3D in utero quantification of T2* relaxation times in human fetal brain tissues for age optimized structural and functional MRI

In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences

PURPOSE

We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements.

METHODS

Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system.

RESULTS

The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies.

CONCLUSION

The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

T2*-Relaxometry MRI to Assess Third Trimester Placental and Fetal Brain Oxygenation and Placental Characteristics in Healthy Fetuses and Fetuses With Congenital Heart Disease

BACKGROUND

Congenital heart disease (CHD) has been linked to impaired placental and fetal brain development. Assessing the placenta and fetal brain in parallel may help further our understanding of the relationship between development of these organs.

HYPOTHESIS

1) Placental and fetal brain oxygenation are correlated, 2) oxygenation in these organs is reduced in CHD compared to healthy controls, and 3) placental structure is altered in CHD.

STUDY TYPE

Retrospective case-control.

POPULATION

Fifty-one human fetuses with CHD (32 male; median [IQR] gestational age [GA] = 32.0 [30.9-32.9] weeks) and 30 from uncomplicated pregnancies with normal birth outcomes (18 male; median [IQR] GA = 34.5 [31.9-36.7] weeks).

FIELD STRENGTH/SEQUENCE

1.5 T single-shot multi-echo-gradient-echo echo-planar imaging.

ASSESSMENT

Masking was performed using an automated nnUnet model. Mean brain and placental T2* and quantitative measures of placental texture, volume, and morphology were calculated.

STATISTICAL TESTS

Spearman's correlation coefficient for determining the association between brain and placental T2*, and between brain and placental characteristics with GA. P-values for comparing brain T2*, placenta T2*, and placental characteristics between groups derived from ANOVA. Significance level P < 0.05.

RESULTS

There was a significant positive association between placental and fetal brain T2* (⍴ = 0.46). Placental and fetal brain T2* showed a significant negative correlation with GA (placental T2* ⍴ = -0.65; fetal brain T2* ⍴ = -0.32). Both placental and fetal brain T2* values were significantly reduced in CHD, after adjusting for GA (placental T2*: control = 97 [±24] msec, CHD = 83 [±23] msec; brain T2*: control = 218 [±26] msec, CHD = 202 [±25] msec). Placental texture and morphology were also significantly altered in CHD (Texture: control = 0.84 [0.83-0.87], CHD = 0.80 [0.78-0.84]; Morphology: control = 9.9 [±2.2], CHD = 10.8 [±2.0]). For all fetuses, there was a significant positive association between placental T2* and placental texture (⍴ = 0.46).

CONCLUSION

Placental and fetal brain T2* values are associated in healthy fetuses and those with CHD. Placental and fetal brain oxygenation are reduced in CHD. Placental appearance is significantly altered in CHD and shows associations with placental oxygenation, suggesting altered placental development and function may be related.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Functional MRI assessment of the lungs in fetuses that deliver very Preterm: An MRI pilot study

OBJECTIVES

To compare mean pulmonary T2* values and pulmonary volumes in fetuses that subsequently spontaneously delivered before 32 weeks with a control cohort with comparable gestational ages and to assess the value of mean pulmonary T2* as a predictor of preterm birth < 32 weeks' gestation.

METHODS

MRI datasets scanned at similar gestational ages were selected from fetuses who spontaneously delivered < 32 weeks of gestation and a control group who subsequently delivered at term with no complications. All women underwent a fetal MRI on a 3 T MRI imaging system. Sequences included T2-weighted single shot fast spin echo and T2* sequences, using gradient echo single shot echo planar sequencing of the fetal thorax. Motion correction was performed using slice-to-volume reconstruction and T2* maps generated using in-house pipelines. Lungs were manually segmented and volumes and mean T2* values calculated for both lungs combined and left and right lung separately. Linear regression was used to compare values between the preterm and control cohorts accounting for the effects of gestation. Receiver operating curves were generated for mean T2* values and pulmonary volume as predictors of preterm birth < 32 weeks' gestation.

RESULTS

Datasets from twenty-eight preterm and 74 control fetuses were suitable for analysis. MRI images were taken at similar fetal gestational ages (preterm cohort (mean ± SD) 24.9 ± 3.3 and control cohort (mean ± SD) 26.5 ± 3.0). Mean gestational age at delivery was 26.4 ± 3.3 for the preterm group and 39.9 ± 1.3 for the control group. Mean pulmonary T2* values remained constant with increasing gestational age while pulmonary volumes increased. Both T2* and pulmonary volumes were lower in the preterm group than in the control group for all parameters (both combined, left, and right lung (p < 0.001 in all cases). Adjusted for gestational age, pulmonary volumes and mean T2* values were good predictors of premature delivery in fetuses < 32 weeks (area under the curve of 0.828 and 0.754 respectively).

CONCLUSION

These findings indicate that mean pulmonary T2* values and volumes were lower in fetuses that subsequently delivered very preterm. This may suggest potentially altered oxygenation and indicate that pulmonary morbidity associated with prematurity has an antenatal antecedent. Future work should explore these results correlating antenatal findings with long term pulmonary outcomes.

Functional assessment of brain development in fetuses that subsequently deliver very preterm: An MRI pilot study

OBJECTIVES

To evaluate changes occurring in the fetal brain prior to very preterm delivery using MRI T2* relaxometry, an indirect assessment of tissue perfusion.

METHOD

Fetuses that subsequently delivered spontaneously <32 weeks gestation and a control cohort were identified from pre-existing datasets. Participants had undergone a 3T MRI assessment including T2* relaxometry of the fetal brain using a 2D multi-slice gradient echo single shot echo planar imaging sequence. T2* maps were generated, supratentorial brain tissue was manually segmented and mean T2* values were generated. Groups were compared using quadratic regression.

RESULTS

Twenty five fetuses that subsequently delivered <32 weeks and 67 that delivered at term were included. Mean gestation at MRI was 24.5 weeks (SD 3.3) and 25.4 weeks (SD 3.1) and gestation at delivery 25.5 weeks (SD 3.4) and 39.7 weeks (SD 1.2) in the preterm and term cohorts respectively. Brain mean T2* values were significantly lower in fetuses that subsequently delivered before 32 weeks gestation (p < 0.001).

CONCLUSION

Alterations in brain maturation appear to occur prior to preterm delivery. Further work is required to explore these associations, but these findings suggest a potential window for therapeutic neuroprotective agents in fetuses at high risk of preterm delivery in the future.

An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field

Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artefacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we introduce a semi-automatic pipeline using quantitative MRI for the fetal body at low field strength resulting in fast and detailed quantitative T2* relaxometry analysis of all major fetal body organs. Multi-echo dynamic sequences of the fetal body were acquired and reconstructed into a single high-resolution volume using deformable slice-to-volume reconstruction, generating both structural and quantitative T2* 3D volumes. A neural network trained using a semi-supervised approach was created to automatically segment these fetal body 3D volumes into ten different organs (resulting in dice values > 0.74 for 8 out of 10 organs). The T2* values revealed a strong relationship with GA in the lungs, liver, and kidney parenchyma (R2 >0.5). This pipeline was used successfully for a wide range of GAs (17-40 weeks), and is robust to motion artefacts. Low field fetal MRI can be used to perform advanced MRI analysis, and is a viable option for clinical scanning.

Exploring the role of a time-efficient MRI assessment of the placenta and fetal brain in uncomplicated pregnancies and these complicated by placental insufficiency

INTRODUCTION

The development of placenta and fetal brain are intricately linked. Placental insufficiency is related to poor neonatal outcomes with impacts on neurodevelopment. This study sought to investigate whether simultaneous fast assessment of placental and fetal brain oxygenation using MRI T2* relaxometry can play a complementary role to US and Doppler US.

METHODS

This study is a retrospective case-control study with uncomplicated pregnancies (n = 99) and cases with placental insufficiency (PI) (n = 49). Participants underwent placental and fetal brain MRI and contemporaneous ultrasound imaging, resulting in quantitative assessment including a combined MRI score called Cerebro-placental-T2*-Ratio (CPTR). This was assessed in comparison with US-derived Cerebro-Placental-Ratio (CPR), placental histopathology, assessed using the Amsterdam criteria [1], and delivery details.

RESULTS

Pplacental and fetal brain T2* decreased with increasing gestational age in both low and high risk pregnancies and were corrected for gestational-age alsosignificantly decreased in PI. Both CPR and CPTR score were significantly correlated with gestational age at delivery for the entire cohort. CPTR was, however, also correlated independently with gestational age at delivery in the PI cohort. It furthermore showed a correlation to birth-weight-centile in healthy controls.

DISCUSSION

This study indicates that MR analysis of the placenta and brain may play a complementary role in the investigation of fetal development. The additional correlation to birth-weight-centile in controls may suggest a role in the determination of placental health even in healthy controls. To our knowledge, this is the first study assessing quantitatively both placental and fetal brain development over gestation in a large cohort of low and high risk pregnancies. Future larger prospective studies will include additional cohorts.

Assessment of normal pulmonary development using functional magnetic resonance imaging techniques

BACKGROUND

The mainstay of assessment of the fetal lungs in clinical practice is via evaluation of pulmonary size, primarily using 2D ultrasound and more recently with anatomical magnetic resonance imaging. The emergence of advanced magnetic resonance techniques such as T2* relaxometry in combination with the latest motion correction post-processing tools now facilitates assessment of the metabolic activity or perfusion of fetal pulmonary tissue in vivo.

OBJECTIVE

This study aimed to characterize normal pulmonary development using T2* relaxometry, accounting for fetal motion across gestation.

METHODS

Datasets from women with uncomplicated pregnancies that delivered at term, were analyzed. All subjects had undergone T2-weighted imaging and T2* relaxometry on a Phillips 3T magnetic resonance imaging system antenatally. T2* relaxometry of the fetal thorax was performed using a gradient echo single-shot echo planar imaging sequence. Following correction for fetal motion using slice-to-volume reconstruction, T2* maps were generated using in-house pipelines. Lungs were manually segmented and mean T2* values calculated for the right and left lungs individually, and for both lungs combined. Lung volumes were generated from the segmented images, and the right and left lungs, as well as both lungs combined were assessed.

RESULTS

Eighty-seven datasets were suitable for analysis. The mean gestation at scan was 29.9±4.3 weeks (range: 20.6-38.3) and mean gestation at delivery was 40±1.2 weeks (range: 37.1-42.4). Mean T2* values of the lungs increased over gestation for right and left lungs individually and for both lungs assessed together (P=.003; P=.04; P=.003, respectively). Right, left, and total lung volumes were also strongly correlated with increasing gestational age (P<.001 in all cases).

CONCLUSION

This large study assessed developing lungs using T2* imaging across a wide gestational age range. Mean T2* values increased with gestational age, which may reflect increasing perfusion and metabolic requirements and alterations in tissue composition as gestation advances. In the future, evaluation of findings in fetuses with conditions known to be associated with pulmonary morbidity may lead to enhanced prognostication antenatally, consequently improving counseling and perinatal care planning.

Fetal behavior during MRI changes with age and relates to network dynamics

Fetal motor behavior is an important clinical indicator of healthy development. However, our understanding of associations between fetal behavior and fetal brain development is limited. To fill this gap, this study introduced an approach to automatically and objectively classify long durations of fetal movement from a continuous four-dimensional functional magnetic resonance imaging (fMRI) data set, and paired behavior features with brain activity indicated by the fMRI time series. Twelve-minute fMRI scans were conducted in 120 normal fetuses. Postnatal motor function was evaluated at 7 and 36 months age. Fetal motor behavior was quantified by calculating the frame-wise displacement (FD) of fetal brains extracted by a deep-learning model along the whole time series. Analyzing only low motion data, we characterized the recurring coactivation patterns (CAPs) of the supplementary motor area (SMA). Results showed reduced motor activity with advancing gestational age (GA), likely due in part to loss of space (r = -.51, p < .001). Evaluation of individual variation in motor movement revealed a negative association between movement and the occurrence of coactivations within the left parietotemporal network, controlling for age and sex (p = .003). Further, we found that the occurrence of coactivations between the SMA to posterior brain regions, including visual cortex, was prospectively associated with postnatal motor function at 7 months (r = .43, p = .03). This is the first study to pair fetal movement and fMRI, highlighting potential for comparisons of fetal behavior and neural network development to enhance our understanding of fetal brain organization.

T2* weighted fetal MRI and the correlation with placental dysfunction

INTRODUCTION

Transverse relaxation time (T2*) is related to tissue oxygenation and morphology. We aimed to describe T2* weighted MRI in selected fetal organs in normal pregnancies, and to investigate the correlation between fetal organ T2* and placental T2*, birthweight (BW) deviation, and redistribution of fetal blood flow.

METHODS

T2*-weighted MRI was performed in 126 singleton pregnancies between 23+6- and 41+3-weeks' gestation. The T2* value was obtained from the placenta and fetal organs (brain, lungs, heart, liver, kidneys, and spleen). In normal BW pregnancies (BW > 10th centile), the correlation between the T2* value and gestational age (GA) at MRI was estimated by linear regression. The correlation between fetal organ Z-score and BW group was demonstrated by boxplots and investigated by analysis of variance (ANOVA) for each organ.

RESULTS

In normal BW pregnancies fetal organ T2* was negatively correlated with GA. We found a significant correlation between BW group and fetal organ T2* z-score in the fetal heart, kidney, lung and spleen. A positive linear correlation was demonstrated between fetal organ T2* and outcomes related to placental function such as BW deviation and placenta T2* in all investigated fetal organs except for the fetal liver. In the fetal heart, kidneys, and spleen the T2* value showed a significant correlation with fetal redistribution of blood flow (Middle cerebral artery Pulsatility Index) before delivery.

DISCUSSION

Fetal T2* is correlated with BW, placental function, and redistribution of fetal blood flow, suggesting that fetal organ T2* reflects fetal oxygenation and morphological changes related to placental dysfunction.

Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders

Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

Early development of sleep and brain functional connectivity in term-born and preterm infants

The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. IMPACT: Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.

APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation

PURPOSE

Artificial-intelligence population-based automated quantification of placental maturation and health from a rapid functional Magnetic Resonance scan. The placenta plays a crucial role for any successful human pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Antenatal assessment in-vivo using T2* relaxometry has shown great promise to inform management and possible interventions but clinical translation is hampered by time consuming manual segmentation and analysis techniques based on comparison against normative curves over gestation.

METHODS

This study proposes a fully automatic pipeline to predict the biological age and health of the placenta based on a free-breathing rapid (sub-30 second) T2* scan in two steps: Automatic segmentation using a U-Net and a Gaussian process regression model to characterize placental maturation and health. These are trained and evaluated on 108 3T MRI placental data sets, the evaluation included 20 high-risk pregnancies diagnosed with pre-eclampsia and/or fetal growth restriction. An independent cohort imaged at 1.5 T is used to assess the generalization of the training and evaluation pipeline.

RESULTS

Across low- and high-risk groups, automatic segmentation performs worse than inter-rater performance (mean Dice coefficients of 0.58 and 0.68, respectively) but is sufficient for estimating placental mean T2* (0.986 Pearson Correlation Coefficient). The placental health prediction achieves an excellent ability to differentiate cases of placental insufficiency between 27 and 33 weeks. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5 T illustrates the ability for direct clinical translation.

CONCLUSION

The presented automatic pipeline facilitates a fast, robust and reliable prediction of placental maturation. It yields human-interpretable and verifiable intermediate results and quantifies uncertainties on the cohort-level and for individual predictions. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency. APPLAUSE generalizes to an independent cohort imaged at 1.5 T, demonstrating robustness to different operational and clinical environments.

Fetal Cerebral Oxygenation Is Impaired in Congenital Heart Disease and Shows Variable Response to Maternal Hyperoxia

Background

Impairments in fetal oxygen delivery have been implicated in brain dysmaturation seen in congenital heart disease (CHD), suggesting a role for in utero transplacental oxygen therapy. We applied a novel imaging tool to quantify fetal cerebral oxygenation by measuring T2* decay. We compared T2* in fetuses with CHD with controls with a focus on cardiovascular physiologies (transposition or left‐sided obstruction) and described the effect of brief administration of maternal hyperoxia on T2* decay.

Methods and Results

This is a prospective study performed on pregnant mothers with a prenatal diagnosis of CHD compared with controls in the third trimester. Participants underwent a fetal brain magnetic resonance imaging scan including a T2* sequence before and after maternal hyperoxia. Comparisons were made between control and CHD fetuses including subgroup analyses by cardiac physiology. Forty‐four mothers (CHD=24, control=20) participated. Fetuses with CHD had lower total brain volume (238.2 mm³, 95% CI, 224.6–251.9) compared with controls (262.4 mm³, 95% CI, 245.0–279.8, P=0.04). T2* decay time was faster in CHD compared with controls (beta=−14.4, 95% CI, −23.3 to −5.6, P=0.002). The magnitude of change in T2* with maternal hyperoxia was higher in fetuses with transposition compared with controls (increase of 8.4 ms, 95% CI, 0.5–14.3, P=0.01), though between‐subject variability was noted.

Conclusions

Cerebral tissue oxygenation is lower in fetuses with complex CHD. There was variability in the response to maternal hyperoxia by CHD subgroup that can be tested in future larger studies. Cardiovascular physiology is critical when designing neuroprotective clinical trials in the fetus with CHD.

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

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

Developmental Pathoconnectomics and Advanced Fetal MRI

Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.

Fetal Echoplanar Imaging: Promises and Challenges

Fetal magnetic resonance imaging (MRI) has been gaining increasing interest in both clinical radiology and research. Echoplanar imaging (EPI) offers a unique potential, as it can be used to acquire images very fast. It can be used to freeze motion, or to get multiple images with various contrast mechanisms that allow studying the microstructure and function of the fetal brain and body organs. In this article, we discuss the current clinical and research applications of fetal EPI. This includes T2*-weighted imaging to better identify blood products and vessels, using diffusion-weighted MRI to investigate connections of the developing brain and using functional MRI (fMRI) to identify the functional networks of the developing brain. EPI can also be used as an alternative structural sequence when banding or standing wave artifacts adversely affect the mainstream sequences used routinely in structural fetal MRI. We also discuss the challenges with EPI acquisitions, and potential solutions. As EPI acquisitions are inherently sensitive to susceptibility artifacts, geometric distortions limit the use of high-resolution EPI acquisitions. Also, interslice motion and transmit and receive field inhomogeneities may create significant artifacts in fetal EPI. We conclude by discussing promising research directions to overcome these challenges to improve the use of EPI in clinical and research applications.

Neonatal brain injury and aberrant connectivity

Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches capable of identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.

Recent advances in the use of MRI to assess early human cortical development

Over the past decade, a number of advanced magnetic resonance-based methods have been brought to bear on questions related to early development of the human cerebral cortex. Herein, we describe studies employing analysis of cortical surface folding (cortical cartography), cortical microstructure (diffusion anisotropy), and cortically-based functional networks (resting state-functional connectivity MRI). The fundamentals of each MR method are described, followed by a discussion of application of the method to developing cortex and potential clinical uses. We use premature birth as an exemplar of how these modalities can be used to investigate the effects of medical and environmental variables on early cortical development.

Quantitative Assessment of Normal Fetal Brain Myelination Using Fast Macromolecular Proton Fraction Mapping

BACKGROUND AND PURPOSE

Fast macromolecular proton fraction mapping is a recently emerged MRI method for quantitative myelin imaging. Our aim was to develop a clinically targeted technique for macromolecular proton fraction mapping of the fetal brain and test its capability to characterize normal prenatal myelination.

MATERIALS AND METHODS

This prospective study included 41 pregnant women (gestational age range, 18-38 weeks) without abnormal findings on fetal brain MR imaging performed for clinical indications. A fast fetal brain macromolecular proton fraction mapping protocol was implemented on a clinical 1.5T MR imaging scanner without software modifications and was performed after a clinical examination with an additional scan time of <5 minutes. 3D macromolecular proton fraction maps were reconstructed from magnetization transfer-weighted, T1-weighted, and proton density-weighted images by the single-point method. Mean macromolecular proton fraction in the brain stem, cerebellum, and thalamus and frontal, temporal, and occipital WM was compared between structures and pregnancy trimesters using analysis of variance. Gestational age dependence of the macromolecular proton fraction was assessed using the Pearson correlation coefficient (r).

RESULTS

The mean macromolecular proton fraction in the fetal brain structures varied between 2.3% and 4.3%, being 5-fold lower than macromolecular proton fraction in adult WM. The macromolecular proton fraction in the third trimester was higher compared with the second trimester in the brain stem, cerebellum, and thalamus. The highest macromolecular proton fraction was observed in the brain stem, followed by the thalamus, cerebellum, and cerebral WM. The macromolecular proton fraction in the brain stem, cerebellum, and thalamus strongly correlated with gestational age (r = 0.88, 0.80, and 0.73; P < .001). No significant correlations were found for cerebral WM regions.

CONCLUSIONS

Myelin is the main factor determining macromolecular proton fraction in brain tissues. Macromolecular proton fraction mapping is sensitive to the earliest stages of the fetal brain myelination and can be implemented in a clinical setting.

Inner-volume echo volumar imaging (IVEVI) for robust fetal brain imaging

PURPOSE

Fetal functional MRI studies using conventional 2-dimensional single-shot echo-planar imaging sequences may require discarding a large data fraction as a result of fetal and maternal motion. Increasing the temporal resolution using echo volumar imaging (EVI) could provide an effective alternative strategy. Echo volumar imaging was combined with inner volume (IV) imaging (IVEVI) to locally excite the fetal brain and acquire full 3-dimensional images, fast enough to freeze most fetal head motion.

METHODS

IVEVI was implemented by modifying a standard multi-echo echo-planar imaging sequence. A spin echo with orthogonal excitation and refocusing ensured localized excitation. To introduce T2* weighting and to save time, the k-space center was shifted relative to the spin echo. Both single and multi-shot variants were tested. Acoustic noise was controlled by adjusting the amplitude and switching frequency of the readout gradient. Image-based shimming was used to minimize B₀ inhomogeneities within the fetal brain.

RESULTS

The sequence was first validated in an adult. Eight fetuses were scanned using single-shot IVEVI at a 3.5 × 3.5 × 5.0 mm³ resolution with a readout duration of 383 ms. Multishot IVEVI showed reduced geometric distortions along the second phase-encode direction.

CONCLUSIONS

Fetal EVI remains challenging. Although effective echo times comparable to the T2* values of fetal cortical gray matter at 3 T could be achieved, controlling acoustic noise required longer readouts, leading to substantial distortions in single-shot images. Although multishot variants enabled us to reduce susceptibility-induced geometric distortions, sensitivity to motion was increased. Future studies should therefore focus on improvements to multishot variants. Magn Reson Med 80:279-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine.