Deciphering the developmental order and microstructural patterns of early white matter pathways in a diffusion MRI based fetal brain atlas

Texture-Based Classification of Fetal Growth Restriction From Intrauterine Neurosonographic Image

OBJECTIVE

Fetal growth restriction (FGR) is a condition where fetuses fail to reach their genetic potential for growth, posing a significant health challenge for newborns. The aim of this research was to explore the efficacy of texture-based analysis of neurosonographic images in identifying FGR in fetuses, which may provide a promising tool for early assessment of FGR.

METHODS

A retrospective analysis collected 100 intrauterine neurosonographic images from 50 FGR and 50 gestational age-appropriate fetuses. Using MaZda software, approximately 300 texture features were extracted from occipital white matter (OWM) and cerebellum of intrauterine neurosonographic images, respectively. Then 10 optimal features were separately selected by 3 algorithms, including the Fisher coefficient method, the method of minimizing classification error probability and average correlation coefficients, and the mutual information coefficient method. Further, the 10 statistically most significant features were selected from these sets to form the mixed feature set. After nonlinear discriminant analysis was performed to reduce feature dimensionality, the artificial neural network (ANN) classifier was conducted, respectively.

RESULTS

For OWM and cerebellum, a total of 11 and 14 statistically significant features were selected. When the mixed feature sets of OWM and cerebellum were applied to ANN classifier, classification accuracy were 90.00% (κ = 0.800; P < .001) and 93.00% (κ = 0.860; P < .001), and the receiver operating characteristic curve for identifying FGR showed an area under the curve of 0.82 and 0.87.

CONCLUSIONS

Texture analysis of fetal intrauterine neurosonographic images is a feasible and noninvasive strategy for evaluating FGR fetuses.

A detailed spatiotemporal atlas of the white matter tracts for the fetal brain

This study presents the construction of a comprehensive spatiotemporal atlas of white matter tracts in the fetal brain for every gestational week between 23 and 36 wk using diffusion MRI (dMRI). Our research leverages data collected from fetal MRI scans, capturing the dynamic changes in the brain's architecture and 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), coinciding with the intensity of histogenic 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.

White Matter Tract Crossing and Bottleneck Regions in the Fetal Brain

There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been investigated for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 62 fetal brain scans and extracted a set of 51 distinct white matter tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20%-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75% and 80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. These results highlight the relevance of these regions to key developmental processes, specifically, the dispersion of projection fibers, the protracted growth of commissural pathways, and the emergence of association tracts that contribute to the formation of complex intersection regions. These developmental interactions lead to a high prevalence of crossing fibers and bottleneck areas, reflecting the intricate organization required for establishing structural and functional connectivity. Additionally, our results highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.

Assessing the Agreement Between Diffusion Tension Imaging (DTI) and T2-Weighted MRI Sequence for Biometry of the Fetal Corpus Callosum

BACKGROUND/OBJECTIVES

Little is known about the advantages of Diffusion Tensor Imaging (DTI) when evaluating the fetal corpus callosum (CC), a sensitive indicator for normal brain development. This study evaluates the contribution of DTI compared to T2-weighted imaging to assess fetal CC biometry.

METHODS

Data from the fetal MRI exams of singleton pregnancies between July 2017 and 2019 were retrospectively analyzed. Mid-sagittal sections were used to measure the CC biometry, and inter- and intra-observer agreements were assessed using the interclass correlation coefficient (ICC), targeting an ICC above 0.85.

RESULTS

The results from 100 patients (mean gestational age, 32.24 weeks) indicated excellent inter-observer reliability for DTI (ICC = 0.904, 95% CI = 0.815-0.952) and moderate agreement for T2-weighted imaging (ICC = 0.719, 95% CI = 0.556-0.842). Intra-observer assessments showed excellent reliability for both DTI and T2-weighted imaging (ICC = 0.967, 95% CI = 0.933-0.984 and ICC = 0.942, 95% CI = 0.884-0.971, respectively). However, a comparison between DTI and T2-weighted images for CC biometry showed poor agreement (ICC = 0.290, 95% CI = 0.071-0.476).

CONCLUSIONS

In conclusion, the study highlights a lack of agreement between DTI and T2-weighted imaging in fetal CC biometry, suggesting the need for further research to understand this discrepancy and the role of DTI in fetal health.

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.

Diffusion tensor transformation for personalizing target volumes in radiation therapy

Diffusion tensor imaging (DTI) is used in tumor growth models to provide information on the infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific DTI is not available, a template image such as a DTI atlas can be transformed to the patient anatomy using image registration. This study investigates a model, the invariance under coordinate transform (ICT), that transforms diffusion tensors from a template image to the patient image, based on the principle that the tumor growth process can be mapped, at any point in time, between the images using the same transformation function that we use to map the anatomy. The ICT model allows the mapping of tumor cell densities and tumor fronts (as iso-levels of tumor cell density) from the template image to the patient image for inclusion in radiotherapy treatment planning. The proposed approach transforms the diffusion tensors to simulate tumor growth in locally deformed anatomy and outputs the tumor cell density distribution over time. The ICT model is validated in a cohort of ten brain tumor patients. Comparative analysis with the tumor cell density in the original template image shows that the ICT model accurately simulates tumor cell densities in the deformed image space. By creating radiotherapy target volumes as tumor fronts, this study provides a framework for more personalized radiotherapy treatment planning, without the use of additional imaging.

Advances in Fetal Brain Imaging

Over the last 20 years, there have been remarkable developments in fetal brain MR imaging analysis methods. This article delves into the specifics of structural imaging, diffusion imaging, functional MR imaging, and spectroscopy, highlighting the latest advancements in motion correction, fetal brain development atlases, and the challenges and innovations. Furthermore, this article explores the clinical applications of these advanced imaging techniques in comprehending and diagnosing fetal brain development and abnormalities.

From circuits to lifespan: translating mouse and human timelines with neuroimaging based tractography

Age is a major predictor of developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging. The timeline of human developmental circuits is well known. It is unclear how such timelines compare to those in mice. We lack age alignments across the lifespan of mice and humans. Here, we build upon our Translating Time resource, which is a tool that equates corresponding ages during development. We collected 477 time points (n=1,132 observations) from age-related changes in body, bone, dental, and brain processes to equate corresponding ages across humans and mice. We acquired high-resolution diffusion MR scans of mouse brains (n=12) at sequential stages of postnatal development (postnatal day 3, 4, 12, 21, 60) to trace the timeline of brain circuit maturation (e.g., olfactory association pathway, corpus callosum). We found heterogeneity in white matter pathway growth. The corpus callosum largely ceases to grow days after birth while the olfactory association pathway grows through P60. We found that a P3 mouse equates to a human at roughly GW24, and a P60 mouse equates to a human in teenage years. Therefore, white matter pathway maturation is extended in mice as it is in humans, but there are species-specific adaptations. For example, olfactory-related wiring is protracted in mice, which is linked to their reliance on olfaction. Our findings underscore the importance of translational tools to map common and species-specific biological processes from model systems to humans.

White matter tract crossing and bottleneck regions in the fetal brain

There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.

Development of the Fetal Brain Corticocortical Structural Network during the Second-to-Third Trimester Based on Diffusion MRI

During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the interwired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and postmortem fetal brains, the in utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in utero dMRI data from human fetuses of both sexes between 26 and 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intrahemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.

Dynamic changes in subplate and cortical plate microstructure at the onset of cortical folding in vivo

Cortical gyrification takes place predominantly during the second to third trimester, alongside other fundamental developmental processes, such as the development of white matter connections, lamination of the cortex and formation of neural circuits. The mechanistic biology that drives the formation cortical folding patterns remains an open question in neuroscience. In our previous work, we modelled the in utero diffusion signal to quantify the maturation of microstructure in transient fetal compartments, identifying patterns of change in diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester. In this work, we apply the same modelling approach to explore whether microstructural maturation of these compartments is correlated with the process of gyrification. We quantify the relationship between sulcal depth and tissue anisotropy within the cortical plate (CP) and underlying subplate (SP), key transient fetal compartments often implicated in mechanistic hypotheses about the onset of gyrification. Using in utero high angular resolution multi-shell diffusion-weighted imaging (HARDI) from the Developing Human Connectome Project (dHCP), our analysis reveals that the anisotropic, tissue component of the diffusion signal in the SP and CP decreases immediately prior to the formation of sulcal pits in the fetal brain. By back-projecting a map of folded brain regions onto the unfolded brain, we find evidence for cytoarchitectural differences between gyral and sulcal areas in the late second trimester, suggesting that regional variation in the microstructure of transient fetal compartments precedes, and thus may have a mechanistic function, in the onset of cortical folding in the developing human brain.

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.

Fetal brain MRI atlases and datasets: A review

Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., "brain template" and "brain atlas"), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging.

Diffusion-Weighted MRI of the Fetal Brain in Fetal Growth Restriction With Maternal Preeclampsia or Gestational Hypertension

BACKGROUND

The fetal neurodevelopmental microstructural alterations of intrauterine exposure to preeclampsia (PE) or gestational hypertension (GH) remain unknown.

PURPOSE

To evaluate the differences in diffusion-weighted imaging (DWI) of the fetal brain between normotensive pregnancies and PE/GH pregnancies, with a focus on PE/GH pregnancies with fetal growth restriction (FGR).

STUDY TYPE

Retrospective matched case-control study.

POPULATION

40 singleton pregnancies with PE/GH complicated by FGR, and 3 paired control groups (PE/GH without FGR, normotensive FGR, normotensive pregnancies) (28-38 gestational weeks).

FIELD STRENGTH/SEQUENCE

DWI with single-shot echo-planar imaging at 1.5 Tesla.

ASSESSMENT

The apparent diffusion coefficient (ADC) values were calculated in the centrum semi-ovale (CSO), parietal white matter (PWM), frontal white matter (FWM), occipital white matter (OWM), temporal white matter (TWM), basal ganglia, thalamus (THAL), pons, and cerebellar hemisphere.

STATISTICAL TESTS

Student t test or Wilcoxon matched test was used to reveal the difference of ADC values among the investigated brain regions. A correlation between gestational age (GA) and ADC values was determined by linear regression analysis.

RESULTS

Compared with fetuses in PE/GH without FGR and those with normotensive pregnancies, fetuses in the PE/GH with FGR group had significantly lower average ADC measurements of supratentorial regions (1.65 ± 0.09 vs. 1.71 ± 0.10 10-3  mm2 /sec; vs. 1.73 ± 0.11 10-3  mm2 /sec, respectively). Regions of significantly decreased ADC values in the fetal brain included CSO, FWM, PWM, OWM, TWM and THAL in cases of PE/GH with FGR. ADC values from supratentorial regions in PE/GH pregnancies were not significantly correlated with GA (P = 0.12, 0.26); however, this trend was statistically significant in the normotensive groups.

DATA CONCLUSION

ADC values may indicate fetal brain developmental alterations in PE/GH with FGR fetuses but more microscopic and morphological studies are necessary to provide additional evidence to offer a different interpretation of this trend in fetal brain.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 3.