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

Population Atlas Analysis of Emerging Brain Structural Connections in the Human Fetus

BACKGROUND

A lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences.

PURPOSE

To evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI).

STUDY TYPE

Retrospective.

POPULATION

Publicly available diffusion atlases, based on 60 healthy women (age 18-45 years) with normal prenatal care, from 23 and 35 weeks of gestation.

FIELD STRENGTH/SEQUENCE

3.0 Tesla/DTI acquired with diffusion-weighted echo planar imaging (EPI).

ASSESSMENT

We performed whole-brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small-worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality.

STATISTICAL TESTS

Linear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. The t-tests were used to assess SW. P-values were corrected using Holm-Bonferroni method. A corrected P-value <0.05 was considered statistically significant.

RESULTS

Network analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32-7.37), LE (5.43%/week, 95% CI 3.63-7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes.

DATA CONCLUSION

Extensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results than standard methods such as Constrained Spherical Deconvolution and two state-of-the-art deep learning methods. For voxels with one and two fibers, respectively, our method shows an agreement rate in terms of the number of fibers of 77.5% and 22.2%, which is 3% and 5.4% higher than other deep learning methods, and an angular error of 10° and 20°, which is 6° and 5° lower than other deep learning methods. To determine baselines for assessing the performance of our method, we compute agreement metrics using densely sampled newborn data. Moreover, we demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical external datasets of newborns and fetuses. We validate fetal FODs, successfully estimated for the first time with deep learning, using post-mortem histological data. Our results show the advantage of deep learning in computing the fiber orientation density for the developing brain from in-vivo dMRI measurements that are often very limited due to constrained acquisition times. Our findings also highlight the intrinsic limitations of dMRI for probing the developing brain microstructure.

Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging

Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.

A detailed spatio-temporal atlas of the white matter tracts for the fetal brain

This study presents the construction of a comprehensive spatiotemporal atlas detailing the development of white matter tracts in the fetal brain using diffusion magnetic resonance imaging (dMRI). Our research leverages data collected from fetal MRI scans conducted between 22 and 37 weeks of gestation, capturing the dynamic changes in the brain's microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), reflecting key neurodevelopmental processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders.

Reproducibility of Diffusion MRI-Based Tractography in the Fetal Brain

BACKGROUND

Tractography based on diffusion MRI (dMRI) is a useful tool to study white matter of the developing brain. However, its application in fetal brains is limited due to motion artifacts and low resolution of in utero dMRI, leading to reduced reliability, which was scarcely investigated in previous studies.

PURPOSE

To identify reliably traceable fibers in fetal brains and assess whether reproducibility varies with gestational age (GA) and varies between brain regions.

STUDY TYPE

Prospective cohort study.

SUBJECTS

A total of 44 healthy fetuses with GAs between 25 and 37 (31 ± 6).

FIELD STRENGTH/SEQUENCE

3-T, diffusion-weighted echo-planar imaging sequence (2-5 repeated dMRI scans within the same session per subject).

ASSESSMENT

We fitted dMRI with constrained spherical deconvolution model and conducted tractography on eight fibers. We extracted volume, fractional anisotropy, and fiber count for each fiber and assessed the reproducibility of these metrics between repeated scans within each subject. Data were divided into two age-based subgroups (≤30 weeks, N = 28, and >30 weeks, N = 16) for further tests.

STATISTICAL TESTS

The reproducibility were compared between fibers by analysis of variance and two-sample t tests. Multiple comparisons were corrected by the false discovery rate (5% was accepted).

RESULTS

The reproducibility of the anterior thalamic radiation, inferior longitudinal fasciculus (ILF), genu of the corpus callosum (GCC), and body of the corpus callosum (BCC) significantly decreased with advancing GA (correlation coefficient = 0.525-0.823), as confirmed by group comparisons between fetuses in early GA (≤30 weeks) and late GA (>30 weeks) groups. Corticospinal tract, inferior fronto-occipital fasciculus, and GCC showed high reproducibility for fiber count (weighted dice average = 0.846 vs. 0.814), while BCC and ILF exhibited the lowest reproducibility in both age groups.

DATA CONCLUSION

The study indicates that the reliability of fetal brain tractography depends on GA and varies among different fibers.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Deep learning microstructure estimation of developing brains from diffusion MRI: a newborn and fetal study

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with standard FOD computation methods, accurate estimation of FODs requires a large number of measurements that usually cannot be acquired for newborns and fetuses. We propose to overcome this limitation by using a deep learning method to map as few as six diffusion-weighted measurements to the target FOD. To train the model, we use the FODs computed using multi-shell high angular resolution measurements as target. Extensive quantitative evaluations show that the new deep learning method, using significantly fewer measurements, achieves comparable or superior results to standard methods such as Constrained Spherical Deconvolution. We demonstrate the generalizability of the new deep learning method across scanners, acquisition protocols, and anatomy on two clinical datasets of newborns and fetuses. Additionally, we compute agreement metrics within the HARDI newborn dataset, and validate fetal FODs with post-mortem histological data. The results of this study show the advantage of deep learning in inferring the microstructure of the developing brain from in-vivo dMRI measurements that are often very limited due to subject motion and limited acquisition times, but also highlight the intrinsic limitations of dMRI in the analysis of the developing brain microstructure. These findings, therefore, advocate for the need for improved methods that are tailored to studying the early development of human brain.

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.

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.

An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field

Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.

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).

Emerging magnetic resonance imaging techniques in open spina bifida in utero

Magnetic resonance imaging (MRI) has become an essential diagnostic modality for congenital disorders of the central nervous system. Recent advancements have transformed foetal MRI into a clinically feasible tool, and in an effort to find predictors of clinical outcomes in spinal dysraphism, foetal MRI began to unveil its potential. The purpose of our review is to introduce MRI techniques to experts with diverse backgrounds, who are involved in the management of spina bifida. We introduce advanced foetal MRI postprocessing potentially improving the diagnostic work-up. Importantly, we discuss how postprocessing can lead to a more efficient utilisation of foetal or neonatal MRI data to depict relevant anatomical characteristics. We provide a critical perspective on how structural, diffusion and metabolic MRI are utilised in an endeavour to shed light on the correlates of impaired development. We found that the literature is consistent about the value of MRI in providing morphological cues about hydrocephalus development, hindbrain herniation or outcomes related to shunting and motor functioning. MRI techniques, such as foetal diffusion MRI or diffusion tractography, are still far from clinical use; however, postnatal studies using these methods revealed findings that may reflect early neural correlates of upstream neuronal damage in spinal dysraphism.

Localization and Identification of Brain Microstructural Abnormalities in Paediatric Concussion

In the United States, approximately 2.53 million people sustain a concussion each year. Relative to adults, youth show greater cognitive deficits following concussion and a longer recovery. An accurate and reliable imaging method is needed to determine injury severity and symptom resolution. The primary objective of this study was to characterize concussions with diffusion tensor imaging (DTI). This was performed through a normative Z-scoring analysis of DTI metrics, fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD), to quantify patient-specific injuries and identify commonly damaged brain regions in paediatric concussion patients relative to healthy controls. It was hypothesized that personalizing the detection analysis through normative Z-scoring would provide an understanding of trauma-induced microstructural damage. Concussion patients were volunteers recruited from the Emergency Department of the McMaster Children's Hospital with a recent concussion (n = 26), 9 males and 17 females, mean age 14.22 ± 2.64, while healthy paediatric brain DTI datasets (25 males and 24 females, mean age 13.52 ± 1.03) were obtained from an MRI data repository. Significant abnormalities were commonly found in the longitudinal fasciculus, fronto-occipital fasciculus, and corticospinal tract, while unique abnormalities were localized in a number of other areas reflecting the individuality of each child's injury. Total injury burden, determined by the number of regions containing outliers per DTI metric per patient, was used as the metric to quantify the overall injury severity of each patient. The primary outcome of this analysis found that younger patients experienced a significantly greater injury burden when measured using fractional anisotropy (p < 0.001). These results show that DTI was able to detect microstructural changes caused by concussion, on a per-person basis, and has the potential to be a useful tool for improving diagnostic accuracy and prognosis of a concussion.

Development of human white matter pathways in utero over the second and third trimester

During the second and third trimesters of human gestation, rapid neurodevelopment is underpinned by fundamental processes including neuronal migration, cellular organization, cortical layering, and myelination. In this time, white matter growth and maturation lay the foundation for an efficient network of structural connections. Detailed knowledge about this developmental trajectory in the healthy human fetal brain is limited, in part, due to the inherent challenges of acquiring high-quality MRI data from this population. Here, we use state-of-the-art high-resolution multishell motion-corrected diffusion-weighted MRI (dMRI), collected as part of the developing Human Connectome Project (dHCP), to characterize the in utero maturation of white matter microstructure in 113 fetuses aged 22 to 37 wk gestation. We define five major white matter bundles and characterize their microstructural features using both traditional diffusion tensor and multishell multitissue models. We found unique maturational trends in thalamocortical fibers compared with association tracts and identified different maturational trends within specific sections of the corpus callosum. While linear maturational increases in fractional anisotropy were seen in the splenium of the corpus callosum, complex nonlinear trends were seen in the majority of other white matter tracts, with an initial decrease in fractional anisotropy in early gestation followed by a later increase. The latter is of particular interest as it differs markedly from the trends previously described in ex utero preterm infants, suggesting that this normative fetal data can provide significant insights into the abnormalities in connectivity which underlie the neurodevelopmental impairments associated with preterm birth.

The impact of cerebral anomalies on cognitive outcome in patients with spina bifida: A systematic review

BACKGROUND

Spina bifida is the most common congenital birth defect affecting the central nervous system. Given the frequent association of cerebral anomalies, spina bifida is not a single developmental abnormality of the central nervous system. Patients with spina bifida typically perform below average on cognitive tasks. It has been hypothesized that associated cerebral anomalies as well negatively affect cognition in spina bifida patients.

OBJECTIVE

This study aims to review the impact of cerebral anomalies on cognitive outcome in patients with spina bifida.

METHODS

A systematic search of multiple databases, including Pubmed, Embase, Web of Science and The Cochrane Central Register of Controlled Trials, was performed. All relevant primary research articles were included. All included articles were methodologically evaluated using a critical appraisal checklist.

RESULTS

In total 27 articles were included in this systematic review. A significant impact of different cerebral anomalies on cognition was found. More specifically, hydrocephalus, Chiari malformation type II and anomalies of the corpus callosum, central executive network, default mode network, cortical thickness and gyrification, fornix, grey matter volume and total brain volume were found to have a significant impact on cognitive outcome. The presence of a CSF shunt was also negatively associated with cognition. The results on Chiari malformation type II decompression and CSF shunt complications are inconsistent.

CONCLUSION

Associated cerebral anomalies have a significant impact on cognitive outcome in patients with spina bifida. The interrelatedness of the different cerebral anomalies makes it difficult to distinguish their individual impact on cognition.

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.

Higher Order Spherical Harmonics Reconstruction of Fetal Diffusion MRI With Intensity Correction

We present a novel method for higher order reconstruction of fetal diffusion MRI signal that enables detection of fiber crossings. We combine data-driven motion and intensity correction with super-resolution reconstruction and spherical harmonic parametrisation to reconstruct data scattered in both spatial and angular domains into consistent fetal dMRI signal suitable for further diffusion analysis. We show that intensity correction is essential for good performance of the method and identify anatomically plausible fiber crossings. The proposed methodology has potential to facilitate detailed investigation of developing brain connectivity and microstructure in-utero.

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.

High Angular Resolution Diffusion MRI Reveals Conserved and Deviant Programs in the Paths that Guide Human Cortical Circuitry

Diffusion magnetic resonance (MR) tractography represents a novel opportunity to investigate conserved and deviant developmental programs between humans and other species such as mice. To that end, we acquired high angular resolution diffusion MR scans of mice [embryonic day (E) 10.5 to postnatal week 4] and human brains [gestational week (GW) 17-30] at successive stages of fetal development to investigate potential evolutionary changes in radial organization and emerging pathways between humans and mice. We compare radial glial development as well as commissural development (e.g., corpus callosum), primarily because our findings can be integrated with previous work. We also compare corpus callosal growth trajectories across primates (i.e., humans and rhesus macaques) and rodents (i.e., mice). One major finding is that the developing cortex of humans is predominated by pathways likely associated with a radial glial organization at GW 17-20, which is not as evident in age-matched mice (E 16.5, 17.5). Another finding is that, early in development, the corpus callosum follows a similar developmental timetable in primates (i.e., macaques and humans) as in mice. However, the corpus callosum grows for an extended period of time in primates compared with rodents. Taken together, these findings highlight deviant developmental programs underlying the emergence of cortical pathways in the human brain.

Automatic, Age Consistent Reconstruction of the Corpus Callosum Guided by Coherency From In Utero Diffusion-Weighted MRI

Reconstruction of white matter connectivity in the fetal brain from in utero diffusion-weighted magnetic resonance imaging (MRI) faces many challenges, including subject motion, small anatomical scale, and limited image resolution and signal. These issues are compounded by the need to track significant changes in structural connectivity throughout development. We present an automated method for improved reliability and completeness of tract extraction across a wide range of gestational ages, based on the geometry of coherent patterns in streamline tractography, and apply it to the reconstruction of the corpus callosum. This method, focused specifically at addressing the challenges of fetal brain imaging, avoids depending on a tractography atlas, and handles variations in size, shape, and tissue properties of developing brains, both between subjects and across ages. Although tractography from in utero MRI generally suffers from a significant number of misleading and missing pathways, we demonstrate the feasibility of extracting the coherent bundle of the corpus callosum while avoiding inappropriate diversions into other tracts.

In Utero Diffusion MRI: Challenges, Advances, and Applications

In utero diffusion magnetic resonance imaging (MRI) provides unique opportunities to noninvasively study the microstructure of tissue during fetal development. A wide range of developmental processes, such as the growth of white matter tracts in the brain, the maturation of placental villous trees, or the fibers in the fetal heart remain to be studied and understood in detail. Advances in fetal interventions and surgery furthermore increase the need for ever more precise antenatal diagnosis from fetal MRI. However, the specific properties of the in utero environment, such as fetal and maternal motion, increased field-of-view, tissue interfaces and safety considerations, are significant challenges for most MRI techniques, and particularly for diffusion. Recent years have seen major improvements, driven by the development of bespoke techniques adapted to these specific challenges in both acquisition and processing. Fetal diffusion MRI, an emerging research tool, is now adding valuable novel information for both research and clinical questions. This paper will highlight specific challenges, outline strategies to target them, and discuss two main applications: fetal brain connectomics and placental maturation.

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.

Challenges and Opportunities in Connectome Construction and Quantification in the Developing Human Fetal Brain

The white matter structure of the human brain undergoes critical developmental milestones in utero, which we can observe noninvasively using diffusion-weighted magnetic resonance imaging. In order to understand this fascinating developmental process, we must establish the variability inherent in such a challenging imaging environment and how measurable quantities can be transformed into meaningful connectomes. We review techniques for reconstructing and studying the brain connectome and explore promising opportunities for in utero studies that could lead to more accurate measurement of structural properties and allow for more refined and insightful analyses of the fetal brain. Opportunities for more sophisticated analyses of the properties of the brain and its dynamic changes have emerged in recent years, based on the development of iterative techniques to reconstruct motion-corrupted diffusion-weighted data. Although reconstruction quality is greatly improved, the treatment of fundamental quantities like edge strength requires careful treatment because of the specific challenges of imaging in utero. There are intriguing challenges to overcome, from those in analysis due to both imaging limitations and the significant changes in structural connectivity, to further image processing to address the specific properties of the target anatomy and quantification into a developmental connectome.

The MRI spectrum of congenital cytomegalovirus infection

Human cytomegalovirus (CMV) is an ubiquitous pathogen, with a high worldwide seroprevalence. When acquired in the prenatal period, congenital CMV (cCMV) is a major cause of neurodevelopmental sequelae and hearing loss. cCMV remains an underdiagnosed condition, with no systematic screening implemented in pregnancy or in the postnatal period. Therefore, imaging takes a prominent role in prenatal diagnosis of cCMV. With the prospect of new viable therapies, accurate and timely diagnosis becomes paramount, as well as identification of fetuses at risk for neurodevelopmental sequelae. Fetal magnetic resonance imaging (MRI) provides a complementary method to ultrasound (US) in fetal brain and body imaging. Anterior temporal lobe lesions are the most specific finding, and MRI is superior to US in their detection. Other findings such as ventriculomegaly, cortical malformations and calcifications, as well as hepatosplenomegaly, liver signal changes and abnormal effusions are unspecific. However, when seen in combination these should raise the suspicion of fetal infection, highlighting the need for a full fetal assessment. Still, some fetuses deemed normal on prenatal imaging are symptomatic at birth or develop delayed cCMV-associated symptoms, leaving room for improvement of diagnostic tools. Advanced MR sequences may help in this field and in determining prognosis, but further studies are needed.

Fetal MRI for dummies: what the fetal medicine specialist should know about acquisitions and sequences

Fetal MRI is an increasingly used tool in the field of prenatal diagnosis. While US remains the first line screening tool, as an adjuvant imaging tool, MRI has been proven to increase diagnostic accuracy and change patient counseling. Further, there are instances when US may not be sufficient for diagnosis. As a multidisciplinary field, it is important that every person involved in the referral, diagnosis, counseling and treatment of the patients is familiar with the basic principles, indications and findings of fetal MRI. The purpose of the current paper is to equip radiologists and non-radiologists with basic MRI principles and essential topics in patient preparation and provide illustrative examples of when fetal MRI may be used. This aims to aid the referring clinician in better selecting and improve patient counseling prior to arrival in the radiology department and, ultimately, patient care.

Connectome verification: inter-rater and connection reliability of tract-tracing-based intrinsic hypothalamic connectivity

MOTIVATION

Structural connectomics supports understanding aspects of neuronal dynamics and brain functions. Conducting metastudies of tract-tracing publications is one option to generate connectome databases by collating neuronal connectivity data. Meanwhile, it is a common practice that the neuronal connections and their attributes of such retrospective data collations are extracted from tract-tracing publications manually by experts. As the description of tract-tracing results is often not clear-cut and the documentation of interregional connections is not standardized, the extraction of connectivity data from tract-tracing publications could be complex. This might entail that different experts interpret such non-standardized descriptions of neuronal connections from the same publication in variable ways. Hitherto, no investigation is available that determines the variability of extracted connectivity information from original tract-tracing publications. A relatively large variability of connectivity information could produce significant misconstructions of adjacency matrices with faults in network and graph analyzes. The objective of this study is to investigate the inter-rater and inter-observation variability of tract-tracing-based documentations of neuronal connections. To demonstrate the variability of neuronal connections, data of 16 publications which describe neuronal connections of subregions of the hypothalamus have been assessed by way of example.

RESULTS

A workflow is proposed that allows detecting variability of connectivity at different steps of data processing in connectome metastudies. Variability between three blinded experts was found by comparing the connection information in a sample of 16 publications that describe tract-tracing-based neuronal connections in the hypothalamus. Furthermore, observation scores, matrix visualizations of discrepant connections and weight variations in adjacency matrices are analyzed.

AVAILABILITY

The resulting data and software are available at http://neuroviisas.med.uni-rostock.de/neuroviisas.shtml.

White and grey matter development in utero assessed using motion-corrected diffusion tensor imaging and its comparison to ex utero measures

Objective

Fetal brain diffusion tensor imaging (DTI) offers quantitative analysis of the developing brain. The objective was to 1) quantify DTI measures across gestation in a cohort of fetuses without brain abnormalities using full retrospective correction for fetal head motion 2) compare results obtained in utero to those in preterm infants.

Materials and methods

Motion-corrected DTI analysis was performed on data sets obtained at 1.5T from 32 fetuses scanned between 21.29 and 37.57 (median 31.86) weeks. Results were compared to 32 preterm infants scanned at 3T between 27.43 and 37.14 (median 33.07) weeks. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were quantified by region of interest measurements and tractography was performed.

Results

Fetal DTI was successful in 84% of fetuses for whom there was sufficient data for DTI estimation, and at least one tract could be obtained in 25 cases. Fetal FA values increased and ADC values decreased with age at scan (PLIC FA: p = 0.001; R² = 0.469; slope = 0.011; splenium FA: p < 0.001; R² = 0.597; slope = 0.019; thalamus ADC: p = 0.001; R² = 0.420; slope = − 0.023); similar trends were found in preterm infants.

Conclusion

This study demonstrates that stable DTI is feasible on fetuses and provides evidence for normative values of diffusion properties that are consistent with aged matched preterm infants.

Electronic supplementary material

The online version of this article (10.1007/s10334-019-00743-5) contains supplementary material, which is available to authorized users.

Fetal brain development at 25-39 weeks gestational age: A preliminary study using intravoxel incoherent motion diffusion-weighted imaging

BACKGROUND

The fetal brain developmental changes of water diffusivity and perfusion has not been extensively explored.

PURPOSE/HYPOTHESIS

To evaluate the fetal brain developmental changes of water diffusivity and perfusion using intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI).

STUDY TYPE

Prospective.

POPULATION

Seventy-nine normal singleton fetuses were scanned without sedation of healthy pregnant women.

FIELD STRENGTH/SEQUENCE

5 T MRI/T₁ /₂ -weighted image and IVIM-DWI.

ASSESSMENT

Pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) values were calculated in the frontal (FWM), temporal (TWM), parietal (PWM), and occipital white matter (OWM) as well as cerebellar hemisphere (CH), basal ganglia region (BGR), thalamus (TH), and pons using an IVIM model.

STATISTICAL TESTS

One-way analysis of variable (ANOVA) followed by Bonferroni post-hoc multiple comparison was employed to reveal the difference of IVIM parameters among the investigated brain regions. The linear and the nonlinear polynomial regression analyses were utilized to reveal the correlation between gestational age (GA) and IVIM parameters.

RESULTS

There were significant differences in both D (F(7,623) = 96.64, P = 0.000) and f values (F(7,623) = 2.361, P = 0.0219), but not D* values among the varied brain regions. D values from TWM (r²  = 0.1402, P = 0.0002), PWM (r²  = 0.2245, P = 0.0002), OWM (r²  = 0.2519, P = 0.0002), CH (r²  = 0.2245, P = 0.0002), BGR (r²  = 0.3393, P = 0.0001), TH (r²  = 0.1259, P = 0.0001), and D* value from pons (r²  = 0.2206, P = 0.0002) were significantly correlated with GA using linear regression analysis. Quadratic regression analysis led to results similar to those using the linear regression model.

DATA CONCLUSION

IVIM-DWI parameters may indicate fetal brain developmental alterations but the conclusion is far from reached due to the not as high-powered correlation between IVIM parameters and GA.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:899-909.

Current state of MRI of the fetal brain in utero

In this article we provide an overview of fetal brain development, describe the range of more common fetal neuropathology, and discuss the relevance of in utero MR (iuMR). Although ultrasonography remains the mainstay of fetal brain imaging, iuMR imaging is both feasible and safe, but presents several challenges. We discuss those challenges, the techniques employed to overcome them, and new approaches that may extend the clinical applicability of fetal iuMR. Level of Evidence: Technical Efficacy Stage. J. Magn. Reson. Imaging 2019;49:632-646.