Validation of In utero Tractography of Human Fetal Commissural and Internal Capsule Fibers with Histological Structure Tensor Analysis

FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI

Diffusion MRI (dMRI) offers unique insights into the microstructure of fetal brain tissue in utero. Longitudinal and cross-sectional studies of fetal dMRI have the potential to reveal subtle but crucial changes associated with normal and abnormal neurodevelopment. However, these studies depend on precise spatial alignment of data across scans and subjects, which is particularly challenging in fetal imaging due to the low data quality, rapid brain development, and limited anatomical landmarks for accurate registration. Existing registration methods, primarily developed for superior-quality adult data, are not well-suited for addressing these complexities. To bridge this gap, we introduce FetDTIAlign, a deep learning approach tailored to fetal brain dMRI, enabling accurate affine and deformable registration. FetDTIAlign integrates a novel dual-encoder architecture and iterative feature-based inference, effectively minimizing the impact of noise and low resolution to achieve accurate alignment. Additionally, it strategically employs different network configurations and domain-specific image features at each registration stage, addressing the unique challenges of affine and deformable registration, enhancing both robustness and accuracy. We validated FetDTIAlign on a dataset covering gestational ages centered between 23 and 36 weeks, encompassing 60 white matter tracts. For all age groups, FetDTIAlign consistently showed superior anatomical correspondence and the best visual alignment in both affine and deformable registration, outperforming two classical optimization-based methods and a deep learning-based pipeline. Further validation on external data from the Developing Human Connectome Project demonstrated the generalizability of our method to data collected with different acquisition protocols. Our results show the feasibility of using deep learning for fetal brain dMRI registration, providing a more accurate and reliable alternative to classical techniques. By enabling precise cross-subject and tract-specific analyses, FetDTIAlign paves the way for new discoveries in early brain development. The code is available at https://gitlab.com/blibli/fetdtialign.

Validation of Structure Tensor Analysis for Orientation Estimation in Brain Tissue Microscopy

Accurate localization of white matter pathways using diffusion MRI is critical to investigating brain connectivity, but the accuracy of current methods is not thoroughly understood. A fruitful approach to validating accuracy is to consider microscopy data that have been co-registered with MRI of post mortem samples. In this setting, structure tensor analysis is a standard approach to computing local orientations for validation. However, structure tensor analysis itself has not been well-validated and is subject to uncertainty in its angular resolution, and selectivity to specific spatial scales. In this work, we conducted a simulation study to investigate the accuracy of using structure tensors to estimate the orientations of fibers arranged in configurations with and without crossings. We examined a range of simulated conditions, with a focus on investigating the method's behavior on images with anisotropic resolution, which is particularly common in microscopy data acquisition. We also analyzed 2D and 3D optical microscopy data. Our results show that parameter choice in structure tensor analysis has relatively little effect on accuracy for estimating single orientations, although accuracy decreases with anisotropy. On the other hand, when estimating the orientations of crossing fibers, the choice of parameters becomes critical, and poor choices result in orientation estimates that are essentially random. This work provides a set of recommendations for researchers seeking to apply structure tensor analysis effectively in the study of axonal orientations in brain imaging data and quantifies the method's limitations, particularly in the case of anisotropic data.

Magnetic resonance imaging and tractography of sensorimotor tracts in fetuses with intraventricular hemorrhage: feasibility and added prognostic value

OBJECTIVES

To assess the feasibility, characteristics and prognostic value of prenatal visualization of the corticospinal tracts (CSTs) using diffusion-weighted magnetic resonance imaging (MRI)-based tractography in fetuses with intraventricular hemorrhage (IVH).

METHODS

This was a retrospective single-center cohort study of singleton fetuses diagnosed with IVH on MRI from January 2011 to December 2018. The left and right CSTs were reconstructed according to an in-utero diffusion tensor imaging sequence using a multi-region of interest (ROI) deterministic tractography approach. The CSTs were segmented by two polygonal ROI: at the level of the posterior limb of the internal capsule and the crus cerebri. The morphology and integrity of the CSTs were assessed visually. Internal capsule and crus cerebri apparent diffusion coefficient and fractional anisotropy values were measured. Postnatal motor function data were obtained from the parents using the functional status scale.

RESULTS

A total of 35 fetuses with IVH (mean ± SD gestational age, 29.1 ± 5.1 (range, 19.9-38.9) weeks) were included in the analysis. Parenchymal involvement on T2-weighted sequences was demonstrated in 19 (54%) of the cohort. CST involvement correlated significantly with the presence of parenchymal damage on T2-weighted imaging (P = 0.02). Among liveborn cases, the rate of motor impairment was 14% (1/7) in children with intact CSTs compared with 100% (5/5) in cases in which the CSTs were impaired (P = 0.015).

CONCLUSIONS

Fetal corticospinal tractography is feasible technically and offers valuable prognostic information. It enhances parental counseling by providing insights into potential motor outcome, underscoring its utility in complementing fetal neurosonography in cases of prenatal IVH. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Multiparametric prenatal imaging characterization of fetal brain edema in Chiari II malformation might help to select candidates for fetal surgery

OBJECTIVE

To identify brain edema in fetuses with Chiari II malformation using a multiparametric approach including structural T2-weighted, diffusion tensor imaging (DTI) metrics, and MRI-based radiomics.

METHODS

A single-center retrospective review of MRI scans obtained in fetuses with Chiari II was performed. Brain edema cases were radiologically identified using the following MR criteria: brain parenchymal T2 prolongation, blurring of lamination, and effacement of external CSF spaces. Fractional anisotropy (FA) values were calculated from regions of interest (ROI), including hemispheric parenchyma, internal capsule, and corticospinal tract, and compared group-wise. After 1:1 age matching and manual single-slice 2D segmentation of the fetal brain parenchyma using ITK-Snap, radiomics features were extracted using pyradiomics. Areas under the curve (AUCs) of the features regarding discriminating subgroups were calculated.

RESULTS

Ninety-one fetuses with Chiari II underwent a total of 101 MRI scans at a median gestational age of 24.4 weeks and were included. Fifty scans were visually classified as Chiari II with brain edema group and showed significantly reduced external CSF spaces compared to the nonedema group (9.8 vs. 18.3 mm, p < 0.001). FA values of all used ROIs were elevated in the edema group (p < 0.001 for all ROIs). The 10 most important radiomics features showed an AUC of 0.81 (95%CI: 0.71, 0.91) for discriminating between Chiari II fetuses with and without edema.

CONCLUSIONS

Brain edema in fetuses with Chiari II is common and radiologically detectable on T2-weighted fetal MRI sequences, and DTI-based FA values and radiomics features provide further evidence of microstructure differences between subgroups with and without edema.

CLINICAL RELEVANCE STATEMENT

A more severe phenotype of fetuses with Chiari II malformation is characterized by prenatal brain edema and more postnatal clinical morbidity and disability. Fetal brain edema is a promising prenatal MR imaging biomarker candidate for optimizing the risk-benefit evaluation of selection for fetal surgery.

KEY POINTS

Brain edema of fetuses prenatally diagnosed with Chiari II malformation is a common, so far unknown, association. DTI metrics and radiomics confirm microstructural differences between the brains of Chiari II fetuses with and without edema. Fetal brain edema may explain worse motor outcomes in this Chiari II subgroup, who may substantially benefit from fetal surgery.

Streamline tractography of the fetal brain in utero with machine learning

Diffusion-weighted magnetic resonance imaging (dMRI) is the only non-invasive tool for studying white matter tracts and structural connectivity of the brain. These assessments rely heavily on tractography techniques, which reconstruct virtual streamlines representing white matter fibers. Much effort has been devoted to improving tractography methodology for adult brains, while tractography of the fetal brain has been largely neglected. Fetal tractography faces unique difficulties due to low dMRI signal quality, immature and rapidly developing brain structures, and paucity of reference data. To address these challenges, this work presents the first machine learning model, based on a deep neural network, for fetal tractography. The model input consists of five different sources of information: (1) Voxel-wise fiber orientation, inferred from a diffusion tensor fit to the dMRI signal; (2) Directions of recent propagation steps; (3) Global spatial information, encoded as normalized distances to keypoints in the brain cortex; (4) Tissue segmentation information; and (5) Prior information about the expected local fiber orientations supplied with an atlas. In order to mitigate the local tensor estimation error, a large spatial context around the current point in the diffusion tensor image is encoded using convolutional and attention neural network modules. Moreover, the diffusion tensor information at a hypothetical next point is included in the model input. Filtering rules based on anatomically constrained tractography are applied to prune implausible streamlines. We trained the model on manually-refined whole-brain fetal tractograms and validated the trained model on an independent set of 11 test scans with gestational ages between 23 and 36 weeks. Results show that our proposed method achieves superior performance across all evaluated tracts. The new method can significantly advance the capabilities of dMRI for studying normal and abnormal brain development in utero.

Anatomically constrained tractography of the fetal brain

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

Brain plasticity following corpus callosum agenesis or loss: a review of the Probst bundles

The corpus callosum is the largest axonal tract in the human brain, connecting the left and right cortical hemipheres. This structure is affected in myriad human neurodevelopmental disorders, and can be entirely absent as a result of congenital or surgical causes. The age when callosal loss occurs, for example via surgical section in cases of refractory epilepsy, correlates with resulting brain morphology and neuropsychological outcomes, whereby an earlier loss generally produces relatively improved interhemispheric connectivity compared to a loss in adulthood (known as the "Sperry's paradox"). However, the mechanisms behind these age-dependent differences remain unclear. Perhaps the best documented and most striking of the plastic changes that occur due to developmental, but not adult, callosal loss is the formation of large, bilateral, longitudinal ectopic tracts termed Probst bundles. Despite over 100 years of research into these ectopic tracts, which are the largest and best described stereotypical ectopic brain tracts in humans, much remains unclear about them. Here, we review the anatomy of the Probst bundles, along with evidence for their faciliatory or detrimental function, the required conditions for their formation, patterns of etiology, and mechanisms of development. We provide hypotheses for many of the remaining mysteries of the Probst bundles, including their possible relationship to preserved interhemispheric communication following corpus callosum absence. Future research into naturally occurring plastic tracts such as Probst bundles will help to inform the general rules governing axon plasticity and disorders of brain miswiring.

Diffusion tensor imaging of fetal spinal cord: feasibility and gestational-age-related changes

OBJECTIVES

Diffusion tensor imaging (DTI) of the fetal brain is a relatively new technique that allows evaluation of white matter tracts of the central nervous system throughout pregnancy, as well as in certain pathological conditions. The objectives of this study were to evaluate the feasibility of DTI of the spinal cord in utero and to examine gestational-age (GA)-related changes in DTI parameters during pregnancy.

METHODS

This was a prospective study conducted between December 2021 and June 2022 in the LUMIERE Platform, Necker-Enfants Malades Hospital, Paris, France, as part of the LUMIERE SUR LE FETUS trial. Women with a pregnancy between 18 and 36 weeks of gestation without fetal or maternal abnormality were eligible for inclusion. Sagittal diffusion-weighted scans of the fetal spine were acquired, without sedation, using a 1.5-Tesla magnetic resonance imaging scanner. The imaging parameters were as follows: 15 non-collinear direction diffusion-weighted magnetic-pulsed gradients with a b-value 700 s/mm2 and one B0 image without diffusion-weighting; slice thickness, 3 mm; field of view (FOV), 36 mm; phase FOV, 1.00; voxel size, 4.5 × 2.8 × 3 mm3 ; number of slices, 7-10; repetition time, 2800 ms; echo time, minimum; and total acquisition time, 2.3 min. DTI parameters, including fractional anisotropy (FA) and apparent diffusion coefficient (ADC), were extracted at the cervical, upper thoracic, lower thoracic and lumbar levels of the spinal cord. Cases with motion degradation and those with aberrant reconstruction of the spinal cord on tractography were excluded. Pearson's correlation analysis was performed to evaluate GA-related changes of DTI parameters during pregnancy.

RESULTS

During the study period, 42 pregnant women were included at a median GA of 29.3 (range, 22.0-35.7) weeks. Five (11.9%) patients were not included in the analysis because of fetal movement. Two (4.8%) patients with aberrant tractography reconstruction were also excluded from analysis. Acquisition of DTI parameters was feasible in all remaining cases (35/35). Increasing GA correlated with increasing FA averaged over the entire fetal spinal cord (r, 0.37; P < 0.01), as well as at the individual cervical (r, 0.519; P < 0.01), upper thoracic (r, 0.468; P < 0.01), lower thoracic (r, 0.425; P = 0.02) and lumbar (r, 0.427; P = 0.02) levels. There was no correlation between GA and ADC averaged over the entire spinal cord (r, 0.01; P = 0.99) or at the individual cervical (r, -0.109; P = 0.56), upper thoracic (r, -0.226; P = 0.22), lower thoracic (r, -0.052; P = 0.78) or lumbar (r, -0.11; P = 0.95) levels.

CONCLUSIONS

This study shows that DTI of the spinal cord is feasible in normal fetuses in typical clinical practice and allows extraction of DTI parameters of the spinal cord. There is a significant GA-related change in FA in the fetal spinal cord during pregnancy, which may result from decreasing water content as observed during myelination of fiber tracts occurring in utero. This study may serve as a basis for further investigation of DTI in the fetus, including research into its potential in pathological conditions that impact spinal cord development. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Diffusion tensor imaging of fetal brain: principles, potential and limitations of promising technique

Human brain development is a complex process that begins in the third week of gestation. During early development, the fetal brain undergoes dynamic morphological changes. These changes result from events such as neurogenesis, neuronal migration, synapse formation, axonal growth and myelination. Disruption of any of these processes is thought to be responsible for a wide array of different pathologies. Recent advances in magnetic resonance imaging, especially diffusion-weighted imaging and diffusion tensor imaging (DTI), have enabled characterization and evaluation of brain development in utero. In this review, aimed at practitioners involved in fetal medicine and high-risk pregnancies, we provide a comprehensive overview of fetal DTI studies focusing on characterization of early normal brain development as well as evaluation of brain pathology in utero. We also discuss the reliability and limitations of fetal brain DTI. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Another Piece of the Puzzle of Anomalous Connectivity in Joubert's Syndrome

We report on the conventional and diffusion tensor imaging (DTI) findings of a 2-year-old child with clinical presentation of Joubert's Syndrome (JS) and brainstem structural abnormalities as depicted by neuroimaging.Conventional magnetic resonance imaging (MRI) showed a "molar tooth" configuration of the brainstem. A band-like formation coursing in an apparent axial plane anterior to the interpeduncular fossa was noted and appeared to partially cover the interpeduncular fossa.DTI maps and three-dimensional (3D) tractography demonstrated a prominent red-encoded white matter bundle anterior to the midbrain. Probable aberrant course of the bilateral corticospinal tracts (CST) was also depicted. Absence of the decussation of the superior cerebellar peduncles and elongated thickened, horizontal superior cerebellar peduncle (SCP) reflecting the molar tooth sign were also shown.Our report and the review of the published cases suggest that DTI and tractography may be very helpful to differentiate between interpeduncular heterotopias and similarly located white matter bundles corroborating the underlying etiology of axonal guidance disorders in the complex group of ciliopathies including JS. Our case represents an important additional puzzle piece to explore the variability of these ciliopathies.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Feasibility and Added Value of Fetal DTI Tractography in the Evaluation of an Isolated Short Corpus Callosum: Preliminary Results

BACKGROUND AND PURPOSE

Prognosis of isolated short corpus callosum is challenging. Our aim was to assess whether fetal DTI tractography can distinguish callosal dysplasia from variants of normal callosal development in fetuses with an isolated short corpus callosum.

MATERIALS AND METHODS

This was a retrospective study of 37 cases referred for fetal DTI at 30.4 weeks (range, 25-34 weeks) because of an isolated short corpus callosum  less than the 5th percentile by sonography at 26 weeks (range, 22-31 weeks). Tractography quality, the presence of Probst bundles, dysmorphic frontal horns, callosal length (internal cranial occipitofrontal dimension/length of the corpus callosum ratio), and callosal thickness were assessed. Cytogenetic data and neurodevelopmental follow-up were systematically reviewed.

RESULTS

Thirty-three of 37 fetal DTIs distinguished the 2 groups: those with Probst bundles (Probst bundles+) in 13/33 cases (40%) and without Probst bundles (Probst bundles-) in 20/33 cases (60%). Internal cranial occipitofrontal dimension/length of the corpus callosum was significantly higher in Probst bundles+ than in Probst bundles-, with a threshold value determined at 3.75 for a sensitivity of 92% (95% CI, 77%-100%) and specificity of 85% (95% CI, 63%-100%). Callosal lipomas (4/4) were all in the Probst bundles- group. More genetic anomalies were found in the Probst bundles+ than in Probst bundles- group (23% versus 10%, P = .08).

CONCLUSIONS

Fetal DTI, combined with anatomic, cytogenetic, and clinical characteristics could suggest the possibility of classifying an isolated short corpus callosum as callosal dysplasia and a variant of normal callosal development.

Single-direction diffusion-weighted imaging may be a simple complementary sequence for evaluating fetal corpus callosum

OBJECTIVES

To explore the feasibility of single-direction diffusion-weighted imaging (DWI) for assessing the fetal corpus callosum (CC).

METHODS

This prospective study included 67 fetuses with normal CC and 35 fetuses suspected with agenesis of the corpus callosum (ACC). The MR protocols included HASTE, TrueFISP, and single-direction DWI. Two radiologists independently evaluated the optimal visibility and the contrast ratio (CR) of the normal fetal CC. The Chi-squared test or Fisher's exact test was used to compare the proportions of "good" visibility (score ≥ 3, and the CC was almost/entirely visible) between single-direction DWI and HASTE/TrueFISP. The CR difference between single-direction DWI and HASTE/TrueFISP was detected using the paired t-test. The diagnostic accuracies were determined by comparison with postnatal imaging. In fetuses suspected of ACC, we measured and compared the length and area of the mid-sagittal CC in the single-direction DWI images.

RESULTS

The proportion of "good" visibility in single-direction DWI was higher than that in HASTE/TrueFISP, with p < 0.0001. The mean CR from single-direction DWI was also higher than that of TrueFISP and HASTE (both with p < 0.0001). The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFisp (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35) (p = 0.013). The length and area of the PACC (p < 0.001, p = 0.001, respectively) and HCC (p < 0.001, p = 0.018, respectively) groups were significantly lower than those of the normal group.

CONCLUSIONS

The single-direction DWI is feasible in displaying fetal CC and can be a complementary sequence in diagnosing ACC.

KEY POINTS

• We suggest a simple method for the display of the fetal CC. • The optimal visibility and contrast ratio from single-direction DWI were higher than those from HASTE and TrueFISP. • The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFISP sequences (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35).

Fundamentals of the Development of Connectivity in the Human Fetal Brain in Late Gestation: From 24 Weeks Gestational Age to Term

During the second half of gestation, the human cerebrum undergoes pivotal histogenetic events that underlie functional connectivity. These include the growth, guidance, selection of axonal pathways, and their first engagement in neuronal networks. Here, we characterize the spatiotemporal patterns of cerebral connectivity in extremely preterm (EPT), very preterm (VPT), preterm and term babies, focusing on magnetic resonance imaging (MRI) and histological data. In the EPT and VPT babies, thalamocortical axons enter into the cortical plate creating the electrical synapses. Additionally, the subplate zone gradually resolves in the preterm and term brain in conjunction with the growth of associative pathways leading to the activation of large-scale neural networks. We demonstrate that specific classes of axonal pathways within cerebral compartments are selectively vulnerable to temporally nested pathogenic factors. In particular, the radial distribution of axonal lesions, that is, radial vulnerability, is a robust predictor of clinical outcome. Furthermore, the subplate tangential nexus that we can visualize using MRI could be an additional marker as pivotal in the development of cortical connectivity. We suggest to direct future research toward the identification of sensitive markers of earlier lesions, the elucidation of genetic mechanisms underlying pathogenesis, and better long-term follow-up using structural and functional MRI.

Interpeduncular Heterotopia and Brain Stem Cleft: An Isolated Finding Not Associated with Joubert Syndrome

Interpeduncular heterotopia is a new neuroimaging finding reported in association with Joubert syndrome (JS) in a few cases in the literature. Nodular interpeduncular tissue was termed as interpeduncular heterotopia and anterior mesencephalic cap dysplasia in the literature in relation to gray and white matter content. We described the imaging findings and diffusion tensor imaging data of a case with interpeduncular heterotopia and brain stem cleft. This is the first case, in which interpeduncular heterotopia was an isolated finding not associated with JS.

How to read a fetal magnetic resonance image 101

Accurate antenatal diagnosis is essential for planning appropriate pregnancy management and improving perinatal outcomes. The provision of information vital for prognostication is a crucial component of prenatal imaging, and this can be enhanced by the use of fetal MRI. Image acquisition, interpretation and reporting of a fetal MR study can be daunting to the individual who has encountered few or none of these examinations. This article provides the radiology trainee with a general approach to interpreting a fetal MRI. The authors review the added value of prenatal MRI in the overall assessment of fetal wellbeing, discuss MRI protocols and techniques, and review the normal appearance of maternal and fetal anatomy. The paper concludes with a sample template for structured reporting, to serve as a checklist and guideline for reporting radiologists.

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.

The Subplate Layers: The Superficial and Deep Subplate Can be Discriminated on 3 Tesla Human Fetal Postmortem MRI

The subplate (SP) is a transient structure of the human fetal brain that becomes the most prominent layer of the developing pallium during the late second trimester. It is important in the formation of thalamocortical and cortico-cortical connections. The SP is vulnerable in perinatal brain injury and may play a role in complex neurodevelopmental disorders, such as schizophrenia and autism. Nine postmortem fetal human brains (19-24 GW) were imaged on a 3 Tesla MR scanner and the T2-w images in the frontal and temporal lobes were compared, in each case, with the histological slices of the same brain. The brains were confirmed to be without any brain pathology. The purpose of this study was to demonstrate that the superficial SP (sSP) and deep SP (dSP) can be discriminated on postmortem MR images. More specifically, we aimed to clarify that the observable, thin, hyperintense layer below the cortical plate in the upper SP portion on T2-weighted MR images has an anatomical correspondence to the histologically established sSP. Therefore, the distinction between the sSP and dSP layers, using clinically available MR imaging methodology, is possible in postmortem MRI and can help in the imaging interpretation of the fetal cerebral layers.

In vivo characterization of emerging white matter microstructure in the fetal brain in the third trimester

The third trimester of pregnancy is a period of rapid development of fiber bundles in the fetal white matter. Using a recently developed motion‐tracked slice‐to‐volume registration (MT‐SVR) method, we aimed to quantify tract‐specific developmental changes in apparent diffusion coefficient (ADC), fractional anisotropy (FA), and volume in third trimester healthy fetuses. To this end, we reconstructed diffusion tensor images from motion corrected fetal diffusion magnetic resonance imaging data. With an approved protocol, fetal MRI exams were performed on healthy pregnant women at 3 Tesla and included multiple (2–8) diffusion scans of the fetal head (1–2 b = 0 s/mm² images and 12 diffusion‐sensitized images at b = 500 s/mm²). Diffusion data from 32 fetuses (13 females) with median gestational age (GA) of 33 weeks 4 days were processed with MT‐SVR and deterministic tractography seeded by regions of interest corresponding to 12 major fiber tracts. Multivariable regression analysis was used to evaluate the association of GA with volume, FA, and ADC for each tract. For all tracts, the volume and FA increased, and the ADC decreased with GA. Associations reached statistical significance for: FA and ADC of the forceps major; volume and ADC for the forceps minor; FA, ADC, and volume for the cingulum; ADC, FA, and volume for the uncinate fasciculi; ADC of the inferior fronto‐occipital fasciculi, ADC of the inferior longitudinal fasciculi; and FA and ADC for the corticospinal tracts. These quantitative results demonstrate the complex pattern and rates of tract‐specific, GA‐related microstructural changes of the developing white matter in human fetal brain.

Fetal Neuroimaging Update

OBJECTIVES

To review the current imaging techniques available for the evaluation of the fetal brain.

FINDINGS

Ultrasound remains the initial screening modality with routine scanning typically performed at 18-20 weeks gestation. When a central nervous system (CNS) abnormality is noted by ultrasound, MRI is increasingly being used to further clarify findings. Fetal MRI has the unique ability to provide high detailed anatomical information of the entire human fetus with high contrast resolution. This technique has grown due to the development of rapid single shot image acquisition sequences, improvement of motion correction strategies and optimizing shimming techniques.

CONCLUSIONS

The assessment of fetal CNS anomalies continues to improve. Advanced MRI techniques have allowed for further delineation of CNS anomalies and have become a cornerstone in the assessment of fetal brain well-being. Those interpreting fetal studies need to be familiar with the strengths and limitations of each exam and be sensitive to the impact discussing findings can have regarding perinatal care and delivery planning. Collaboration with neurologists, neurosurgeons, geneticists, counselors, and maternal fetal specialists are key in providing the best care to the families we treat.

Developmental dynamics of the periventricular parietal crossroads of growing cortical pathways in the fetal brain - In vivo fetal MRI with histological correlation

The periventricular crossroads have been described as transient structures of the fetal brain where major systems of developing fibers intersect. The triangular parietal crossroad constitutes one major crossroad region. By combining in vivo and post-mortem fetal MRI with histological and immunohistochemical methods, we aimed to characterize these structures. Data from 529 in vivo and 66 post-mortem MRI examinations of fetal brains between gestational weeks (GW) 18-39 were retrospectively reviewed. In each fetus, the area adjacent to the trigone of the lateral ventricles at the exit of the posterior limb of the internal capsule (PLIC) was assessed with respect to signal intensity, size, and shape on T2-weighted images. In addition, by using in vivo diffusion tensor imaging (DTI), the main fiber pathways that intersect in these areas were identified. In order to explain the in vivo features of the parietal crossroads (signal intensity and developmental profile), we analyzed 23 post-mortem fetal human brains, between 16 and ​40 GW of age, processed by histological and immunohistochemical methods. The parietal crossroads were triangular-shaped areas with the base in the continuity of the PLIC, adjacent to the germinal matrix and the trigone of the lateral ventricles, with the tip pointing toward the subplate. These areas appeared hyperintense to the subplate, and corresponded to a convergence zone of the developing external capsule, the PLIC, and the fronto-occipital association fibers. They were best detected between GW 25-26, and, at term, they became isointense to the adjacent structures. The immunohistochemical results showed a distinct cellular, fibrillar, and extracellular matrix arrangement in the parietal crossroads, depending on the stage of development, which influenced the MRI features. The parietal crossroads are transient, but important structures in white matter maturation and their damage may be indicative of a poor prognosis for a fetus with regard to neurological development. In addition, impairment of this region may explain the complex neurodevelopmental deficits in preterm infants with periventricular hypoxic/ischemic or inflammatory lesions.

Impact of prematurity on neurodevelopment

The consequences of prematurity on brain functional development are numerous and diverse, and impact all brain functions at different levels. Prematurity occurs between 22 and 36 weeks of gestation. This period is marked by extreme dynamics in the physiologic maturation, structural, and functional processes. These different processes appear sequentially or simultaneously. They are dependent on genetic and/or environmental factors. Disturbance of these processes or of the fine-tuning between them, when caring for premature children, is likely to induce disturbances in the structural and functional development of the immature neural networks. These will appear as impairments in learning skills progress and are likely to have a lasting impact on the development of children born prematurely. The level of severity depends on the initial alteration, whether structural or functional. In this chapter, after having briefly reviewed the neurodevelopmental, structural, and functional processes, we describe, in a nonexhaustive manner, the impact of prematurity on the different brain, motor, sensory, and cognitive functions.

Ex vivo fetal brain MRI: Recent advances, challenges, and future directions

During early development, the fetal brain undergoes dynamic morphological changes. These changes result from neurogenic events, such as neuronal proliferation, migration, axonal elongation, retraction, and myelination. The duration and intensity of these events vary across species. Comparative assessments of these neurogenic events give us insight into evolutionary changes and the complexity of human brain development. Recent advances in magnetic resonance imaging (MRI), especially ex vivo MRI, permit characterizing and comparing fetal brain development across species. Comparative ex vivo MRI studies support the detection of species-specific differences that occur during early brain development. In this review, we provide a comprehensive overview of ex vivo MRI studies that characterize early brain development in humans, monkeys, cats, as well as rats/mice. Finally, we discuss the current advantages and limitations of ex vivo fetal brain MRI.

Exploring early human brain development with structural and physiological neuroimaging

Early brain development, from the embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and the important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.

Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images

Altered structural fetal brain development has been linked to neuro-developmental disorders. These structural alterations can be potentially detected in utero using diffusion tensor imaging (DTI). However, acquisition and reconstruction of in utero fetal brain DTI remains challenging. Until now, motion-robust DTI methods have been employed for reconstruction of in utero fetal DTIs. However, due to the unconstrained fetal motion and permissible in utero acquisition times, these methods yielded limited success and have typically resulted in noisy DTIs. Consequently, atlases and methods that could enable groupwise studies, multi-modality imaging, and computer-aided diagnosis from in utero DTIs have not yet been developed. This paper presents the first DTI atlas of the fetal brain computed from in utero diffusion-weighted images. For this purpose an algorithm for computing an unbiased spatiotemporal DTI atlas, which integrates kernel-regression in age with a diffeomorphic tensor-to-tensor registration of motion-corrected and reconstructed individual fetal brain DTIs, was developed. Our new algorithm was applied to a set of 67 fetal DTI scans acquired from healthy fetuses each scanned at a gestational age between 21 and 39 weeks. The neurodevelopmental trends in the fetal brain, characterized by the atlas, were qualitatively and quantitatively compared with the observations reported in prior ex vivo and in utero studies, and with results from imaging gestational-age equivalent preterm infants. Our major findings revealed early presence of limbic fiber bundles, followed by the appearance and maturation of projection pathways (characterized by an age related increase in FA) during late 2nd and early 3rd trimesters. During the 3rd trimester association fiber bundles become evident. In parallel with the appearance and maturation of fiber bundles, from 21 to 39 gestational weeks gradual disappearance of the radial coherence of the telencephalic wall was qualitatively identified. These results and analyses show that our DTI atlas of the fetal brain is useful for reliable detection of major neuronal fiber bundle pathways and for characterization of the fetal brain reorganization that occurs in utero. The atlas can also serve as a useful resource for detection of normal and abnormal fetal brain development in utero.

How accurate are prenatal tractography results? A postnatal in vivo follow-up study using diffusion tensor imaging

Prenatal detection of abnormal white matter tracts might serve as a structural marker for altered neurodevelopment. As a result of many technical and patient-related challenges, the accuracy of prenatal tractography remains unknown. We hypothesized that characteristics of prenatal tractography of the corpus callosum and corticospinal tracts derived from fetal diffusion tensor imaging (DTI) data are accurate and predictive of the integrity of these tracts postnatally. We compared callosal and corticospinal tracts of 12 subjects with paired prenatal (age: 23-35 gestational weeks) and postnatal (age: 1 day to 2 years) DTI examinations (b values of 0 s/mm² and 700 s/mm², 16 gradient encoding directions) using deterministic tractography. Evaluation for the presence of callosal segments and corticospinal tracts showed moderate degrees of accuracy (67-75%) for the four segments of the corpus callosum and moderate to high degrees of accuracy (75-92%) for the corticospinal tracts. Positive predictive values for segments of the corpus callosum ranged from 50% to 100% and for the corticospinal tracts, 89% to 100%. Negative predictive values for segments of the corpus callosum ranged from 25% to 80% and for the corticospinal tracts, 33% to 50%. The results suggest that when the tracts are not well characterized on the fetal MR, predictions about the postnatal tracts are difficult to make. However, accounting for brain maturation, prenatal visualization of the main projection and commissural tracts can be clinically used as an important predictive tool in the context of image interpretation for the assessment of fetal brain malformations.

Anterior Mesencephalic Cap Dysplasia: Novel Brain Stem Malformative Features Associated with Joubert Syndrome

In Joubert syndrome, the "molar tooth" sign can be associated with several additional supra- and infratentorial malformations. Here we report on 3 subjects (2 siblings, 8-14 years of age) with Joubert syndrome, showing an abnormal thick bulging of the anterior profile of the mesencephalon causing a complete obliteration of the interpeduncular fossa. DTI revealed that the abnormal tissue consisted of an ectopic white matter tract with a laterolateral transverse orientation. Tractographic reconstructions support the hypothesis of impaired axonal guidance mechanisms responsible for the malformation. The 2 siblings were compound heterozygous for 2 missense variants in the TMEM67 gene, while no mutations in a panel of 120 ciliary genes were detected in the third patient. The name "anterior mesencephalic cap dysplasia," referring to the peculiar aspect of the mesencephalon on sagittal MR imaging, is proposed for this new malformative feature.

Design and validation of diffusion MRI models of white matter

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the "biological accuracy" of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

Human Fetal Brain Connectome: Structural Network Development from Middle Fetal Stage to Birth

Complicated molecular and cellular processes take place in a spatiotemporally heterogeneous and precisely regulated pattern in the human fetal brain, yielding not only dramatic morphological and microstructural changes, but also macroscale connectomic transitions. As the underlying substrate of the fetal brain structural network, both dynamic neuronal migration pathways and rapid developing fetal white matter (WM) fibers could fundamentally reshape early fetal brain connectome. Quantifying structural connectome development can not only shed light on the brain reconfiguration in this critical yet rarely studied developmental period, but also reveal alterations of the connectome under neuropathological conditions. However, transition of the structural connectome from the mid-fetal stage to birth is not yet known. The contribution of different types of neural fibers to the structural network in the mid-fetal brain is not known, either. In this study, diffusion tensor magnetic resonance imaging (DT-MRI or DTI) of 10 fetal brain specimens at the age of 20 postmenstrual weeks (PMW), 12 in vivo brains at 35 PMW, and 12 in vivo brains at term (40 PMW) were acquired. The structural connectome of each brain was established with evenly parcellated cortical regions as network nodes and traced fiber pathways based on DTI tractography as network edges. Two groups of fibers were categorized based on the fiber terminal locations in the cerebral wall in the 20 PMW fetal brains. We found that fetal brain networks become stronger and more efficient during 20–40 PMW. Furthermore, network strength and global efficiency increase more rapidly during 20–35 PMW than during 35–40 PMW. Visualization of the whole brain fiber distribution by the lengths suggested that the network reconfiguration in this developmental period could be associated with a significant increase of major long association WM fibers. In addition, non-WM neural fibers could be a major contributor to the structural network configuration at 20 PMW and small-world network organization could exist as early as 20 PMW. These findings offer a preliminary record of the fetal brain structural connectome maturation from the middle fetal stage to birth and reveal the critical role of non-WM neural fibers in structural network configuration in the middle fetal stage.

In utero diffusion tensor imaging of the fetal brain: A reproducibility study

Our purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures. Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5 T or 3.0 T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1 ∗ 1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm². Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test. White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction. Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways.

Growth of Thalamocortical Fibers to the Somatosensory Cortex in the Human Fetal Brain

Thalamocortical (TH-C) fiber growth begins during the embryonic period and is completed by the third trimester of gestation in humans. Here we determined the timing and trajectories of somatosensory TH-C fibers in the developing human brain. We analyzed the periods of TH-C fiber outgrowth, path-finding, "waiting" in the subplate (SP), target selection, and ingrowth in the cortical plate (CP) using histological sections from post-mortem fetal brain [from 7 to 34 postconceptional weeks (PCW)] that were processed with acetylcholinesterase (AChE) histochemistry and immunohistochemical methods. Images were compared with post mortem diffusion tensor imaging (DTI)-based fiber tractography (code No NO1-HD-4-3368). The results showed TH-C axon outgrowth occurs as early as 7.5 PCW in the ventrolateral part of the thalamic anlage. Between 8 and 9.5 PCW, TH-C axons form massive bundles that traverse the diencephalic-telencephalic boundary. From 9.5 to 11 PCW, thalamocortical axons pass the periventricular area at the pallial-subpallial boundary and enter intermediate zone in radiating fashion. Between 12 and 14 PCW, the TH-C axons, aligned along the fibers from the basal forebrain, continue to grow for a short distance within the deep intermediate zone and enter the deep CP, parallel with SP expansion. Between 14 and 18 PCW, the TH-C interdigitate with callosal fibers, running shortly in the sagittal stratum and spreading through the deep SP ("waiting" phase). From 19 to 22 PCW, TH-C axons accumulate in the superficial SP below the somatosensory cortical area; this occurs 2 weeks earlier than in the frontal and occipital cortices. Between 23 and 24 PCW, AChE-reactive TH-C axons penetrate the CP concomitantly with its initial lamination. Between 25 and 34 PCW, AChE reactivity of the CP exhibits an uneven pattern suggestive of vertical banding, showing a basic 6-layer pattern. In conclusion, human thalamocortical axons show prolonged growth (4 months), and somatosensory fibers precede the ingrowth of fibers destined for frontal and occipital areas. The major features of growing TH-C somatosensory fiber trajectories are fan-like radiation, short runs in the sagittal strata, and interdigitation with the callosal system. These results support our hypothesis that TH-C axons are early factors in SP and CP morphogenesis and synaptogenesis and may regulate cortical somatosensory system maturation.

Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis

Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion. In this paper we introduce a novel robust algorithm to reconstruct in-vivo diffusion-tensor MRI (DTI) of the moving fetal brain and show its effect on structural connectivity analysis. The proposed algorithm involves multiple steps of image registration incorporating a dynamic registration-based motion tracking algorithm to restore the spatial correspondence of DWI data at the slice level and reconstruct DTI of the fetal brain in the standard (atlas) coordinate space. A weighted linear least squares approach is adapted to remove the effect of intra-slice motion and reconstruct DTI from motion-corrected data. The proposed algorithm was tested on data obtained from 21 healthy fetuses scanned in-utero at 22-38 weeks gestation. Significantly higher fractional anisotropy values in fiber-rich regions, and the analysis of whole-brain tractography and group structural connectivity, showed the efficacy of the proposed method compared to the analyses based on original data and previously proposed methods. The results of this study show that slice-level motion correction and robust reconstruction is necessary for reliable in-vivo structural connectivity analysis of the fetal brain. Connectivity analysis based on graph theoretic measures show high degree of modularity and clustering, and short average characteristic path lengths indicative of small-worldness property of the fetal brain network. These findings comply with previous findings in newborns and a recent study on fetuses. The proposed algorithm can provide valuable information from DWI of the fetal brain not available in the assessment of the original 2D slices and may be used to more reliably study the developing fetal brain connectome.

Joubert syndrome: neuroimaging findings in 110 patients in correlation with cognitive function and genetic cause

BACKGROUND

Joubert syndrome is a clinically and genetically heterogeneous ciliopathy. Neuroimaging findings have not been systematically evaluated in a large cohort of patients with Joubert syndrome in correlation with molecular genetic cause and cognitive function.

METHODS

Brain MRI of 110 patients with Joubert syndrome was included in this study. A comprehensive evaluation of brain MRI studies for infratentorial and supratentorial morphological abnormalities was performed. Genetic cause was identified by whole-exome sequencing, and cognitive functions were assessed with age-appropriate neurocognitive tests in a subset of patients.

RESULTS

The cerebellar hemispheres were enlarged in 18% of the patients, mimicking macrocerebellum. The posterior fossa was enlarged in 42% of the patients, resembling Dandy-Walker malformation. Abnormalities of the brainstem, such as protuberance at the ventral contour of the midbrain, were present in 66% of the patients. Abnormalities of the supratentorial brain were present in approximately one-third of the patients, most commonly malrotation of the hippocampi. Mild ventriculomegaly, which typically did not require shunting, was present in 23% of the patients. No correlation between neuroimaging findings and molecular genetic cause was apparent. A novel predictor of outcome was identified; the more severe the degree of vermis hypoplasia, the worse the neurodevelopmental outcome was.

CONCLUSIONS

The spectrum of neuroimaging findings in Joubert syndrome is wide. Neuroimaging does not predict the genetic cause, but may predict the neurodevelopmental outcome. A high degree of vermis hypoplasia correlates with worse neurodevelopmental outcome. This finding is important for prognostic counselling in Joubert syndrome.

MRI and M/EEG studies of the White Matter Development in Human Fetuses and Infants: Review and Opinion

Already during the last trimester of gestation, functional responses are recorded in foetuses and preterm newborns, attesting an already complex cerebral architecture. Then throughout childhood, anatomical connections are further refined but at different rates and over asynchronous periods across functional networks. Concurrently, infants gradually achieve new psychomotor and cognitive skills. Only the recent use of non-invasive techniques such as magnetic resonance imaging (MRI) and magneto- and electroencephalography (M/EEG) has opened the possibility to understand the relationships between brain maturation and skills development in vivo. In this review, we describe how these techniques have been applied to study the white matter maturation. At the structural level, the early architecture and myelination of bundles have been assessed with diffusion and relaxometry MRI, recently integrated in multi-compartment models and multi-parametric approaches. Nevertheless, technical limitations prevent us to map major developmental mechanisms such as fibers growth and pruning, and the progressive maturation at the bundle scale in case of mixing trajectories. At the functional level, M/EEG have been used to record different visual, somatosensory and auditory evoked responses. Because the conduction velocity of neural impulses increases with the myelination of connections, major changes in the components latency are observed throughout development. But so far, only a few studies have related structural and functional markers of white matter myelination. Such multi-modal approaches will be a major challenge in future research, not only to understand normal development, but also to characterize early mechanisms of pathologies and the influence of fetal and perinatal interventions on later outcome.