Advertisement
Research ArticlePediatrics

New Ultrasound Measurements to Bridge the Gap between Prenatal and Neonatal Brain Growth Assessment

I.V. Koning, J.A. Roelants, I.A.L. Groenenberg, M.J. Vermeulen, S.P. Willemsen, I.K.M. Reiss, P.P. Govaert, R.P.M. Steegers-Theunissen and J. Dudink
American Journal of Neuroradiology September 2017, 38 (9) 1807-1813; DOI: https://doi.org/10.3174/ajnr.A5278

Abstract

BACKGROUND AND PURPOSE: Most ultrasound markers for monitoring brain growth can only be used in either the prenatal or the postnatal period. We investigated whether corpus callosum length and corpus callosum–fastigium length could be used as markers for both prenatal and postnatal brain growth.

MATERIALS AND METHODS: A 3D ultrasound study embedded in the prospective Rotterdam Periconception Cohort was performed at 22, 26 and 32 weeks' gestational age in fetuses with fetal growth restriction, congenital heart defects, and controls. Postnatally, cranial ultrasound was performed at 42 weeks' postmenstrual age. First, reliability was evaluated. Second, associations between prenatal and postnatal corpus callosum and corpus callosum–fastigium length were investigated. Third, we created reference curves and compared corpus callosum and corpus callosum–fastigium length growth trajectories of controls with growth trajectories of fetuses with fetal growth retardation and congenital heart defects.

RESULTS: We included 199 fetuses; 22 with fetal growth retardation, 20 with congenital heart defects, and 157 controls. Reliability of both measurements was excellent (intraclass correlation coefficient ≥ 0.97). Corpus callosum growth trajectories were significantly decreased in fetuses with fetal growth restriction and congenital heart defects (β = −2.295; 95% CI, −3.320–1.270; P < .01; β = −1.267; 95% CI, −0.972–0.562; P < .01, respectively) compared with growth trajectories of controls. Corpus callosum–fastigium growth trajectories were decreased in fetuses with fetal growth restriction (β = −1.295; 95% CI, −2.595–0.003; P = .05).

CONCLUSIONS: Corpus callosum and corpus callosum–fastigium length may serve as reliable markers for monitoring brain growth from the prenatal into the postnatal period. The clinical applicability of these markers was established by the significantly different corpus callosum and corpus callosum–fastigium growth trajectories in fetuses at risk for abnormal brain growth compared with those of controls.

ABBREVIATIONS:

CC
corpus callosum
CCF
corpus callosum–fastigium
CHD
congenital heart defect
FGR
fetal growth restriction
GA
gestational age
US
ultrasound

In preterm infants and those small-for-gestational age, brain growth is an important predictor of neurodevelopmental outcome.1⇓⇓–4 Although prenatal growth often predicts postnatal growth, there is a traditional division between fetal and neonatal growth charts.5 This is mainly due to the lack of consistent measures of brain growth that can be used in both the prenatal and postnatal periods.

Markers of brain growth that can theoretically be used in both the prenatal and postnatal periods include head circumference and a few ultrasound (US) and MR imaging measures. Head circumference measured postnatally, however, lacks precision and does not correspond well with neurodevelopmental outcome.6,7 Prenatal and postnatal US markers are largely based on individual brain structures, only reflecting growth of a specific part of the brain.8⇓⇓⇓–12 Moreover, these brain structures are not measured consistently during the prenatal and postnatal periods due to the absence of corresponding standard US planes. Although MR imaging provides more precise measures of brain growth, volume, and development, this technique is expensive and therefore not suitable for serial measurements.

Recently, we demonstrated that corpus callosum–fastigium (CCF) length is a reliable bedside-available US marker that can be used to monitor brain growth in preterm infants during neonatal intensive care unit stays.13 CCF length is considered a composite marker of diencephalon and mesencephalon size and thereby adds information to the more widely used corpus callosum (CC) length.13 We hypothesized that these 2 cranial ultrasound measures are feasible for use during prenatal US examinations. Thereby, these markers would provide a continuum for monitoring brain growth, bridging the period before and after birth.

Our main aim was to investigate whether CC and CCF lengths can be used as reliable US markers for monitoring fetal and neonatal brain growth. First, we assessed the reliability of the measurements. Second, we created reference curves from 22 to 42 weeks' gestational age (GA) by combining fetal and neonatal measurements. Finally, as a first step to evaluate the clinical applicability of these US markers, we investigated CC and CCF growth trajectories in fetuses at risk of abnormal brain growth and compared them with those of control fetuses.

Materials And Methods

Study Design

This 3D-US study was embedded in the Rotterdam Periconceptional Cohort (Predict Study), an ongoing prospective cohort study at the Department of Obstetrics and Gynecology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands.14 At enrollment, all participating women and their partners gave written informed consent on behalf of themselves and their unborn child. This study was approved by the regional medical ethical committee and institutional review board of the Erasmus MC, University Medical Center in Rotterdam (MEC 2004-227; date of approval, January 25, 2013).

Pregnant women were enrolled between November 2013 and July 2015. They were either enrolled before 12 weeks' GA or between 22 and 32 weeks' GA. Controls were enrolled before 12 weeks' GA and were defined as fetuses without fetal growth restriction (FGR) before 32 weeks' GA, born after 37 weeks' GA, and without congenital anomalies. Cases included those pregnancies referred to our outpatient clinic with FGR or an isolated fetal congenital heart defect (CHD) between 22 and 32 weeks' GA. The diagnosis was confirmed by an extended structural US examination at our hospital. FGR was defined as abdominal circumference or estimated fetal weight percentile of <5 according to Hadlock et al.15

For this analysis, we excluded pregnancies ending in intrauterine fetal death, termination of pregnancy, or only preterm birth (without FGR or CHD). We also excluded fetuses with congenital anomalies other than CHD, with trisomy 21, and without US images.

Study Parameters

According to Dutch clinical practice, GA in spontaneously conceived pregnancies was calculated on the basis of the first trimester crown-rump length measurements before 13 weeks' GA.16 In pregnancies conceived through in vitro fertilization, with or without intracytoplasmic sperm injection procedures, GA was calculated from the date of oocyte retrieval plus 14 days or from the day of embryo transfer plus 17 or 18 days after cryopreserved embryo transfer, depending on the number of days between oocyte retrieval and cryopreservation.

Data were collected on maternal characteristics, medical and obstetric history, pregnancy course, and neonatal outcome from self-administered questionnaires in the first trimester, second trimester, and around delivery. Follow-up data on pregnancy outcomes were validated on the basis of a US report of the routine second trimester anomaly scan and on obstetric medical records.

Prenatal Sonography

Prenatal 3D-US examinations were performed on the Voluson E8 system (GE Healthcare, Milwaukee, Wisconsin) by using a 1 to 7 MHz transabdominal transducer or a 6 to 12 MHz transvaginal transducer. Primarily, we used an abdominal approach, but a transvaginal approach was considered when the fetus was in a head-down presentation. Serial prenatal 3D-US examinations and measurements were performed at 22, 26, and 32 weeks of gestation by 1 certified sonographer (I.V.K.). Standard biometry was measured, including biparietal diameter, head circumference, abdominal circumference, and femur length. An estimation of fetal weight was calculated with the Hadlock equation.15 Biometry was followed by detailed 3D neurosonography. Standard planes were obtained according to the International Society of Ultrasound in Obstetrics and Gynecology guidelines.17 CC and CCF length measurements were performed off-line in an exact midsagittal plane (Fig 1). CC length is measured from the genu to the splenium, outer-outer border. CCF length represents the length between the genu of the CC and the fastigium (roof of the fourth ventricle).13 CCF length was only measured in images in which CC measurement was performed successfully. Manipulation of the 3D-US volume to ensure an exact midsagittal plane for the measurements was performed in 4D View, Version 5.0 (GE Healthcare).

Fig 1.
Fig 1.

Prenatal measurement of CC and CCF lengths. 1, Corpus callosum length, outer-outer border. 2, Corpus callosum–fastigium length, from the genu of the corpus callosum to the fastigium (roof of the fourth ventricle).

Postnatal Assessments

After birth, cranial ultrasound was planned between 42 + 0 and 42 + 6 weeks' postmenstrual age, independent of GA at birth. Cranial ultrasound was performed by an experienced team of researchers with MyLab 70 (Esaote, Genoa, Italy) with a convex neonatal probe (7.5 MHz). CC and CCF length measurements were performed off-line by 1 researcher (J.A.R.) according to the method described above, with MyLab software.

To enhance precision, we repeated all prenatal and postnatal measurements 3 times. The mean values were used in the statistical analyses.

Statistical Analysis

For data analyses, we used SPSS (Release 21 for Windows; IBM, Armonk, New York) and R statistical and computing software, Version 3.1.3 (http://www.r-project.org). Results with P values < .05 were considered statistically significant.

Previously, we demonstrated that postnatal measurements of CC and CCF length had good intra- and interobserver agreement.13 To evaluate the reliability and reproducibility of prenatal measurements, we randomly selected 30 US examinations of 30 different fetuses, equally divided across the 3 prenatal time points from the whole study population. CC and CCF length measurements were then performed in 3-fold by 2 independent observers (I.V.K. [1] and J.A.R. [2]). We performed analyses for intra- and interobserver reliability, calculating the mean differences with 95% CIs and intraclass correlation coefficients. Moreover, the extent of agreement was examined with the Bland-Altman method.

Generalized Additive Models for Location and Scale were used to create reference ranges of CC and CCF length measurements between 22 and 42 weeks' GA in controls.18 To investigate whether cases showed deviations in CC and CCF growth, we created growth trajectories for each subject of the serial measurements of CC and CCF lengths between 22 and 42 weeks' GA. A maximum-likelihood approach was used to test whether polynomials of GA contributed to the best model fit. In the same manner, we tested the contribution of random and fixed effects of the intercept and slopes for all included polynomials. A quadratic model of GA with random intercept and slopes was designated as the best model. We placed the origin of the GA scale at 140 days' GA. In this model, the variable indicating whether a fetus was FGR, CHD, or control was used as the covariate of interest (model 1). Last, the final model (model 2) was adjusted for serial measurements of fetal weight and sex.

Results

Study Population

In total, 227 pregnant women were enrolled prenatally. After excluding pregnancies ending in intrauterine fetal death (n = 1), termination of pregnancy (n = 1), preterm birth (n = 14), and those with congenital anomalies other than CHD (n = 4), trisomy 21(n = 2), and withdrawals (n = 6), the study population consisted of 199 pregnancies. Of these 199 fetuses, 22 had FGR, 20 had CHD, and 157 were controls. The general characteristics of the study populations are listed in Table 1.

View this table:
Table 1:

Baseline characteristicsa

Success Rates and Reliability Analyses

Of 542 prenatal 3D-US scans, 377 contained a high-quality midsagittal plane eligible for CC and CCF length measurements. Means and success rates of CC and CCF length measurements per gestational age are listed in Table 2. Success rates ranged between 61% and 75% for prenatal CC length measurements and between 59% and 72% for prenatal CCF length measurements. Postnatally, CC and CCF length measurements were successful in 97%. In 83% of the subjects, CC length was measured at least at 2 time points during the whole study period, and CCF length, in 65%.

View this table:
Table 2:

Success rates and means of corpus callosum and corpus callosum–fastigium length per gestational agea

The intra- and interobserver reliability and agreement are shown in Table 3. CC lengths measured by observer 1 were slightly smaller (mean difference, −1.109 mm; mean percentage difference, −3.4%) than those measured by observer 2. Ninety-five percent limits of agreement for all measurements represented excellent agreement when the CC and CCF length measurements were repeated by the same observer and good agreement when repeated by a second observer. Intraclass correlation coefficient values of both intra- and interobserver were ≥0.97, which represents excellent reliability.

View this table:
Table 3:

Intraobserver and interobserver reliability for prenatal measurements of corpus callosum and corpus callosum–fastigium lengtha

Linear Mixed-Model Analyses

In Fig 2A, -B, the reference curves and individual growth trajectories of CC and CCF lengths are shown. The results of the linear mixed-models estimating differences in the mean growth trajectories of CC and CCF lengths among controls and fetuses with FGR and CHD are shown in Table 4. Growth trajectories of CC length were significantly decreased in fetuses with FGR and CHD compared with growth trajectories of controls. CCF growth trajectories were only significantly decreased in fetuses with FGR compared with those of controls. In Fig 2C, these trajectories are graphically displayed.

Fig 2.
Fig 2.

Growth curves. A, Reference curves between 22 and 42 weeks of gestation for CCF (left) and CC (right) length, with the 5th, 10th, 50th, 90th, and 95th percentiles. B, Individual growth trajectories of CCF (left) and CC (right) length between 22 and 42 weeks of gestation. C, Growth trajectories for controls (black) and fetuses with FGR (striped blue) and CHD (dotted red).

View this table:
Table 4:

Linear mixed models—growth trajectories of CC and CCF influenced by the presence of fetal growth restriction and congenital heart defectsa

Discussion

Here, we demonstrate that CCF and CC length may serve as reliable markers for monitoring prenatal and postnatal brain growth. Fetuses with FGR showed decreased growth of both CC and CCF length, while in fetuses with CHD, only CC growth was decreased between 22 and 42 weeks' GA.

Our findings suggest that we are able to bridge the traditional division between fetal and neonatal US growth charts. To date, studies that combine fetal and neonatal US markers of brain growth in a single cohort are scarce. One explanation is that standard prenatal US planes containing easily recognizable landmarks of the brain do not correspond well with the standardized planes accessible by cranial ultrasound. This lack of correspondence results in differences in prenatal and postnatal measures and measuring methods. For example, head circumference assessed prenatally, calculated from the biparietal diameter and occipital frontal diameter, correlates poorly with direct postnatal measurements with a tape measure.7,19 Furthermore, changes in head shape can be induced by delivery (eg, skull molding, edematous swelling, and hematomas).

In contrast to other prenatal US measurements, excellent reliability was shown for CC and CCF lengths, comparable with the reliability of the postnatal measurements.13 On the basis of our data, we suggest that CCF length is the most reliable and relevant marker for monitoring brain growth. CCF length can be assumed to be a composite marker of multiple brain structures with different embryologic origins. Therefore, CCF length may be a better representative of global brain growth than previous sonographic markers based on individual brain structures.8⇓⇓⇓–12

Growth trajectories of CC and CCF length were decreased in fetuses at risk for abnormal brain growth and impaired long-term neurodevelopmental outcome. While studies using CCF length have not been published in the literature before, CC length findings are in line with those in previous literature. The decreased CC growth trajectories in fetuses with FGR are in accordance with findings of a recent MR imaging study that showed significantly reduced CC length in fetuses with FGR compared with CC length of appropriate-for-gestational-age controls.20 Results from our previous study in preterm infants demonstrated a similar association between CCF length and birth weight SD score.13 There are, to the best of our knowledge, no publications on CC length in fetuses with CHD with which to compare our results, though previous studies did report anomalies of the CC and reduction of CC volume in children with CHD.21,22 The decreased growth trajectory of CC length in fetuses with CHD is, however, supported by accumulating evidence reporting that fetuses with CHD are at risk for abnormal brain growth and development.23⇓⇓–26

Brain growth is an important predictor of neurodevelopmental outcome.1,3,27 We hypothesize that the decreased CC and CCF growth trajectories observed in cases may have consequences for long-term outcome. In preterm infants, a shorter CC length is related to a higher risk of an adverse neurodevelopmental outcome at 2 years' corrected age.4 Moreover, a significantly smaller corpus callosum was found in individuals with schizophrenia and autism.28,29 CCF length represents the diencephalon and thus includes thalamus development, which is crucial for cognitive functioning. Derangements in thalamus development are associated with adverse neurodevelopmental outcome.30 Yet, the clinical relevance for neurodevelopmental outcome of differences in CC and CCF growth trajectories needs further investigation.

Clinical Applicability

The landmarks used for CC and CCF length measurements are relatively easy to distinguish on US images. Prenatally, the main challenge is obtaining an exact midsagittal plane. The prenatal success rates are predominantly influenced by acoustic shadowing and the position of the fetus. 3D-US can enhance precision by manipulating volumes to reconstruct the exact midsagittal plane.31⇓–33 When a midsagittal plane is obtained, both measurements take <1 minute in experienced hands. Postnatally, a standard midsagittal plane is easy to obtain through the anterior fontanelle; also, the off-line measurements of CC and CCF lengths take <1 minute. Newly developed software that enables the identification of the midline automatically could still improve the measurements for clinical practice.34

Strengths and Limitations

Some considerations should be taken into account. First, our study was conducted in a tertiary hospital population, with a relatively high maternal age, mainly of Western origin, and a high educational level. Therefore, replication of the data is warranted to validate our findings for the general population. Second, the small number of cases limits the conclusions of our study. We cannot exclude that absence of statistically significant findings may be due to lack of power. Third, the growth charts are based on measurements at 4 time points and may improve by including intermediate time points to further smooth the curves. Finally, the US scans and measurements were performed by experienced observers, which potentially enhanced the quality of the midsagittal images and thus success rates and reliability. Clinical applicability may be overestimated as a consequence. Success rates of the measurements were mostly influenced by fetal position, which we assume to be independent of the variables in this study. We consider the prospective and longitudinal study design as a strength of our study. Combining prenatal and postnatal measurements in 1 reference curve is an innovative method to facilitate monitoring of fetuses at risk of impaired brain growth.

Future Implications for Clinical Care and Research

Tight collaboration between obstetric and neonatal researchers and caregivers is needed for bridging the gap when monitoring fetal and neonatal brain growth. This is of great importance for optimizing neurodevelopmental care in fetuses and infants at risk of abnormal brain growth and neurodevelopmental impairment. Easily applicable US tools that can be used independent of the prenatal or postnatal period will have clinical implications. We consider our reference curves useful for age-equivalent preterm infants because they are largely comparable with the postnatal reference curves between 24 and 32 weeks in preterm infants from Roelants et al.13 In addition, CC and CCF length measurements may be applicable from midgestation onward and may theoretically be prolonged until closure of the anterior fontanelle in the first year of life. Future research should correlate these measurements to commonly used MR imaging markers and explore the link between the growth measures and functional neurodevelopmental outcome.

Conclusions

In this prospective cohort, we demonstrated that CC and CCF length measurements are reliable markers for brain growth from the fetal into the early neonatal period. By combining prenatal and postnatal CC and CCF length measurements in 1 reference curve, we created a continuum for monitoring brain growth, irrespective of the intra- or extra-uterine environment. We demonstrated that fetuses at risk of abnormal brain growth (ie, those with CHD and FGR) showed significantly decreased CC and CCF growth between 22 and 42 weeks' GA. Whether these markers could serve as early predictors of neurodevelopmental outcome in later life warrants further research.

Acknowledgments

We thank the Department of Obstetrics and Gynecology, Division of Obstetrics and Prenatal Medicine, Erasmus MC, University Medical Center, and the research group of the Rotterdam Predict study for their contribution to the study.

Footnotes

  • Disclosures: Irene V. Koning—RELATED: Grant: Sophia Foundation for Medical Research, Comments: grant No. 644.

  • This work was supported by a grant of the Sophia Children's Hospital Fund, Rotterdam, the Netherlands (Sophia Foundation for Medical Research, grant No. 644).

References

  1. 1.↵
    2. Young JM,
    3. Powell TL,
    4. Morgan BR, et al
    . Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children. Neuroimage 2015;111:360–68 doi:10.1016/j.neuroimage.2015.02.030 pmid:25711136
    CrossRefPubMed
  2. 2.↵
    2. Lee W,
    3. Al-Dossary H,
    4. Raybaud C, et al
    . Longitudinal cerebellar growth following very preterm birth. J Magn Reson Imaging 2016;43:1462–73 doi:10.1002/jmri.25098 pmid:26595366
    CrossRefPubMed
  3. 3.↵
    2. Stiles J,
    3. Jernigan TL
    . The basics of brain development. Neuropsychol Rev 2010;20:327–48 doi:10.1007/s11065-010-9148-4 pmid:21042938
    CrossRefPubMed
  4. 4.↵
    2. Park HW,
    3. Yoon HK,
    4. Han SB, et al
    . Brain MRI measurements at a term-equivalent age and their relationship to neurodevelopmental outcomes. AJNR Am J Neuroradiol 2014;35:599–603 doi:10.3174/ajnr.A3720 pmid:23988755
    Abstract/FREE Full Text
  5. 5.↵
    2. van Uitert EM,
    3. Exalto N,
    4. Burton GJ, et al
    . Human embryonic growth trajectories and associations with fetal growth and birthweight. Hum Reprod 2013;28:1753–61 doi:10.1093/humrep/det115 pmid:23569080
    CrossRefPubMed
  6. 6.↵
    2. Kan E,
    3. Roberts G,
    4. Anderson PJ, et al
    . The association of growth impairment with neurodevelopmental outcome at eight years of age in very preterm children. Early Hum Dev 2008;84:409–16 doi:10.1016/j.earlhumdev.2007.11.002 pmid:18096332
    CrossRefPubMed
  7. 7.↵
    2. Sutter K,
    3. Engstrom JL,
    4. Johnson TS, et al
    . Reliability of head circumference measurements in preterm infants. Pediatr Nurs 1997;23:485–90 pmid:9355585
    PubMed
  8. 8.↵
    2. Anderson NG,
    3. Laurent I,
    4. Cook N, et al
    . Growth rate of corpus callosum in very premature infants. AJNR Am J Neuroradiol 2005;26:2685–90 pmid:16286423
    Abstract/FREE Full Text
  9. 9.↵
    2. Imamoglu EY,
    3. Gursoy T,
    4. Ovali F, et al
    . Nomograms of cerebellar vermis height and transverse cerebellar diameter in appropriate-for-gestational-age neonates. Early Hum Dev 2013;89:919–23 doi:10.1016/j.earlhumdev.2013.10.001 pmid:24183100
    CrossRefPubMed
  10. 10.↵
    2. Hagmann CF,
    3. Robertson NJ,
    4. Acolet D, et al
    . Cerebral measurements made using cranial ultrasound in term Ugandan newborns. Early Hum Dev 2011;87:341–47 doi:10.1016/j.earlhumdev.2011.01.044 pmid:21353402
    CrossRefPubMed
  11. 11.↵
    2. Maunu J,
    3. Parkkola R,
    4. Rikalainen H, et al
    . Brain and ventricles in very low birth weight infants at term: a comparison among head circumference, ultrasound, and magnetic resonance imaging. Pediatrics 2009;123:617–26 doi:10.1542/peds.2007-3264 pmid:19171630
    Abstract/FREE Full Text
  12. 12.↵
    2. Rademaker KJ,
    3. Lam JN,
    4. Van Haastert IC, et al
    . Larger corpus callosum size with better motor performance in prematurely born children. Semin Perinatol 2004;28:279–87 doi:10.1053/j.semperi.2004.08.005 pmid:15565788
    CrossRefPubMed
  13. 13.↵
    2. Roelants JA,
    3. Koning IV,
    4. Raets MM, et al
    . A new ultrasound marker for bedside monitoring of preterm brain growth. AJNR Am J Neuroradiol 2016;37:1516–22 doi:10.3174/ajnr.A4731 pmid:26988817
    Abstract/FREE Full Text
  14. 14.↵
    2. Steegers-Theunissen RP,
    3. Verheijden-Paulissen JJ,
    4. van Uitert EM, et al
    . Cohort profile: the Rotterdam Periconceptional Cohort (Predict Study). Int J Epidemiol 2016;45:374–81 doi:10.1093/ije/dyv147 pmid:26224071
    CrossRefPubMed
  15. 15.↵
    2. Hadlock FP,
    3. Harrist RB,
    4. Sharman RS, et al
    . Estimation of fetal weight with the use of head, body, and femur measurements: a prospective study. Am J Obstet Gynecol 1985;151:333–37 doi:10.1016/0002-9378(85)90298-4 pmid:3881966
    CrossRefPubMed
  16. 16.↵
    2. Robinson HP,
    3. Fleming JE
    . A critical evaluation of sonar “crown-rump length” measurements. Br J Obstet Gynaecol 1975;82:702–10 doi:10.1111/j.1471-0528.1975.tb00710.x pmid:1182090
    CrossRefPubMed
  17. 17.↵
    2. Merz E,
    3. Benoit B,
    4. Blaas HG, et al
    ; ISUOG 3D Focus Group. Standardization of three-dimensional images in obstetrics and gynecology: consensus statement. Ultrasound Obstet Gynecol 2007;29:697–703 doi:10.1002/uog.4009 pmid:17523164
    CrossRefPubMed
  18. 18.↵
    2. Rigby RA,
    3. Stasinopoulos DM
    . Generalized additive models for location, scale and shape (with discussion). J R Stat Soc Ser C Appl Stat 2005;54:507–44 doi:10.1111/j.1467-9876.2005.00510.x
    CrossRef
  19. 19.↵
    2. Melamed N,
    3. Yogev Y,
    4. Danon D, et al
    . Sonographic estimation of fetal head circumference: how accurate are we? Ultrasound Obstet Gynecol 2011;37:65–71 doi:10.1002/uog.7760 pmid:20661958
    CrossRefPubMed
  20. 20.↵
    2. Egaña-Ugrinovic G,
    3. Sanz-Cortés M,
    4. Couve-Pérez C, et al
    . Corpus callosum differences assessed by fetal MRI in late-onset intrauterine growth restriction and its association with neurobehavior. Prenat Diagn 2014;34:843–49 doi:10.1002/pd.4381 pmid:24711150
    CrossRefPubMed
  21. 21.↵
    2. Mlczoch E,
    3. Brugger P,
    4. Ulm B, et al
    . Structural congenital brain disease in congenital heart disease: results from a fetal MRI program. Eur J Paediatr Neurol 2013;17:153–60 doi:10.1016/j.ejpn.2012.07.004 pmid:22944287
    CrossRefPubMed
  22. 22.↵
    2. von Rhein M,
    3. Buchmann A,
    4. Hagmann C, et al
    . Brain volumes predict neurodevelopment in adolescents after surgery for congenital heart disease. Brain 2014;137:268–76 doi:10.1093/brain/awt322 pmid:24277720
    CrossRefPubMed
  23. 23.↵
    2. Khalil A,
    3. Suff N,
    4. Thilaganathan B, et al
    . Brain abnormalities and neurodevelopmental delay in congenital heart disease: systematic review and meta-analysis. Ultrasound Obstet Gynecol 2014;43:14–24 doi:10.1002/uog.12526 pmid:23737029
    CrossRefPubMed
  24. 24.↵
    2. Jansen FA,
    3. Everwijn SM,
    4. Scheepjens R, et al
    . Fetal brain imaging in isolated congenital heart defects – a systematic review and meta-analysis. Prenat Diagn 2016;36:601–13 doi:10.1002/pd.4842 pmid:27187181
    CrossRefPubMed
  25. 25.↵
    2. Masoller N,
    3. Martinez JM,
    4. Gómez O, et al
    . Evidence of second-trimester changes in head biometry and brain perfusion in fetuses with congenital heart disease. Ultrasound Obstet Gynecol 2014;44:182–87 doi:10.1002/uog.13373 pmid:24687311
    CrossRefPubMed
  26. 26.↵
    2. Williams IA,
    3. Fifer WP,
    4. Andrews H
    . Fetal growth and neurodevelopmental outcome in congenital heart disease. Pediatr Cardiol 2015;36:1135–44 doi:10.1007/s00246-015-1132-6 pmid:25753684
    CrossRefPubMed
  27. 27.↵
    2. Henrichs J,
    3. Schenk JJ,
    4. Barendregt CS, et al
    . Fetal growth from mid- to late pregnancy is associated with infant development: the Generation R Study. Dev Med Child Neurol 2010;52:644–51 doi:10.1111/j.1469-8749.2009.03513.x pmid:19832882
    CrossRefPubMed
  28. 28.↵
    2. Piven J,
    3. Bailey J,
    4. Ranson BJ, et al
    . An MRI study of the corpus callosum in autism. Am J Psychiatry 1997;154:1051–56 doi:10.1176/ajp.154.8.1051 pmid:9247388
    CrossRefPubMed
  29. 29.↵
    2. Woodruff PW,
    3. McManus IC,
    4. David AS
    . Meta-analysis of corpus callosum size in schizophrenia. J Neurol Neurosurg Psychiatry 1995;58:457–61 doi:10.1136/jnnp.58.4.457 pmid:7738554
    Abstract/FREE Full Text
  30. 30.↵
    2. Eaton-Rosen Z,
    3. Melbourne A,
    4. Orasanu E, et al
    . Longitudinal measurement of the developing thalamus in the preterm brain using multi-modal MRI. Med Image Comput Comput Assist Interv 2014;17:276–83 pmid:25485389
    PubMed
  31. 31.↵
    2. Monteagudo A,
    3. Timor-Tritsch IE,
    4. Mayberry P
    . Three-dimensional transvaginal neurosonography of the fetal brain: ‘navigating’ in the volume scan. Ultrasound Obstet Gynecol 2000;16:307–13 doi:10.1046/j.1469-0705.2000.00264.x pmid:11169305
    CrossRefPubMed
  32. 32.↵
    2. Mueller GM,
    3. Weiner CP,
    4. Yankowitz J
    . Three-dimensional ultrasound in the evaluation of fetal head and spine anomalies. Obstet Gynecol 1996;88:372–78 doi:10.1016/0029-7844(96)00207-4 pmid:8752242
    CrossRefPubMed
  33. 33.↵
    2. Wang PH,
    3. Ying TH,
    4. Wang PC, et al
    . Obstetrical three-dimensional ultrasound in the visualization of the intracranial midline and corpus callosum of fetuses with cephalic position. Prenat Diagn 2000;20:518–20 pmid:10861721
    CrossRefPubMed
  34. 34.↵
    2. Yaqub M,
    3. Rueda S,
    4. Kopuri A, et al
    . Plane localization in 3-D fetal neurosonography for longitudinal analysis of the developing brain. IEEE J Biomed Health Inform 2016;20:1120–28 doi:10.1109/JBHI.2015.2435651 pmid:26011873
    CrossRefPubMed
  • Received December 23, 2016.
  • Accepted after revision April 24, 2017.
View Abstract
Back to top

In this issue

Advertisement
Print
Download PDF
Email Article
Citation Tools
New Ultrasound Measurements to Bridge the Gap between Prenatal and Neonatal Brain Growth Assessment
I.V. Koning, J.A. Roelants, I.A.L. Groenenberg, M.J. Vermeulen, S.P. Willemsen, I.K.M. Reiss, P.P. Govaert, R.P.M. Steegers-Theunissen, J. Dudink
American Journal of Neuroradiology Sep 2017, 38 (9) 1807-1813; DOI: 10.3174/ajnr.A5278
del.icio.us logo Twitter logo Facebook logo Mendeley logo
Purchase

Jump to section

Related Articles

  • No related articles found.

Cited By...

More in this TOC Section

Similar Articles

Advertisement