Fetal medicine
DOI: 10.1111/1471-0528.13347 www.bjog.org
Functional brain development in growthrestricted and constitutionally small fetuses: a fetal magnetoencephalography case–control study EC Morin,a,b F Schleger,b H Preissl,b J Braendle,a,b H Eswaran,c H Abele,a S Brucker,a,d I Kiefer-Schmidta,b a
Department of Obstetrics and Gynaecology, University of Tuebingen, Tuebingen, Germany b fMEG-Center, University of Tuebingen, Tuebingen, Germany c SARA Research Center, Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR, USA d University Women’s Hospital and Research Institute for Women’s Health, Tuebingen, Germany Correspondence: Dr I Kiefer-Schmidt, Department of Obstetrics and Gynaecology, University of Tuebingen, Calwerstrasse 7, 72076 Tuebingen, Germany. Email [email protected] Accepted 26 January 2015. Published Online 2 April 2015.
Objective Fetal magnetoencephalography records fetal brain activity
non-invasively. Delayed brain responses were reported for fetuses weighing below the tenth percentile. To investigate whether this delay indicates delayed brain maturation resulting from placental insufficiency, this study distinguished two groups of fetuses below the tenth percentile: growth-restricted fetuses with abnormal umbilical artery Doppler velocity (IUGR) and constitutionally small-forgestational-age fetuses with normal umbilical artery Doppler findings (SGA) were compared with fetuses of adequate weight for gestational age (AGA), matched for age and behavioural state. Design A case–control study of matched pairs. Setting Fetal magnetoencephalography-Center at the University
Hospital of Tuebingen. Population Fourteen IUGR fetuses and 23 SGA fetuses were
matched for gestational age and fetal behavioural state with 37 healthy, normal-sized fetuses. Methods A 156-channel fetal magentoencephalography system was
used to record fetal brain activity. Light flashes as visual
stimulation were applied to the fetus. The Student’s t-test for paired groups was performed. Main outcome measure Latency of fetal visual evoked magnetic
responses (VER). Results The IUGR fetuses showed delayed VERs compared with controls (IUGR, 233.1 ms; controls, 184.6 ms; P = 0.032). SGA fetuses had similar evoked response latencies compared with controls (SGA, 216.1 ms; controls, 219.9 ms; P = 0.828). Behavioural states were similarly distributed. Conclusion Visual evoked responses are delayed in IUGR fetuses,
but not in SGA. Fetal behavioural state as an influencing factor of brain response latency was accounted for in the comparison. This reinforces that delayed brain maturation is the result of placental insufficiency. Keywords Fetal behavioural state, fetal brain development, fetal magnetoencephalography, intrauterine growth restriction, visual evoked response.
Please cite this paper as: Morin EC, Schleger F, Preissl H, Braendle J, Eswaran H, Abele H , Brucker S, Kiefer-Schmidt I. Functional brain development in growth-restricted and constitutionally small fetuses: a fetal magnetoencephalography case–control study BJOG 2015;122:1184–1190.
Introduction Fetal magnetoencephalography (fMEG) is a non-invasive method of detecting fetal brain activity. As purpose-built systems for obstetrical recordings have become available, more extensive knowledge about the development of brain function in utero has been achieved.1 Fetal brain responses to auditory and visual stimulation have been successfully
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recorded after 28 weeks of gestational age (GA).2,3 Decreasing latencies of evoked brain responses are a marker of functional brain development in healthy fetuses.4,5 Based on evoked responses, the development of higher cognitive functions, such as habituation or stimulus discrimination, has been assessed.6,7 Of clinical interest is the functional brain development in fetuses at risk, which cannot be assessed with conventional obstetrical monitoring. The
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Delayed cerebral responses in IUGR fetuses
impact of placental insufficiency leading to intrauterine growth-restricted (IUGR) fetuses is a particular matter of debate. Structural defects and long-term effects on cognitive development are evident. Based on epidemiological investigations on IUGR children, several specific deficits were observed: lower intelligence quotients (IQs), constrained memory function, learning skills, and neuromotor deficits.8,9 With fMEG, a promising tool is available to assess brain function in fetuses deemed to be at risk. An initial study, conducted with the first MEG device dedicated for obstetrical recordings, revealed delayed brain responses to auditory stimulation in SGA fetuses, presumably in those with signs of a more severe growth restriction, as indicated by a retrospective Doppler evaluation.10 A recent study revealed that the fetal behavioural state influences fetal brain activity: awake fetuses showed faster evoked brain responses than sleeping fetuses.11 Thus, the fetal behavioural state should be taken into account when comparing fetal brain responses. The aim of this study was to determine whether delayed brain maturation becomes evident in placental insufficiency, by distinguishing two groups of fetuses: growth-restricted (IUGR), with evidence of placental malfunction shown by abnormal umbilical artery Doppler, and constitutionally small-for-gestationalage (SGA) fetuses. Gestational age and fetal behavioural state was taken into account when comparing evoked responses with control AGA fetuses.
Material and methods Subjects For this study, 128 women with a singleton pregnancy were recruited through the Department of Obstetrics at the University of Tuebingen after 26+6 weeks of gestation. All women gave written informed consent prior to the study, which was approved by the local ethics committee. Chromosomal abnormalities, fetal infections, and stillbirths were excluded. Fetuses with estimated weights below the tenth percentile for GA estimated by ultrasound measurement, according to Hadlock,12 were included in the study groups. In addition, the weight at birth had to be below the tenth percentile for GA. If an elevated umbilical artery pulsatility index above the 90th percentile for GA was observed during the pregnancy, the fetus was classified as IUGR on the basis of insufficient placental blood supply.13 If the umbilical artery Doppler remained normal, placental insufficiency could not be verified, and the fetus was classified as SGA. In addition, the ponderal index, based on body weight and length [body weight (kg) 9 100/body length (m3)],14 was determined at birth according to the classification of a preliminary study.10 Based on a threshold of 2.2, the newborns were classified as asymmetrically growth-restricted,
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indicating a emaciated fetal body below and symmetrical body proportions above this threshold.10 Furthermore, the pH of the umbilical artery, Apgar score after 5 minutes, gestational age, and mode of delivery were collected. Healthy fetuses with normal growth and adequate birthweights were included as controls. A single fMEG recording per fetus was included.
Recording The study was performed using a 156-channel system (VSM MedTech Ltd., Port Coquitlam, BC, Canada) dedicated for fetal measurements. Prior to the study, CTG monitoring was performed over 30 minutes to confirm fetal wellbeing. An ultrasound (Logiq 500MD, GE, UK) was conducted to determine fetal body and eye position. A detailed ultrasound scan including fetometry and Doppler status in general was performed at the Department of Prenatal Diagnostics, no longer than 10 days before the recording. For IUGR fetuses, a Doppler scan was performed on the same day of the study. The mother was seated on the magnetograph leaning forwards, with her abdomen placed into the sensor array, in a magnetically shielded room (Vakuumschmelze, Hanau, Germany). The position of the fetal head was marked with a single sensor (head coil) on an elastic belt, with three additional coils marking the woman’s abdomen to detect maternal movement during the procedure. The recording lasted 10 minutes, with a sampling rate of 610.352 Hz. Visual stimulation consisted of light flashes (wavelength 625 nm, intensity 8000 Lux) presented from outside into the shielded room via fiber optic wires to a light pad fixed on the maternal abdomen above the location of the fetal eyes. Each flash lasted 500 ms (interstimulus interval 2.0 0.5 seconds). The light passes through the maternal tissue without electromagnetic interference or any harm to the fetus or neonate.15
Data analysis All data sets were analysed offline. For the analysis of the visual evoked response (VER), data were high-pass filtered (0.5 Hz) and transformed by a first-order synthetic gradiometer to eliminate further external disturbances. The interfering maternal and fetal heart signals were removed from the data by signal space projection.16,17 The data set was then split into trials (time range from 200 ms before to 1 s after the stimulation). A low-pass filter (10 Hz) was applied and the trials were averaged and visually analysed. An evoked response was classified by showing a positive or negative peak 80–500 ms after the stimulus, with an amplitude minimum of 4 fT (femto Tesla) in at least four sensors at the area of the fetal head coil (Figure 1). The responses were validated according to the plus/minus
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fT 20 10
fT
Peak
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–20
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−10 0
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Figure 1. Visual evoked response (VER) ~230 ms after the stimulus (0 ms) of 10–16 fT in five channels.
criteria, calculating the difference between no response and a discernible response in the odd and the even trials, indicating the signal-to-noise ratio.18 The latency between stimulus and the peak was documented. For the analysis of the fetal behavioural states, the 10minute data set containing the markers for maternal and fetal heart (fMCG) activity was split into two trials of 5 minutes. An ‘actocardiogram’ for each trial was created based on the fMCG markers: a ‘cardiogram’ illustrating the heart beats in beats per minute over time in a CTG-like fashion and an ‘actogram’, where variations of the vector amplitude were plotted as fluctuations of a baseline over time, as the variation of the fetal heart vector in relation to the sensors indicates fetal movement.19 The analysis was performed with MATLAB 7.7 R2008b (Mathworks, Natick, MA, USA). The actocardiogram was visually analysed according to the method described by Nijhuis,20 adapted to fetal state classification for magnetographic recordings based on prior studies.11,21,22 The characteristics of fetal heart rate pattern and body movement define four states after 32 weeks of gestation (1F, passive sleep; 2F, active sleep; 3F, passive awake; and 4F, active awake), or two states (quiescence or activity) prior to 32 weeks of gestation,23 in common use.11,21,22 By definition, 3 minutes was considered the minimum duration for each state. Figure S1 shows an actocardiogram of a fetus at 34 weeks of gestation in state 2F/active sleep, and Table S1 indicates the state criteria based on fetal heart rate pattern and fetal movement. Each IUGR and SGA data set was matched for GA and fetal state with a control data set. In the case of an unsuccessful GA match, the fetuses had to belong to the same GA group (a, 27+1–32+0 weeks of gestation; b, 32+1– 36+0 weeks of gestation; c, 36+1–41+0 weeks of gestation). If more than one control matched the GA, the control with
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the fitting fetal state was chosen. If a control fetus did not show the same fetal state as the matched IUGR or SGA fetus in both 5-minute trials, only the matching 5 minutes of the control was used for the further VER analysis. IBM SPSS 21 for WINDOWS was used for the statistical analysis. Data were examined for Gaussian distribution using the Shapiro–Wilk test. Paired Student’s t-tests were used to compare the latencies of IUGR and SGA fetuses, and their respective controls. A Student’s t-test for unpaired groups was used to compare the latencies of IUGR and SGA. Significance was defined with P < 0.05.
Results The final analysis is based on 74 subjects. Fourteen were classified as IUGR, with an average age at the recording of 33+2 weeks of gestation (range 29+0–37+3 weeks of gestation). For 11 subjects the Doppler scan was collected on the day of the study, and for two fetuses 1 day prior to the study and in one case 2 days earlier. All IUGR fetuses showed a decreasesd end-diastolic velocity of the umbilical artery blood flow with an increased resistance index above the 90th percentile for GA. An absent or reversed end-diastolic flow was not apparent, but the middle cerebral artery index was decreased below the tenth percentile, indicating a brain-sparing effect in one case. Four were born at term and ten were delivered prematurely for signs of fetal deterioration, with weights below the tenth percentile for GA (mean, 1751 g; range, 985–2510 g). All were delivered via caesarean section. Postnatally, the ponderal index of the IUGR group was below 2.2 in seven babies and above in another seven. Table S2a shows the birthweights of the IUGR babies in detail. Thirty-eight fetuses were classified as SGA with constantly normal Doppler at a mean age of 34+2 weeks of gestation (range 28+7–39+3 weeks of gestation). These were all born SGA and were below the tenth percentile (mean, 2552 g; range, 1900–2920 g). Thirty-six were born at term and two were delivered in the 37th week of gestation. Eighteen SGA neonates were born with adequate ponderal index, and five showed a ponderal index below 2.2. Five data sets were unsuitable because of technical problems at the recording and ten more could not be further analysed because of artifacts. This gave 23 SGA data sets for the final examination. Table S2b indicates the birthweights of the SGA group in detail. A total of 160 data sets from 76 women were used as controls. Thirty-seven fetuses were successfully matched with their GA and fetal behavioural state at the recording: 14 were matched with the IUGR subjects (IUGR-C) and 23 were matched with the SGA fetuses (SGA-C). The mean ages of the IUGR-C and SGA-C groups at recording were 32+6 weeks of gestation (range: 28+4–38+3 weeks of gesta-
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Delayed cerebral responses in IUGR fetuses
tion) and 33+7 weeks of gestation (range: 27+3–40+6 weeks of gestation), respectively. All 37 controls were born with adequate weights between the tenth and 90th percentile for GA (average 3405 g, range 2150–4210 g), with two born prematurely and 35 born at term. All fetuses of the study had Apgar scores > 5 after 5 minutes and umbilical cord blood gases pH > 7.0.
Table 1 shows the results of the VER latencies between IUGR and IUGR-C, and Table 2 shows the VER results of the SGA and the SGA-C. There was a significant difference in VER latencies between IUGR and IUGR-C [P = 0.032; t(13) = 2.406; 95% confidence interval 95% CI = 4.96–92.18], with longer latencies in the IUGR group and a mean difference of 48.6 ms. There was no significant difference in VER latencies between SGA and SGA-C [mean difference of 3.8 ms; P = 0.828; t(22) = 0.220; 95% CI = 39.87 to 32.22]. There was no significant difference in VER latencies between IUGR and SGA [mean difference, 17 ms; P = 0.416; t(35) = 0.822; Figure 2]. For a retrospective analysis the 14 IUGR fetuses were subdivided into two groups, depending on fetal age at the first evidence of IUGR during gestation. Nine fetuses diagnosed ≤32+0 weeks of gestation formed the ‘early-onset’ group, and five fetuses diagnosed after 32+0 weeks of gestation formed the ‘late-onset’ group. The mean VER latency of the early-onset group was 226.8 ms (SD 71.2 ms), compared with 186.1 ms (SD 45.9 ms) in the matched controls. Late-onset IUGR had a mean latency of 244.5 ms (SD 28.5 ms) compared with 181.9 ms (RMS 65.6 ms). Fig-
Table 1. VER latencies of IUGR fetuses (n = 14) and IUGR–C fetuses (n = 14)
29 30 31 32 32 33 34 34 34 34 35 36 38 38
Fetal behavioural states Table 3 indicates the percentage of states in fetuses prior to and after 32 weeks of gestation.
Discussion
Visual evoked responses
GA at the recording (weeks)
ure 3 shows the box plots of the VER latencies of earlyand late-onset IUGR, and of their controls.
VER latency IUGR (ms)
VER latency IUGR–C (ms)
Difference in latency (ms)
294.9 232.7 267.1 214.6 109.8 147.8 303.1 254.0 172.0 299.8 211.4 217.9 262.1 276.9
188.4 195.0 208.1 254.0 155.6 239.2 168.8 158.9 101.6 163.8 113.0 221.2 275.3 140.9
106.5 37.7 59 39.4 45.8 91.4 134.3 95.1 70.4 136 98.4 3.3 13.2 136
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Main findings In the current study, we determined latencies of evoked responses of IUGR fetuses (caused by placental insufficiency) and of constitutional SGA fetuses (without signs of placental insufficiency), and compared both with matched AGA controls. The values of VER latencies measured were in the range of those reported in former studies within this field.24,25 The main finding was a significant delay in VER latency in the IUGR group compared with controls, which was not evident in SGA fetuses. The results of this study indicate delayed brain maturation in intrauterine placental insufficiency independent of gestational age and fetal behavioural state. It is known that a lack of oxygen impairs the structural development of the highly oxygen-dependent brain.26
Table 2. VER latencies of SGA fetuses (n = 23) and SGA-C fetuses (n = 23) GA at the recording (weeks) 29 30 30 31 32 33 33 33 33 34 35 35 36 36 36 36 36 37 37 38 38 39 40
VER latency IUGR (ms)
VER latency IUGR-C (ms)
Difference in latency (ms)
260.5 145.8 314.6 157.3 337.5 198.2 175.3 232.7 132.7 217.9 190.1 329.3 147.5 247.4 285.1 235.9 250.7 163.8 193.3 198.8 144.2 144.2 267.1
222.8 196.6 176.9 234.3 152.4 199.9 280.2 335.9 221.2 186.8 198.2 299.8 262.1 199.9 272.0 278.5 283.4 175.3 103.2 276.9 211.4 167.1 122.9
37.7 50.8 137.7 77 185.1 1.7 104.9 103.2 88,5 31.1 8.1 29.5 114.6 47.5 13.1 42.6 32.7 11.5 90.1 78.1 67.2 22.9 144.2
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Figure 2. Box plot of latencies of IUGR and SGA versus controls. The coloured box-plot boxes represent the medians, interquartiles, and ranges, which include 50% of all data. Horizontal black lines in the boxes mark the median values. The black vertical lines represent the total range of all data, except outliers. Outliers (circle) are defined as values with a box length of 1.5–3.0 under the 25th or over the 75th percentile.
Figure 3. Box plot of latencies of early- and late-onset IUGR versus controls. Box plots display median values, quartiles and ranges. Coloured boxes represent the interquartile range that includes 50% of all data. Horizontal black lines in boxes mark the median values. The black vertical lines represent the total range of all data, excepting outliers. Outliers are defined as values with a box length of 1.5–3.0 under the 25th or over the 75th percentile.
Table 3. Occurrence of fetal states 32 weeks of gestation Group (n) 1F (%) 2F (%) IUGR (9) SGA (18) IUGR–C (9) SGA–C (18) Controls (76)
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28 36 31 41 30
56 61 69 59 58
3F (%)
4F (%)
None (%)
6 3 –
– – – – 8
11 – – – 3
1
IUGR is associated with structural grey and white matter decrements and delayed myelination.27,28 For the first time, the current findings indicate functional impact detectable during the fetal stage. The incidences of fetal behavioural states after 32 weeks of gestation in the 76 controls were comparable with findings in similar studies, as summarised in a recently published survey from our group;22 however, the active awake state 4F was not detectable in the IUGR and SGA group. Notably, no state could be classified in 11.1% of the IUGR. In a sonographic observation of IUGR fetuses the development of behavioural states was described to be impaired.29 There is evidence from fMEG that the maturation and complexity of heart rate variability is altered in IUGR.30 This is in accordance with the deviant state findings of our study, but more detailed analysis of the underlying causes of non-observable states is needed in these cases.
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Delayed cerebral responses in IUGR fetuses
Strengths and limitations The evidence of placental insufficiency as the underlying cause was included using the umbilical artery Doppler as study group criteria. In the pre-study to this investigation the ponderal index was evaluated as an indicator for fetal wasting.10 The ponderal index failed to detect early-onset IUGR, however, as a comparable effect to cellular mass gain and cellular proliferation exists that leads to symmetrical growth retardation.31 Hence, the most retarded brain responses in the group of symmetrical growth-retarded fetuses were explainable by the assertion of early, severe placental insufficiency, as retrospectively identified on Doppler findings. This time, the umbilical artery Doppler was prospectively taken into account. The results of this study verify that functional brain maturation is delayed in assured placental insufficiency; however, we could not confirm more pronounced VER delay in early-onset IUGR fetuses, as suggested in the primary study and in a newer study of different spectral power differences of spontaneous brain activity in young IUGR fetuses. This might be because of the small number of cases in both IUGR subgroups. In addition, we admit that the wide range of VER latencies between the groups makes the interpretation of a single measurement difficult in each individual case. A major limitation is the limited availability of fMEG to date. The analysis procedures remain in development in order to improve the detection of brain signals. Visual evoked responses were successfully introduced in IUGR alongside auditory evoked responses for a broader understanding of the impact of placental insufficiency on functional brain development. Furthermore, VERs have the advantage of not being influenced by maternal perception of the stimuli, which cannot be avoided in auditory stimulation. Based on recent findings,11 the fetal behavioural state was determined as an influencing factor on brain response latency for the first time alongside gestational age.
Interpretation The latency of VERs is delayed in IUGR fetuses, but not in SGA fetuses. The results provide further support for the hypothesis that intrauterine placental insufficiency leads to delayed brain maturation, as determined by evoked responses.10 For the first time, fetal behavioural state as an influencing factor of brain response latency was accounted for in the comparison based on recent findings.11 This study reinforces that delayed brain maturation is a result of placental insufficiency.
Conclusion In conclusion, fMEG offers the unique possibility to monitor fetal brain development and indicates significant retardation
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in IUGR fetuses based on placental insufficiency. Whether these findings predict neonatal or infantile neurocognitive sequels is of further interest. The investigation of fetal neurodevelopment could be helpful for the surveillance and management of IUGR fetuses; however, the method is limited in its application and the large variance of the values hinder the interpretation of a individual result. More data will help to define normal and deviant ranges corrected for fetal age and behavioural state, and further methodical progress is necessary to support the further implementation of fMEG in obstetrics.
Disclosure of interests The authors report no conflicts of interest.
Contribution to authorship IKS, HP, and HA were involved in the design of the study, data acquisition and analysis, and interpretation of data, and drafted and revised the article; EM and FS performed data analysis; HE and JB developed the methods; SB was involved in the interpretation of clinical data. All authors revised and reviewed the final text.
Details of ethics approval The study was approved by the Ethics Committee of the University of Tuebingen (ref. no. 476/2008MPG1).
Funding This study was supported by the Deutsche Forschungsgemeinschaft (DFG BI 195/50 and KI 1306/3-1), the University of Tuebingen (E.05.00303 and E.05.0259.1), and the Landesstiftung Baden-Wuerttemberg.
Acknowledgements We thank Magdalene Weiss from the fMEG-Center Tuebingen for her substantial work, and Dr Sybille Lessmann from the Department of Obstetrics and Gynaecology of the University of Tuebingen for her great support in preparing this paper.
Supporting Information Additional Supporting Information may be found in the online version of this article: Figure S1. Actocardiogram of a fetus at 34 weeks of gestation in state 2F (active sleep). Table S1. Definition criteria for rest and activity (at 25– 32 weeks of gestation) and fetal behavioural states 1F–4F (at 33–40 weeks of gestation) based on fetal heart rate characteristics and fetal movement. Table S2. Gestational age at birth and birthweight in grams, percentiles, and Z–scores of IUGR and SGA fetuses. &
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References 1 Preissl H, Lowery CL, Eswaran H. Fetal magnetoencephalography: current progress and trends. Exp Neurol 2004;190 (Suppl 1):S28–36. 2 Eswaran H, Lowery CL, Wilson JD, Murphy P, Preissl H. Fetal magnetoencephalography–a multimodal approach. Brain Res Dev Brain Res 2005;154:57–62. 3 Lengle JM, Chen M, Wakai RT. Improved neuromagnetic detection of fetal and neonatal auditory evoked responses. Clin Neurophysiol 2001;112:785–92. 4 Holst M, Eswaran H, Lowery C, Murphy P, Norton J, Preissl H. Development of auditory evoked fields in human fetuses and newborns: a longitudinal MEG study. Clin Neurophysiol 2005;116:1949–55. 5 Schleussner E, Schneider U. Developmental changes of auditoryevoked fields in fetuses. Exp Neurol 2004;190 (Suppl 1):S59–64. 6 Draganova R, Eswaran H, Murphy P, Huotilainen M, Lowery C, Preissl H. Sound frequency change detection in fetuses and newborns, a magnetoencephalographic study. NeuroImage 2005;28:354–61. 7 Muenssinger J, Matuz T, Schleger F, Kiefer-Schmidt I, Goelz R, Wacker-Gussmann A, et al. Auditory habituation in the fetus and neonate: an fMEG study. Dev Sci 2013;16:287–95. 8 Sizonenko SV, Borradori-Tolsa C, Bauthay DM, Lodygensky G, Lazeyras F, Huppi P. Impact of intrauterine growth restriction and glucocorticoids on brain development: insights using advanced magnetic resonance imaging. Mol Cell Endocrinol 2006;254– 255:163–71. 9 Thompson C, Syddall H, Rodin I, Osmond C, Barker DJ. Birth weight and the risk of depressive disorder in late life. Br J Psychiatry 2001;179:450–5. 10 Kiefer I, Siegel E, Preissl H, Ware M, Schauf B, Lowery C, et al. Delayed maturation of auditory-evoked responses in growthrestricted fetuses revealed by magnetoencephalographic recordings. Am J Obstet Gynecol 2008;199:503 e1–7. 11 Kiefer-Schmidt I, Raufer J, Brandle J, Munssinger J, Abele H, Wallwiener D, et al. Is there a relationship between fetal brain function and the fetal behavioral state? A fetal MEG-study J Perinat Med 2013;41:605–12. 12 Hadlock FP, Harrist RB, Sharman RS, Deter RL, Park SK. Estimation of fetal weight with the use of head, body, and femur measurements–a prospective study. Am J Obstet Gynecol 1985;151:333–7. 13 Baschat AA. Arterial and venous Doppler in the diagnosis and management of early onset fetal growth restriction. Early Human Dev 2005;81:877–87. 14 Prasad SR, Mohan M, Kumar A, Kapani V. Ponderal index as a marker of intrauterine growth. Indian J Med Res 1989;90:442–7. 15 Wilson JD, Adams AJ, Murphy P, Eswaran H, Preissl H. Design of a light stimulator for fetal and neonatal magnetoencephalography. Physiol Meas 2009;30:N1–10. 16 McCubbin J, Robinson SE, Cropp R, Moiseev A, Vrba J, Murphy P, et al. Optimal reduction of MCG in fetal MEG recordings. IEEE Trans Biomed Eng 2006;53:1720–4.
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17 Wilson JD, Govindan RB, Hatton JO, Lowery CL, Preissl H. Integrated approach for fetal QRS detection. IEEE Trans Biomed Eng 2008;55:2190–7. 18 Draganova R, Eswaran H, Murphy P, Lowery C, Preissl H. Serial magnetoencephalographic study of fetal and newborn auditory discriminative evoked responses. Early Hum Dev 2007;83:199–207. 19 Govindan RB, Vairavan S, Ulusar UD, Wilson JD, McKelvey SS, Preissl H, et al. A novel approach to track fetal movement using multisensor magnetocardiographic recordings. Ann Biomed Eng 2011;39:964–72. 20 Nijhuis JG, Prechtl HF, Martin CB Jr, Bots RS. Are there behavioural states in the human fetus? Early Hum Dev 1982;6:177–95. 21 Schneider U, Frank B, Fiedler A, Kaehler C, Hoyer D, Liehr M, et al. Human fetal heart rate variability-characteristics of autonomic regulation in the third trimester of gestation. J Perinat Med 2008;36:433–41. 22 Sonanini A, Stingl K, Preissl H, Brandle J, Hoopmann M, Kagan O, et al. Fetal behavioral states are stable over daytime – evidence by longitudinal and cross-sectional fetal biomagnetic recordings. J Perinat Med 2014;42:307–14. 23 Pillai M, James D. The development of fetal heart rate patterns during normal pregnancy. Obstet Gynecol 1990;76(5 Pt 1):812–6. 24 Eswaran H, Wilson J, Preissl H, Robinson S, Vrba J, Murphy P, et al. Magnetoencephalographic recordings of visual evoked brain activity in the human fetus. Lancet 2002;360:779–80. 25 Eswaran H, Lowery CL, Wilson JD, Murphy P, Preissl H. Functional development of the visual system in human fetus using magnetoencephalography. Exp Neurol 2004;190 (Suppl 1):S52–8. 26 Back SA, Han BH, Luo NL, Chricton CA, Xanthoudakis S, Tam J, et al. Selective vulnerability of late oligodendrocyte progenitors to hypoxia-ischemia. J Neurosci 2002;22:455–63. 27 Padilla N, Junque C, Figueras F, Sanz-Cortes M, Bargallo N, Arranz A, et al. Differential vulnerability of gray matter and white matter to intrauterine growth restriction in preterm infants at 12 months corrected age. Brain Res 2014;1545:1–11. 28 Reid MV, Murray KA, Marsh ED, Golden JA, Simmons RA, Grinspan JB. Delayed myelination in an intrauterine growth retardation model is mediated by oxidative stress upregulating bone morphogenetic protein 4. J Neuropathol Exp Neurol 2012;71:640–53. 29 Romanini C, Rizzo G. Fetal behaviour in normal and compromised fetuses. An overview.. Early Human Dev 1995;43:117–31. 30 Schneider U, Fiedler A, Liehr M, Kahler C, Schleussner E. Fetal heart rate variability in growth restricted fetuses. Biomed Tech (Berl) 2006;51:248–50. 31 Lin CC, Su SJ, River LP. Comparison of associated high-risk factors and perinatal outcome between symmetric and asymmetric fetal intrauterine growth retardation. Am J Obstet Gynecol 1991;1:1535– 41 discussion 41–2. 32 Eswaran H, Govindan RB, Haddad NI, Siegel ER, Preissl HT, Murphy P, et al. Spectral power differences in the brain activity of growth-restricted and normal fetuses. Early Human Dev 2012; 88:451–4.
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DOI: 10.1111/1471-0528.13347 www.bjog.org
Functional brain development in growthrestricted and constitutionally small fetuses: a fetal magnetoencephalography case–control study EC Morin,a,b F Schleger,b H Preissl,b J Braendle,a,b H Eswaran,c H Abele,a S Brucker,a,d I Kiefer-Schmidta,b a
Department of Obstetrics and Gynaecology, University of Tuebingen, Tuebingen, Germany b fMEG-Center, University of Tuebingen, Tuebingen, Germany c SARA Research Center, Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR, USA d University Women’s Hospital and Research Institute for Women’s Health, Tuebingen, Germany Correspondence: Dr I Kiefer-Schmidt, Department of Obstetrics and Gynaecology, University of Tuebingen, Calwerstrasse 7, 72076 Tuebingen, Germany. Email [email protected] Accepted 26 January 2015. Published Online 2 April 2015.
Objective Fetal magnetoencephalography records fetal brain activity
non-invasively. Delayed brain responses were reported for fetuses weighing below the tenth percentile. To investigate whether this delay indicates delayed brain maturation resulting from placental insufficiency, this study distinguished two groups of fetuses below the tenth percentile: growth-restricted fetuses with abnormal umbilical artery Doppler velocity (IUGR) and constitutionally small-forgestational-age fetuses with normal umbilical artery Doppler findings (SGA) were compared with fetuses of adequate weight for gestational age (AGA), matched for age and behavioural state. Design A case–control study of matched pairs. Setting Fetal magnetoencephalography-Center at the University
Hospital of Tuebingen. Population Fourteen IUGR fetuses and 23 SGA fetuses were
matched for gestational age and fetal behavioural state with 37 healthy, normal-sized fetuses. Methods A 156-channel fetal magentoencephalography system was
used to record fetal brain activity. Light flashes as visual
stimulation were applied to the fetus. The Student’s t-test for paired groups was performed. Main outcome measure Latency of fetal visual evoked magnetic
responses (VER). Results The IUGR fetuses showed delayed VERs compared with controls (IUGR, 233.1 ms; controls, 184.6 ms; P = 0.032). SGA fetuses had similar evoked response latencies compared with controls (SGA, 216.1 ms; controls, 219.9 ms; P = 0.828). Behavioural states were similarly distributed. Conclusion Visual evoked responses are delayed in IUGR fetuses,
but not in SGA. Fetal behavioural state as an influencing factor of brain response latency was accounted for in the comparison. This reinforces that delayed brain maturation is the result of placental insufficiency. Keywords Fetal behavioural state, fetal brain development, fetal magnetoencephalography, intrauterine growth restriction, visual evoked response.
Please cite this paper as: Morin EC, Schleger F, Preissl H, Braendle J, Eswaran H, Abele H , Brucker S, Kiefer-Schmidt I. Functional brain development in growth-restricted and constitutionally small fetuses: a fetal magnetoencephalography case–control study BJOG 2015;122:1184–1190.
Introduction Fetal magnetoencephalography (fMEG) is a non-invasive method of detecting fetal brain activity. As purpose-built systems for obstetrical recordings have become available, more extensive knowledge about the development of brain function in utero has been achieved.1 Fetal brain responses to auditory and visual stimulation have been successfully
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recorded after 28 weeks of gestational age (GA).2,3 Decreasing latencies of evoked brain responses are a marker of functional brain development in healthy fetuses.4,5 Based on evoked responses, the development of higher cognitive functions, such as habituation or stimulus discrimination, has been assessed.6,7 Of clinical interest is the functional brain development in fetuses at risk, which cannot be assessed with conventional obstetrical monitoring. The
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Delayed cerebral responses in IUGR fetuses
impact of placental insufficiency leading to intrauterine growth-restricted (IUGR) fetuses is a particular matter of debate. Structural defects and long-term effects on cognitive development are evident. Based on epidemiological investigations on IUGR children, several specific deficits were observed: lower intelligence quotients (IQs), constrained memory function, learning skills, and neuromotor deficits.8,9 With fMEG, a promising tool is available to assess brain function in fetuses deemed to be at risk. An initial study, conducted with the first MEG device dedicated for obstetrical recordings, revealed delayed brain responses to auditory stimulation in SGA fetuses, presumably in those with signs of a more severe growth restriction, as indicated by a retrospective Doppler evaluation.10 A recent study revealed that the fetal behavioural state influences fetal brain activity: awake fetuses showed faster evoked brain responses than sleeping fetuses.11 Thus, the fetal behavioural state should be taken into account when comparing fetal brain responses. The aim of this study was to determine whether delayed brain maturation becomes evident in placental insufficiency, by distinguishing two groups of fetuses: growth-restricted (IUGR), with evidence of placental malfunction shown by abnormal umbilical artery Doppler, and constitutionally small-for-gestationalage (SGA) fetuses. Gestational age and fetal behavioural state was taken into account when comparing evoked responses with control AGA fetuses.
Material and methods Subjects For this study, 128 women with a singleton pregnancy were recruited through the Department of Obstetrics at the University of Tuebingen after 26+6 weeks of gestation. All women gave written informed consent prior to the study, which was approved by the local ethics committee. Chromosomal abnormalities, fetal infections, and stillbirths were excluded. Fetuses with estimated weights below the tenth percentile for GA estimated by ultrasound measurement, according to Hadlock,12 were included in the study groups. In addition, the weight at birth had to be below the tenth percentile for GA. If an elevated umbilical artery pulsatility index above the 90th percentile for GA was observed during the pregnancy, the fetus was classified as IUGR on the basis of insufficient placental blood supply.13 If the umbilical artery Doppler remained normal, placental insufficiency could not be verified, and the fetus was classified as SGA. In addition, the ponderal index, based on body weight and length [body weight (kg) 9 100/body length (m3)],14 was determined at birth according to the classification of a preliminary study.10 Based on a threshold of 2.2, the newborns were classified as asymmetrically growth-restricted,
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indicating a emaciated fetal body below and symmetrical body proportions above this threshold.10 Furthermore, the pH of the umbilical artery, Apgar score after 5 minutes, gestational age, and mode of delivery were collected. Healthy fetuses with normal growth and adequate birthweights were included as controls. A single fMEG recording per fetus was included.
Recording The study was performed using a 156-channel system (VSM MedTech Ltd., Port Coquitlam, BC, Canada) dedicated for fetal measurements. Prior to the study, CTG monitoring was performed over 30 minutes to confirm fetal wellbeing. An ultrasound (Logiq 500MD, GE, UK) was conducted to determine fetal body and eye position. A detailed ultrasound scan including fetometry and Doppler status in general was performed at the Department of Prenatal Diagnostics, no longer than 10 days before the recording. For IUGR fetuses, a Doppler scan was performed on the same day of the study. The mother was seated on the magnetograph leaning forwards, with her abdomen placed into the sensor array, in a magnetically shielded room (Vakuumschmelze, Hanau, Germany). The position of the fetal head was marked with a single sensor (head coil) on an elastic belt, with three additional coils marking the woman’s abdomen to detect maternal movement during the procedure. The recording lasted 10 minutes, with a sampling rate of 610.352 Hz. Visual stimulation consisted of light flashes (wavelength 625 nm, intensity 8000 Lux) presented from outside into the shielded room via fiber optic wires to a light pad fixed on the maternal abdomen above the location of the fetal eyes. Each flash lasted 500 ms (interstimulus interval 2.0 0.5 seconds). The light passes through the maternal tissue without electromagnetic interference or any harm to the fetus or neonate.15
Data analysis All data sets were analysed offline. For the analysis of the visual evoked response (VER), data were high-pass filtered (0.5 Hz) and transformed by a first-order synthetic gradiometer to eliminate further external disturbances. The interfering maternal and fetal heart signals were removed from the data by signal space projection.16,17 The data set was then split into trials (time range from 200 ms before to 1 s after the stimulation). A low-pass filter (10 Hz) was applied and the trials were averaged and visually analysed. An evoked response was classified by showing a positive or negative peak 80–500 ms after the stimulus, with an amplitude minimum of 4 fT (femto Tesla) in at least four sensors at the area of the fetal head coil (Figure 1). The responses were validated according to the plus/minus
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fT 20 10
fT
Peak
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0 –5 –10 222ms
–20
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0
−10 0
200
400
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Figure 1. Visual evoked response (VER) ~230 ms after the stimulus (0 ms) of 10–16 fT in five channels.
criteria, calculating the difference between no response and a discernible response in the odd and the even trials, indicating the signal-to-noise ratio.18 The latency between stimulus and the peak was documented. For the analysis of the fetal behavioural states, the 10minute data set containing the markers for maternal and fetal heart (fMCG) activity was split into two trials of 5 minutes. An ‘actocardiogram’ for each trial was created based on the fMCG markers: a ‘cardiogram’ illustrating the heart beats in beats per minute over time in a CTG-like fashion and an ‘actogram’, where variations of the vector amplitude were plotted as fluctuations of a baseline over time, as the variation of the fetal heart vector in relation to the sensors indicates fetal movement.19 The analysis was performed with MATLAB 7.7 R2008b (Mathworks, Natick, MA, USA). The actocardiogram was visually analysed according to the method described by Nijhuis,20 adapted to fetal state classification for magnetographic recordings based on prior studies.11,21,22 The characteristics of fetal heart rate pattern and body movement define four states after 32 weeks of gestation (1F, passive sleep; 2F, active sleep; 3F, passive awake; and 4F, active awake), or two states (quiescence or activity) prior to 32 weeks of gestation,23 in common use.11,21,22 By definition, 3 minutes was considered the minimum duration for each state. Figure S1 shows an actocardiogram of a fetus at 34 weeks of gestation in state 2F/active sleep, and Table S1 indicates the state criteria based on fetal heart rate pattern and fetal movement. Each IUGR and SGA data set was matched for GA and fetal state with a control data set. In the case of an unsuccessful GA match, the fetuses had to belong to the same GA group (a, 27+1–32+0 weeks of gestation; b, 32+1– 36+0 weeks of gestation; c, 36+1–41+0 weeks of gestation). If more than one control matched the GA, the control with
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the fitting fetal state was chosen. If a control fetus did not show the same fetal state as the matched IUGR or SGA fetus in both 5-minute trials, only the matching 5 minutes of the control was used for the further VER analysis. IBM SPSS 21 for WINDOWS was used for the statistical analysis. Data were examined for Gaussian distribution using the Shapiro–Wilk test. Paired Student’s t-tests were used to compare the latencies of IUGR and SGA fetuses, and their respective controls. A Student’s t-test for unpaired groups was used to compare the latencies of IUGR and SGA. Significance was defined with P < 0.05.
Results The final analysis is based on 74 subjects. Fourteen were classified as IUGR, with an average age at the recording of 33+2 weeks of gestation (range 29+0–37+3 weeks of gestation). For 11 subjects the Doppler scan was collected on the day of the study, and for two fetuses 1 day prior to the study and in one case 2 days earlier. All IUGR fetuses showed a decreasesd end-diastolic velocity of the umbilical artery blood flow with an increased resistance index above the 90th percentile for GA. An absent or reversed end-diastolic flow was not apparent, but the middle cerebral artery index was decreased below the tenth percentile, indicating a brain-sparing effect in one case. Four were born at term and ten were delivered prematurely for signs of fetal deterioration, with weights below the tenth percentile for GA (mean, 1751 g; range, 985–2510 g). All were delivered via caesarean section. Postnatally, the ponderal index of the IUGR group was below 2.2 in seven babies and above in another seven. Table S2a shows the birthweights of the IUGR babies in detail. Thirty-eight fetuses were classified as SGA with constantly normal Doppler at a mean age of 34+2 weeks of gestation (range 28+7–39+3 weeks of gestation). These were all born SGA and were below the tenth percentile (mean, 2552 g; range, 1900–2920 g). Thirty-six were born at term and two were delivered in the 37th week of gestation. Eighteen SGA neonates were born with adequate ponderal index, and five showed a ponderal index below 2.2. Five data sets were unsuitable because of technical problems at the recording and ten more could not be further analysed because of artifacts. This gave 23 SGA data sets for the final examination. Table S2b indicates the birthweights of the SGA group in detail. A total of 160 data sets from 76 women were used as controls. Thirty-seven fetuses were successfully matched with their GA and fetal behavioural state at the recording: 14 were matched with the IUGR subjects (IUGR-C) and 23 were matched with the SGA fetuses (SGA-C). The mean ages of the IUGR-C and SGA-C groups at recording were 32+6 weeks of gestation (range: 28+4–38+3 weeks of gesta-
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tion) and 33+7 weeks of gestation (range: 27+3–40+6 weeks of gestation), respectively. All 37 controls were born with adequate weights between the tenth and 90th percentile for GA (average 3405 g, range 2150–4210 g), with two born prematurely and 35 born at term. All fetuses of the study had Apgar scores > 5 after 5 minutes and umbilical cord blood gases pH > 7.0.
Table 1 shows the results of the VER latencies between IUGR and IUGR-C, and Table 2 shows the VER results of the SGA and the SGA-C. There was a significant difference in VER latencies between IUGR and IUGR-C [P = 0.032; t(13) = 2.406; 95% confidence interval 95% CI = 4.96–92.18], with longer latencies in the IUGR group and a mean difference of 48.6 ms. There was no significant difference in VER latencies between SGA and SGA-C [mean difference of 3.8 ms; P = 0.828; t(22) = 0.220; 95% CI = 39.87 to 32.22]. There was no significant difference in VER latencies between IUGR and SGA [mean difference, 17 ms; P = 0.416; t(35) = 0.822; Figure 2]. For a retrospective analysis the 14 IUGR fetuses were subdivided into two groups, depending on fetal age at the first evidence of IUGR during gestation. Nine fetuses diagnosed ≤32+0 weeks of gestation formed the ‘early-onset’ group, and five fetuses diagnosed after 32+0 weeks of gestation formed the ‘late-onset’ group. The mean VER latency of the early-onset group was 226.8 ms (SD 71.2 ms), compared with 186.1 ms (SD 45.9 ms) in the matched controls. Late-onset IUGR had a mean latency of 244.5 ms (SD 28.5 ms) compared with 181.9 ms (RMS 65.6 ms). Fig-
Table 1. VER latencies of IUGR fetuses (n = 14) and IUGR–C fetuses (n = 14)
29 30 31 32 32 33 34 34 34 34 35 36 38 38
Fetal behavioural states Table 3 indicates the percentage of states in fetuses prior to and after 32 weeks of gestation.
Discussion
Visual evoked responses
GA at the recording (weeks)
ure 3 shows the box plots of the VER latencies of earlyand late-onset IUGR, and of their controls.
VER latency IUGR (ms)
VER latency IUGR–C (ms)
Difference in latency (ms)
294.9 232.7 267.1 214.6 109.8 147.8 303.1 254.0 172.0 299.8 211.4 217.9 262.1 276.9
188.4 195.0 208.1 254.0 155.6 239.2 168.8 158.9 101.6 163.8 113.0 221.2 275.3 140.9
106.5 37.7 59 39.4 45.8 91.4 134.3 95.1 70.4 136 98.4 3.3 13.2 136
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Main findings In the current study, we determined latencies of evoked responses of IUGR fetuses (caused by placental insufficiency) and of constitutional SGA fetuses (without signs of placental insufficiency), and compared both with matched AGA controls. The values of VER latencies measured were in the range of those reported in former studies within this field.24,25 The main finding was a significant delay in VER latency in the IUGR group compared with controls, which was not evident in SGA fetuses. The results of this study indicate delayed brain maturation in intrauterine placental insufficiency independent of gestational age and fetal behavioural state. It is known that a lack of oxygen impairs the structural development of the highly oxygen-dependent brain.26
Table 2. VER latencies of SGA fetuses (n = 23) and SGA-C fetuses (n = 23) GA at the recording (weeks) 29 30 30 31 32 33 33 33 33 34 35 35 36 36 36 36 36 37 37 38 38 39 40
VER latency IUGR (ms)
VER latency IUGR-C (ms)
Difference in latency (ms)
260.5 145.8 314.6 157.3 337.5 198.2 175.3 232.7 132.7 217.9 190.1 329.3 147.5 247.4 285.1 235.9 250.7 163.8 193.3 198.8 144.2 144.2 267.1
222.8 196.6 176.9 234.3 152.4 199.9 280.2 335.9 221.2 186.8 198.2 299.8 262.1 199.9 272.0 278.5 283.4 175.3 103.2 276.9 211.4 167.1 122.9
37.7 50.8 137.7 77 185.1 1.7 104.9 103.2 88,5 31.1 8.1 29.5 114.6 47.5 13.1 42.6 32.7 11.5 90.1 78.1 67.2 22.9 144.2
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Figure 2. Box plot of latencies of IUGR and SGA versus controls. The coloured box-plot boxes represent the medians, interquartiles, and ranges, which include 50% of all data. Horizontal black lines in the boxes mark the median values. The black vertical lines represent the total range of all data, except outliers. Outliers (circle) are defined as values with a box length of 1.5–3.0 under the 25th or over the 75th percentile.
Figure 3. Box plot of latencies of early- and late-onset IUGR versus controls. Box plots display median values, quartiles and ranges. Coloured boxes represent the interquartile range that includes 50% of all data. Horizontal black lines in boxes mark the median values. The black vertical lines represent the total range of all data, excepting outliers. Outliers are defined as values with a box length of 1.5–3.0 under the 25th or over the 75th percentile.
Table 3. Occurrence of fetal states 32 weeks of gestation Group (n) 1F (%) 2F (%) IUGR (9) SGA (18) IUGR–C (9) SGA–C (18) Controls (76)
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28 36 31 41 30
56 61 69 59 58
3F (%)
4F (%)
None (%)
6 3 –
– – – – 8
11 – – – 3
1
IUGR is associated with structural grey and white matter decrements and delayed myelination.27,28 For the first time, the current findings indicate functional impact detectable during the fetal stage. The incidences of fetal behavioural states after 32 weeks of gestation in the 76 controls were comparable with findings in similar studies, as summarised in a recently published survey from our group;22 however, the active awake state 4F was not detectable in the IUGR and SGA group. Notably, no state could be classified in 11.1% of the IUGR. In a sonographic observation of IUGR fetuses the development of behavioural states was described to be impaired.29 There is evidence from fMEG that the maturation and complexity of heart rate variability is altered in IUGR.30 This is in accordance with the deviant state findings of our study, but more detailed analysis of the underlying causes of non-observable states is needed in these cases.
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Strengths and limitations The evidence of placental insufficiency as the underlying cause was included using the umbilical artery Doppler as study group criteria. In the pre-study to this investigation the ponderal index was evaluated as an indicator for fetal wasting.10 The ponderal index failed to detect early-onset IUGR, however, as a comparable effect to cellular mass gain and cellular proliferation exists that leads to symmetrical growth retardation.31 Hence, the most retarded brain responses in the group of symmetrical growth-retarded fetuses were explainable by the assertion of early, severe placental insufficiency, as retrospectively identified on Doppler findings. This time, the umbilical artery Doppler was prospectively taken into account. The results of this study verify that functional brain maturation is delayed in assured placental insufficiency; however, we could not confirm more pronounced VER delay in early-onset IUGR fetuses, as suggested in the primary study and in a newer study of different spectral power differences of spontaneous brain activity in young IUGR fetuses. This might be because of the small number of cases in both IUGR subgroups. In addition, we admit that the wide range of VER latencies between the groups makes the interpretation of a single measurement difficult in each individual case. A major limitation is the limited availability of fMEG to date. The analysis procedures remain in development in order to improve the detection of brain signals. Visual evoked responses were successfully introduced in IUGR alongside auditory evoked responses for a broader understanding of the impact of placental insufficiency on functional brain development. Furthermore, VERs have the advantage of not being influenced by maternal perception of the stimuli, which cannot be avoided in auditory stimulation. Based on recent findings,11 the fetal behavioural state was determined as an influencing factor on brain response latency for the first time alongside gestational age.
Interpretation The latency of VERs is delayed in IUGR fetuses, but not in SGA fetuses. The results provide further support for the hypothesis that intrauterine placental insufficiency leads to delayed brain maturation, as determined by evoked responses.10 For the first time, fetal behavioural state as an influencing factor of brain response latency was accounted for in the comparison based on recent findings.11 This study reinforces that delayed brain maturation is a result of placental insufficiency.
Conclusion In conclusion, fMEG offers the unique possibility to monitor fetal brain development and indicates significant retardation
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in IUGR fetuses based on placental insufficiency. Whether these findings predict neonatal or infantile neurocognitive sequels is of further interest. The investigation of fetal neurodevelopment could be helpful for the surveillance and management of IUGR fetuses; however, the method is limited in its application and the large variance of the values hinder the interpretation of a individual result. More data will help to define normal and deviant ranges corrected for fetal age and behavioural state, and further methodical progress is necessary to support the further implementation of fMEG in obstetrics.
Disclosure of interests The authors report no conflicts of interest.
Contribution to authorship IKS, HP, and HA were involved in the design of the study, data acquisition and analysis, and interpretation of data, and drafted and revised the article; EM and FS performed data analysis; HE and JB developed the methods; SB was involved in the interpretation of clinical data. All authors revised and reviewed the final text.
Details of ethics approval The study was approved by the Ethics Committee of the University of Tuebingen (ref. no. 476/2008MPG1).
Funding This study was supported by the Deutsche Forschungsgemeinschaft (DFG BI 195/50 and KI 1306/3-1), the University of Tuebingen (E.05.00303 and E.05.0259.1), and the Landesstiftung Baden-Wuerttemberg.
Acknowledgements We thank Magdalene Weiss from the fMEG-Center Tuebingen for her substantial work, and Dr Sybille Lessmann from the Department of Obstetrics and Gynaecology of the University of Tuebingen for her great support in preparing this paper.
Supporting Information Additional Supporting Information may be found in the online version of this article: Figure S1. Actocardiogram of a fetus at 34 weeks of gestation in state 2F (active sleep). Table S1. Definition criteria for rest and activity (at 25– 32 weeks of gestation) and fetal behavioural states 1F–4F (at 33–40 weeks of gestation) based on fetal heart rate characteristics and fetal movement. Table S2. Gestational age at birth and birthweight in grams, percentiles, and Z–scores of IUGR and SGA fetuses. &
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17 Wilson JD, Govindan RB, Hatton JO, Lowery CL, Preissl H. Integrated approach for fetal QRS detection. IEEE Trans Biomed Eng 2008;55:2190–7. 18 Draganova R, Eswaran H, Murphy P, Lowery C, Preissl H. Serial magnetoencephalographic study of fetal and newborn auditory discriminative evoked responses. Early Hum Dev 2007;83:199–207. 19 Govindan RB, Vairavan S, Ulusar UD, Wilson JD, McKelvey SS, Preissl H, et al. A novel approach to track fetal movement using multisensor magnetocardiographic recordings. Ann Biomed Eng 2011;39:964–72. 20 Nijhuis JG, Prechtl HF, Martin CB Jr, Bots RS. Are there behavioural states in the human fetus? Early Hum Dev 1982;6:177–95. 21 Schneider U, Frank B, Fiedler A, Kaehler C, Hoyer D, Liehr M, et al. Human fetal heart rate variability-characteristics of autonomic regulation in the third trimester of gestation. J Perinat Med 2008;36:433–41. 22 Sonanini A, Stingl K, Preissl H, Brandle J, Hoopmann M, Kagan O, et al. Fetal behavioral states are stable over daytime – evidence by longitudinal and cross-sectional fetal biomagnetic recordings. J Perinat Med 2014;42:307–14. 23 Pillai M, James D. The development of fetal heart rate patterns during normal pregnancy. Obstet Gynecol 1990;76(5 Pt 1):812–6. 24 Eswaran H, Wilson J, Preissl H, Robinson S, Vrba J, Murphy P, et al. Magnetoencephalographic recordings of visual evoked brain activity in the human fetus. Lancet 2002;360:779–80. 25 Eswaran H, Lowery CL, Wilson JD, Murphy P, Preissl H. Functional development of the visual system in human fetus using magnetoencephalography. Exp Neurol 2004;190 (Suppl 1):S52–8. 26 Back SA, Han BH, Luo NL, Chricton CA, Xanthoudakis S, Tam J, et al. Selective vulnerability of late oligodendrocyte progenitors to hypoxia-ischemia. J Neurosci 2002;22:455–63. 27 Padilla N, Junque C, Figueras F, Sanz-Cortes M, Bargallo N, Arranz A, et al. Differential vulnerability of gray matter and white matter to intrauterine growth restriction in preterm infants at 12 months corrected age. Brain Res 2014;1545:1–11. 28 Reid MV, Murray KA, Marsh ED, Golden JA, Simmons RA, Grinspan JB. Delayed myelination in an intrauterine growth retardation model is mediated by oxidative stress upregulating bone morphogenetic protein 4. J Neuropathol Exp Neurol 2012;71:640–53. 29 Romanini C, Rizzo G. Fetal behaviour in normal and compromised fetuses. An overview.. Early Human Dev 1995;43:117–31. 30 Schneider U, Fiedler A, Liehr M, Kahler C, Schleussner E. Fetal heart rate variability in growth restricted fetuses. Biomed Tech (Berl) 2006;51:248–50. 31 Lin CC, Su SJ, River LP. Comparison of associated high-risk factors and perinatal outcome between symmetric and asymmetric fetal intrauterine growth retardation. Am J Obstet Gynecol 1991;1:1535– 41 discussion 41–2. 32 Eswaran H, Govindan RB, Haddad NI, Siegel ER, Preissl HT, Murphy P, et al. Spectral power differences in the brain activity of growth-restricted and normal fetuses. Early Human Dev 2012; 88:451–4.
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