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We present a novel method for higher order reconstruction of fetal diffusion MRI signal that enables detection of fiber crossings. We combine data-driven motion and intensity correction with super-resolution reconstruction and spherical harmonic parametrisation to reconstruct data scattered in both spatial and angular domains into consistent fetal dMRI signal suitable for further diffusion analysis. We show that intensity correction is essential for good performance of the method and identify anatomically plausible fiber crossings. The proposed methodology has potential to facilitate detailed investigation of developing brain connectivity and microstructure in-utero. ispartof: IEEE TRANSACTIONS ON MEDICAL IMAGING vol:39 issue:4 pages:1104-1113 ispartof: location:United States status: published

IntroductionThe dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors.MethodsWe sought to first map typical cortical micro and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n=270). Then we offer a comprehensive characterisation of the cortical consequences of preterm birth in 78 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months.ResultsIn the term-born neonatal brain, we observed regionally specific age-associated changes in cortical morphology and microstructure, including rapid surface expansion, cortical thickness increase, reduction in cortical anisotropy and increase in neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months.ConclusionWe showed that preterm birth alters cortical micro and macrostructural maturation near the time of fullterm birth. Deviations from normative development were highly variable between individual preterm infants.

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

Diffusion MRI has the potential to provide important information about the connectivity and microstructure of the human brain during normal and abnormal development, non-invasively and in vivo. Recent developments in MRI hardware and reconstruction methods now permit the acquisition of large amounts of data within relatively short scan times. This makes it possible to acquire more informative multi-shell data, with diffusion-sensitisation applied along many directions over multiple b-value shells. Such schemes are characterised by the number of shells acquired, and the specific b-value and number of directions sampled for each shell. However, there is currently no clear consensus as to how to optimise these parameters. In this work, we propose a means of optimising multi-shell acquisition schemes by estimating the information content of the diffusion MRI signal, and optimising the acquisition parameters for sensitivity to the observed effects, in a manner agnostic to any particular diffusion analysis method that might subsequently be applied to the data. This method was used to design the acquisition scheme for the neonatal diffusion MRI sequence used in the developing Human Connectome Project, which aims to acquire high quality data and make it freely available to the research community. The final protocol selected by the algorithm, and currently in use within the dHCP, consists of b = 0, 400, 1000, 2600 s/mm2 with 20, 64, 88 & 128 DW directions per shell respectively.HighlightsA data driven method is presented to design multi-shell diffusion MRI acquisition schemes (b-values and no. directions).This method optimises the multi-shell scheme for maximum sensitivity to the information content in the signal.When applied in neonates, the data suggest that a b=0 + 3 shell strategy is appropriate

Diffusion MRI offers a unique probe into neural microstructure and connectivity in the developing brain. However, analysis of neonatal brain imaging data is complicated by inevitable subject motion, leading to a series of scattered slices that need to be aligned within and across diffusion-weighted contrasts. Here, we develop a reconstruction method for scattered slice multi-shell high angular resolution diffusion imaging (HARDI) data, jointly estimating an uncorrupted data representation and motion parameters at the slice or multiband excitation level. The reconstruction relies on data-driven representation of multi-shell HARDI data using a bespoke spherical harmonics and radial decomposition (SHARD), which avoids imposing model assumptions, thus facilitating to compare various microstructure imaging methods in the reconstructed output. Furthermore, the proposed framework integrates slice-level outlier rejection, distortion correction, and slice profile correction. We evaluate the method in the neonatal cohort of the developing Human Connectome Project (650 scans). Validation experiments demonstrate accurate slice-level motion correction across the age range and across the range of motion in the population. Results in the neonatal data show successful reconstruction even in severely motion-corrupted subjects. In addition, we illustrate how local tissue modelling can extract advanced microstructure features such as orientation distribution functions from the motion-corrected reconstructions., revision. 15 pages, 10 figures, 2 tables

Prenatal detection of congenital heart disease facilitates the opportunity for potentially life-saving care immediately after the baby is born. Echocardiography is routinely used for screening of morphological malformations, but functional measurements of blood flow are scarcely used in fetal echocardiography due to technical assumptions and issues of reliability. Magnetic resonance imaging (MRI) is readily used for quantification of abnormal blood flow in adult hearts, however, existing in utero approaches are compromised by spontaneous fetal motion. Here, we present and validate a novel method of MRI velocity-encoding combined with a motion-robust reconstruction framework for four-dimensional visualization and quantification of blood flow in the human fetal heart and major vessels. We demonstrate simultaneous 4D visualization of the anatomy and circulation, which we use to quantify flow rates through various major vessels. The framework introduced here could enable new clinical opportunities for assessment of the fetal cardiovascular system in both health and disease., Three-dimensional imaging of the fetal heart and quantification of blood flow in the surrounding vessels is very challenging because the heart is small and the fetus is free to move in the womb. Here, the authors demonstrate motion-corrected 4D flow MRI of the whole fetal heart and major vessels.

In this study we combined ultra-high field diffusion MRI fiber tracking and super-resolution track density imaging (TDI) to map the relay locations and connectivity of the somatosensory pathway in paraformaldehyde fixed, C57Bl/6J mouse brains. Super-resolution TDI was used to achieve 20 μm isotropic resolution to inform the 3D topography of the relay locations including thalamic barreloids and brainstem barrelettes, not described previously using MRI methodology. TDI-guided mapping results for thalamo-cortical connectivity were consistent with thalamo-cortical projections labeled using virus mediated fluorescent protein expression. Trigemino-thalamic TDI connectivity maps were concordant with results obtained using anterograde dye tracing from brainstem to thalamus. Importantly, TDI mapping overcame the constraint of tissue distortion observed in mechanically sectioned tissue, enabling 3D reconstruction and long-range connectivity data. In conclusion, our results showed that diffusion micro-imaging at ultra-high field MRI revealed the stereotypical pattern of somatosensory connectivity and is a valuable tool to complement histologic methods, achieving 3D spatial preservation of whole brain networks for characterization in mouse models of human disease.

Recent developments in semi-global tractogram optimisation algorithms have opened the field of diffusion MRI to the possibility of performing quantitative assessment of structural fibre connectivity. The proper application of these methods in neuroscience research has however been limited by a lack of awareness, understanding, or appreciation for the consequences of these methods; furthermore, particular steps necessary to use these tools in an appropriate manner to fully exploit their quantitative properties have not yet been described. This article therefore serves three purposes: to increase awareness of the fact that there are existing tools that attempt to address the well-known non-quantitative nature of streamlines counts; to illustrate why these algorithms work the way they do to give quantitative results; and to explain how to properly utilise these results for quantitative tractography analysis across subjects.

Probing microstructure with diffusion magnetic resonance imaging (dMRI) on a scale orders of magnitude below the imaging resolution relies on biophysical modelling of the signal response in the tissue. The vast majority of these biophysical models of diffusion in white matter assume that the measured dMRI signal is the sum of the signals emanating from each of the constituent compartments, each of which exhibits a distinct behaviour in the b-value and/or orientation domain. Many of these models further assume that the dMRI behaviour of the oriented compartments (e.g. the intra-axonal space) is identical between distinct fibre populations, at least at the level of a single voxel. This implicitly assumes that any potential biological differences between fibre populations are negligible, at least as far as is measurable using dMRI. Here, we validate this assumption by means of a voxel-wise, model-free signal decomposition that, under the assumption above and in the absence of noise, is shown to be rank-1. We evaluate the effect size of signal components beyond this rank-1 representation and use permutation testing to assess their significance. We conclude that in the healthy adult brain, the dMRI signal is adequately represented by a rank-1 model, implying that biologically more realistic, but mathematically more complex fascicle-specific microstructure models do not capture statistically significant or anatomically meaningful structure, even in extended high-b diffusion MRI scans. ispartof: Neuroimage vol:208 ispartof: location:United States status: published

MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualisation, with a particular emphasis on the investigation of the brain using diffusion MRI. It is implemented using a fast, modular and flexible general-purpose code framework for image data access and manipulation, enabling efficient development of new applications, whilst retaining high computational performance and a consistent command-line interface between applications. In this article, we provide a high-level overview of the features of the MRtrix3 framework and general-purpose image processing applications provided with the software. ispartof: NEUROIMAGE vol:202 ispartof: location:United States status: published

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation.

INTRODUCTION: The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors. METHODS: We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months. RESULTS: In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months. CONCLUSION: We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants. ispartof: NEUROIMAGE vol:243 ispartof: location:United States status: published

Objective To investigate whether genetics, underlying pathology, or repeated seizures contribute to atrophy in specific white matter tracts. Methods Medically refractory unilateral temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS-TLE, n = 26) was studied as an archetype of focal epilepsy, using fixel-based analysis of diffusion-weighted imaging. A genetic effect was assessed in first-degree relatives of HS-TLE subjects who did not have epilepsy themselves (HS-1°Rel; n = 26). The role of disease process was uncovered by comparing HS-TLE to unilateral TLE with normal clinical magnetic resonance imaging (MRI-neg TLE; n = 26, matched for seizure severity). The effect of focal seizures was inferred from lateralized atrophy common to both HS-TLE and MRI-neg TLE, in comparison to healthy controls (n = 76). Results HS-1 °Rel had bilaterally small hippocampi, but no focal white matter atrophy was detected, indicating a limited effect of genetics. HS-TLE subjects had lateralized atrophy of most temporal lobe tracts, and hippocampal volumes in HS-TLE correlated with parahippocampal cingulum and anterior commissure atrophy, indicating an effect of the underlying pathology. Ipsilateral atrophy of the tapetum, uncinate, and inferior fronto-occipital fasciculus was found in both HS-TLE and MRI-neg TLE, suggesting a common lateralized effect of focal seizures. Both epilepsy groups had bilateral atrophy of the dorsal cingulum and corpus callosum fibers, which we interpret as a consequence of bilateral insults (potentially generalized seizures and/or medications). Interpretation Underlying pathology, repeated focal seizures, and global insults each contribute to atrophy in specific tracts. Genetic factors make less of a contribution in this cohort. A multifactorial model of white matter atrophy in focal epilepsy is proposed. Ann Neurol 2017;81:240–250

Purpose To investigate whether it is possible in patients with periventricular nodular heterotopia (PVNH) to detect abnormal fiber projections that have only previously been reported in the histopathology literature. Materials and Methods Whole-brain diffusion-weighted (DW) imaging data from 14 patients with bilateral PVNH and 14 age- and sex-matched healthy control subjects were prospectively acquired by using 3.0-T magnetic resonance (MR) imaging between August 1, 2008, and December 5, 2012. All participants provided written informed consent. The DW imaging data were processed to generate whole-brain constrained spherical deconvolution (CSD)-based tractography data and super-resolution track-density imaging (TDI) maps. The tractography data were overlaid on coregistered three-dimensional T1-weighted images to visually assess regions of heterotopia. A panel of MR imaging researchers independently assessed each case and indicated numerically (no = 1, yes = 2) as to the presence of abnormal fiber tracks in nodular tissue. The Fleiss κ statistical measure was applied to assess the reader agreement. Results Abnormal fiber tracks emanating from one or more regions of heterotopia were reported by all four readers in all 14 patients with PVNH (Fleiss κ = 1). These abnormal structures were not visible on the tractography data from any of the control subjects and were not discernable on the conventional T1-weighted images of the patients with PVNH. Conclusion Whole-brain CSD-based fiber tractography and super-resolution TDI mapping reveals abnormal fiber projections in nodular tissue suggestive of abnormal organization of white matter (with abnormal fibers both within nodules and projecting to the surrounding white matter) in patients with bilateral PVNH. (©) RSNA, 2016.

PurposeTo develop an MRI framework for reconstruction of 4D velocity vector blood flow volumes for visualisation and quantification of circulation in the fetal heart and major vessels.MethodsA novel method of velocity-encoding using multiple non-coplanar stacks of bSSFP phase images was combined with a previous framework for reconstruction of motion-corrected 4D magnitude cine volumes to generate spatiotemporally-paired 4D flow cine volumes of the fetal circulatory system. The multiple stack velocity-encoding scheme was validated in a simulated flow phantom and compared with a gold-standard method for velocity-encoding in a physical flow phantom. The 4D flow cine framework was evaluated in seven fetal subjects. Reconstructed 4D flow volumes were evaluated by an expert fetal cardiologist and preliminary flow measurements were taken in various major vessels of the heart.ResultsPhantom experiments showed that the multiple non-coplanar stack velocity-encoding scheme was accurate. The 4D flow cine reconstruction framework was robust in fetal subjects and generated multi-dimensional velocity vector maps of blood flow through the cardiac cycle. Directionality of blood flow was consistent with expected fetal circulatory hemodynamics. Relative blood flow rates in the major vessels were in line with previous observations, although absolute values were underestimated by a factor of approximately two due to limitations of spatial and temporal resolution.Conclusion4D flow cine volumes can be reconstructed from multiple non-coplanar stacks of slices. The proposed framework was used to visualise and quantify flow through the whole fetal heart and great vessels, but is applicable to any imaging scenario where motion is a major challenge.

We present a summary of competition results in the multi-shell diffusion MRI harmonisation and enhancement challenge (MUSHAC). MUSHAC is an open competition intended to stimulate the development of computational methods that reduce scanner- and protocol-related variabilities in multi-shell diffusion MRI data across multi-site studies. Twelve different methods from seven research groups have been tested in this challenge. The results show that cross-vendor harmonization and enhancement can be performed by using suitable computational algorithms such as deep convolutional neural networks. Moreover, parametric models for multi-shell diffusion MRI signals also provide reliable performances.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20353-3

Hemidisconnections (i.e. hemispherectomies or hemispherotomies) invariably lead to contralateral hemiparesis. Many patients with a pre-existing hemiparesis, however, experience no deterioration in motor functions, and some can still grasp with their paretic hand after hemidisconnection. The scope of our study was to predict this phenomenon. Hypothesizing that preserved contralateral grasping ability after hemidisconnection can only occur in patients controlling their paretic hands via ipsilateral corticospinal projections already in the preoperative situation, we analysed the asymmetries of the brainstem (by manual magnetic resonance imaging volumetry) and of the structural connectivity of the corticospinal tracts within the brainstem (by magnetic resonance imaging diffusion tractography), assuming that marked hypoplasia or Wallerian degeneration on the lesioned side in patients who can grasp with their paretic hands indicate ipsilateral control. One hundred and two patients who underwent hemidisconnections between 0.8 and 36 years of age were included. Before the operation, contralateral hand function was normal in 3/102 patients, 47/102 patients showed hemiparetic grasping ability and 52/102 patients could not grasp with their paretic hands. After hemidisconnection, 20/102 patients showed a preserved grasping ability, and 5/102 patients began to grasp with their paretic hands only after the operation. All these 25 patients suffered from pre- or perinatal brain lesions. Thirty of 102 patients lost their grasping ability. This group included all seven patients with a post-neonatally acquired or progressive brain lesion who could grasp before the operation, and also all three patients with a preoperatively normal hand function. The remaining 52/102 patients were unable to grasp pre- and postoperatively. On magnetic resonance imaging, the patients with preserved grasping showed significantly more asymmetric brainstem volumes than the patients who lost their grasping ability. Similarly, these patients showed striking asymmetries in the structural connectivity of the corticospinal tracts. In summary, normal preoperative hand function and a post-neonatally acquired or progressive lesion predict a loss of grasping ability after hemidisconnection. A postoperatively preserved grasping ability is possible in hemiparetic patients with pre- or perinatal lesions, and this is highly likely when the brainstem is asymmetric and especially when the structural connectivity of the corticospinal tracts within the brainstem is asymmetric.

Diffusion MRI streamlines tractography allows for the investigation of the brain white matter pathways non-invasively. However a fundamental limitation of this technology is its non-quantitative nature, i.e. the density of reconstructed connections is not reflective of the density of underlying white matter fibres. As a solution to this problem, we have previously published the "spherical-deconvolution informed filtering of tractograms (SIFT)" method, which determines a subset of the streamlines reconstruction such that the streamlines densities throughout the white matter are as close as possible to fibre densities estimated using the spherical deconvolution diffusion model; this permits the use of streamline count as a valid biological marker of connection density. Particular aspects of its performance may have however limited its uptake in the diffusion MRI research community. Here we present an alternative to this method, entitled SIFT2, which provides a more logically direct and computationally efficient solution to the streamlines connectivity quantification problem: by determining an appropriate cross-sectional area multiplier for each streamline rather than removing streamlines altogether, biologically accurate measures of fibre connectivity are obtained whilst making use of the complete streamlines reconstruction.

PurposeTo investigate whether diffusion MRI can be used to study cortical segregation based on a contrast related to neurite density, thus providing a complementary tool to myelin-based MRI techniques used for myeloarchitecture. MethodsSeveral myelin-sensitive MRI methods (e.g., based on T-1, T-2, and T2*) have been proposed to parcellate cortical areas based on their myeloarchitecture. Recent improvements in hardware, acquisition, and analysis methods have opened the possibility of achieving a more robust characterization of cortical microstructure using diffusion MRI. High-quality diffusion MRI data from the Human Connectome Project was combined with recent advances in fiber orientation modeling. The orientational average of the fiber orientation distribution was used as a summary parameter, which was displayed as inflated brain surface views. ResultsDiffusion MRI identifies cortical patterns consistent with those previously seen by MRI methods used for studying myeloarchitecture, which have shown patterns of high myelination in the sensorimotor strip, visual cortex, and auditory areas and low myelination in frontal and anterior temporal areas. ConclusionIn vivo human diffusion MRI provides a useful complementary noninvasive approach to myelin-based methods used to study whole-brain cortical parcellation, by exploiting a contrast based on tissue microstructure related to neurite density, rather than myelin itself. Magn Reson Med 79:2738-2744, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.

Newborns with hypoxic-ischemic encephalopathy (HIE) are at high risk of brain injury, with subsequent developmental problems including severe neuromotor, cognitive and behavioral impairment. Neural correlates of cognitive and behavioral impairment in neonatal HIE, in particular in infants who survive without severe neuromotor impairment, are poorly understood. It is reasonable to hypothesize that in HIE both structural and functional brain networks are altered, and that this might be the neural correlate of impaired cognitive and/or behavioral impairment in HIE. Here, an analysis pipeline to study the structural and functional brain networks from neonatal MRI in newborns with HIE is presented. The structural connectivity is generated from dense whole-brain tractograms derived from diffusion-weighted MR fibre tractography. This investigation of functional connectivity focuses on the emerging resting state networks (RSNs), which are sensitive to injuries from hypoxic-ischemic insults to the newborn brain. In conjunction with the structural connectivity, alterations to the structuro-functional connectivity of the RSNs can be studied. Preliminary results from a proof-of-concept study in a small cohort of newborns with HIE are promising. The obstacles encountered and improvements to the pipeline are discussed. The framework can be further extended for joint analysis with EEG functional-connectivity.

BACKGROUND AND PURPOSE: Diffusion-weighted MR imaging and fiber tractography can be used to investigate alterations in white matter tracts in patients with early acquired brain lesions and cerebral palsy. Most existing studies have used diffusion tensor tractography, which is limited in areas of complex fiber structures or pathologic processes. We explored a combined normalization and probabilistic fiber-tracking method for more realistic fiber tractography in this patient group. MATERIALS AND METHODS: This cross-sectional study included 17 children with unilateral cerebral palsy and 24 typically developing controls. DWI data were collected at 1.5T (45 directions, b=1000 s/mm2). Regions of interest were defined on a study-specific fractional anisotropy template and mapped onto subjects for fiber tracking. Probabilistic fiber tracking of the corticospinal tract and thalamic projections to the somatosensory cortex was performed by using constrained spherical deconvolution. Tracts were qualitatively assessed, and DTI parameters were extracted close to and distant from lesions and compared between groups. RESULTS: The corticospinal tract and thalamic projections to the somatosensory cortex were realistically reconstructed in both groups. Structural changes to tracts were seen in the cerebral palsy group and included splits, dislocations, compaction of the tracts, or failure to delineate the tract and were associated with underlying pathology seen on conventional MR imaging. Comparisons of DTI parameters indicated primary and secondary neurodegeneration along the corticospinal tract. Corticospinal tract and thalamic projections to the somatosensory cortex showed dissimilarities in both structural changes and DTI parameters. CONCLUSIONS: Our proposed method offers a sensitive means to explore alterations in WM tracts to further understand pathophysiologic changes following early acquired brain injury.

Highlights • Diffusion weighted MRI can assist in the prognosis of neuropsychological deficits. • We explored white matter changes and language outcome in people with brain injury. • Sentence generation impairments were found in dysarthric participants. • Impairments were linked to reduced corpus callosum and left arcuate fasciculus size. • This dual blow seriously reduces the potential for language reorganisation., Pediatric traumatic brain injury (TBI) may result in long-lasting language impairments alongside dysarthria, a motor-speech disorder. Whether this co-morbidity is due to the functional links between speech and language networks, or to widespread damage affecting both motor and language tracts, remains unknown. Here we investigated language function and diffusion metrics (using diffusion-weighted tractography) within the arcuate fasciculus, the uncinate fasciculus, and the corpus callosum in 32 young people after TBI (approximately half with dysarthria) and age-matched healthy controls (n = 17). Only participants with dysarthria showed impairments in language, affecting sentence formulation and semantic association. In the whole TBI group, sentence formulation was best predicted by combined corpus callosum and left arcuate volumes, suggesting this “dual blow” seriously reduces the potential for functional reorganisation. Word comprehension was predicted by fractional anisotropy in the right arcuate. The co-morbidity between dysarthria and language deficits therefore seems to be the consequence of multiple tract damage.

Children born very preterm (VPT) are at risk for visual impairments, the main risk factors being retinopathy of prematurity and cerebral white matter injury, however these only partially account for visual impairments in VPT children. This study aimed to compare optic radiation microstructure and volume between VPT and term-born children, and to investigate associations between 1) perinatal variables and optic radiations; 2) optic radiations and visual function in VPT children. We hypothesized that optic radiation microstructure would be altered in VPT children, predicted by neonatal cerebral white matter abnormality and retinopathy of prematurity, and associated with visual impairments. 142 VPT children and 32 controls underwent diffusion-weighted magnetic resonance imaging at 7 years of age. Optic radiations were delineated using constrained spherical deconvolution tractography. Tract volume and average diffusion tensor values for the whole optic radiations and three sub-regions were compared between the VPT and control groups, and correlated with perinatal variables and 7-year visual outcome data. Total tract volumes and average diffusion values were similar between VPT and control groups. On regional analysis of the optic radiation, mean and radial diffusivity were higher within the middle sub-regions in VPT compared with control children. Neonatal white matter abnormalities and retinopathy of prematurity were associated with optic radiation diffusion values. Lower fractional anisotropy in the anterior sub-regions was associated with poor visual acuity and increased likelihood of other visual defects. This study presents evidence for microstructural alterations in the optic radiations of VPT children, which are largely predicted by white matter abnormality or severe retinopathy of prematurity, and may partially explain the higher rate of visual impairments in VPT children., Highlights • This study compares optic radiations between very preterm and control 7-year-olds. • There are microstructural alterations in the optic radiations of VPT children. • The main risk factors are retinopathy of prematurity and white matter injury. • Microstructural alterations associate with poor visual acuity and visual defects. • This study elucidates neuroanatomical correlates of visual impairment in prematurity.

A shift is emerging in the way in which we view post-stroke recovery. This shift, supported by evidence from neuroimaging studies, encourages us to look beyond the lesion and to identify viable brain networks with capacity for plasticity. In this article, the authors review current advances in neuroimaging techniques and the new insights that they have contributed. The ability to quantify salvageable tissue, evidence of changes in remote networks, changes of functional and structural connectivity, and alterations in cortical thickness are reviewed in the context of their impact on post-stroke recovery. The value of monitoring spared structural connections and functional connectivity of brain networks within and across hemispheres is highlighted.

High-angular-resolution diffusion-weighted imaging (HARDI) is one of the most common MRI acquisition schemes for use with higher order models of diffusion. However, the optimal b value and number of diffusion-weighted (DW) directions for HARDI are still undetermined, primarily as a result of the large number of available reconstruction methods and corresponding parameters, making it impossible to identify a single criterion by which to assess performance. In this study, we estimate the minimum number of DW directions and optimal b values required for HARDI by focusing on the angular frequency content of the DW signal itself. The spherical harmonic (SH) series provides the spherical analogue of the Fourier series, and can hence be used to examine the angular frequency content of the DW signal. Using high-quality data acquired along 500 directions over a range of b values, we estimate that SH terms above l = 8 are negligible in practice for b values up to 5000 s/mm(2), implying that a minimum of 45 DW directions is sufficient to fully characterise the DW signal. l > 0 SH terms were found to increase as a function of b value, levelling off at b = 3000 s/mm(2), suggesting that this value already provides the highest achievable angular resolution. In practice, it is recommended to acquire more than the minimum of 45 DW directions to avoid issues with imperfections in the uniformity of the DW gradient directions and to meet signal-to-noise requirements of the intended reconstruction method.

Object Diffusion-based MRI tractography is an imaging tool increasingly used in neurosurgical procedures to generate 3D maps of white matter pathways as an aid to identifying safe margins of resection. The majority of white matter fiber tractography software packages currently available to clinicians rely on a fundamentally flawed framework to generate fiber orientations from diffusion-weighted data, namely diffusion tensor imaging (DTI). This work provides the first extensive and systematic exploration of the practical limitations of DTI-based tractography and investigates whether the higher-order tractography model constrained spherical deconvolution provides a reasonable solution to these problems within a clinically feasible timeframe. Methods Comparison of tractography methodologies in visualizing the corticospinal tracts was made using the diffusion-weighted data sets from 45 healthy controls and 10 patients undergoing presurgical imaging assessment. Tensor-based and constrained spherical deconvolution–based tractography methodologies were applied to both patients and controls. Results Diffusion tensor imaging–based tractography methods (using both deterministic and probabilistic tractography algorithms) substantially underestimated the extent of tracks connecting to the sensorimotor cortex in all participants in the control group. In contrast, the constrained spherical deconvolution tractography method consistently produced the biologically expected fan-shaped configuration of tracks. In the clinical cases, in which tractography was performed to visualize the corticospinal pathways in patients with concomitant risk of neurological deficit following neurosurgical resection, the constrained spherical deconvolution–based and tensor-based tractography methodologies indicated very different apparent safe margins of resection; the constrained spherical deconvolution–based method identified corticospinal tracts extending to the entire sensorimotor cortex, while the tensor-based method only identified a narrow subset of tracts extending medially to the vertex. Conclusions This comprehensive study shows that the most widely used clinical tractography method (diffusion tensor imaging–based tractography) results in systematically unreliable and clinically misleading information. The higher-order tractography model, using the same diffusion-weighted data, clearly demonstrates fiber tracts more accurately, providing improved estimates of safety margins that may be useful in neurosurgical procedures. We therefore need to move beyond the diffusion tensor framework if we are to begin to provide neurosurgeons with biologically reliable tractography information.

The thalamus is one of the most important brain structures, with strong connections between subcortical and cortical areas of the brain. Most of the incoming information to the cortex passes through the thalamus. Accurate identification of substructures of the thalamus is therefore of great im- portance for the understanding of human brain connectivity. Direct visualization of thalamic substruc- tures, however, is not easily achieved with currently available magnetic resonance imaging (MRI), including ultra-high field MRI such as 7.0T, mainly due to the limited contrast between the relevant structures. Recently, improvements in ultra-high field 7.0T MRI have opened the possibility of observ- ing thalamic substructures by well-adjusted high-resolution T1-weighted imaging. Moreover, the recently developed super-resolution track-density imaging (TDI) technique, based on results from whole-brain fiber-tracking, produces images with sub-millimeter resolution. These two methods enable us to show markedly improved anatomical detail of the substructures of the thalamus, including their detailed locations and directionality. In this study, we demonstrate the role of TDI for the visualization of the substructures of the thalamic nuclei, and relate these images to T1-weighted imaging at 7.0T MRI. Hum Brain Mapp 34:2538-2548, 2013. V C 2012 Wiley Periodicals, Inc.

To investigate whether genetics, underlying pathology, or repeated seizures contribute to atrophy in specific white matter tracts.Medically refractory unilateral temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS-TLE, n = 26) was studied as an archetype of focal epilepsy, using fixel-based analysis of diffusion-weighted imaging. A genetic effect was assessed in first-degree relatives of HS-TLE subjects who did not have epilepsy themselves (HS-1°Rel; n = 26). The role of disease process was uncovered by comparing HS-TLE to unilateral TLE with normal clinical magnetic resonance imaging (MRI-neg TLE; n = 26, matched for seizure severity). The effect of focal seizures was inferred from lateralized atrophy common to both HS-TLE and MRI-neg TLE, in comparison to healthy controls (n = 76).HS-1 °Rel had bilaterally small hippocampi, but no focal white matter atrophy was detected, indicating a limited effect of genetics. HS-TLE subjects had lateralized atrophy of most temporal lobe tracts, and hippocampal volumes in HS-TLE correlated with parahippocampal cingulum and anterior commissure atrophy, indicating an effect of the underlying pathology. Ipsilateral atrophy of the tapetum, uncinate, and inferior fronto-occipital fasciculus was found in both HS-TLE and MRI-neg TLE, suggesting a common lateralized effect of focal seizures. Both epilepsy groups had bilateral atrophy of the dorsal cingulum and corpus callosum fibers, which we interpret as a consequence of bilateral insults (potentially generalized seizures and/or medications).Underlying pathology, repeated focal seizures, and global insults each contribute to atrophy in specific tracts. Genetic factors make less of a contribution in this cohort. A multifactorial model of white matter atrophy in focal epilepsy is proposed. Ann Neurol 2017;81:240-250.

Diffusion tensor imaging (DTI) is presently one of the most popular diffusion magnetic resonance imaging techniques available. Its ability to characterize the dispersion pattern of water molecules in tissue has made it the method of choice for investigating brain microstructure and connectivity in clinical populations. However, its optimal implementation is confounded by both theoretical and practical challenges associated with data acquisition and analysis.

It has long been recognized that the diffusion tensor model is inappropriate to characterize complex fiber architecture, causing tensor-derived measures such as the primary eigenvector and fractional anisotropy to be unreliable or misleading in these regions. There is however still debate about the impact of this problem in practice. A recent study using a Bayesian automatic relevance detection (ARD) multicompartment model suggested that a third of white matter (WM) voxels contain crossing fibers, a value that, whilst already significant, is likely to be an underestimate. The aim of this study is to provide more robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor-derived analyses, using large, high-quality diffusion-weighted data sets, with reconstruction parameters optimized specifically for this task. Two reconstruction algorithms were used: constrained spherical deconvolution (CSD), and the ARD method used in the previous study. We estimate the proportion of WM voxels containing crossing fibers to be ∼90% (using CSD) and 63% (using ARD). Both these values are much higher than previously reported, strongly suggesting that the diffusion tensor model is inadequate in the vast majority of WM regions. This has serious implications for downstream processing applications that depend on this model, particularly tractography, and the interpretation of anisotropy and radial/axial diffusivity measures.

The diffusion of water molecules inside organic tissues is often anisotropic (1). Namely, if there are aligned structures in the tissue, the apparent diffusion coefficient (ADC) of water may vary depending on the orientation along which the diffusion-weighted (DW) measurements are taken. In the late 1980s, diffusion-weighted imaging (DWI) became possible by combining MR diffusion measurements with imaging, enabling the mapping of both diffusion constants and diffusion anisotropy inside the brain and revealing valuable information about axonal architectures (2-14). In the beginning of the 1990s, the diffusion tensor model was introduced to describe the degree of anisotropy and the structural orientation information quantitatively (15,16). This diffusion tensor imaging (DTI) approach provided a simple and elegant way to model this complex neuroanatomical information using only six parameters. Since then, we have witnessed a tremendous amount of growth in this research field, including more sophisticated nontensor models to describe diffusion properties and to extract finer anatomical information from each voxel. Three-dimensional (3D) reconstruction technologies for white matter tracts are also developing beyond the initial deterministic line-propagation models (17-20). As these new reconstruction methods are an area of very active research, it is important to remember that the theory cannot be dissociated from practical aspects of the technology. Importantly, DWI is inherently a noise-sensitive and artifact-prone technique (Fig. 1). Thus, we cannot overemphasize the importance of image quality assurance and robust image analysis techniques. Last but not least, data acquisition technologies have also been steadfastly evolving. In this article, we review the recent advances in these areas since 2000. FIG. 1 Examples of typical artifacts: (i) signal/slice dropouts, (ii) eddy-current induced geometric distortions, (iii) systematic vibration artifacts, and (iv) ghosting (insufficient/incorrect fat-suppression).

Neuroimaging advances have given rise to major progress in neurosciences and neurology, as ever more subtle and specific imaging methods reveal new aspects of the brain. One major limitation of current methods is the spatial scale of the information available. We present an approach to gain spatial resolution using post-processing methods based on diffusion MRI fiber-tracking, to reveal structures beyond the resolution of the acquired imaging voxel; we term such a method as super-resolution track-density imaging (TDI). A major unmet challenge in imaging is the identification of abnormalities in white matter as a cause of illness; super-resolution TDI is shown to produce high-quality white matter images, with high spatial resolution and outstanding anatomical contrast. A unique property of these maps is demonstrated: their spatial resolution and signal-to-noise ratio can be tailored depending on the chosen image resolution and total number of fiber-tracks generated. Super-resolution TDI should greatly enhance the study of white matter in disorders of the brain and mind.

Diffusion-weighted imaging can potentially be used to infer the connectivity of the human brain in vivo using fibre-tracking techniques, and is therefore of great interest to neuroscientists and clinicians. A key requirement for fibre tracking is the accurate estimation of white matter fibre orientations within each imaging voxel. The diffusion tensor model, which is widely used for this purpose, has been shown to be inadequate in crossing fibre regions. A number of approaches have recently been proposed to address this issue, based on high angular resolution diffusion-weighted imaging (HARDI) data. In this study, an experimental model of crossing fibres, consisting of water-filled plastic capillaries, is used to thoroughly assess three such techniques: constrained spherical deconvolution (CSD), super-resolved CSD (super-CSD) and Q-ball imaging (QBI). HARDI data were acquired over a range of crossing angles and b-values, from which fibre orientations were computed using each technique. All techniques were capable of resolving the two fibre populations down to a crossing angle of 45 degrees , and down to 30 degrees for super-CSD. A bias was observed in the fibre orientations estimated by QBI for crossing angles other than 90 degrees, consistent with previous simulation results. Finally, for a 45 degrees crossing, the minimum b-value required to resolve the fibre orientations was 4000 s/mm(2) for QBI, 2000 s/mm(2) for CSD, and 1000 s/mm(2) for super-CSD. The quality of estimation of fibre orientations may profoundly affect fibre tracking attempts, and the results presented provide important additional information regarding performance characteristics of well-known methods.

Diffusion MRI tractography algorithm development is increasingly moving towards global techniques to incorporate "downstream" information and conditional probabilities between neighbouring tracts. Such approaches also enable white matter to be represented more tangibly than the abstract lines generated by the most common approaches to fibre tracking. However, previously proposed algorithms still use fibre-like models of white matter corresponding to thin strands of white matter tracts rather than the tracts themselves, and therefore require many components for accurate representations, which leads to poorly constrained inverse problems. We propose a novel tract-based model of white matter, the 'Fourier tract', which is able to represent rich tract shapes with a relatively low number of parameters, and explicitly decouples the spatial extent of the modelled tract from its 'Apparent Connection Strength (ACS)'. The Fourier tract model is placed within a novel Bayesian framework, which relates the tract parameters directly to the observed signal, enabling a wide range of acquisition schemes to be used. The posterior distribution of the Bayesian framework is characterised via Markov-chain Monte-Carlo sampling to infer probable values of the ACS and spatial extent of the imaged white matter tracts, providing measures that can be directly applied to many research and clinical studies. The robustness of the proposed tractography algorithm is demonstrated on simulated basic tract configurations, such as curving, twisting, crossing and kissing tracts, and sections of more complex numerical phantoms. As an illustration of the approach in vivo, fibre tracking is performed on a central section of the brain in three subjects from 60 direction HARDI datasets.

Diffusion MRI streamlines tractography is increasingly being used to characterise and assess the structural connectome of the human brain. However, issues pertaining to quantification of structural connectivity using streamlines reconstructions are well-established in the field, and therefore the validity of any conclusions that may be drawn from these analyses remains ambiguous. We recently proposed a post-processing method entitled “SIFT: Spherical-deconvolution Informed Filtering of Tractograms” as a mechanism for reducing the biases in quantitative measures of connectivity introduced by the streamlines reconstruction method. Here, we demonstrate the advantage of this approach in the context of connectomics in three steps. Firstly, we carefully consider the model imposed by the SIFT method, and the implications this has for connectivity quantification. Secondly, we investigate the effects of SIFT on the reproducibility of structural connectome construction. Thirdly, we compare quantitative measures extracted from structural connectomes derived from streamlines tractography, with and without the application of SIFT, to published estimates drawn from post-mortem brain dissection. The combination of these sources of evidence demonstrates the important role the SIFT methodology has for the robust quantification of structural connectivity of the brain using diffusion MRI.