source model embedded in a finite element volume conductor. Using this process, changes in NI-FECG signal morphology are assessed in an extensive set of finite element models including spatially variable distributions of vernix caseosa.

MAIN RESULTS

Our simulations show that volume conductor asymmetry can result in over 70% error in the observed T/QRS ratio and significant changes to signal morphology compared to a homogeneous volume conductor model. Volume conductor effects must be considered when analyzing T/QRS ratios obtained via NI-FECG and should be considered in future algorithm benchmarks using simulated data.

SIGNIFICANCE

This work shows that without knowledge of the influence of volume conductor effects, clinical evaluation of the T/QRS ratio derived via NI-FECG should be avoided.

A systematic review of cardiac time intervals utilising non-invasive fetal electrocardiogram in normal fetuses

BACKGROUND

Non-invasive fetal electrocardiogram (NIFECG) is an evolving technology in fetal surveillance which is attracting increasing research interest. There is however, only limited data outlining the reference ranges for normal cardiac time intervals (CTIs). The objective of our group was to carry out a systematic review to outline normal fetal CTIs using NIFECG.

METHODS

A systematic review of peer reviewed literature was performed, searching PUBMED,Ovid MEDLINE and EMBASE. The outcomes of interest included fetal CTIs (P wave duration, PR interval, QRS duration and QT interval) and a descriptive summary of relevant studies as well. The outcomes were grouped as early pre-term (≤ 32 weeks), moderate to late pre-term (32-37 weeks) and term (37-41 weeks).

RESULTS

8 studies were identified as suitable for inclusion. Reference ranges of CTIs were generated. Both PR interval and QRS duration demonstrated a linear correlation with advancing gestation. Several studies also demonstrated a reduction in signal acquisition between 27 and 32 weeks due to the attenuation by vernix caseosa. In this group, both the P wave and T waves were difficult to detect due to signal strength and interference.

CONCLUSION

NIFECG demonstrates utility to quantify CTIs in the fetus, particularly at advanced gestations. Larger prospective studies should be directed towards establishing reliable CTIs across various gestations.

Waveform analysis of the fetal ECG in labor in patients with intrahepatic cholestasis of pregnancy

AIM

Intrahepatic cholestasis of pregnancy (ICP) is reported to be associated with an increased risk of sudden fetal death. The possible mechanism is thought to be cardiac arrhythmia. Prolonged QT interval of the electrocardiogram (ECG) is associated with arrhytmogenic events. The aim of the study was to compare the fetal ECG QT interval during labor in pregnancies complicated with ICP to healthy controls.

METHODS

The fetal ECG and QT interval was reviewed retrospectively. The intrapartum QT interval was measured in 61 fetuses born to mothers with ICP and in a control group of similar size. The corrected QT interval (QTc) was calculated using Bazett's formula: QT/√RR. The occurrence of ST segment depression was also included in the analysis.

RESULTS

The groups were similar regarding to maternal age, parity, BMI, gestational age and smoking habits. The rate of labor induction was significantly higher in ICP patients (P < 0.001). The QTc at the beginning and the end of recording was analyzed and there were no significant differences in these values between the ICP patients and healthy controls (P = 0.467). Most ICP patients used ursodeoxycholic acid (UDCA) for mediation. We analyzed separately patients who had elevated liver enzymes before labor. No significant differences in the QTc were noted in these patients either. Nor were there any significant ST depressions in ICP patients.

CONCLUSIONS

The etiology of adverse perinatal outcome and even sudden fetal death in ICP is still controversial. No differences in QTc intervals and ST waveforms during labor were found in our study material.

Evaluation of the fetal QT interval using non-invasive fetal ECG technology

Non-invasive fetal electrocardiography (NI-FECG) is a promising alternative continuous fetal monitoring method that has the potential to allow morphological analysis of the FECG. However, there are a number of challenges associated with the evaluation of morphological parameters from the NI-FECG, including low signal to noise ratio of the NI-FECG and methodological challenges for getting reference annotations and evaluating the accuracy of segmentation algorithms. This work aims to validate the measurement of the fetal QT interval in term laboring women using a NI-FECG electrocardiogram monitor. Fetal electrocardiogram data were recorded from 22 laboring women at term using the NI-FECG and an invasive fetal scalp electrode simultaneously. A total of 105 one-minute epochs were selected for analysis. Three pediatric electrophysiologists independently annotated individual waveforms and averaged waveforms from each epoch. The intervals measured on the averaged cycles taken from the NI-FECG and the fetal scalp electrode showed a close agreement; the root mean square error between all corresponding averaged NI-FECG and fetal scalp electrode beats was 13.6 ms, which is lower than the lowest adult root mean square error of 16.1 ms observed in related adult QT studies. These results provide evidence that NI-FECG technology enables accurate extraction of the fetal QT interval.

Comparison of ECG-based physiological markers for hypoxia in a preterm ovine model

BACKGROUND

Current methods for assessing perinatal hypoxic conditions did not improve infant outcomes. Various waveform-based and interval-based ECG markers have been suggested, but not directly compared. We compare performance of ECG markers in a standardized ovine model for fetal hypoxia.

METHODS

Sixty-nine fetal sheep of 0.7 gestation had ECG recorded 4 h before, during, and 4 h after a 25-min period of umbilical cord occlusion (UCO), leading to severe hypoxia. Various ECG markers were calculated, among which were heart rate (HR), HR-corrected ventricular depolarization/repolarization interval (QTc), and ST-segment analysis (STAN) episodic and baseline rise markers, analogue to clinical STAN device alarms. Performance of interval- and waveform-based ECG markers was assessed by correlating predicted and actual hypoxic/normoxic state.

RESULTS

Of the markers studied, HR and QTc demonstrated high sensitivity (≥86%), specificity (≥96%), and positive predictive value (PPV) (≥86%) and detected hypoxia in ≥90% of fetuses at 4 min after UCO. In contrast, STAN episodic and baseline rise markers displayed low sensitivity (≤20%) and could not detect severe fetal hypoxia in 65 and 28% of the animals, respectively.

CONCLUSION

Interval-based HR and QTc markers could assess the presence of severe hypoxia. Waveform-based STAN episodic and baseline rise markers were ineffective as markers for hypoxia.

The Use of Fetal Noninvasive Electrocardiography

Preeclampsia (PE) is one of the severe complications of pregnancy that leads to fetal deterioration. The aim was to survey the validity of fetal distress diagnostics in case of Doppler ultrasonic umbilical vein and arteries blood flow velocity investigation and ECG parameters analysis obtained from maternal abdominal signal before labor in preeclamptic patients. Fetal noninvasive ECG and umbilical arterial and venous Doppler investigation were performed in 120 patients at 34-40 weeks of gestation. And 30 of them had physiological gestation and were involved in Group I. In Group II 52 pregnant women with mild-moderate PE were observed. 38 patients with severe PE were monitored in Group III. The most considerable negative correlation was determined in pair Apgar score 1 versus T/QRS (R = -0.50; p < 0.05). So the increased T/QRS ratio was the most evident marker of fetal distress. Fetal noninvasive ECG showed sensitivity of 96.6% and specificity of 98.4% and, therefore, was determined as more accurate method for fetal monitoring.

Extraction of the fetal ECG in noninvasive recordings by signal decompositions

No signal processing technique has been able to reliably deliver an undistorted fetal electrocardiographic (fECG) signal from electrodes placed on the maternal abdomen because of the low signal-to-noise ratio of the fECG recorded from the maternal body surface. As a result, this led to increased rates of Caesarean deliveries of healthy infants. In an attempt to solve the problem, Physionet/Computing in Cardiology announced the 2013 Challenge: noninvasive fetal ECG.We are suggesting a method for cancellation of the maternal ECG consisting of: maternal QRS detection, heart rate dependant P-QRS-T interval selection, location of the fiducial points inside this interval for best matching by cross correlation, superimposition of the intervals, calculation of the mean signal of the P-QRS-T interval, and sequential subtraction of the mean signal from the whole fECG recording. Three signal decomposition methods were further applied in order to enhance the fetal QRSs (fQRS): principal component analysis, root-mean-square and Hotelling's T-squared. A combined lead of all decompositions was synthesized and fQRS detection was performed on it.The current research differs from the Challenge in that it uses three signal decomposition methods to enhance the fECG. The new results for 97 recordings of test set B are: 305.657 for Event 4: Fetal heart rate (FHR) and 23.062 for Event 5: Fetal RR interval (FRR).

Non-invasive fetal ECG analysis

Despite the important advances achieved in the field of adult electrocardiography signal processing, the analysis of the non-invasive fetal electrocardiogram (NI-FECG) remains a challenge. Currently no gold standard database exists which provides labelled FECG QRS complexes (and other morphological parameters), and publications rely either on proprietary databases or a very limited set of data recorded from few (or more often, just one) individuals.The PhysioNet/Computing in Cardiology Challenge 2013 enables to tackle some of these limitations by releasing a set of NI-FECG data publicly to the scientific community in order to evaluate signal processing techniques for NI-FECG extraction. The Challenge aim was to encourage development of accurate algorithms for locating QRS complexes and estimating the QT interval in non-invasive FECG signals. Using carefully reviewed reference QRS annotations and QT intervals as a gold standard, based on simultaneous direct FECG when possible, the Challenge was designed to measure and compare the performance of participants' algorithms objectively. Multiple challenge events were designed to test basic FHR estimation accuracy, as well as accuracy in measurement of inter-beat (RR) and QT intervals needed as a basis for derivation of other FECG features.This editorial reviews the background issues, the design of the Challenge, the key achievements, and the follow-up research generated as a result of the Challenge, published in the concurrent special issue of Physiological Measurement.

Towards computational modelling of the human foetal electrocardiogram: normal sinus rhythm and congenital heart block

AIMS

We aim to engineer a computational model of propagation during normal sinus rhythm in the foetal human heart, by modifying models for adult cardiac tissue to match foetal electrocardiogram (fECG) characteristics. The model will be partially validated by fECG data, and applied to explore possible mechanisms of arrhythmogenesis in the foetal heart.

METHODS AND RESULTS

Foetal electrocardiograms have been recorded during pregnancy, with P- and T-waves, and the QRS complex, identified by averaging and signal processing. Intervals of the fECG are extracted and used to modify currently available human adult cardiomyocyte models. RR intervals inform models of the pacemaking cells by constraining their rate, the QT interval and its rate dependence constrain models of ventricular cells, and the width of the P-wave, the QR and PR intervals constrain propagation times, conduction velocities, and intercellular coupling. These cell models are coupled into a one-dimensional (1D) model of propagation during normal sinus rhythm in the human foetal heart. We constructed a modular, heterogeneous 1D model for propagation in the foetal heart, and predicted the effects of reduction in L-type Ca(++) current. These include bradycardia and atrioventricular conduction blocks. These may account quantitatively for congenital heart block produced by positive IgG antibodies.

CONCLUSION

The fECG can be interpreted mechanistically and quantitatively by using a simple computational model for propagation. After further validation, by clinical recordings of the fECG and the electrophysiological experiments on foetal cardiac cells and tissues, the model may be used to predict the effects of maternally administered pharmaceuticals on the fECG.

A comparison of single channel fetal ECG extraction methods

The abdominal electrocardiogram (ECG) provides a non-invasive method for monitoring the fetal cardiac activity in pregnant women. However, the temporal and frequency overlap between the fetal ECG (FECG), the maternal ECG (MECG) and noise results in a challenging source separation problem. This work seeks to compare temporal extraction methods for extracting the fetal signal and estimating fetal heart rate. A novel method for MECG cancelation using an echo state neural network (ESN) based filtering approach was compared with the least mean square (LMS), the recursive least square (RLS) adaptive filter and template subtraction (TS) techniques. Analysis was performed using real signals from two databases composing a total of 4 h 22 min of data from nine pregnant women with 37,452 reference fetal beats. The effects of preprocessing the signals was empirically evaluated. The results demonstrate that the ESN based algorithm performs best on the test data with an F1 measure of 90.2% as compared to the LMS (87.9%), RLS (88.2%) and the TS (89.3%) techniques. Results suggest that a higher baseline wander high pass cut-off frequency than traditionally used for FECG analysis significantly increases performance for all evaluated methods. Open source code for the benchmark methods are made available to allow comparison and reproducibility on the public domain data.

Reference values for fetal tissue velocity imaging and a new approach to evaluate fetal myocardial function

OBJECTIVES

Myocardial function can be evaluated using color-coded tissue velocity imaging (TVI) to analyze the longitudinal myocardial velocity profile, and by expressing the motion of the atrioventricular plane during a cardiac cycle as coordinated events in the cardiac state diagram (CSD). The objective of this study was to establish gestational age specific reference values for fetal TVI measurements and to introduce the CSD as a potential aid in fetal myocardial evaluation.

METHODS

TVI recordings from 125 healthy fetuses, at 18 to 42 weeks of gestation, were performed with the transducer perpendicular to the apex to provide a four-chamber view. The myocardial velocity data was extracted from the basal segment of septum as well as the left and right ventricular free wall for subsequent offline analysis.

RESULTS

During a cardiac cycle the longitudinal peak velocities of septum increased with gestational age, as did the peak velocities of the left and right ventricular free wall, except for the peak velocity of post ejection. The duration of rapid filling and atrial contraction increased during pregnancy while the duration of post ejection decreased. The duration of pre ejection and ventricular ejection did not change significantly with gestational age.

CONCLUSION

Evaluating fetal systolic and diastolic performance using TVI together with CSD could contribute to increase the knowledge and understanding of fetal myocardial function and dysfunction. The pre and post ejection phases are the variables most likely to indicate fetuses with abnormal myocardial function.

ST segment analysis as an adjunct to electronic fetal monitoring, Part I: background, physiology, and interpretation

Fetal electrocardiogram (ECG) ST segment analysis (STAN) was approved in 2005 in the United States as an adjunct to electronic fetal heart rate monitoring to determine whether obstetrical intervention is warranted when there is an increased risk for developing metabolic acidosis. STAN has utility in the reduction of fetal acidosis at birth, decreased need for fetal scalp blood sampling during labor, and decreased need for operative vaginal delivery and emergency cesarean delivery for fetal indications. This article discusses specific fetal ECG changes and their significance and the use of the STAN system.

Fetal short time variation during labor: a non-invasive alternative to fetal scalp pH measurements?

OBJECTIVE

To determine whether short time variation (STV) of fetal heart beat correlates with scalp pH measurements during labor.

PATIENTS AND METHODS

From 1279 deliveries, 197 women had at least one fetal scalp pH measurement. Using the CTG-Player, STVs were calculated from the electronically saved cardiotocography (CTG) traces and related to the fetal scalp pH measurements.

RESULTS

There was no correlation between STV and fetal scalp pH measurements (r=-0.0592).

CONCLUSIONS

Fetal STV is an important parameter with high sensitivity for antenatal fetal acidosis. This study shows that STV calculations do not correlate with fetal scalp pH measurements during labor, hence are not helpful in identifying fetal acidosis.

INTRAPARTUM ST ANALYSIS

The last century has seen dramatic developments in medical care as technological advances have been applied to both diagnosis and treatment. Some areas of obstetrics have been slow to benefit from these advances – and none more so than the care of the fetus in labour.

Fetal electrocardiogram waveform analysis in labour

PURPOSE OF REVIEW

ST-waveform analysis of the fetal electrocardiogram (ECG) has emerged from experimental and observational studies to clinical use based on the outcome of two large randomized controlled trials and a European Union-supported project on the structured dissemination of knowledge and experience by establishing regional centres of excellence. The review focuses on the outcome from the host of studies and those recently published.

RECENT FINDINGS

The database is dominated by a Swedish randomized controlled trial demonstrating not only improved outcome with regard to cord-artery metabolic acidosis and fewer operative interventions for non-reassuring fetal state but, most importantly, the marked and significant reduction in the risk of neonates showing signs of moderate or severe neonatal encephalopathy. The first report from the European Union project is presented, verifying the clinical relevance of the STAN methodology. The outcome of the large European Union project of 8000 deliveries confirms the observations of the randomized controlled trials. A study on the outcome shows improvements in accuracy and consistency among clinicians when automated ST analysis is added to the fetal heart rate trace.

SUMMARY

After years of dedicated research, it appears as though ST analysis of the fetal ECG has become an additional source of information allowing detailed analysis of fetal responses and more accurate identification of a non-reassuring fetal status. The technology provides continuous information throughout labour. As with any new methodology, structured efforts on training and user feedback are required to fully implement the STAN methodology in clinical practice.