Bias field inconsistency correction of motion-scattered multislice MRI for improved 3D image reconstruction

Structural and functional fetal cardiac imaging using low field (0.55 T) MRI

Purpose

This study aims to investigate the feasibility of using a commercially available clinical 0.55 T MRI scanner for comprehensive structural and functional fetal cardiac imaging.

Methods

Balanced steady-state free precession (bSSFP) and phase contrast (PC) sequences were optimized by in utero studies consisting of 14 subjects for bSSFP optimization and 9 subjects for PC optimization. The signal-to-noise ratio (SNR) of the optimized sequences were investigated. Flow measurements were performed in three vessels, umbilical vein (UV), descending aorta (DAo), and superior vena cava (SVC) using the PC sequences and retrospective gating. The optimized bSSFP, PC and half-Fourier single shot turbo spin-echo (HASTE) sequences were acquired in a cohort of 21 late gestation-age fetuses (>36 weeks) to demonstrate the feasibility of a fetal cardiac exam at 0.55 T. The HASTE stacks were reconstructed to create an isotropic reconstruction of the fetal thorax, followed by automatic great vessel segmentations. The intra-abdominal UV blood flow measurements acquired with MRI were compared to ultrasound UV free-loop flow measurements.

Results

Using the parameters from 1.5 T as a starting point, the bSSFP sequences were optimized at 0.55 T, resulting in a 1.6-fold SNR increase and improved image contrast compared to starting parameters, as well as good visibility of most cardiac structures as rated by two experienced fetal cardiologists. The PC sequence resulted in increased SNR and reduced scan time, subsequent retrospective gating enabled successful blood flow measurements. The reconstructions and automatic great vessel segmentations showed good quality, with 18/21 segmentations requiring no or minor refinements. Blood flow measurements were within the expected range. A comparison of the UV measurements performed with ultrasound and MRI showed agreement between the two sets of measurements, with better correlation observed at lower flows.

Conclusion

We demonstrated the feasibility of low-field (0.55 T) MRI for fetal cardiac imaging. The reduced SNR at low field strength can be effectively compensated for by strategically optimizing sequence parameters. Major fetal cardiac structures and vessels were consistently visualized, and flow measurements were successfully obtained. The late gestation study demonstrated the robustness and reproducibility at low field strength. MRI performed at 0.55 T is a viable option for fetal cardiac examination.

Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation

Introduction

Brain atrophy is a critical biomarker of disease progression and treatment response in neurodegenerative diseases such as multiple sclerosis (MS). Confounding factors such as inconsistent imaging acquisitions hamper the accurate measurement of brain atrophy in the clinic. This study aims to develop and validate a robust deep learning model to overcome these challenges; and to evaluate its impact on the measurement of disease progression.

Methods

Voxel-wise pseudo-atrophy labels were generated using SIENA, a widely adopted tool for the measurement of brain atrophy in MS. Deformation maps were produced for 195 pairs of longitudinal 3D T1 scans from patients with MS. A 3D U-Net, namely DeepBVC, was specifically developed overcome common variances in resolution, signal-to-noise ratio and contrast ratio between baseline and follow up scans. The performance of DeepBVC was compared against SIENA using McLaren test-retest dataset and 233 in-house MS subjects with MRI from multiple time points. Clinical evaluation included disability assessment with the Expanded Disability Status Scale (EDSS) and traditional imaging metrics such as lesion burden.

Results

For 3 subjects in test-retest experiments, the median percent brain volume change (PBVC) for DeepBVC and SIENA was 0.105 vs. 0.198% (subject 1), 0.061 vs. 0.084% (subject 2), 0.104 vs. 0.408% (subject 3). For testing consistency across multiple time points in individual MS subjects, the mean (± standard deviation) PBVC difference of DeepBVC and SIENA were 0.028% (± 0.145%) and 0.031% (±0.154%), respectively. The linear correlation with baseline T2 lesion volume were r = -0.288 (p < 0.05) and r = -0.249 (p < 0.05) for DeepBVC and SIENA, respectively. There was no significant correlation of disability progression with PBVC as estimated by either method (p = 0.86, p = 0.84).

Discussion

DeepBVC is a deep learning powered brain volume change estimation method for assessing brain atrophy used T1-weighted images. Compared to SIENA, DeepBVC demonstrates superior performance in reproducibility and in the context of common clinical scan variances such as imaging contrast, voxel resolution, random bias field, and signal-to-noise ratio. Enhanced measurement robustness, automation, and processing speed of DeepBVC indicate its potential for utilisation in both research and clinical environments for monitoring disease progression and, potentially, evaluating treatment effectiveness.

Three-Dimensional Volumetric Magnetic Resonance Imaging Detects Early Alterations of the Brain Growth in Fetuses With Congenital Heart Disease

BACKGROUND

Several published studies have shown alterations of brain development in third-trimester fetuses with congenital heart disease (CHD). However, little is known about the timing and pattern of altered brain development in fetuses with CHD.

PURPOSE

To investigate the changes in the volume of intracranial structures in fetuses with CHD by three-dimensional (3D) volumetric magnetic resonance imaging (MRI) in the earlier stages of pregnancy (median gestational age [GA], 26 weeks).

STUDY TYPE

Retrospective.

POPULATION

Forty women carrying a fetus with CHD (including 20 fetuses with GA <26 weeks) and 120 pregnant women carrying a healthy fetus (including 50 fetuses with GA <26 weeks).

FIELD STRENGTH/SEQUENCE

Two-dimensional single-shot turbo spin echo sequence at 1.5 -T.

ASSESSMENT

Three-dimensional volumetric parameters from slice-to-volume registered images, including cortical gray matter volume (GMV), subcortical brain tissue volume (SBV), intracranial cavity volume (ICV), lateral ventricles volume (VV), cerebellum, brainstem, and extra-cerebrospinal fluid (e-CSF) were quantified by manual segmentation from one primary and two secondary observers.

STATISTICAL TESTS

Volumes were presented graphically with quadratic curve fitting. Scatterplots were produced mapping volumes against GA in normal and CHD fetuses. For GA <26 weeks, Z scores were calculated and Student's t-tests were conducted to compare volumes between the normal and CHD fetuses.

RESULTS

In fetuses with CHD GMV, SBV, cerebellum, and brainstem were significantly reduced (all P < 0.05) in early stages of pregnancy (GA <26 weeks), with differences becoming progressively greater with increasing GA. Compared with normal fetuses, e-CSF, e-CSF to ICV ratio, and VV were higher in fetuses with CHD (all P < 0.05). However, ICV volume and the GMV to SBV ratio were not significantly reduced in the CHD group (P = 0.94 and P = 0.13, respectively) during the middle gestation (GA <26 weeks).

DATA CONCLUSION

There appear to be alterations of brain development trajectory in CHD fetuses that can be detected by 3D volumetric MRI in the earlier stages of pregnancy.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 3.

In utero MRI identifies consequences of early-gestation alcohol drinking on fetal brain development in rhesus macaques

One factor that contributes to the high prevalence of fetal alcohol spectrum disorder (FASD) is binge-like consumption of alcohol before pregnancy awareness. It is known that treatments are more effective with early recognition of FASD. Recent advances in retrospective motion correction for the reconstruction of three-dimensional (3D) fetal brain MRI have led to significant improvements in the quality and resolution of anatomical and diffusion MRI of the fetal brain. Here, a rhesus macaque model of FASD, involving oral self-administration of 1.5 g/kg ethanol per day beginning prior to pregnancy and extending through the first 60 d of a 168-d gestational term, was utilized to determine whether fetal MRI could detect alcohol-induced abnormalities in brain development. This approach revealed differences between ethanol-exposed and control fetuses at gestation day 135 (G135), but not G110 or G85. At G135, ethanol-exposed fetuses had reduced brainstem and cerebellum volume and water diffusion anisotropy in several white matter tracts, compared to controls. Ex vivo electrophysiological recordings performed on fetal brain tissue obtained immediately following MRI demonstrated that the structural abnormalities observed at G135 are of functional significance. Specifically, spontaneous excitatory postsynaptic current amplitudes measured from individual neurons in the primary somatosensory cortex and putamen strongly correlated with diffusion anisotropy in the white matter tracts that connect these structures. These findings demonstrate that exposure to ethanol early in gestation perturbs development of brain regions associated with motor control in a manner that is detectable with fetal MRI.

Fetal Cardiac MRI: A Review of Technical Advancements

Magnetic resonance imaging (MRI) is an appealing technology for fetal cardiovascular assessment. It can be used to visualize fetal cardiac and vascular anatomy, to quantify fetal blood flow, and to quantify fetal blood oxygen saturation and hematocrit. However, there are practical limitations to the use of conventional MRI for fetal cardiovascular assessment, including the small size and high heart rate of the human fetus, the lack of conventional cardiac gating methods to synchronize data acquisition, and the potential corruption of MRI data due to maternal respiration and unpredictable fetal movements. In this review, we discuss recent technical advances in accelerated imaging, image reconstruction, cardiac gating, and motion compensation that have enabled dynamic MRI of the fetal heart.

Anatomical and diffusion MRI brain atlases of the fetal rhesus macaque brain at 85, 110 and 135 days gestation

Recent advances in image reconstruction techniques have enabled high resolution MRI studies of fetal brain development in human subjects. Rhesus macaques (Macaca mulatta) are valuable animal models for use in studies of fetal brain development due to the similarities between this species and humans in brain development and anatomy. There is a need to develop fetal brain templates for the rhesus macaque to facilitate the characterization of the normal brain growth trajectory and departures from this trajectory in rhesus models of neurodevelopmental disorders. Here we have developed unbiased population-based anatomical T₂-weighted, fractional anisotropy (FA) and apparent diffusion coefficient (ADC) templates for fetal brain from MR images scanned at 3 time points over the second and third trimesters of the 168 day gestational term. Specifically, atlas images are constructed for brains at gestational ages of 85 days (G85, N = 18, 9 females), 110 days (G110, N = 10, 7 females) and 135 days (G135, N = 16, 7 females). We utilized this atlas to perform segmentation of fetal brain MR images and fetal brain volumetric and microstructure analysis. The T₂-weighted template images facilitated characterization of the growth within six fetal brain regions. The template images of diffusion tensor indices provided information related to the maturation of white matter tracts. These growth trajectories are referenced to human studies of fetal brain development. Similarities in the temporal and regional patterns of brain growth over the corresponding periods of central nervous system development are identified between the two species. Atlas images are available online as a reference for registration, reconstruction, segmentation, and for longitudinal analysis of early fetal brain growth over this unique time window.

Three-Layer Image Representation by an Enhanced Illumination-Based Image Fusion Method

The recently developed multiscale-based fusion methods can be improved with two approaches: an advanced image decomposition scheme and an advanced fusion rule. In this paper, three-layer image decomposition, enhanced illumination fusion rule-based method is proposed. The proposed method includes three steps. First, each input image is decomposed into its corresponding smooth, texture, and edge layers using defined local extrema and low-pass filters in the spatial domain. Second, three different strategies are applied as fusion rules for the three-layer representation. To preserve the illumination closely related to tumors, the illumination is corrected by applying a higher contrast to the decomposed image details, including the texture and edge inputs, such as those found in grayscale CT and MRI images. The final fused image is created by the addition of the normalized smooth, texture, and edge image layers. The experiments demonstrate that the proposed method performs better than the existing state-of-the-art fusion methods.

Congenital Zika virus infection as a silent pathology with loss of neurogenic output in the fetal brain

Zika virus (ZIKV) is a flavivirus with teratogenic effects on fetal brain, but the spectrum of ZIKV-induced brain injury is unknown, particularly when ultrasound imaging is normal. In a pregnant pigtail macaque (Macaca nemestrina) model of ZIKV infection, we demonstrate that ZIKV-induced injury to fetal brain is substantial, even in the absence of microcephaly, and may be challenging to detect in a clinical setting. A common and subtle injury pattern was identified, including (i) periventricular T2-hyperintense foci and loss of fetal noncortical brain volume, (ii) injury to the ependymal epithelium with underlying gliosis and (iii) loss of late fetal neuronal progenitor cells in the subventricular zone (temporal cortex) and subgranular zone (dentate gyrus, hippocampus) with dysmorphic granule neuron patterning. Attenuation of fetal neurogenic output demonstrates potentially considerable teratogenic effects of congenital ZIKV infection even without microcephaly. Our findings suggest that all children exposed to ZIKV in utero should receive long-term monitoring for neurocognitive deficits, regardless of head size at birth.

Three-dimensional motion corrected sensitivity encoding reconstruction for multi-shot multi-slice MRI: Application to neonatal brain imaging

PURPOSE

To introduce a methodology for the reconstruction of multi-shot, multi-slice magnetic resonance imaging able to cope with both within-plane and through-plane rigid motion and to describe its application in structural brain imaging.

THEORY AND METHODS

The method alternates between motion estimation and reconstruction using a common objective function for both. Estimates of three-dimensional motion states for each shot and slice are gradually refined by improving on the fit of current reconstructions to the partial k-space information from multiple coils. Overlapped slices and super-resolution allow recovery of through-plane motion and outlier rejection discards artifacted shots. The method is applied to T₂ and T₁ brain scans acquired in different views.

RESULTS

The procedure has greatly diminished artifacts in a database of 1883 neonatal image volumes, as assessed by image quality metrics and visual inspection. Examples showing the ability to correct for motion and robustness against damaged shots are provided. Combination of motion corrected reconstructions for different views has shown further artifact suppression and resolution recovery.

CONCLUSION

The proposed method addresses the problem of rigid motion in multi-shot multi-slice anatomical brain scans. Tests on a large collection of potentially corrupted datasets have shown a remarkable image quality improvement. Magn Reson Med 79:1365-1376, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cerebrospinal Fluid and Parenchymal Brain Development and Growth in the Healthy Fetus

OBJECTIVE

The objective of this study was to apply quantitative magnetic resonance imaging to characterize absolute cerebrospinal fluid (CSF) development, as well as its relative development to fetal brain parenchyma in the healthy human fetus.

DESIGN

We created three-dimensional high-resolution reconstructions of the developing brain for healthy fetuses between 18 and 40 weeks' gestation, segmented the parenchymal and CSF spaces, and calculated the volumes for the lateral, third, and fourth ventricles; extra-axial CSF space; and the cerebrum, cerebellum, and brainstem. From these data, we constructed normograms of the resulting volumes according to gestational age and described the relative development of CSF to fetal brain parenchyma.

RESULTS

Each CSF space demonstrated major increases in volumetric growth during the second half of gestation: third ventricle (23-fold), extra-axial CSF (11-fold), fourth ventricle (8-fold), and lateral ventricle (2-fold). Total CSF volume was related to total brain volume (p < 0.01), as was lateral ventricle to cerebral volume (p < 0.01); however, the fourth ventricle was not related to cerebellar or brainstem volume (p = 0.18-0.19).

RELEVANCE

Abnormalities of the CSF spaces are the most common anomalies of neurologic development detected on fetal screening using neurosonography. Normative values of absolute CSF volume, as well as relative growth in comparison to intracranial parenchyma, provide valuable insight into normal fetal neurodevelopment. These data may provide important biomarkers of early deviations from normal growth, better distinguish between benign variants and early disease, and serve as reference standards for postnatal growth and development in the premature infant.

Spatiotemporal alignment of in utero BOLD-MRI series

PURPOSE

To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs.

MATERIALS AND METHODS

The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison.

RESULTS

The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01).

CONCLUSION

The proposed approach to align MRI time series enables more accurate quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:403-412.

Folding, But Not Surface Area Expansion, Is Associated with Cellular Morphological Maturation in the Fetal Cerebral Cortex

Altered macroscopic anatomical characteristics of the cerebral cortex have been identified in individuals affected by various neurodevelopmental disorders. However, the cellular developmental mechanisms that give rise to these abnormalities are not understood. Previously, advances in image reconstruction of diffusion magnetic resonance imaging (MRI) have made possible high-resolution in utero measurements of water diffusion anisotropy in the fetal brain. Here, diffusion anisotropy within the developing fetal cerebral cortex is longitudinally characterized in the rhesus macaque, focusing on gestation day (G85) through G135 of the 165 d term. Additionally, for subsets of animals characterized at G90 and G135, immunohistochemical staining was performed, and 3D structure tensor analyses were used to identify the cellular processes that most closely parallel changes in water diffusion anisotropy with cerebral cortical maturation. Strong correlations were found between maturation of dendritic arbors on the cellular level and the loss of diffusion anisotropy with cortical development. In turn, diffusion anisotropy changes were strongly associated both regionally and temporally with cortical folding. Notably, the regional and temporal dependence of diffusion anisotropy and folding were distinct from the patterns observed for cerebral cortical surface area expansion. These findings strengthen the link proposed in previous studies between cellular-level changes in dendrite morphology and noninvasive diffusion MRI measurements of the developing cerebral cortex and support the possibility that, in gyroencephalic species, structural differentiation within the cortex is coupled to the formation of gyri and sulci.SIGNIFICANCE STATEMENT Abnormal brain morphology has been found in populations with neurodevelopmental disorders. However, the mechanisms linking cellular level and macroscopic maturation are poorly understood, even in normal brains. This study contributes new understanding to this subject using serial in utero MRI measurements of rhesus macaque fetuses, from which macroscopic and cellular information can be derived. We found that morphological differentiation of dendrites was strongly associated both regionally and temporally with folding of the cerebral cortex. Interestingly, parallel associations were not observed with cortical surface area expansion. These findings support the possibility that perturbed morphological differentiation of cells within the cortex may underlie abnormal macroscopic characteristics of individuals affected by neurodevelopmental disorders.

Fetal brain lesions after subcutaneous inoculation of Zika virus in a pregnant nonhuman primate

We describe the development of fetal brain lesions after Zika virus (ZIKV) inoculation in a pregnant pigtail macaque. Periventricular lesions developed within 10 d and evolved asymmetrically in the occipital-parietal lobes. Fetal autopsy revealed ZIKV in the brain and significant cerebral white matter hypoplasia, periventricular white matter gliosis, and axonal and ependymal injury. Our observation of ZIKV-associated fetal brain lesions in a nonhuman primate provides a model for therapeutic evaluation.

Registration and Modeling From Spaced and Misaligned Image Volumes

We address the problem of object modeling from 3D and 3D+T data made up of images, which contain different parts of an object of interest, are separated by large spaces, and are misaligned with respect to each other. These images have only a limited number of intersections, hence making their registration particularly challenging. Furthermore, such data may result from various medical imaging modalities and can, therefore, present very diverse spatial configurations. Previous methods perform registration and object modeling (segmentation and interpolation) sequentially. However, sequential registration is ill-suited for the case of images with few intersections. We propose a new methodology, which, regardless of the spatial configuration of the data, performs the three stages of registration, segmentation, and shape interpolation from spaced and misaligned images simultaneously. We integrate these three processes in a level set framework, in order to benefit from their synergistic interactions. We also propose a new registration method that exploits segmentation information rather than pixel intensities, and that accounts for the global shape of the object of interest, for increased robustness and accuracy. The accuracy of registration is compared against traditional mutual information based methods, and the total modeling framework is assessed against traditional sequential processing and validated on artificial, CT, and MRI data.

Characterization of Laminar Zones in the Mid-Gestation Primate Brain with Magnetic Resonance Imaging and Histological Methods

Distinct populations of progenitor and postmitotic neural and glial cells are stratified in the fetal primate brain across developmentally transient tissue zones between the ventricular and pial surfaces. These zones were originally identified by light microscopy. However, it has subsequently been shown that various forms of magnetic resonance image (MRI) contrast can be used to distinguish layers of developing neural tissue in ex vivo, as well as in vivo (including in utero) conditions. Here we compare mid-gestation rhesus macaque tissue zones identified using histological techniques to ex vivo as well as in utero MRI performed on the same brains. These data are compared to mid-gestation fetal human brain MRI results, obtained in utero. We observe strong similarity between MRI contrast in vivo and post mortem, which facilitates interpretation of in utero images based on the histological characterization performed here. Additionally, we observe differential correspondence between the various forms of ex vivo MRI contrast and microscopy data, with maps of the water apparent diffusion coefficient providing the closest match to histologically-identified lamina of the nonhuman primate brain. Examination of histology and post mortem MRI helps to provide a better understanding of cytoarchitectrual characteristics that give rise to in utero MRI contrast.

Computer-assisted surgical planning and intraoperative guidance in fetal surgery: a systematic review

Fetal surgery has become a clinical reality, with interventions for twin‐to‐twin transfusion syndrome (TTTS) and spina bifida demonstrated to improve outcome. Fetal imaging is evolving, with the use of 3D ultrasound and fetal MRI becoming more common in clinical practise. Medical imaging analysis is also changing, with technology being developed to assist surgeons by creating 3D virtual models that improve understanding of complex anatomy, and prove powerful tools in surgical planning and intraoperative guidance.

We introduce the concept of computer‐assisted surgical planning, and present the results of a systematic review of image reconstruction for fetal surgical planning that identified six articles using such technology.

Indications from other specialities suggest a benefit of surgical planning and guidance to improve outcomes. There is therefore an urgent need to develop fetal‐specific technology in order to improve fetal surgical outcome. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd.

What's already known about this topic?

Fetal surgery has now become a clinical reality, with interventions such as laser treatment for twin‐to‐twin transfusion syndrome (TTTS) and open fetal surgery for spina bifida demonstrated in randomised control trials to improve neonatal outcome

Other specialities are increasingly utilising computer‐assisted surgical planning software, with evidence that this can improve outcome

What does this study add?

We feel that there is an urgent need to develop fetal‐specific technology for surgical planning as it is likely to play an important role in improving outcomes from fetal surgery

Mapping the developing human brain in utero using quantitative MR imaging techniques

Magnetic resonance imaging of the human fetal brain has been a clinical tool for many years and provides valuable additional information to compliment more common ultrasound studies. Advances in both MRI acquisition and post processing over the last 10 years have enabled full 3D imaging and the accurate combination of data acquired in different head positions to create improved geometric integrity, tissue contrast, and resolution. This research is now motivating the development of new quantitative MRI-based techniques for clinical imaging that can more accurately characterize brain development and detect abnormalities. In this article, we will review some of the key areas that are driving changes in our understanding of fetal brain growth using quantitative measures derived from in utero MRI and the possible directions for its increased use in improving the evaluation of pregnancies and the accurate characterization of abnormal brain growth.

Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction

There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies.

Quantifying and modelling tissue maturation in the living human fetal brain

Recent advances in medical imaging are beginning to allow us to quantify brain tissue maturation in the growing human brain prior to normal term age, and are beginning to shed new light on early human brain growth. These advances compliment the work already done in cellular level imaging in animal and post mortem studies of brain development. The opportunities for collaborative research that bridges the gap between macroscopic and microscopic windows on the developing brain are significant. The aim of this paper is to provide a review of the current research into MR imaging of the living fetal brain with the aim of motivating improved interfaces between the two fields. The review begins with a description of faster MRI techniques that are capable of freezing motion of the fetal head during the acquisition of a slice, and how these have been combined with advanced post-processing algorithms to build 3D images from motion scattered slices. Such rich data has motivated the development of techniques to automatically label developing tissue zones within MRI data allowing their quantification in 3D and 4D within the normally growing fetal brain. These methods have provided the basis for later work that has created the first maps of tissue growth rate and cortical folding in normally developing brains in-utero. These measurements provide valuable findings that compliment those derived from post-mortem anatomy, and additionally allow for the possibility of larger population studies of the influence of maternal environmental and genes on early brain development.

A method for handling intensity inhomogenieties in fMRI sequences of moving anatomy of the early developing brain

This paper presents a method for intensity inhomogeniety removal in fMRI studies of a moving subject. In such studies, subtle changes in signal as the subject moves in the presence of a bias field can be a significant confound for BOLD signal analysis. The proposed method avoids the need for a specific tissue model or assumptions about tissue homogeneity by making use of the multiple views of the underlying bias field provided by the subject's motion. A parametric bias field model is assumed and a regression model is used to estimate the basis function weights of this model. Quantitative evaluation of the effects of motion and noise in motion estimates are performed using simulated data. Results demonstrate the strength and robustness of the new method compared to the state of the art 4D nonparametric bias estimator (N4ITK). We also qualitatively demonstrate the impact of the method on resting state neuroimage analysis of a moving adult brain with simulated motion and bias fields, as well as on in vivo moving fetal fMRI.

BTK: an open-source toolkit for fetal brain MR image processing

Studies about brain maturation aim at providing a better understanding of brain development and links between brain changes and cognitive development. Such studies are of great interest for diagnosis help and clinical course of development and treatment of illnesses. However, the processing of fetal brain MR images remains complicated which limits the translation from the research to the clinical domain. In this article, we describe an open-source image processing toolkit dedicated to these images. In this toolkit various tools are included such as: denoising, image reconstruction, super-resolution and tractography. The BTK resource program (distributed under CeCILL-B license) is developed in C++ and relies on common medical imaging libraries such as Insight Toolkit (ITK), Visualization Toolkit (VTK) and Open Multi-Processing (OpenMP).

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.