MR imaging methods for assessing fetal brain development

Fetal-BET: Brain Extraction Tool for Fetal MRI

Goal: In this study, we address the critical challenge of fetal brain extraction from MRI sequences. Fetal MRI has played a crucial role in prenatal neurodevelopmental studies and in advancing our knowledge of fetal brain development in-utero. Fetal brain extraction is a necessary first step in most computational fetal brain MRI pipelines. However, it poses significant challenges due to 1) non-standard fetal head positioning, 2) fetal movements during examination, and 3) vastly heterogeneous appearance of the developing fetal brain and the neighboring fetal and maternal anatomy across gestation, and with various sequences and scanning conditions. Development of a machine learning method to effectively address this task requires a large and rich labeled dataset that has not been previously available. Currently, there is no method for accurate fetal brain extraction on various fetal MRI sequences. Methods: In this work, we first built a large annotated dataset of approximately 72,000 2D fetal brain MRI images. Our dataset covers the three common MRI sequences including T2-weighted, diffusion-weighted, and functional MRI acquired with different scanners. These data include images of normal and pathological brains. Using this dataset, we developed and validated deep learning methods, by exploiting the power of the U-Net style architectures, the attention mechanism, feature learning across multiple MRI modalities, and data augmentation for fast, accurate, and generalizable automatic fetal brain extraction. Results: Evaluations on independent test data, including data available from other centers, show that our method achieves accurate brain extraction on heterogeneous test data acquired with different scanners, on pathological brains, and at various gestational stages. Conclusions:By leveraging rich information from diverse multi-modality fetal MRI data, our proposed deep learning solution enables precise delineation of the fetal brain on various fetal MRI sequences. The robustness of our deep learning model underscores its potential utility for fetal brain imaging.

Neuromorphological Atlas of Human Prenatal Brain Development: White Paper

Recent morphological data on human brain development are quite fragmentary. However, they are highly requested for a number of medical practices, educational programs, and fundamental research in the fields of embryology, cytology and histology, neurology, physiology, path anatomy, neonatology, and others. This paper provides the initial information on the new online Human Prenatal Brain Development Atlas (HBDA). The Atlas will start with forebrain annotated hemisphere maps, based on human fetal brain serial sections at the different stages of prenatal ontogenesis. Spatiotemporal changes in the regional-specific immunophenotype profiles will also be demonstrated on virtual serial sections. The HBDA can serve as a reference database for the neurological research, which provides opportunity to compare the data obtained by noninvasive techniques, such as neurosonography, X-ray computed tomography and magnetic resonance imaging, functional magnetic resonance imaging, 3D high-resolution phase-contrast computed tomography visualization techniques, as well as spatial transcriptomics data. It could also become a database for the qualitative and quantitative analysis of individual variability in the human brain. Systemized data on the mechanisms and pathways of prenatal human glio- and neurogenesis could also contribute to the search for new therapy methods for a large spectrum of neurological pathologies, including neurodegenerative and cancer diseases. The preliminary data are now accessible on the special HBDA website.

BOUNTI: Brain vOlumetry and aUtomated parcellatioN for 3D feTal MRI

Fetal MRI is widely used for quantitative brain volumetry studies. However, currently, there is a lack of universally accepted protocols for fetal brain parcellation and segmentation. Published clinical studies tend to use different segmentation approaches that also reportedly require significant amounts of time-consuming manual refinement. In this work, we propose to address this challenge by developing a new robust deep learning-based fetal brain segmentation pipeline for 3D T2w motion corrected brain images. At first, we defined a new refined brain tissue parcellation protocol with 19 regions-of-interest using the new fetal brain MRI atlas from the Developing Human Connectome Project. This protocol design was based on evidence from histological brain atlases, clear visibility of the structures in individual subject 3D T2w images and the clinical relevance to quantitative studies. It was then used as a basis for developing an automated deep learning brain tissue parcellation pipeline trained on 360 fetal MRI datasets with different acquisition parameters using semi-supervised approach with manually refined labels propagated from the atlas. The pipeline demonstrated robust performance for different acquisition protocols and GA ranges. Analysis of tissue volumetry for 390 normal participants (21-38 weeks gestational age range), scanned with three different acquisition protocols, did not reveal significant differences for major structures in the growth charts. Only minor errors were present in < 15% of cases thus significantly reducing the need for manual refinement. In addition, quantitative comparison between 65 fetuses with ventriculomegaly and 60 normal control cases were in agreement with the findings reported in our earlier work based on manual segmentations. These preliminary results support the feasibility of the proposed atlas-based deep learning approach for large-scale volumetric analysis. The created fetal brain volumetry centiles and a docker with the proposed pipeline are publicly available online at https://hub.docker.com/r/fetalsvrtk/segmentation (tag brain_bounti_tissue).

Semi-automatic segmentation of the fetal brain from magnetic resonance imaging

BACKGROUND

Volumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings.

METHODS

Adult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9-36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB's Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman's test for repeated measures.

RESULTS

Comparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6-0.8] and 0.54 (IQR = 0.4-0.6), respectively. A Friedman's test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001).

CONCLUSION

Deformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.

Retrospective motion correction in foetal MRI for clinical applications: existing methods, applications and integration into clinical practice

Foetal MRI is a complementary imaging method to antenatal ultrasound. It provides advanced information for detection and characterisation of foetal brain and body anomalies. Even though modern single shot sequences allow fast acquisition of 2D slices with high in-plane image quality, foetal MRI is intrinsically corrupted by motion. Foetal motion leads to loss of structural continuity and corrupted 3D volumetric information in stacks of slices. Furthermore, the arbitrary and constantly changing position of the foetus requires dynamic readjustment of acquisition planes during scanning.

Early magnetic resonance imaging biomarkers of schizophrenia spectrum disorders: Toward a fetal imaging perspective

There is mounting evidence to implicate the intrauterine environment as the initial pathogenic stage for neuropsychiatric disease. Recent developments in magnetic resonance imaging technology are making a multimodal analysis of the fetal central nervous system a reality, allowing analysis of structural and functional parameters. Exposures to a range of pertinent risk factors whether preconception or in utero can now be indexed using imaging techniques within the fetus' physiological environment. This approach may determine the first "hit" required for diseases that do not become clinically manifest until adulthood, and which only have subtle clinical markers during childhood and adolescence. A robust characterization of a "multi-hit" hypothesis may necessitate a longitudinal birth cohort; within this investigative paradigm, the full range of genetic and environmental risk factors can be assessed for their impact on the early developing brain. This will lay the foundation for the identification of novel biomarkers and the ability to devise methods for early risk stratification and disease prevention. However, these early markers must be followed over time: first, to account for neural plasticity, and second, to assess the effects of postnatal exposures that continue to drive the individual toward disease. We explore these issues using the schizophrenia spectrum disorders as an illustrative paradigm. However, given the potential richness of fetal magnetic resonance imaging, and the likely overlap of biomarkers, these concepts may extend to a range of neuropsychiatric conditions.

Fetal dynamic magnetic resonance imaging using Doppler ultrasound gating for the assessment of the aortic isthmus: A feasibility study

INTRODUCTION

Cardiovascular magnetic resonance imaging (MRI) is established in cardiac evaluation in postnatal life, but its application to the fetus has been hampered by technical limitations. We aimed to investigate the feasibility of dynamic MRI of the fetal aortic isthmus using a magnetic resonance-compatible Doppler ultrasound device for cardiac gating.

MATERIAL AND METHODS

This prospective study included 19 fetuses at a median gestational age of 32.3 weeks (range 26-38 weeks). Imaging of the fetal aortic isthmus was assessed by (a) dynamic steady-state free precession MRI using a magnetic resonance-compatible Doppler ultrasound device for cardiac gating and (b) echocardiography. Diameters of the aortic isthmus were compared by two blinded observers. Magnetic resonance image quality was assessed independently by two observers using a four-point scale (1 = low quality, 4 = high quality). Furthermore, we performed four-dimensional flow MRI of the fetal aorta in three of these fetuses.

RESULTS

The Doppler ultrasound device for cardiac gating allowed successful dynamic MRI examinations of the aortic isthmus in 18/19 (95%) fetuses. Evaluation of the fetal aortic isthmus was possible by both MRI (15/18, 83%) and echocardiography (16/18, 89%) (P < .05). Diameters of the aortic isthmus were concordant for MRI (3.8 ± 0.9 mm) and echocardiography (4.0 ± 1.1 mm), with a variability of 10.8% (bias -2.3%, 95% limits of agreement -23.9% to 19.3%). Overall magnetic resonance image quality was good (score 4 in 67% and score 3 in 23%) with good inter-observer agreement (κ = 0.75; 95% CI 0.5-1). Fetal four-dimensional flow MRI allowed visualization of aortic flow dynamics.

CONCLUSIONS

Doppler ultrasound-gating allows dynamic MRI of the fetal aorta with the potential to serve as a complementary imaging tool in cases where echocardiography is inconclusive.

A new approach to automatic fetal brain extraction from MRI using a variational level set method

BACKGROUND AND PURPOSE

Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal brain, it is not possible to use methods routinely used for extraction of adult brains for fetal brains. The aim of the present study was to use a variational level set approach to extract fetal brain from T2-weighted MR images of the womb.

METHODS

Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the fetus brain was automatically determined. Then, the variational level set was used for fetus brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated.

RESULTS AND CONCLUSIONS

The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal brain from MR images was confirmed, both statistically and visually through cross-validation.

The "vermian-crest angle": does it allow accurate categorisation of fetal upward rotation of cerebellar vermis on intrauterine MRI? A pilot study

AIM

To test a new parameter to assess the position of the fetal cerebellar vermis in the posterior fossa (PF) using intrauterine magnetic resonance imaging (MRI).

MATERIALS AND METHODS

The angle between the cerebellar vermis and the internal occipital crest (vermian-crest angle, VCA) was assessed retrospectively using MRI in fetuses with and without PF anomalies. Spearman's rank test was used to investigate correlation of the VCA with gestational age (GA). Groups were compared using Student's t-test and the one-way analysis of variance (ANOVA) with the Bonferroni adjustment. Box-and-whisker plots were also used.

RESULTS

One hundred and two normal cases were identified. Mean±SD GA at MRI was 26.5±2.8 weeks (range: 22-32 weeks). The VCA was 64.49±11.5° independently of GA (r=0.19; p=0.12). In addition, 30 fetuses at 19-28 weeks were identified with Blake's pouch cyst (BPC; n=5), Dandy-Walker malformation (DWM; n=12), mega cisterna magna (MCM; n=10), and vermian hypoplasia (VH; n=3). The VCA was significantly different in the DWM (p<0.001) and BPC (p<0.001) subgroups, but was not significantly different in cases of VH (p=0.84) and MCM (p=0.95) in comparison with controls.

CONCLUSIONS

A new method to assess vermian position within the PF using intrauterine MRI was assessed. In combination with the other existing parameters, it may be helpful for addressing the categorisation of upward rotation of the fetal cerebellar vermis; however, further studies are necessary to strengthen the present findings.

Magnetic resonance imaging of the fetal brain at 3 Tesla: Preliminary experience from a single series

To report our preliminary experience with cerebral fetal magnetic resonance imaging (MRI) with a 3 Tesla (3T) scanner. We assessed feasibility, time of acquisition, and possibility to establish a diagnosis.Fifty-nine pregnant women had fetal MRI performed during the third trimester of pregnancy due to clinical or sonography concern of a central nervous system anomaly. No fetal or maternal sedation was used. The MRI protocol consisted of T2 turbo-spin-echo images in 3 planes of space. No T1-weighted images were performed. All images were analyzed by 2 pediatric neuroradiologists, who evaluated spatial resolution, artifacts, time of acquisition, and possibility to establish a diagnosis suspected by sonography.Examinations were performed safely for all patients. The images required longer time of acquisition (approximately 75 seconds for each plane in the space). The specific absorption rate was not exceeded in any fetus. Cerebral fetal MRI was normal in 22 cases. The spectrum of diagnostics included isolated ventriculomegaly, posterior fossa malformation, corpus callosum malformation, gyration anomalies, craniosynostosis, tuberous sclerosis, microcephaly, external hydrocephaly, midline arachnoid cyst, cerebral lesions, and persistent hyperplastic primitive vitreous.In our series, 3 T MRI of fetal brain was feasible and able to establish a diagnosis but required longer time of acquisition.

Neuroimaging perspectives on fetal motor behavior

We are entering a new era of understanding human development with the ability to perform studies at the earliest time points possible. There is a substantial body of evidence to support the concept that early motor behaviour originates from supraspinal motor centres, reflects neurological integrity, and that altered patterns of behaviour precede clinical manifestation of disease. Cine Magnetic Resonance Imaging (cineMRI) has established its value as a novel method to visualise motor behaviour in the human fetus, building on the wealth of knowledge gleaned from ultrasound based studies. This paper presents a state of the art review incorporating findings from human and preclinical models, the insights from which, we propose, can proceed a reconceptualisation of fetal motor behaviour using advanced imaging techniques. Foremost is the need to better understand the role of the intrauterine environment, and its inherent unique set of stimuli that activate sensorimotor pathways and shape early brain development. Finally, an improved model of early motor development, combined with multimodal imaging, will provide a novel source of in utero biomarkers predictive of neurodevelopmental disorders.

Single-Shot Version of FLAIR Sequence in the Detection of Intraventricular Anomalies: Preliminary Experience in Fetal MR Imaging

OBJECTIVE

To evaluate single-shot (ss) FLAIR sequence in the detection of intraventricular anomalies in a series of fetuses showing mild-moderate ventriculomegaly at ultrasound.

SUBJECTS AND METHODS

Fetuses with mild-moderate isolated ventriculomegaly, which underwent MR imaging between 2003 and 2014 were considered eligible. Fetuses were examined by standard MR protocol and ss-FLAIR sequence, tailored for snapshot imaging. Two paediatric neuroradiologists evaluated MR images.

RESULTS

542 cases were selected. MR imaging was performed at mean 26 weeks of gestation. ss-FLAIR sequence detected intraventricular findings, consistent with cysts in 10 cases. In 3/10 intraventricular cysts were also evident on ss-FSE T2 and FSE T1-weighted images. In no case diffusion weighted imaging was able to detect cyst. No cyst was highlighted on ss-FSE-T2 and FSE-T1-weighted images, without being visible also on ss-FLAIR.

CONCLUSION

ss-FLAIR sequence may be useful to detect intraventricular anomalies especially when fetal position or maternal obesity prevents adequate visualization by ultrasound.

Imaging putative foetal cerebral blood oxygenation using susceptibility weighted imaging (SWI)

OBJECTIVE

To evaluate the magnetic susceptibility, ∆χ v , as a surrogate marker of venous blood oxygen saturation, S v O 2, in second- and third-trimester normal human foetuses.

METHODS

Thirty-six pregnant women, having a mean gestational age (GA) of 31 2/7 weeks, underwent magnetic resonance imaging (MRI). Susceptibility-weighted imaging (SWI) data from the foetal brain were acquired. ∆χ v of the superior sagittal sinus (SSS) was quantified using MR susceptometry from the intra-vascular phase measurements. Assuming the magnetic property of foetal blood, ∆χ do , is the same as that of adult blood, S v O 2 was derived from the measured Δχ v . The variation of ∆χ v and S v O 2, as a function of GA, was statistically evaluated.

RESULTS

The mean ∆χ v in the SSS in the second-trimester (n = 8) and third-trimester foetuses (n = 28) was found to be 0.34± 0.06 ppm and 0.49 ±0.05 ppm, respectively. Correspondingly, the derived S v O 2 values were 69.4% ±3.27% and 62.6% ±3.25%. Although not statistically significant, an increasing trend (p = 0.08) in Δχ v and a decreasing trend (p = 0.22) in S v O 2 with respect to advancing gestation was observed.

CONCLUSION

We report cerebral venous blood magnetic susceptibility and putative oxygen saturation in healthy human foetuses. Cerebral oxygen saturation in healthy human foetuses, despite a slight decreasing trend, does not change significantly with advancing gestation.

KEY POINTS

• Cerebral venous magnetic susceptibility and oxygenation in human foetuses can be quantified. • Cerebral venous oxygenation was not different between second- and third-trimester foetuses. • Foetal cerebral venous oxygenation does not change significantly with advancing gestation.

Annual Research Review: Not just a small adult brain: understanding later neurodevelopment through imaging the neonatal brain

BACKGROUND

There has been a recent proliferation in neuroimaging research focusing on brain development in the prenatal, neonatal and very early childhood brain. Early brain injury and preterm birth are associated with increased risk of neurodevelopmental disorders, indicating the importance of this early period for later outcome.

SCOPE AND METHODOLOGY

Although using a wide range of different methodologies and investigating diverse samples, the common aim of many of these studies has been to both track normative development and investigate deviations in this development to predict behavioural, cognitive and neurological function in childhood. Here we review structural and functional neuroimaging studies investigating the developing brain. We focus on practical and technical complexities of studying this early age range and discuss how neuroimaging techniques have been successfully applied to investigate later neurodevelopmental outcome.

CONCLUSIONS

Neuroimaging markers of later outcome still have surprisingly low predictive power and their specificity to individual neurodevelopmental disorders is still under question. However, the field is still young, and substantial challenges to both acquiring and modeling neonatal data are being met.

Evaluation of a Portable Doppler Ultrasound Gating Device for Fetal Cardiac MR Imaging: Initial Results at 1.5T and 3T

Purpose:

Fetal cardiac MRI has the potential to play an important role in the assessment of fetal cardiac pathologies, but it is up to now not feasible due to a missing gating method. The purpose of this work was the evaluation of Doppler ultrasound (DUS) for external fetal cardiac gating with regard to compatibility, functionality, and reliability. Preliminary results were assessed performing fetal cardiac MRI.

Methods:

An MRI conditional DUS device was developed to obtain a gating signal from the fetal heart. The MRI compatibility was evaluated at 1.5T and 3T using B₁ field maps and gradient echo images. The quality and sensitivity of the DUS device to detect the fetal heart motion for cardiac gating were evaluated outside the MRI room in 15 fetuses. A dynamic fetal cardiac phantom was employed to evaluate distortions of the DUS device and gating signal due to electromagnetic interferences at 1.5T and 3T. In the first in vivo experience, dynamic fetal cardiac images were acquired in four-chamber view at 1.5T and 3T in two fetuses.

Results:

The maximum change in the B₁ field and signal intensity with and without the DUS device was <6.5% for 1.5T and 3T. The sensitivity of the DUS device to detect the fetal heartbeat was 99.1%. Validation of the DUS device using the fetal cardiac phantom revealed no electromagnetic interferences at 1.5T or 3T and a high correlation to the simulated heart frequencies. Fetal cardiac cine images were successfully applied and showed good image quality.

Conclusion:

An MR conditional DUS gating device was developed and evaluated revealing safety, compatibility, and reliability for different field strengths. In a preliminary experience, the DUS device was successfully applied for in vivo fetal cardiac imaging at 1.5T and 3T.

Toward the automatic quantification of in utero brain development in 3D structural MRI: A review

Investigating the human brain in utero is important for researchers and clinicians seeking to understand early neurodevelopmental processes. With the advent of fast magnetic resonance imaging (MRI) techniques and the development of motion correction algorithms to obtain high-quality 3D images of the fetal brain, it is now possible to gain more insight into the ongoing maturational processes in the brain. In this article, we present a review of the major building blocks of the pipeline toward performing quantitative analysis of in vivo MRI of the developing brain and its potential applications in clinical settings. The review focuses on T1- and T2-weighted modalities, and covers state of the art methodologies involved in each step of the pipeline, in particular, 3D volume reconstruction, spatio-temporal modeling of the developing brain, segmentation, quantification techniques, and clinical applications. Hum Brain Mapp 38:2772-2787, 2017. © 2017 Wiley Periodicals, Inc.

An exploration of the potential utility of fetal cardiovascular MRI as an adjunct to fetal echocardiography

OBJECTIVES

Fetal cardiovascular magnetic resonance imaging (MRI) offers a potential alternative to echocardiography, although in practice, its use has been limited. We sought to explore the need for additional imaging in a tertiary fetal cardiology unit and the usefulness of standard MRI sequences.

METHODS

Cases where the diagnosis was not fully resolved using echocardiography were referred for MRI. Following a three-plane localiser, fetal movement was assessed with a balanced steady-state free precession (bSSFP) cine. Single-shot fast spin echo and bSSFP sequences were used for diagnostic imaging.

RESULTS

Twenty-two fetal cardiac MRIs were performed over 12 months, at mean gestation of 32 weeks (26-38 weeks). The majority of referrals were for suspected vascular abnormalities (17/22), particularly involving the aortic arch (n = 10) and pulmonary vessels (n = 4). Single-shot fast spin echo sequences produced 'black-blood' images, useful for examining the extracardiac vasculature in these cases. BSSFP sequences were more useful for intracardiac structures. Real-time SSFP allowed for dynamic assessment of structures such as cardiac masses, with enhancement patterns also allowing for tissue characterisation in these cases.

CONCLUSIONS

Fetal vascular abnormalities such as coarctation can be difficult to diagnose by using ultrasound. Fetal MRI may have an adjunctive role in the evaluation of the extracardiac vascular anatomy and tissue characterisation. © 2016 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.

Normal development

Numerous events are involved in brain development, some of which are detected by neuroimaging. Major changes in brain morphology are depicted by brain imaging during the fetal period while changes in brain composition can be demonstrated in both pre- and postnatal periods. Although ultrasonography and computed tomography can show changes in brain morphology, these techniques are insensitive to myelination that is one of the most important events occurring during brain maturation. Magnetic resonance imaging (MRI) is therefore the method of choice to evaluate brain maturation. MRI also gives insight into the microstructure of brain tissue through diffusion-weighted imaging and diffusion tensor imaging. Metabolic changes are also part of brain maturation and are assessed by proton magnetic resonance spectroscopy. Understanding and knowledge of the different steps in brain development are required to be able to detect morphologic and structural changes on neuroimaging. Consequently alterations in normal development can be depicted.

Fast Volume Reconstruction From Motion Corrupted Stacks of 2D Slices

Capturing an enclosing volume of moving subjects and organs using fast individual image slice acquisition has shown promise in dealing with motion artefacts. Motion between slice acquisitions results in spatial inconsistencies that can be resolved by slice-to-volume reconstruction (SVR) methods to provide high quality 3D image data. Existing algorithms are, however, typically very slow, specialised to specific applications and rely on approximations, which impedes their potential clinical use. In this paper, we present a fast multi-GPU accelerated framework for slice-to-volume reconstruction. It is based on optimised 2D/3D registration, super-resolution with automatic outlier rejection and an additional (optional) intensity bias correction. We introduce a novel and fully automatic procedure for selecting the image stack with least motion to serve as an initial registration target. We evaluate the proposed method using artificial motion corrupted phantom data as well as clinical data, including tracked freehand ultrasound of the liver and fetal Magnetic Resonance Imaging. We achieve speed-up factors greater than 30 compared to a single CPU system and greater than 10 compared to currently available state-of-the-art multi-core CPU methods. We ensure high reconstruction accuracy by exact computation of the point-spread function for every input data point, which has not previously been possible due to computational limitations. Our framework and its implementation is scalable for available computational infrastructures and tests show a speed-up factor of 1.70 for each additional GPU. This paves the way for the online application of image based reconstruction methods during clinical examinations. The source code for the proposed approach is publicly available.

The Contribution of MRI after Fetal Anomalies Have Been Diagnosed by Ultrasound: Correlation with Postnatal Outcomes

Objective: The aim of this study was to investigate the additional value of fetal magnetic resonance imaging (MRI) in the assessment and management of fetuses with abnormal findings on ultrasound. Methods: A total of 257 patients who had fetal MRI following the ultrasound diagnosis of a fetal anomaly, or were at high risk, were included. The patients were grouped by referral category for fetal MRI. Fetal MRI was compared to ultrasound in the detection of anomalies, i.e. whether additional findings were identified and if this changed diagnosis, prognosis and management during pregnancy. Results: Ultrasound findings were confirmed on fetal MRI in 89% of the cases. Additional findings were seen with MRI in 28% of all patients. The diagnosis changed in 21% and the prognosis in 19% of the cases. Perinatal management changed in 8%. The antenatal findings were confirmed in all cases that had a postmortem examination following termination of pregnancy. In all the pregnancies that continued to delivery and for which the postnatal outcome is known, the findings correlated in 97% of the cases. Conclusion: Fetal MRI provided additional detection of fetal anomalies, leading to a change in diagnosis and prognosis in 19% of the cases. Neonatal and postmortem findings mostly confirmed the fetal MRI diagnosis, suggesting it to be a useful tool for clinical decision making in perinatal management.

Use of resting-state functional MRI to study brain development and injury in neonates

Advances in methodology have led to expanded application of resting-state functional MRI (rs-fMRI) to the study of term and prematurely born infants during the first years of life, providing fresh insight into the earliest forms of functional cerebral development. In this review, we detail our evolving understanding of the use of rs-fMRI for studying neonates. We initially focus on the biological processes of cortical development related to resting-state network development. We then review technical issues principally affecting neonatal investigations, including the effects of subject motion during acquisition and image distortions related to magnetic susceptibility effects. We next summarize the literature in which rs-fMRI is used to study normal brain development during the early postnatal period, the effects of prematurity, and the effects of cerebral injury. Finally, we review potential future directions for the field, such as the use of complementary imaging modalities and advanced analysis techniques.

Automated fetal brain segmentation from 2D MRI slices for motion correction

Motion correction is a key element for imaging the fetal brain in-utero using Magnetic Resonance Imaging (MRI). Maternal breathing can introduce motion, but a larger effect is frequently due to fetal movement within the womb. Consequently, imaging is frequently performed slice-by-slice using single shot techniques, which are then combined into volumetric images using slice-to-volume reconstruction methods (SVR). For successful SVR, a key preprocessing step is to isolate fetal brain tissues from maternal anatomy before correcting for the motion of the fetal head. This has hitherto been a manual or semi-automatic procedure. We propose an automatic method to localize and segment the brain of the fetus when the image data is acquired as stacks of 2D slices with anatomy misaligned due to fetal motion. We combine this segmentation process with a robust motion correction method, enabling the segmentation to be refined as the reconstruction proceeds. The fetal brain localization process uses Maximally Stable Extremal Regions (MSER), which are classified using a Bag-of-Words model with Scale-Invariant Feature Transform (SIFT) features. The segmentation process is a patch-based propagation of the MSER regions selected during detection, combined with a Conditional Random Field (CRF). The gestational age (GA) is used to incorporate prior knowledge about the size and volume of the fetal brain into the detection and segmentation process. The method was tested in a ten-fold cross-validation experiment on 66 datasets of healthy fetuses whose GA ranged from 22 to 39 weeks. In 85% of the tested cases, our proposed method produced a motion corrected volume of a relevant quality for clinical diagnosis, thus removing the need for manually delineating the contours of the brain before motion correction. Our method automatically generated as a side-product a segmentation of the reconstructed fetal brain with a mean Dice score of 93%, which can be used for further processing.

Multidimensional analysis of fetal posterior fossa in health and disease

Fetal magnetic resonance imaging (MRI) is now routinely used to further investigate cerebellar malformations detected with ultrasound. However, the lack of 2D and 3D biometrics in the current literature hinders the detailed characterisation and classification of cerebellar anomalies. The main objectives of this fetal neuroimaging study were to provide normal posterior fossa growth trajectories during the second and third trimesters of pregnancy via semi-automatic segmentation of reconstructed fetal brain MR images and to assess common cerebellar malformations in comparison with the reference data. Using a 1.5-T MRI scanner, 143 MR images were obtained from 79 normal control and 53 fetuses with posterior fossa abnormalities that were grouped according to the severity of diagnosis on visual MRI inspections. All quantifications were performed on volumetric datasets, and supplemental outcome information was collected from the surviving infants. Normal growth trajectories of total brain, cerebellar, vermis, pons and fourth ventricle volumes showed significant correlations with 2D measurements and increased in second-order polynomial trends across gestation (Pearson r, p < 0.05). Comparison of normal controls to five abnormal cerebellum subgroups depicted significant alterations in volumes that could not be detected exclusively with 2D analysis (MANCOVA, p < 0.05). There were 15 terminations of pregnancy, 8 neonatal deaths, and a spectrum of genetic and neurodevelopmental outcomes in the assessed 24 children with cerebellar abnormalities. The given posterior fossa biometrics enhance the delineation of normal and abnormal cerebellar phenotypes on fetal MRI and confirm the advantages of utilizing advanced neuroimaging tools in clinical fetal research.

Atlas learning in fetal brain development

Magnetic resonance imaging has become an important noninvasive technique to gain insight into fetal brain development. Its capabilities go beyond ultrasound when diagnosing high-risk pregnancies. To summarize observations across a population in magnetic resonance imaging studies, reference systems such as atlases that establish correspondences across a cohort are key. In this article, we review the evolution of atlas-building methods in light of their relevance, limitations, and benefits for the modeling of human brain development. Starting with single anatomical templates to which brain scans where mapped to such as Talairach and Montreal Neurological Institute space, we explore the uses of atlases as a means to establish correspondences across a cohort and as a model that captures the population characteristics of the cases the atlas is built from. We discuss methods that capture features of increasingly heterogeneous populations and approaches that are able to generalize with only minimal annotation. The main focus of this review are methods that explicitly model the variability in the population with regard to time, such as in the modeling of disease progression and brain development. We highlight the applicability and limitations of state-of-the art approaches, how insights from the study of disease progression are helpful in developmental studies, and point to the directions of future research that is still necessary.

Spatial-temporal atlas of human fetal brain development during the early second trimester

During the second trimester, the human fetal brain undergoes numerous changes that lead to substantial variation in the neonatal in terms of its morphology and tissue types. As fetal MRI is more and more widely used for studying the human brain development during this period, a spatiotemporal atlas becomes necessary for characterizing the dynamic structural changes. In this study, 34 postmortem human fetal brains with gestational ages ranging from 15 to 22 weeks were scanned using 7.0 T MR. We used automated morphometrics, tensor-based morphometry and surface modeling techniques to analyze the data. Spatiotemporal atlases of each week and the overall atlas covering the whole period with high resolution and contrast were created. These atlases were used for the analysis of age-specific shape changes during this period, including development of the cerebral wall, lateral ventricles, Sylvian fissure, and growth direction based on local surface measurements. Our findings indicate that growth of the subplate zone is especially striking and is the main cause for the lamination pattern changes. Changes in the cortex around Sylvian fissure demonstrate that cortical growth may be one of the mechanisms for gyration. Surface deformation mapping, revealed by local shape analysis, indicates that there is global anterior-posterior growth pattern, with frontal and temporal lobes developing relatively quickly during this period. Our results are valuable for understanding the normal brain development trajectories and anatomical characteristics. These week-by-week fetal brain atlases can be used as reference in in vivo studies, and may facilitate the quantification of fetal brain development across space and time.

Development and validation of a semiquantitative brain maturation score on fetal MR images: initial results

PURPOSE

To develop a valid, reliable, and simple-to-use semiquantitative visual scale of fetal brain maturation for use in clinical fetal MR imaging assessment and interpretation.

MATERIALS AND METHODS

This is a retrospective assessment of data from a previous study that was prospective, institutional review board approved, and HIPAA compliant. Forty-eight normal pregnancies with a gestational age (GA) of 25 to 35 weeks were studied. A fetal total maturation score (fTMS) was developed by utilizing six subscores that evaluated cortical sulcation, myelination, and the germinal matrix and provided a single combined numerical value to be evaluated as a marker of brain maturity. The fTMS was correlated with GA and segmented brain volume. A regression model that associated GA based on the visual fTMS scoring was determined. The model was validated with a leave-one-out cross validation procedure.

RESULTS

Mean GA was 29.3 weeks ± 2.9 (standard deviation) (range, 25.2-35.3 weeks) and mean fTMS was 8.6 ± 3.7 (range, 4-16). The intraclass correlation coefficient between the three readers (independent and blinded) was 0.948 (P < .001). The correlations were as follows: GA and brain volume, r = 0.964 (P < .001); fTMS and brain volume, r = 0.970 (P < .001); and GA and fTMS, r = 0.975 (P < .001). A regression model to calculate GA based on fTMS yielded the following equation: calculated GA (weeks) = 22.86 + 0.748 fTMS (P < .001; adjusted R(2) = 0.946). The standard error of the model for calculation of fetal GA from the visual fTMS scale was ± 4.8 days.

CONCLUSION

If validated further, the fTMS scale might be used to assess morphologic brain maturity of fetuses between 25 and 35 weeks GA on a single-case basis in a clinical setting.

The brain in the belly: what and how of fetal neuroimaging?

This work reviews magnetic resonance imaging in the developing human brain. It focuses on fetal brain imaged in vivo and in utero with complementary sections on abnormalities seen in clinical settings, and on potential of diffusion tensor imaging and of proton magnetic resonance spectroscopy. The main purposes are to illustrate the normal fetal developing brain and its abnormalities commonly encountered in utero, and to emphasize the potential role of adjunct techniques such as diffusion imaging and spectroscopy that may help elucidate fetal brain maturation and its abnormalities.

Reconstruction of fetal brain MRI with intensity matching and complete outlier removal

We propose a method for the reconstruction of volumetric fetal MRI from 2D slices, comprising super-resolution reconstruction of the volume interleaved with slice-to-volume registration to correct for the motion. The method incorporates novel intensity matching of acquired 2D slices and robust statistics which completely excludes identified misregistered or corrupted voxels and slices. The reconstruction method is applied to motion-corrupted data simulated from MRI of a preterm neonate, as well as 10 clinically acquired thick-slice fetal MRI scans and three scan-sequence optimized thin-slice fetal datasets. The proposed method produced high quality reconstruction results from all the datasets to which it was applied. Quantitative analysis performed on simulated and clinical data shows that both intensity matching and robust statistics result in statistically significant improvement of super-resolution reconstruction. The proposed novel EM-based robust statistics also improves the reconstruction when compared to previously proposed Huber robust statistics. The best results are obtained when thin-slice data and the correct approximation of the point spread function is used. This paper addresses the need for a comprehensive reconstruction algorithm of 3D fetal MRI, so far lacking in the scientific literature.

Motion-compensation techniques in neonatal and fetal MR imaging

SUMMARY

Fetal and neonatal MR imaging is increasingly used as a complementary diagnostic tool to sonography. MR imaging is an ideal technique for imaging fetuses and neonates because of the absence of ionizing radiation, the superior contrast of soft tissues compared with sonography, the availability of different contrast options, and the increased FOV. Motion in the normally mobile fetus and the unsettled, sleeping, or sedated neonate during a long acquisition will decrease image quality in the form of motion artifacts, hamper image interpretation, and often necessitate a repeat MR imaging to establish a diagnosis. This article reviews current techniques of motion compensation in fetal and neonatal MR imaging, including the following: 1) motion-prevention strategies (such as adequate patient preparation, patient coaching, and sedation, when required), 2) motion-artifacts minimization methods (such as fast imaging protocols, data undersampling, and motion-resistant sequences), and 3) motion-detection/correction schemes (such as navigators and self-navigated sequences, external motion-tracking devices, and postprocessing approaches) and their application in fetal and neonatal brain MR imaging. Additionally some background on the repertoire of motion of the fetal and neonatal patient and the resulting artifacts will be presented, as well as insights into future developments and emerging techniques of motion compensation.

Multi-atlas multi-shape segmentation of fetal brain MRI for volumetric and morphometric analysis of ventriculomegaly

The recent development of motion robust super-resolution fetal brain MRI holds out the potential for dramatic new advances in volumetric and morphometric analysis. Volumetric analysis based on volumetric and morphometric biomarkers of the developing fetal brain must include segmentation. Automatic segmentation of fetal brain MRI is challenging, however, due to the highly variable size and shape of the developing brain; possible structural abnormalities; and the relatively poor resolution of fetal MRI scans. To overcome these limitations, we present a novel, constrained, multi-atlas, multi-shape automatic segmentation method that specifically addresses the challenge of segmenting multiple structures with similar intensity values in subjects with strong anatomic variability. Accordingly, we have applied this method to shape segmentation of normal, dilated, or fused lateral ventricles for quantitative analysis of ventriculomegaly (VM), which is a pivotal finding in the earliest stages of fetal brain development, and warrants further investigation. Utilizing these innovative techniques, we introduce novel volumetric and morphometric biomarkers of VM comparing these values to those that are generated by standard methods of VM analysis, i.e., by measuring the ventricular atrial diameter (AD) on manually selected sections of 2D ultrasound or 2D MRI. To this end, we studied 25 normal and abnormal fetuses in the gestation age (GA) range of 19 to 39 weeks (mean=28.26, stdev=6.56). This heterogeneous dataset was essentially used to 1) validate our segmentation method for normal and abnormal ventricles; and 2) show that the proposed biomarkers may provide improved detection of VM as compared to the AD measurement.

Measurements using 7.0 T post-mortem magnetic resonance imaging of the scalar dimensions of the fetal brain between 12 and 20 weeks gestational age

In this study, scalar values for the fetal brain from 12 to 20 weeks gestational age were obtained. Fifty-two fetal specimens of 12-20 weeks gestational age with an anatomically normal and developmentally appropriate central nervous system (CNS) were scanned using a 7.0 T magnetic resonance imaging (MRI) scanner. The linear biometric measurements of the brain were then determined. All the measurements (except for the interhemispheric distance) were found to increase linearly with gestational age, although each increased at a different growth rates. The 95% confidence interval for each value was obtained. These data may be considered to be a valuable reference for the assessment of normal fetal brain development in clinical settings and as a supplement to post-mortem MRI or anatomical investigations.

Functional connectivity MRI in infants: exploration of the functional organization of the developing brain

Advanced neuroimaging techniques have been increasingly applied to the study of preterm and term infants in an effort to further define the functional cerebral architecture of the developing brain. Despite improved understanding of the complex relationship between structure and function obtained through these investigations, significant questions remain regarding the nature, location, and timing of the maturational changes which occur during early development. Functional connectivity magnetic resonance imaging (fcMRI) utilizes spontaneous, low frequency (< 0.1 Hz), coherent fluctuations in blood oxygen level dependent (BOLD) signal to identify networks of functional cerebral connections. Due to the intrinsic characteristics of its image acquisition and analysis, fcMRI offers a novel neuroimaging approach well suited to investigation of infants. Recently, this methodology has been successfully applied to examine neonatal populations, defining normative patterns of large-scale neural network development in the maturing brain. The resting-state networks (RSNs) identified in these studies reflect the evolving cerebral structural architecture, presumably driven by varied genetic and environmental influences. Principal features of these investigations and their role in characterization of the tenets of neural network development during this critical developmental period are highlighted in this review. Despite these successes, optimal methods for fcMRI data acquisition and analysis for this population have not yet been defined. Further, appropriate schemes for interpretation and translation of fcMRI results remain unknown, a matter of increasing importance as functional neuroimaging findings are progressively applied in the clinical arena. Notwithstanding these concerns, fcMRI provides insight into the earliest forms of cerebral connectivity and therefore holds great promise for future neurodevelopmental investigations.

Early folding patterns and asymmetries of the normal human brain detected from in utero MRI

Early cortical folding and the emergence of structural brain asymmetries have been previously analyzed by neuropathology as well as qualitative analysis of magnetic resonance imaging (MRI) of fetuses and preterm neonates. In this study, we present a dedicated image analysis framework and its application for the detection of folding patterns during the critical period for the formation of many primary sulci (20-28 gestational weeks). Using structural information from in utero MRI, we perform morphometric analysis of cortical plate surface development and modeling of early folding in the normal fetal brain. First, we identify regions of the fetal brain surface that undergo significant folding changes during this developmental period and provide precise temporal staging of these changes for each region of interest. Then, we highlight the emergence of interhemispheric structural asymmetries that may be related to future functional specialization of cortical areas. Our findings complement previous descriptions of early sulcogenesis based on neuropathology and qualitative evaluation of 2D in utero MRI by accurate spatial and temporal mapping of the emergence of individual sulci as well as structural brain asymmetries. The study provides the missing starting point for their developmental trajectories and extends our understanding of normal cortical folding.

Development of axonal pathways in the human fetal fronto-limbic brain: histochemical characterization and diffusion tensor imaging

The development of cortical axonal pathways in the human brain begins during the transition between the embryonic and fetal period, happens in a series of sequential events, and leads to the establishment of major long trajectories by the neonatal period. We have correlated histochemical markers (acetylcholinesterase (AChE) histochemistry, antibody against synaptic protein SNAP-25 (SNAP-25-immunoreactivity) and neurofilament 200) with the diffusion tensor imaging (DTI) database in order to make a reconstruction of the origin, growth pattern and termination of the pathways in the period between 8 and 34 postconceptual weeks (PCW). Histological sections revealed that the initial outgrowth and formation of joined trajectories of subcortico-frontal pathways (external capsule, cerebral stalk-internal capsule) and limbic bundles (fornix, stria terminalis, amygdaloid radiation) occur by 10 PCW. As early as 11 PCW, major afferent fibers invade the corticostriatal junction. At 13-14 PCW, axonal pathways from the thalamus and basal forebrain approach the deep moiety of the cortical plate, causing the first lamination. The period between 15 and 18 PCW is dominated by elaboration of the periventricular crossroads, sagittal strata and spread of fibers in the subplate and marginal zone. Tracing of fibers in the subplate with DTI is unsuccessful due to the isotropy of this zone. Penetration of the cortical plate occurs after 24-26 PCW. In conclusion, frontal axonal pathways form the periventricular crossroads, sagittal strata and 'waiting' compartments during the path-finding and penetration of the cortical plate. Histochemistry is advantageous in the demonstration of a growth pattern, whereas DTI is unique for demonstrating axonal trajectories. The complexity of fibers is the biological substrate of selective vulnerability of the fetal white matter.

Contributions of diffusion-weighted imaging to fetal and neonatal imaging

Diffusion-weighted imaging has contributed to our understanding of fetal and neonatal brain development. This article will review the role of diffusion-weighted imaging and diffusion tensor imaging in fetuses and neonates, focusing primarily on normal brain developmental processes and then on pathologic processes that can be characterized using diffusion tensor imaging.

Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses

Imaging of the human fetus using magnetic resonance (MR) is an essential tool for quantitative studies of normal as well as abnormal brain development in utero. However, because of fundamental differences in tissue types, tissue properties and tissue distribution between the fetal and adult brain, automated tissue segmentation techniques developed for adult brain anatomy are unsuitable for this data. In this paper, we describe methodology for automatic atlas-based segmentation of individual tissue types in motion-corrected 3D volumes reconstructed from clinical MR scans of the fetal brain. To generate anatomically correct automatic segmentations, we create a set of accurate manual delineations and build an in utero 3D statistical atlas of tissue distribution incorporating developing gray and white matter as well as transient tissue types such as the germinal matrix. The probabilistic atlas is associated with an unbiased average shape and intensity template for registration of new subject images to the space of the atlas. Quantitative whole brain 3D validation of tissue labeling performed on a set of 14 fetal MR scans (20.57-22.86 weeks gestational age) demonstrates that this atlas-based EM segmentation approach achieves consistently high DSC performance for the main tissue types in the fetal brain. This work indicates that reliable measures of brain development can be automatically derived from clinical MR imaging and opens up possibility of further 3D volumetric and morphometric studies with multiple fetal subjects.

Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI

Fast magnetic resonance imaging slice acquisition techniques such as single shot fast spin echo are routinely used in the presence of uncontrollable motion. These techniques are widely used for fetal magnetic resonance imaging (MRI) and MRI of moving subjects and organs. Although high-quality slices are frequently acquired by these techniques, inter-slice motion leads to severe motion artifacts that are apparent in out-of-plane views. Slice sequential acquisitions do not enable 3-D volume representation. In this study, we have developed a novel technique based on a slice acquisition model, which enables the reconstruction of a volumetric image from multiple-scan slice acquisitions. The super-resolution volume reconstruction is formulated as an inverse problem of finding the underlying structure generating the acquired slices. We have developed a robust M-estimation solution which minimizes a robust error norm function between the model-generated slices and the acquired slices. The accuracy and robustness of this novel technique has been quantitatively assessed through simulations with digital brain phantom images as well as high-resolution newborn images. We also report here successful application of our new technique for the reconstruction of volumetric fetal brain MRI from clinically acquired data.

Analysis of the harmonized growth pattern of fetal organs by multidimensional scaling and hierarchical clustering

The development of an organ may be affected by various growth and differentiation factors released from other organs. These factors are believed to have important effects on the development of multiple organs. To detect and analyze harmonized development among multiple organs, similarities in growth patterns among fetal organs were examined using multivariate analysis. Ninety human fetuses obtained from the Kyoto Collection of Human Embryos were dissected. Harmonized development of organs was evaluated by multidimensional scaling and cluster analysis using measurements (length, width, height, and weight) of the fetal organs. Similar growth patterns were observed between the brain, including cerebrum, diencephalon, and midbrain (cerebrum-to-midbrain [Cer-Mid]), and pituitary (crown-rump length [CRL] 95-155 mm). Further, similar growth patterns were observed between the liver and Cer-Mid and cerebellum (Cb; CRL 156-202 mm), and between Cer-Mid and Cb (CRL 203-253 mm). Similarities in growth patterns were also observed between right and left lungs (CRL 99-235 mm) and between the aorta and heart (CRL 139-187 mm), but not between the lung and pulmonary trunk. These findings revealed synchronized development among fetal organs and suggested a functional and structural relationship among different organs in the prenatal period. These relationships include the existence of common factors in organ development, such as cross-talk mediated by humoral factors, and the presence of an anatomical and functional relationship in the fetal circulatory system.

A spatiotemporal atlas of MR intensity, tissue probability and shape of the fetal brain with application to segmentation

Modeling and analysis of MR images of the developing human brain is a challenge due to rapid changes in brain morphology and morphometry. We present an approach to the construction of a spatiotemporal atlas of the fetal brain with temporal models of MR intensity, tissue probability and shape changes. This spatiotemporal model is created from a set of reconstructed MR images of fetal subjects with different gestational ages. Groupwise registration of manual segmentations and voxelwise nonlinear modeling allow us to capture the appearance, disappearance and spatial variation of brain structures over time. Applying this model to atlas-based segmentation, we generate age-specific MR templates and tissue probability maps and use them to initialize automatic tissue delineation in new MR images. The choice of model parameters and the final performance are evaluated using clinical MR scans of young fetuses with gestational ages ranging from 20.57 to 24.71 weeks. Experimental results indicate that quadratic temporal models can correctly capture growth-related changes in the fetal brain anatomy and provide improvement in accuracy of atlas-based tissue segmentation.

Magnetic resonance imaging of the fetal brain

PURPOSE OF REVIEW

Fetal magnetic resonance imaging (MRI) is a relatively new clinical application but is becoming increasingly used in fetal medicine in combination with the established technique of antenatal ultrasound. A review of the literature to date provides information for clinicians to help assess which patients they should be referring for fetal MRI and what additional information to ultrasound they can obtain.

RECENT FINDINGS

This review covers recent articles on practical aspects of imaging, MR findings in common disorders and comparisons with ultrasound. It includes information on current applications for fetal MRI, new sequence acquisitions and postprocessing techniques. Fetal motion is the single most important barrier to improving image data.

SUMMARY

Fetal MR has become an established tool for assessing the fetal brain. It provides complementary information to ultrasound. However, further optimization of this technique is still required to ensure it is exploited to the full in fetal medicine.

Diagnostic pitfalls in fetal brain MRI

Recent technological advances in fetal magnetic resonance imaging (MRI) and increased reliability of MRI in depicting abnormalities and lesions, especially in the central nervous system, are increasingly bringing up challenging issues with regard to accurate diagnosis. There are also pitfalls not only attributable to image acquisition but also in clinical interpretation. The misinterpretation of findings because of insufficient knowledge about fetal brain development as visualized by MRI may also be regarded as an important limitation of fetal MRI. We provide an overview of the most common pitfalls experienced in fetal MRI in routine practice, demonstrate how to identify some of the factors that lead to imaging misinterpretation, and suggest ways to tackle these problems, with an emphasis on MR techniques and image calibration.

Normal development of the fetal brain by MRI

The fetal brain is a dynamic structure, which can now be imaged using magnetic resonance imaging (MRI). This article will review techniques of fetal MRI as well as several key aspects of brain development and their appearance on MRI. An understanding of normal fetal brain development is essential to correctly identifying developmental abnormalities.