Indices of fetal development derived from heart rate patterns

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.

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals

The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors.

The Relationship between Gestational Diabetes Metabolic Control and Fetal Autonomic Regulation, Movement and Birth Weight

(1) Background: Maternal metabolic control in gestational diabetes is suggested to influence fetal autonomic control and movement activity, which may have fetal outcome implications. We aimed to analyze the relationship between maternal metabolic control, fetal autonomic heart rate regulation, activity and birth weight. (2) Methods: Prospective noninterventional longitudinal cohort monitoring study accompanying 19 patients with specialist clinical care for gestational diabetes. Monthly fetal magnetocardiography with electro-physiologically-based beat-to-beat heart rate recording for analysis of heart rate variability (HRV) and the ‘fetal movement index’ (FMI) was performed. Data were compared to 167 healthy pregnant women retrieved from our pre-existing study database. (3) Results: Fetal vagal tone was increased with gestational diabetes compared to controls, whereas sympathetic tone and FMI did not differ. Within the diabetic population, sympathetic activation was associated with higher maternal blood-glucose levels. Maternal blood-glucose levels correlated positively with birth weight z scores. FMI showed no correlation with birth weight but attenuated the positive correlation between maternal blood-glucose levels and birth weight. (4) Conclusion: Fetal autonomic control is altered by gestational diabetes and maternal blood-glucose level, even if metabolic adjustment and outcome is comparable to healthy controls.

In vivo biomarkers of structural and functional brain development and aging in humans

Brain aging is a major determinant of aging. Along with the aging population, prevalence of neurodegenerative diseases is increasing, therewith placing economic and social burden on individuals and society. Individual rates of brain aging are shaped by genetics, epigenetics, and prenatal environmental. Biomarkers of biological brain aging are needed to predict individual trajectories of aging and the risk for age-associated neurological impairments for developing early preventive and interventional measures. We review current advances of in vivo biomarkers predicting individual brain age. Telomere length and epigenetic clock, two important biomarkers that are closely related to the mechanistic aging process, have only poor deterministic and predictive accuracy regarding individual brain aging due to their high intra- and interindividual variability. Phenotype-related biomarkers of global cognitive function and brain structure provide a much closer correlation to age at the individual level. During fetal and perinatal life, autonomic activity is a unique functional marker of brain development. The cognitive and structural biomarkers also boast high diagnostic specificity for determining individual risks for neurodegenerative diseases.

Assessment of human fetal cardiac autonomic nervous system development using color tissue Doppler imaging

Objectives

Functional development of the fetal cardiac autonomic nervous system (cANS) plays a key role in fetal maturation and can be assessed through fetal heart rate variability (fHRV)‐analysis, with each HRV parameter representing different aspects of cANS activity. Current available techniques, however, are unable to assess the fHRV parameters accurately throughout the whole pregnancy. This study aims to test the feasibility of color tissue Doppler imaging (cTDI) as a new ultrasound technique for HRV analysis. Secondly, we explored time trends of fHRV parameters using this technique.

Methods

18 healthy singleton fetuses were examined sequentially every 8 weeks from 10 weeks GA onwards. From each examination, 3 cTDI recordings of the four‐chamber view of 10 seconds were retrieved to determine accurate beat‐to‐beat intervals. The fHRV parameters SDNN, RMSSD, SDNN/RMSSD, and pNN10, each representing different functional aspects of the cANS, were measured, and time trends during pregnancy were explored using spline functions within a linear mixed‐effects model.

Results

In total, 77% (95% Cl 66–87%) of examinations were feasible for fHRV analysis from the first trimester onwards, which is a great improvement compared to other techniques. The technique is able to determine different maturation rates of the fHRV parameters, showing that cANS function, presumably parasympathetic activity, establishes around 20 weeks GA and matures rapidly until 30 weeks GA.

Conclusions

This is the first study able to assess cANS function through fHRV analysis from the first trimester onwards. The use of cTDI to determine beat‐to‐beat intervals seems feasible in just 3 clips of 10 seconds, which holds promise for future clinical use in assessing fetal well‐being.

Estimating Fetal Age by Fetal Maternal Heart Rate Coupling Parameters

Beat-by-beat maternal and fetal heart couplings were reported to be evident throughout the fetal development. However, it is still unknown whether maternal-fetal heartbeat coupling parameters are associated with fetal development, and the potential interrelationships. Therefore, this study aims to investigate the associations of coupling parameters with fetal gestational age by multivariate regression models. Ten min abdominal lead-based maternal and fetal ECG signals were collected from 16 healthy pregnant women with healthy singleton pregnancies (19-32 weeks). Maternal and Fetal Heart Rate Variability (MHRV and FHRV) values as well as maternal-fetal heart rate coupling (strength, measured by A) parameters at various coupling ratios (associated with different Maternal:Fetal heartbeat ratios of 1:2, 1:3, 2:3, 2:4, 3:4, and 3:5) were calculated. Based on those features stepwise multivariate regression models were constructed by validating against the gold standard gestational age identified by crown-rump length from doppler echocardiogram. Among all models, the best model (Root Mean Square Error, RMSE=1.92) was found to be significantly (p<0.05) associated with mean fetal heart rate, mean maternal heart rate, standard deviation of maternal heart rate, λ[1:3], λ[2:3], λ[2:4]. Correlation coefficients and Bland Altman plots were constructed to statistically validate the results. The model developed based on coupling parameters only, showed the second-best performance (RMSE=2.50). Therefore, combining maternal and fetal heart rate variability parameters with maternal-fetal heart rate coupling values (rather than considering FHRV or MHRV parameters only) is found to be better associated with fetal development.Clinical relevance- This is a brief additional statement on why this might be of interest to practicing clinicians. Example: This establishes the anesthetic efficacy of 10% intraosseous injections with epinephrine to positively influence cardiovascular function.

Fetal Heart Rate Variability Is Affected by Fetal Movements: A Systematic Review

Introduction: Fetal heart rate variability (FHRV) evaluates the fetal neurological state, which is poorly assessed by conventional prenatal surveillance including cardiotocography (CTG). Accurate FHRV on a beat-to-beat basis, assessed by time domain and spectral domain analyses, has shown promising results in the scope of fetal surveillance. However, accepted standards for these techniques are lacking, and the influence of fetal breathing movements and gross movements may be especially challenging. Thus, current standards for equivalent assessments in adults prescribe rest and controlled respiration. The aim of this review is to clarify the importance of fetal movements on FHRV. Methods: A systematic review in accordance with the PRISMA guidelines based on publications in the EMBASE, the MEDLINE, and the Cochrane Library databases was performed. Studies describing the impact of fetal movements on time domain, spectral domain and entropy analyses in healthy human fetuses were reviewed. Only studies based on fetal electrocardiography or fetal magnetocardiography were included. PROSPERO registration number: CRD42018068806. Results: In total, 14 observational studies were included. Fetal movement detection, signal processing, length, and selection of appropriate time series varied across studies. Despite these divergences, all studies showed an increase in overall FHRV in the moving fetus compared to the resting fetus. Especially short-term, vagal mediated indexes showed an increase during fetal breathing movements including an increase in Root Mean Square of the Successive Differences (RMSSD) and High Frequency power (HF) and a decrease in Low Frequency power/High Frequency power (LF/HF). These findings were present even in analyses restricted to one specific fetal behavioral state defined by Nijhuis. On the other hand, fetal body movements seemed to increase parameters supposed to represent the sympathetic response [LF and Standard Deviation of RR-intervals from normal sinus beats (SDNN)] proportionally more than parameters representing the parasympathetic response (RMSSD, HF). Results regarding entropy analyses were inconclusive. Conclusion: Time domain analyses as well as spectral domain analyses are affected by fetal movements. Fetal movements and especially breathing movements should be considered in these analyses of FHRV.

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.

Advanced automatic detection of fetal body movements from multichannel magnetocardiographic signals

OBJECTIVE

Both heart rate (HR) monitoring and detection and description of fetal movements provide essential information of the integrity of in utero development and fetal wellbeing. Our previously described method to identify movements from multichannel magnetocardiographic (MCG) recordings lacks of reliability in some cases. This work is aimed at the improvement of fetal movement detection by means of an advanced signal processing and validation strategy.

APPROACH

The previously proposed methodology of fetal body movement detection from MCG recordings using single space angle (SSA), min-max amplitude (MMA) and a measure of the overall signal strength across (RSS) was extended by moving correlation coefficient (MCC). The methodology was developed with respect to the discrimination between active and quiet sleep, validated by testing its coupling with HR accelerations in a total of 137 recordings lasting 30 min from 98 fetuses aged 34-38 weeks of gestation (WGA) of normal pregnancy.

MAIN RESULTS

The developed algorithm improves the reliable automatic detection of fetal body movements independent of the fetal sleep states and their changes in the individual MCG recordings. In the fetuses aged 34-38 WGA 94% of 15  ×  15 HR accelerations were coupled with detected movements. The visual inspection of the movement graphs of 30 fetuses aged 20-32 WGA supports the transferability of the movement detector to this age. In four subjects MCG-based movement detection and maternal report on percepted fetal movements were consistent.

SIGNIFICANCE

The presented methodology allows the parallel automatic acquisition of precise fetal heart rate variability (HRV) indices based on subsequent beat intervals and of fetal body movements from MCG recordings during late 2nd and 3rd trimester. Potential advantages of parallel monitoring of fetal HRV and movements using MCG compared to established ultrasound technology should be investigated in subsequent studies with respect to the identification of fetuses at risk.

Cardiotocography and beyond: a review of one-dimensional Doppler ultrasound application in fetal monitoring

One-dimensional Doppler ultrasound (1D-DUS) provides a low-cost and simple method for acquiring a rich signal for use in cardiovascular screening. However, despite the use of 1D-DUS in cardiotocography (CTG) for decades, there are still challenges that limit the effectiveness of its users in reducing fetal and neonatal morbidities and mortalities. This is partly due to the noisy, transient, complex and nonstationary nature of the 1D-DUS signals. Current challenges also include lack of efficient signal quality metrics, insufficient signal processing techniques for extraction of fetal heart rate and other vital parameters with adequate temporal resolution, and lack of appropriate clinical decision support for CTG and Doppler interpretation. Moreover, the almost complete lack of open research in both hardware and software in this field, as well as commercial pressures to market the much more expensive and difficult to use Doppler imaging devices, has hampered innovation. This paper reviews the basics of fetal cardiac function, 1D-DUS signal generation and processing, its application in fetal monitoring and assessment of fetal development and wellbeing. It also provides recommendations for future development of signal processing and modeling approaches, to improve the application of 1D-DUS in fetal monitoring, as well as the need for annotated open databases.

Developmental milestones of the autonomic nervous system revealed via longitudinal monitoring of fetal heart rate variability

BACKGROUND

Fetal heart rate variability (fHRV) of normal-to-normal (NN) beat intervals provides high-temporal resolution access to assess the functioning of the autonomic nervous system (ANS).

AIM

To determine critical periods of fetal autonomic maturation. The developmental pace is hypothesized to change with gestational age (GA).

STUDY DESIGN

Prospective longitudinal observational study.

SUBJECTS

60 healthy singleton fetuses were followed up by fetal magnetocardiographic heart rate monitoring 4-11 times (median 6) during the second half of gestation.

OUTCOME MEASURE

FHRV parameters, accounting for differential aspects of the ANS, were studied applying linear mixed models over four predefined pregnancy segments of interest (SoI: <27; 27+0-31+0; 31+1-35+0; >35+1 weeks GA). Periods of fetal active sleep and quiescence were accounted for separately.

RESULTS

Skewness of the NN interval distribution VLF/LF band power ratio and complexity describe a saturation function throughout the period of interest. A decreasing LF/HF ratio and an increase in pNN5 indicate a concurrent shift in sympathovagal balance. Fluctuation amplitude and parameters of short-term variability (RMSSD, HF band) mark a second acceleration towards term. In contrast, fetal quiescence is characterized by sequential, but low-margin transformations; ascending overall variability followed by an increase of complexity and superseded by fluctuation amplitude.

CONCLUSIONS

An increase in sympathetic activation, connected with by a higher ability of parasympathetic modulation and baseline stabilization, is reached during the transition from the late 2nd into the early 3rd trimester. Pattern characteristics indicating fetal well-being saturate at 35 weeks GA. Pronounced fetal breathing efforts near-term mirror in fHRV as respiratory sinus arrhythmia.

An antenatal marker of neurodevelopmental outcomes in infants with congenital heart disease

OBJECTIVE

Prenatal exposures are known to alter fetal neurodevelopment and autonomic control. We aimed to explore the correlation between fetal autonomic activity, measured by fetal heart rate variability, and 18-month developmental outcome in subjects with congenital heart disease.

STUDY DESIGN

From 2010 to 2013, 5 fetuses with hypoplastic left heart syndrome, 9 with transposition of the great arteries and 9 with tetralogy of Fallot were included in this prospective cohort study. A maternal abdominal fetal electrocardiogram monitor recorded fetal heart rate at 34 to 38 weeks gestational age. We assessed associations between fetal heart rate parameters including interquartile range and s.d. of the fetal RR intervals and 18-month Bayley Scales of Infant Development-III scores using Pearson's correlation coefficient. Multivariable regression modeling identified predictors of neurodevelopmental scores.

RESULTS

Fetal heart rate variability parameters at 34 to 38 weeks gestational age correlated with 18-month Cognition (r=0.47, P=0.03) and Motor scores (r=0.66, P=0.001). The interquartile range of the fetal RR intervals predicted Cognition (β=0.462, P=0.028, R2=0.282) and Motor (β=0.637, P<0.001, R2=0.542) scores.

CONCLUSIONS

In fetuses with congenital heart disease, low heart rate variability at 34 to 38 weeks gestational age predicts diminished 18-month Cognitive and Motor performance. Prenatal autonomic activity may serve as a marker of early childhood development in these high-risk patients.

Assessment of Fetal Development Using Cardiac Valve Intervals

An automated method to assess the fetal physiological development is introduced which uses the component intervals between fetal cardiac valve timings and the Q-wave of fetal electrocardiogram (fECG). These intervals were estimated automatically from one-dimensional Doppler Ultrasound and noninvasive fECG. We hypothesize that the fetal growth can be estimated by the cardiac valve intervals. This hypothesis was evaluated by modeling the fetal development using the cardiac intervals and validating against the gold standard gestational age identified by Crown-Rump Length (CRL). Among the intervals, electromechanical delay time, isovolumic contraction time, ventricular filling time and their interactions were selected in a stepwise regression process that used gestational age as the target in a cohort of 57 fetuses. Compared with the gold standard age, the newly proposed regression model resulted in a mean absolute error of 3.8 weeks for all recordings and 2.7 weeks after excluding the low quality recordings. Since Fetal Heart Rate Variability (FHRV) has been proposed in the literature for assessing the fetal development, we compared the performance of gestational age estimation by our new valve-interval based method, vs. FHRV, while assuming the CRL as the gold standard. The valve interval-based method outperformed both the model based on FHRV. Results of evaluation for 30 abnormal cases showed that the new method is less affected by arrhythmias such as tachycardia and bradycardia compared to FHRV, however certain types of heart anomalies cause large errors (more than 10 weeks) with respect to the CRL-based gold standard age. Therefore, discrepancies between the regression based estimation and CRL age estimation could indicate the abnormalities. The cardiac valve intervals have been known to reflect the autonomic function. Therefore the new method potentially provides a novel approach for assessing the development of fetal autonomic nervous system, which may be growth curve independent.

Monitoring fetal maturation-objectives, techniques and indices of autonomic function

Monitoring the fetal behavior does not only have implications for acute care but also for identifying developmental disturbances that burden the entire later life. The concept, of 'fetal programming', also known as 'developmental origins of adult disease hypothesis', e.g. applies for cardiovascular, metabolic, hyperkinetic, cognitive disorders. Since the autonomic nervous system is involved in all of those systems, cardiac autonomic control may provide relevant functional diagnostic and prognostic information. The fetal heart rate patterns (HRP) are one of the few functional signals in the prenatal period that relate to autonomic control and, therefore, is predestinated for its evaluation. The development of sensitive markers of fetal maturation and its disturbances requires the consideration of physiological fundamentals, recording technology and HRP parameters of autonomic control. Based on the ESGCO2016 special session on monitoring the fetal maturation we herein report the most recent results on: (i) functional fetal autonomic brain age score (fABAS), Recurrence Quantitative Analysis and Binary Symbolic Dynamics of complex HRP resolve specific maturation periods, (ii) magnetocardiography (MCG) based fABAS was validated for cardiotocography (CTG), (iii) 30 min recordings are sufficient for obtaining episodes of high variability, important for intrauterine growth restriction (IUGR) detection in handheld Doppler, (iv) novel parameters from PRSA to identify Intra IUGR fetuses, (v) evaluation of fetal electrocardiographic (ECG) recordings, (vi) correlation between maternal and fetal HRV is disturbed in pre-eclampsia. The reported novel developments significantly extend the possibilities for the established CTG methodology. Novel HRP indices improve the accuracy of assessment due to their more appropriate consideration of complex autonomic processes across the recording technologies (CTG, handheld Doppler, MCG, ECG). The ultimate objective is their dissemination into routine practice and studies of fetal developmental disturbances with implications for programming of adult diseases.

Frequency and Time Domain Analysis of Foetal Heart Rate Variability with Traditional Indexes: A Critical Survey

Monitoring of foetal heart rate and its variability (FHRV) covers an important role in assessing health of foetus. Many analysis methods have been used to get quantitative measures of FHRV. FHRV has been studied in time and in frequency domain and interesting clinical results have been obtained. Nevertheless, a standardized definition of FHRV and a precise methodology to be used for its evaluation are lacking. We carried out a literature overview about both frequency domain analysis (FDA) and time domain analysis (TDA). Then, by using simulated FHR signals, we defined the methodology for FDA. Further, employing more than 400 real FHR signals, we analysed some of the most common indexes, Short Term Variability for TDA and power content of the spectrum bands and sympathovagal balance for FDA, and evaluated their ranges of values, which in many cases are a novelty. Finally, we verified the relationship between these indexes and two important parameters: week of gestation, indicator of foetal growth, and foetal state, classified as active or at rest. Our results indicate that, according to literature, it is necessary to standardize the procedure for FHRV evaluation and to consider week of gestation and foetal state before FHR analysis.

Postnatal Cardiac Autonomic Nervous Control in Pediatric Congenital Heart Disease

Congenital heart disease is the most common congenital defect. During childhood, survival is generally good but, in adulthood, late complications are not uncommon. Abnormal autonomic control in children with congenital heart disease may contribute considerably to the pathophysiology of these long term sequelae. This narrative review of 34 studies aims to summarize current knowledge on function of the autonomic nervous system in children with a congenital heart defect. Large scale studies that measure both branches of the nervous system for prolonged periods of time in well-defined patient cohorts in various phases of childhood and adolescence are currently lacking. Pending such studies, there is not yet a good grasp on the extent and direction of sympathetic and parasympathetic autonomic function in pediatric congenital heart disease. Longitudinal studies in homogenous patient groups linking autonomic nervous system function and clinical outcome are warranted.

Assessment of fetal maturation age by heart rate variability measures using random forest methodology

Fetal maturation age assessment based on heart rate variability (HRV) is a predestinated tool in prenatal diagnosis. To date, almost linear maturation characteristic curves are used in univariate and multivariate models. Models using complex multivariate maturation characteristic curves are pending. To address this problem, we use Random Forest (RF) to assess fetal maturation age and compare RF with linear, multivariate age regression. We include previously developed HRV indices such as traditional time and frequency domain indices and complexity indices of multiple scales. We found that fetal maturation was best assessed by complexity indices of short scales and skewness in state-dependent datasets (quiet sleep, active sleep) as well as in state-independent recordings. Additionally, increasing fluctuation amplitude contributed to the model in the active sleep state. None of the traditional linear HRV parameters contributed to the RF models. Compared to linear, multivariate regression, the mean prediction of gestational age (GA) is more accurate with RF than in linear, multivariate regression (quiet state: R(2)=0,617 vs. R(2)=0,461, active state: R(2)=0,521 vs. R(2)=0,436, state independent: R(2)=0,583 vs. R(2)=0,548). We conclude that classification and regression tree models such as RF methodology are appropriate for the evaluation of fetal maturation age. The decisive role of adjustments between different time scales of complexity may essentially extend previous analysis concepts mainly based on rhythms and univariate complexity indices. Those system characteristics may have implication for better understanding and accessibility of the maturating complex autonomic control and its disturbance.

Validation of functional fetal autonomic brain age score fABAS in 5 min short recordings

With the objective of evaluating the functional maturation age and developmental disturbances we have previously introduced the fetal autonomic brain age score (fABAS) using 30 min fetal magnetocardiographic recordings (fMCG, Jena). The score is based on heart rate pattern indices that are related to universal principles of developmental biology. The present work aims at the validation of the fABAS methodology on 5 min recordings from an independent database (fMCG, Bochum).We found high agreement of fABAS obtained from Jena normal fetuses (5 min subsets, n =  364) and Bochum recordings (n =  322, normal fetuses). fABAS of 48 recordings from fetuses with intra-uterine growth restriction (IUGR, Bochum) was reduced in most of the cases, a result consistent with IUGR fetuses from Jena previously reported. fABAS calculated from 5 min snapshots only partly covers the accuracy when compared to fABAS from 30 min recordings. More precise diagnosis requires longer recordings.fABAS obtained from fMCG recordings is a strong candidate for standardized assessment of functional maturation age and developmental disturbances. Even 5 min recordings seem to be valuable for screening for maturation problems.

Formation of functional associations across time scales in the fetal autonomic control system--a multifractal analysis

During fetal development, different control systems mediated by the autonomic nervous system form functional connections over a wide range of time scales. Using multiscale multifractal analysis (MMA) of fetal heart rate variability (HRV), we describe fundamental relationships in the developing scale-wide adjustments within fetal behavior states as well as across state changes. MMA yields the local Hurst exponent surface h(q,s) with q as the multifractal parameter and s as the scale. In 30-minute recordings of healthy fetuses between 24 and 36weeks of gestation (n=25 in quiet sleep, n=29 in active sleep, n=30 changing sleep state) we investigated the dependency of h(q,s) on gestation age. In univariate models, we found a decreasing persistence for short scales and small amplitudes in the quiet (s1=39, q1=-0.7, R(2)=0.52) and in the active (s1=69, q1=-1.4, R(2)=0.23) sleep in contrast to an increasing persistency for long scales and large amplitudes (s1=147, q1=2.4, R(2)=0.29) in the mixed state. Bivariate models (additional scales considered) presented increased coefficients of determination R(2)=0.56, 0.4, and 0.43, respectively. Persistency increasing with age in connection with the sleep state changes (independent of the age related short range dependencies within the separate homogeneous sleep states) is reported here for the first time. The MMA indices obtained for the fetal HRV represent characteristics of the maturating scale-wide cardiovascular control in the context of the evolving sleep state dynamics, which have so far not been considered. They should be incorporated in the search for HRV indices for prenatal diagnosis of developmental disorders and risk assessment.

Autonomic regulation in fetuses with congenital heart disease

BACKGROUND

Exposure to antenatal stressors affects autonomic regulation in fetuses. Whether the presence of congenital heart disease (CHD) alters the developmental trajectory of autonomic regulation is not known.

AIMS/STUDY DESIGN

This prospective observational cohort study aimed to further characterize autonomic regulation in fetuses with CHD; specifically hypoplastic left heart syndrome (HLHS), transposition of the great arteries (TGA), and tetralogy of Fallot (TOF).

SUBJECTS

From 11/2010 to 11/2012, 92 fetuses were enrolled: 41 controls and 51 with CHD consisting of 19 with HLHS, 12 with TGA, and 20 with TOF. Maternal abdominal fetal electrocardiogram (ECG) recordings were obtained at 3 gestational ages: 19-27 weeks (F1), 28-33 weeks (F2), and 34-38 weeks (F3).

OUTCOME MEASURES

Fetal ECG was analyzed for mean heart rate along with 3 measures of autonomic variability of the fetal heart rate: interquartile range, standard deviation, and root mean square of the standard deviation of the heart rate (RMSSD), a measure of parasympathetic activity.

RESULTS

During F1 and F2 periods, HLHS fetuses demonstrated significantly lower mean HR than controls (p<0.05). Heart rate variability at F3, as measured by standard deviation, interquartile range, and RMSSD was lower in HLHS than controls (p<0.05). Other CHD subgroups showed a similar, though non-significant trend towards lower variability.

CONCLUSIONS

Autonomic regulation in CHD fetuses differs from controls, with HLHS fetuses most markedly affected.

Strategies of symbolization in cardiovascular time series to test individual gestational development in the fetus

The analysis of symbolic dynamics applied to physiological time series retrieves dynamical properties of the underlying regulation which are robust against the symbolic transformation. In this study, three different transformations to produce a symbolic series were applied to fetal RR interval series to test whether they reflect individual changes of fetal heart rate variability in the course of pregnancy. Each transformation was applied to 215 heartbeat datasets obtained from 11 fetuses during the second and the third trimester of pregnancy (at least 10 datasets per fetus, median 17). In the symbolic series, the occurrence of symbolic sequences of length 3 was categorized according to the amount of variations in the sequence: no variation of the symbols, one variation, two variations. Linear regression with respect to gestational age showed that the individual course during pregnancy performed best using a binary transformation reflecting whether the RR interval differences are below or above a threshold. The median goodness of fit of the individual regression lines was 0.73 and also the variability among the individual slopes was low. Other transformations to symbolic dynamics performed worse but were still able to reflect the individual progress of fetal cardiovascular regulation.

Fetal autonomic brain age scores, segmented heart rate variability analysis, and traditional short term variability

Disturbances of fetal autonomic brain development can be evaluated from fetal heart rate patterns (HRP) reflecting the activity of the autonomic nervous system. Although HRP analysis from cardiotocographic (CTG) recordings is established for fetal surveillance, temporal resolution is low. Fetal magnetocardiography (MCG), however, provides stable continuous recordings at a higher temporal resolution combined with a more precise heart rate variability (HRV) analysis. A direct comparison of CTG and MCG based HRV analysis is pending. The aims of the present study are: (i) to compare the fetal maturation age predicting value of the MCG based fetal Autonomic Brain Age Score (fABAS) approach with that of CTG based Dawes-Redman methodology; and (ii) to elaborate fABAS methodology by segmentation according to fetal behavioral states and HRP. We investigated MCG recordings from 418 normal fetuses, aged between 21 and 40 weeks of gestation. In linear regression models we obtained an age predicting value of CTG compatible short term variability (STV) of R (2) = 0.200 (coefficient of determination) in contrast to MCG/fABAS related multivariate models with R (2) = 0.648 in 30 min recordings, R (2) = 0.610 in active sleep segments of 10 min, and R (2) = 0.626 in quiet sleep segments of 10 min. Additionally segmented analysis under particular exclusion of accelerations (AC) and decelerations (DC) in quiet sleep resulted in a novel multivariate model with R (2) = 0.706. According to our results, fMCG based fABAS may provide a promising tool for the estimation of fetal autonomic brain age. Beside other traditional and novel HRV indices as possible indicators of developmental disturbances, the establishment of a fABAS score normogram may represent a specific reference. The present results are intended to contribute to further exploration and validation using independent data sets and multicenter research structures.

Developing fetal motor-cardiovascular coordination analyzed from multi-channel magnetocardiography

Fetal movements (FM) related heart rate accelerations (AC) are an important maturation criterion. Since Doppler-based time resolution is not sufficient for accompanying heart rate variability analysis, the work is aimed at a comprehensive FM-AC analysis using magnetocardiographic recordings from fetuses during sleep.We identify FM and AC by independent component analysis and automatic recognition algorithms. We investigate associations between FM and AC of different magnitude by means of event coincidence and time series cross-correlation over the maturation period of 21-40 weeks of gestation (WGA).FM related AC appear with increasing AC magnitude and WGA. Vice versa, AC related FM appear independent of WGA, but more frequently with increasing AC amplitude. The FM-AC correlation exists already at 21 WGA and further increases with WGA while the variability of its time delay decreases. Hence, FM and AC are clearly associated over the whole investigated maturation period. The increase of FM related AC runs parallel to the increasing AC magnitude.The MCG methodology was confirmed and results from previous Doppler-based analyses reproduced. Hence, MCG recordings allow the collective analysis of heart rate variability based maturation indices and FM related AC. This synergism may improve the diagnosis of fetal developmental disorders.

Fetal functional brain age assessed from universal developmental indices obtained from neuro-vegetative activity patterns

Fetal brain development involves the development of the neuro-vegetative (autonomic) control that is mediated by the autonomic nervous system (ANS). Disturbances of the fetal brain development have implications for diseases in later postnatal life. In that context, the fetal functional brain age can be altered. Universal principles of developmental biology applied to patterns of autonomic control may allow a functional age assessment. The work aims at the development of a fetal autonomic brain age score (fABAS) based on heart rate patterns. We analysed n = 113 recordings in quiet sleep, n = 286 in active sleep, and n = 29 in active awakeness from normals. We estimated fABAS from magnetocardiographic recordings (21.4–40.3 weeks of gestation) preclassified in quiet sleep (n = 113, 63 females) and active sleep (n = 286, 145 females) state by cross-validated multivariate linear regression models in a cross-sectional study. According to universal system developmental principles, we included indices that address increasing fluctuation range, increasing complexity, and pattern formation (skewness, power spectral ratio VLF/LF, pNN5). The resulting models constituted fABAS. fABAS explained 66/63% (coefficient of determination R² of training and validation set) of the variance by age in quiet, while 51/50% in active sleep. By means of a logistic regression model using fluctuation range and fetal age, quiet and active sleep were automatically reclassified (94.3/93.1% correct classifications). We did not find relevant gender differences. We conclude that functional brain age can be assessed based on universal developmental indices obtained from autonomic control patterns. fABAS reflect normal complex functional brain maturation. The presented normative data are supplemented by an explorative study of 19 fetuses compromised by intrauterine growth restriction. We observed a shift in the state distribution towards active awakeness. The lower WGA dependent fABAS values found in active sleep may reflect alterations in the universal developmental indices, namely fluctuation amplitude, complexity, and pattern formation that constitute fABAS.

Development of multiscale complexity and multifractality of fetal heart rate variability

During fetal development a complex system grows and coordination over multiple time scales is formed towards an integrated behavior of the organism. Since essential cardiovascular and associated coordination is mediated by the autonomic nervous system (ANS) and the ANS activity is reflected in recordable heart rate patterns, multiscale heart rate analysis is a tool predestined for the diagnosis of prenatal maturation. The analyses over multiple time scales requires sufficiently long data sets while the recordings of fetal heart rate as well as the behavioral states studied are themselves short. Care must be taken that the analysis methods used are appropriate for short data lengths. We investigated multiscale entropy and multifractal scaling exponents from 30 minute recordings of 27 normal fetuses, aged between 23 and 38 weeks of gestational age (WGA) during the quiet state. In multiscale entropy, we found complexity lower than that of non-correlated white noise over all 20 coarse graining time scales investigated. Significant maturation age related complexity increase was strongest expressed at scale 2, both using sample entropy and generalized mutual information as complexity estimates. Multiscale multifractal analysis (MMA) in which the Hurst surface h(q,s) is calculated, where q is the multifractal parameter and s is the scale, was applied to the fetal heart rate data. MMA is a method derived from detrended fluctuation analysis (DFA). We modified the base algorithm of MMA to be applicable for short time series analysis using overlapping data windows and a reduction of the scale range. We looked for such q and s for which the Hurst exponent h(q,s) is most correlated with gestational age. We used this value of the Hurst exponent to predict the gestational age based only on fetal heart rate variability properties. Comparison with the true age of the fetus gave satisfying results (error 2.17±3.29 weeks; p<0.001; R(2)=0.52). In addition, we found that the normally used DFA scale range is non-optimal for fetal age evaluation. We conclude that 30 min recordings are appropriate and sufficient for assessing fetal age by multiscale entropy and multiscale multifractal analysis. The predominant prognostic role of scale 2 heart beats for MSE and scale 39 heart beats (at q=-0.7) for MMA cannot be explored neither by single scale complexity measures nor by standard detrended fluctuation analysis.

Fetal development of complex autonomic control evaluated from multiscale heart rate patterns

Development of the fetal autonomic nervous system's integrative capacity in relation to gestational age and emerging behavioral pattern is reflected in fetal heart rate patterns. Conventional indices of vagal and sympathetic rhythms cannot sufficiently reflect their complex interrelationship. Universal behavioral indices of developing complex systems may provide additional information regarding the maturating complex autonomic control. We investigated fetal magnetocardiographic recordings undertaken at 10-min intervals in active (n = 248) and quiet (n = 111) states between 22 and 39 wk gestational age. Standard deviation of heartbeat intervals, skewness, contribution of particular rhythms to the total power, and multiscale entropy were analyzed. The multiscale entropy methodology was validated for 10-min data sets. Age dependence was analyzed by linear regression. In the quiet state, contribution of sympathovagal rhythms and their complexity over a range of corresponding short scales increased with rising age, and skewness shifted from negative to positive values. In the active state, age dependencies were weaker. Skewness as the strongest parameter shifted in the same direction. Fluctuation amplitude and the complexity of scales associated with sympathovagal rhythms increased. We conclude that in the quiet state, stable complex organized rhythms develop. In the active state, however, increasing behavioral variability due to multiple internal coordinations, such as movement-related heart rate accelerations, and external influences develop. Hence, the state-selective assessment in association with developmental indices used herein may substantially improve evaluation of maturation age and early detection and interpretation of developmental problems in prenatal diagnosis.

Linear and nonlinear measures of fetal heart rate patterns evaluated on very short fetal magnetocardiograms

We analyzed the effectiveness of linear short- and long-term variability time domain parameters, an index of sympatho-vagal balance (SDNN/RMSSD) and entropy in differentiating fetal heart rate patterns (fHRPs) on the fetal heart rate (fHR) series of 5, 3 and 2 min duration reconstructed from 46 fetal magnetocardiograms. Gestational age (GA) varied from 21 to 38 weeks. FHRPs were classified based on the fHR standard deviation. In sleep states, we observed that vagal influence increased with GA, and entropy significantly increased (decreased) with GA (SDNN/RMSSD), demonstrating that a prevalence of vagal activity with autonomous nervous system maturation may be associated with increased sleep state complexity. In active wakefulness, we observed a significant negative (positive) correlation of short-term (long-term) variability parameters with SDNN/RMSSD. ANOVA statistics demonstrated that long-term irregularity and standard deviation of normal-to-normal beat intervals (SDNN) best differentiated among fHRPs. Our results confirm that short- and long-term variability parameters are useful to differentiate between quiet and active states, and that entropy improves the characterization of sleep states. All measures differentiated fHRPs more effectively on very short HR series, as a result of the fMCG high temporal resolution and of the intrinsic timescales of the events that originate the different fHRPs.

Multi-scale characteristics of resampled fetal heart rate pattern provide novel fetal developmental indices

The increasing functional integrity of the organism during fetal maturation is connected with increasing complex internal coordination mediated by the autonomic nervous system. We hypothesize that time scales of complex and dynamic inter-dependencies over more than one heart beat interval reflect the increasing complex adjustments within the fetal organism during its prenatal development. We investigated multi-scale complexity and time irreversibility from equidistantly resampled heart rate time series of 73 fetal magnetocardiographic recordings over the third trimester. We found scale dependent changes in complexity and time irreversibility. The functions obtained from equidistantly resampled heart rate time series showed qualitatively similar curves compared to those obtained from heart beat intervals series previously reported. Time scales of fetal heart rate characteristics may provide novel information for the identification of developmental disorders in prenatal diagnosis.

Fetal development assessed by heart rate patterns--time scales of complex autonomic control

The increasing functional integrity of the organism during fetal maturation is connected with increasing complex internal coordination. We hypothesize that time scales of complexity and dynamics of heart rate patterns reflect the increasing inter-dependencies within the fetal organism during its prenatal development. We investigated multi-scale complexity, time irreversibility and fractal scaling from 73 fetal magnetocardiographic 30min recordings over the third trimester. We found different scale dependent complexity changes, increasing medium scale time irreversibility, and increasing long scale fractal correlations (all changes p<0.05). The results confirm the importance of time scales to be considered in fetal heart rate based developmental indices.

The effect of antenatal steroid treatment on fetal autonomic heart rate regulation revealed by fetal magnetocardiography (fMCG)

BACKGROUND

Steroid administration to accelerate fetal lung maturation reduces neonatal morbidity and mortality in the case of preterm delivery. Behavioral observations suggest effects on fetal cardiovascular regulation.

AIM

We hypothesize that beat to beat heart rate variability (fHRV) derived from fetal magnetocardiography (fMCG) will reveal a direct, acute steroidal effect on fetal autonomic heart rate regulation.

SUBJECTS

Eight patients between 29 and 34 weeks of gestation at risk for preterm birth who were treated with betamethasone (2x12 mg within 24 h).

STUDY DESIGN

Subjects were studied prior to the first and within 6 h after the second administration. Continuous fMCG was recorded with a 31-channel-SQUID biomagnetometer. Each dataset was processed by subtracting maternal cardiac artefacts and determining the time instants of the fetal heart beats. fHRV analysis was applied to periods of fetal quiescence of 4 min length.

OUTCOME MEASURES

We compared fHRV prior versus post steroid administration.

RESULTS

Steroid exposure reduced all parameters of overall fHRV significantly. The fHRV parameters representing short term variability remained unaffected. Mean fetal heart rate significantly decreased. The complexity of the heart rate patterns increased.

CONCLUSION

Our results suggest an acute shift in the sympatho-vagal balance of fetuses exposed to betamethasone in utero toward sympathetic suppression.