Functional brain development in growth-restricted and constitutionally small fetuses: a fetal magnetoencephalography case-control study

Evaluation of parameters for fetal behavioural state classification

Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate. Automatic state detection through algorithms relies on different parameters and thresholds derived from both the heart rate variability (HRV) and the actogram, which are highly dependent on the specific datasets and are prone to artefacts. Furthermore, the development of the fetal states is dynamic over the gestational period and the evaluation usually only separated into early and late gestation (before and after 32 weeks). In the current work, fBS detection was consistent between the classification algorithm and visual inspection in 87 fetal magnetocardiographic data segments between 27 and 39 weeks of gestational age. To identify how automated fBS detection could be improved, we first identified commonly used parameters for fBS classification in both the HRV and the actogram, and investigated their distribution across the different fBS. Then, we calculated a receiver operating characteristics (ROC) curve to determine the performance of each parameter in the fBS classification. Finally, we investigated the development of parameters over gestation through linear regression. As a result, the parameters derived from the HRV have a higher classification accuracy compared to those derived from the body movement as defined by the actogram. However, the overlapping distributions of several parameters across states limit a clear separation of states based on these parameters. The changes over gestation of the HRV parameters reflect the maturation of the fetal autonomic nervous system. Given the higher classification accuracy of the HRV in comparison to the actogram, we suggest to focus further research on the HRV. Furthermore, we propose to develop probabilistic fBS classification approaches to improve classification in less prototypical datasets.

Neurodevelopmental Outcome of Preterm Newborns with Abnormal Umbilical Artery Doppler - A Prospective Cohort Study

OBJECTIVE

To assess the neurodevelopmental outcome of preterm neonates with absent/reversed end diastolic flow (A/REDF) in umbilical artery Doppler at 1 year of corrected age.

METHODS

A cohort of 70 preterm newborns with fetal growth restriction (FGR), defined as estimated fetal weight (EFW) <10th centile, confirmed by birthweight <10th centile, along with A/REDF in the umbilical artery Doppler was followed up till 1 year of corrected age (CA). An equal number of gestation and gender matched preterm newborns with birthweight >10th centile [appropriate for gestational age (AGA)] and normal antenatal ultrasound were taken as controls. Primary outcome was a composite of death or major neurodevelopmental disability (NDD) at 1 year of corrected age. Matched analysis was performed.

RESULTS

A total of 140 newborns were enrolled, of which, 20 expired and 8 were lost to follow-up. The primary outcome (death/major NDD) occurred in 26.8% of the FGR (A/REDF) newborns as compared to 9.3% of their AGA counterparts (RR-2.83, p = 0.02, 95% CI:1.11-7.18). Mean motor quotient in Development Assessment Scale for Indian Infants (DASII) at 1 year of corrected age was significantly lower in FGR (A/REDF) infants (91 ± 13.6 vs. 96.3 ± 7.1, p < 0.05). Multiple other co-morbidities were also significantly more among these newborns.

CONCLUSIONS

Preterm newborns with FGR and A/REDF are at significantly increased risk of death/major NDD at 1 year of corrected age.

Back to basics: the neuronal substrates and mechanisms that underlie the electroencephalogram in premature neonates

Electroencephalography is the only clinically available technique that can address the premature neonate normal and pathological functional development week after week. The changes in the electroencephalogram (EEG) result from gradual structural and functional modifications that arise during the last trimester of pregnancy. Here, we review the structural changes over time that underlie the establishment of functional immature neural networks, the impact of certain anatomical specificities (fontanelles, connectivity, etc.) on the EEG, limitations in EEG interpretation, and the utility of high-resolution EEG (HR-EEG) in premature newborns (a promising technique with a high degree of spatiotemporal resolution). In particular, we classify EEG features according to whether they are manifestations of endogenous generators (i.e. theta activities that coalesce with a slow wave or delta brushes) or come from a broader network. Furthermore, we review publications on EEG in premature animals because the data provide a better understanding of what is happening in premature newborns. We then discuss the results and limitations of functional connectivity analyses in premature newborns. Lastly, we report on the magnetoelectroencephalographic studies of brain activity in the fetus. A better understanding of complex interactions at various structural and functional levels during normal neurodevelopment (as assessed using electroencephalography as a benchmark method) might lead to better clinical care and monitoring for premature neonates.

A pilot study: Auditory steady-state responses (ASSR) can be measured in human fetuses using fetal magnetoencephalography (fMEG)

Background

Auditory steady-state responses (ASSRs) are ongoing evoked brain responses to continuous auditory stimuli that play a role for auditory processing of complex sounds and speech perception. Transient auditory event-related responses (AERRs) have previously been recorded using fetal magnetoencephalography (fMEG) but involve different neurological pathways. Previous studies in children and adults demonstrated that the cortical components of the ASSR are significantly affected by state of consciousness and by maturational changes in neonates and young infants. To our knowledge, this is the first study to investigate ASSRs in human fetuses.

Methods

47 fMEG sessions were conducted with 24 healthy pregnant women in three gestational age groups (30–32 weeks, 33–35 weeks and 36–39 weeks). The stimulation consisted of amplitude-modulated (AM) tones with a duration of one second, a carrier frequency (CF) of 500 Hz and a modulation frequency (MF) of 27 Hz or 42 Hz. Both tones were presented in a random order with equal probability adding up to 80–100 repetitions per tone. The ASSR across trials was quantified by assessing phase synchrony in the cortical signals at the stimulation frequency.

Results and conclusion

Ten out of 47 recordings were excluded due to technical problems or maternal movements. Analysis of the included 37 fetal recordings revealed a statistically significant response for the phase coherence between trials for the MF of 27 Hz but not for 42 Hz. An exploratory subgroup analysis moreover suggested an advantage in detectability for fetal behavioral state 2F (active asleep) compared to 1F (quiet asleep) detected using fetal heart rate. In conclusion, this pilot study is the first description of a method to detect human ASSRs in fetuses. The findings warrant further investigations of the developing fetal brain.

Tracking evoked responses to auditory and visual stimuli in fetuses exposed to maternal high-risk conditions

Magnetoencephalography (MEG) has been successfully applied to record fetal auditory (auditory evoked response [AER]) and visual evoked responses (VER). In this study, we report the AER and VER development trajectory by tracking the evoked response detectability and latency from recordings starting at 27 weeks of gestation in pregnancies classified as high risk. Fetal MEG and ultrasound recordings were performed on 158 pregnant women, and the total number of fetal auditory and visual tests conducted was 321 and 237, respectively. The overall evoked response analysis showed 237 AER (73.8%) and 164 VER detections (69.2%). The mean AER latency was 290.7 (SD 125.5) ms and the mean VER latency was 293.7 (SD 114.5) ms. The rate of decrease (95% confidence limits) in average AER and VER first-peak latency between 100-350 ms was 1.97 (-1.86, +5.81) ms/week and 1.35 (-3.83, +6.53) ms/week, respectively. This trend in high-risk fetuses conforms to the general trajectory of decrease in latency with gestational age progression, even though this decrease was non-significant, as reported in the case of normal growing fetuses. Although there was a significant difference in detection rates between male and female fetuses, this was not reflected in either latency values or the sensory modality applied. Furthermore, the main factors that had the most significant effect on response detectability included the presence of intervening layers of adipose tissue between the fetal head and stimulus source and an increase in the maternal body mass index.

Development of Brain Networks In Utero: Relevance for Common Neural Disorders

Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.

Automated Detection of Fetal Brain Signals with Principal Component Analysis

Detection of fetal brain signals in fetal magnetoencephalographic recordings is - due to the low signal to noise ratio - challenging for researchers in this field. Up to now, state of the art is a manual evaluation of the signal. To make the evaluation more reproducible and less time consuming, an approach using Principal Component Analysis is introduced. Locations of the channels of most importance for the first three principal components are taken into account and their possibility of resembling brain activity evaluated. Data with auditory stimulation are taken for this analysis and trigger averaged signals from the channels selected as brain activity (manually & automatically) compared. Comparisons are done with regard to their average baseline activity, activity during a window of interest and timing and amplitude of their highest auditory event-related peak. The number of evaluable data sets showed to be lower for the automated compared to manual approach but auditory event-related peaks did not differ significantly in amplitude or timing and in both cases there was a significant activity change following the tone event. The given results and the advantage of reproducibility make this method a valid alternative.

Evaluating Complexity of Fetal MEG Signals: A Comparison of Different Metrics and Their Applicability

In this work, we aim to investigate whether information based metrics of neural activity are a useful tool for the quantification of consciousness before and shortly after birth. Neural activity is measured using fetal magnetoencephalography (fMEG) in human fetuses and neonates. Based on recent theories on consciousness, information-based metrics are established to measure brain complexity and to assess different levels of consciousness. Different metrics (measures of entropy, compressibility and fractality) are, thus, explored in a reference population and their usability is evaluated. For comparative analysis, two fMEG channels were selected: one where brain activity was previously detected and one at least 15 cm away, that represented a control channel. The usability of each metric was evaluated and results from the brain and control channel were compared. Concerning the ease of use with fMEG data, Lempel-Ziv-Complexity (LZC) was evaluated as best, as it is unequivocal and needs low computational effort. The fractality measures have a high number of parameters that need to be adjusted prior to analysis and therefore forfeit comparability, while entropy measures require a higher computational effort and more parameters to adjust compared to LZC. Comparison of a channel with brain activity and a control channel in neonatal recordings showed significant differences in most complexity metrics. This clear difference can be seen as proof of concept for the usability of complexity metrics in fMEG. For fetal data, this comparison produced less clear results which can be related to leftover maternal signals included in the control channel. Further work is necessary to conclusively interpret results from the analysis of fetal recordings. Yet this study shows that complexity metrics can be used for fMEG data on early consciousness and the evaluation gives a guidance for future work. The inconsistency of results from different metrics highlights the challenges of working with complexity metrics as neural correlates of consciousness, as well as the caution one should apply to interpret them.

Impact of Intrauterine Growth Restriction on Cognitive and Motor Development at 2 Years of Age

Intrauterine growth restriction (IUGR), which is already known to be a risk factor for pathological intrauterine development, perinatal mortality, and morbidity, is now also assumed to cause both physical and cognitive alterations in later child development. In the current study, effects of IUGR on infantile brain function were investigated during the fetal period and in a follow-up developmental assessment during early childhood. During the fetal period, visual and auditory event-related responses (VER and AER) were recorded using fetal magnetoencephalography (fMEG). VER latencies were analyzed in 73 fetuses (14 IUGR fetuses) while AER latencies were analyzed in 66 fetuses (11 IUGR fetuses). Bayley Scales of Infant Development, Second Edition (BSID-II) were used to assess the developmental status of the infants at the age of 24 months. The Mental Development Index (MDI) was available from 66 children (8 IUGR fetuses) and the Psychomotor Development Index (PDI) from 63 children (7 IUGR fetuses). Latencies to visual stimulation were more delayed in IUGR than in small for gestational age (SGA) or appropriate for gestational age (AGA) fetuses, albeit not to any significant extent (p = 0.282). The MDI in former IUGR infants was significantly lower (p = 0.044) than in former SGA and AGA infants. However, IUGR had no impact on PDI (p = 0.213). These findings support the hypothesis that IUGR may constitute a risk factor for neurodevelopmental delay. Further investigation of the possible underlying mechanisms, as well as continued long-term developmental research, is therefore necessary.

Family History of Diabetes Is Associated With Delayed Fetal Postprandial Brain Activity

Introduction: We have previously shown that fetuses of mothers with gestational diabetes mellitus (GDM) and insulin resistance exhibit a prolongation of fetal auditory event-related brain responses (fAER) compared to fetuses of normal glucose tolerant women during an oral glucose tolerance test (oGTT). This implies that maternal metabolism may program the developing fetal brain. We now asked whether a family history of type 2 diabetes without metabolic programing also impacts fetal brain activity. We therefore investigated brain activity in fetuses of normal glucose tolerant mothers with and without family history of type 2 diabetes (FHD+ and FHD-). Methods: A 75 g oGTT was performed in healthy pregnant women. Plasma glucose and insulin levels were measured after 0, 60, and 120 min. Each blood draw was preceded by fetal magnetoencephalographic (fMEG) recordings of fAER. From a group of 167 participants, a subsample of 52 metabolically healthy women, 37 with a negative, and 15 with a positive FHD (at least one first- or second-degree relative) was carefully selected based on the following inclusion criteria: inconspicuous pregnancy, no GDM, BMI 18.5-30 kg/m², no preterm birth and at least two fMEG with detectable fetal responses during oGTT. Results: An ANOVA showed a significant interaction between fMEG measurement time during the oGTT and FHD on fAER latency [F ₍₂₎ = 4.163, p = 0.018]. Fetuses of mothers with FHD+ had a prolonged fAER (273 ± 113 ms) compared to fetuses of mothers with FHD- (219 ± 69 ms) at 60 min during the oGTT [F ₍₁₎ = 4.902, p = 0.032]. There were no significant differences in age, BMI before pregnancy, weight gain during pregnancy and gestational age between the groups. Maternal glucose levels and insulin sensitivity were also not significantly different. Discussion: In addition to the previously shown influence of maternal metabolism on fetal brain activity, maternal family history of diabetes (FHD) is also linked to fetal postprandial brain activity. This indicates that genetic and/or epigenetic factors modulate the postprandial brain response of the developing fetus.

Association between small for gestational age and low birth weight with attention deficit and impaired executive functions in 3-6 years old children

BACKGROUND

Behavioral disorders and attention deficit hyperactivity disorder (ADHD) symptoms are frequently reported among children with history of small body size at birth and disproportionate intrauterine growth retardation. The current study aimed to investigate some factors like executive functions and attention deficit in children with history of Small for gestational age (SGA) and/or Low Birth Weight (LBW) at birth.

METHODS

A historical cohort study was done and 3-6 years old preschool children (with past history of SGA/LBW) from some kindergartens and health centers were selected. Control group was randomly selected among children with history of normal birth weight and appropriate for gestational age at birth. All children were interviewed by an expert psychologist. Variables related to their attention, development, and executive functions were assessed by ASQ, Conner's, and Wisconsin Card Sorting Test. Completed questionnaires related Attention deficit and indexes of executive functions were evaluated between children in case groups and their counterparts in controls.

RESULTS

Based on inclusion criteria, 229 preschool children entered the study. With regard to size for gestational age, 124 cases were categorized in the SGA/LBW group and the rest were assigned in the appropriate for gestational age (AGA) group. In the case group, NPE and Percent Perseverative Errors (PPE) scores were significantly lower than normal birth weight group (p = .0001, p = .015). Scores related B item of Conner's was significantly different between cases and their controls (p = .039, p = .035).

CONCLUSIONS

Our results indicated that children with past history of some risks at birth may suffer from complications related attention and executive functions in their childhood. Recommendations for further research are strongly suggested.

Detection and assessment of brain injury in the growth-restricted fetus and neonate

Fetal growth restriction (FGR) is a common complication of pregnancy and, in severe cases, is associated with elevated rates of perinatal mortality, neonatal morbidity, and poor neurodevelopmental outcomes. The leading cause of FGR is placental insufficiency, with the placenta failing to adequately meet the increasing oxygen and nutritional needs of the growing fetus with advancing gestation. The resultant chronic fetal hypoxia induces a decrease in fetal growth, and a redistribution of blood flow preferentially to the brain. However, this adaptation does not ensure normal brain development. Early detection of brain injury in FGR, allowing for the prediction of short- and long-term neurodevelopmental consequences, remains a significant challenge. Furthermore, in FGR infants the detection and diagnosis of neuropathology is complicated by preterm birth, the etiological heterogeneity of FGR, timing of onset of growth restriction, its severity, and coexisting complications. In this review, we examine existing and emerging diagnostic tools from human and preclinical studies for the detection and assessment of brain injury in FGR fetuses and neonates. Increased detection rates, and early detection of brain injury associated with FGR, will offer opportunities for developing and assessing interventions to improve long-term outcomes.