REKINDLE: Robust extraction of kurtosis INDices with linear estimation

White matter characteristics of motor, sensory and interhemispheric tracts underlying impaired upper limb function in children with unilateral cerebral palsy

This study explored the role of lesion timing (periventricular white matter versus cortical and deep grey matter lesions) and type of corticospinal tract (CST) wiring pattern (contralateral, bilateral, ipsilateral) on white matter characteristics of the CST, medial lemniscus, superior thalamic radiations and sensorimotor transcallosal fibers in children with unilateral cerebral palsy (CP), and examined the association with upper limb function. Thirty-four children (mean age 10 years 7 months ± 2 years 3 months) with unilateral CP underwent a comprehensive upper limb evaluation and diffusion weighted imaging (75 directions, b value 2800). Streamline count, fractional anisotropy and mean diffusivity were extracted from the targeted tracts and asymmetry indices were additionally calculated. Transcranial magnetic stimulation was applied to assess the CST wiring pattern. Results showed a more damaged CST in children with cortical and deep grey matter lesions (N = 10) and ipsilateral CST projections (N = 11) compared to children with periventricular white matter lesions (N = 24; p < 0.02) and contralateral CST projections (N = 9; p < 0.025), respectively. Moderate to high correlations were found between diffusion metrics of the targeted tracts and upper limb function (r = 0.45-0.72; p < 0.01). Asymmetry indices of the CST and sensory tracts could best explain bimanual performance (74%, p < 0.0001) and unimanual capacity (50%, p = 0.004). Adding lesion timing and CST wiring pattern did not further improve the model of bimanual performance, while for unimanual capacity lesion timing was additionally retained (58%, p = 0.0002). These results contribute to a better understanding of the underlying neuropathology of upper limb function in children with unilateral CP and point towards a clinical potential of tractography.

Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease

A popular solution to control for edge density variability in structural brain network analysis is to threshold the networks to a fixed density across all subjects. However, it remains unclear how this type of thresholding affects the basic network architecture in terms of edge weights, hub location, and hub connectivity and, especially, how it affects the sensitivity to detect disease-related abnormalities. We investigated these two questions in a cohort of patients with cerebral small vessel disease and age-matched controls. Brain networks were reconstructed from diffusion magnetic resonance imaging data using deterministic fiber tractography. Networks were thresholded to a fixed density by removing edges with the lowest number of streamlines. We compared edge length (mm), fractional anisotropy (FA), proportion of hub connections, and hub location between the unthresholded and the thresholded networks of each subject. Moreover, we compared weighted graph measures of global and local connectivity obtained from the (un)thresholded networks between patients and controls. We performed these analyses over a range of densities (2-20%). Results indicate that fixed-density thresholding disproportionally removes edges composed of long streamlines, but is independent of FA. The edges removed were not preferentially connected to hub or nonhub nodes. Over half of the original hubs were reproducible when networks were thresholded to a density ≥10%. Furthermore, the between-group differences in graph measures observed in the unthresholded network remained present after thresholding, irrespective of the chosen density. We therefore conclude that moderate fixed-density thresholds can successfully be applied to control for the effects of density in structural brain network analysis.

Word learning reveals white matter plasticity in preschool children

Word learning plays a central role in language development and is a key predictor for later academic success. The underlying neural basis of successful word learning in children is still unknown. Here, we took advantage of the opportunity afforded by diffusion-weighted magnetic resonance imaging to investigate neural plasticity in the white matter of typically developing preschool children as they learn words. We demonstrate that after 3 weeks of word learning, children showed significantly larger increases of fractional anisotropy (FA) in the left precentral white matter compared to two control groups. Average training accuracy was correlated with FA change in the white matter underlying the left dorsal postcentral gyrus, with children who learned more slowly showing larger FA increases in this region. Moreover, we found that the status of white matter in the left middle temporal gyrus, assumed to support semantic processes, is predictive for early stages of word learning. Our findings provide the first evidence for white matter plasticity following word learning in preschool children. The present results on learning novel words in children point to a key involvement of the left fronto-parietal fiber connection, known to be implicated in top-down attention as well as working memory. While working memory and attention have been discussed to participate in word learning in children, our training study provides evidence that the neural structure supporting these cognitive processes plays a direct role in word learning.

Microstructural imaging in temporal lobe epilepsy: Diffusion imaging changes relate to reduced neurite density

PURPOSE

Previous imaging studies in patients with refractory temporal lobe epilepsy (TLE) have examined the spatial distribution of changes in imaging parameters such as diffusion tensor imaging (DTI) metrics and cortical thickness. Multi-compartment models offer greater specificity with parameters more directly related to known changes in TLE such as altered neuronal density and myelination. We studied the spatial distribution of conventional and novel metrics including neurite density derived from NODDI (Neurite Orientation Dispersion and Density Imaging) and myelin water fraction (MWF) derived from mcDESPOT (Multi-Compartment Driven Equilibrium Single Pulse Observation of T1/T2)] to infer the underlying neurobiology of changes in conventional metrics.

METHODS

20 patients with TLE and 20 matched controls underwent magnetic resonance imaging including a volumetric T1-weighted sequence, multi-shell diffusion from which DTI and NODDI metrics were derived and a protocol suitable for mcDESPOT fitting. Models of the grey matter-white matter and grey matter-CSF surfaces were automatically generated from the T1-weighted MRI. Conventional diffusion and novel metrics of neurite density and MWF were sampled from intracortical grey matter and subcortical white matter surfaces and cortical thickness was measured.

RESULTS

In intracortical grey matter, diffusivity was increased in the ipsilateral temporal and frontopolar cortices with more restricted areas of reduced neurite density. Diffusivity increases were largely related to reductions in neurite density, and to a lesser extent CSF partial volume effects, but not MWF. In subcortical white matter, widespread bilateral reductions in fractional anisotropy and increases in radial diffusivity were seen. These were primarily related to reduced neurite density, with an additional relationship to reduced MWF in the temporal pole and anterolateral temporal neocortex. Changes were greater with increasing epilepsy duration. Bilaterally reduced cortical thickness in the mesial temporal lobe and centroparietal cortices was unrelated to neurite density and MWF.

CONCLUSIONS

Diffusivity changes in grey and white matter are primarily related to reduced neurite density with an additional relationship to reduced MWF in the temporal pole. Neurite density may represent a more sensitive and specific biomarker of progressive neuronal damage in refractory TLE that deserves further study.

Boom Chack Boom-A multimethod investigation of motor inhibition in professional drummers

INTRODUCTION

Our hands are the primary means for motor interaction with the environment, and their neural organization is fundamentally asymmetric: While most individuals can perform easy motor tasks with two hands equally well, only very few individuals can perform complex fine motor tasks with both hands at a similar level of performance. The reason why this phenomenon is so rare is not well understood. Professional drummers represent a unique population to study it, as they have remarkable abilities to perform complex motor tasks with their two limbs independently.

METHODS

Here, we used a multimethod neuroimaging approach to investigate the structural, functional, and biochemical correlates of fine motor behavior in professional drummers (n = 20) and nonmusical controls (n = 24).

RESULTS

Our results show that drummers have higher microstructural diffusion properties in the corpus callosum than controls. This parameter also predicts drumming performance and GABA levels in the motor cortex. Moreover, drummers show less activation in the motor cortex when performing a finger-tapping task than controls.

CONCLUSION

In conclusion, professional drumming is associated with a more efficient neuronal design of cortical motor areas as well as a stronger link between commissural structure and biochemical parameters associated with motor inhibition.

Regions of white matter abnormalities in the arcuate fasciculus in veterans with anger and aggression problems

Aggression after military deployment is a common occurrence in veterans. Neurobiological research has shown that aggression is associated with a dysfunction in a network connecting brain regions implicated in threat processing and emotion regulation. However, aggression may also be related to deficits in networks underlying communication and social cognition. The uncinate and arcuate fasciculi are integral to these networks, thus studying potential abnormalities in these white matter connections can further our understanding of anger and aggression problems in military veterans. Here, we use diffusion tensor imaging tractography to investigate white matter microstructural properties of the uncinate fasciculus and the arcuate fasciculus in veterans with and without anger and aggression problems. A control tract, the parahippocampal cingulum was also included in the analyses. More specifically, fractional anisotropy (FA) estimates are derived along the trajectory from all fiber pathways and compared between both groups. No between-group FA differences are observed for the uncinate fasciculus and the cingulum, however parts of the arcuate fasciculus show a significantly lower FA in the group of veterans with aggression and anger problems. Our data suggest that abnormalities in arcuate fasciculus white matter connectivity that are related to self-regulation may play an important role in the etiology of anger and aggression in military veterans.

Brain structure and internalizing and externalizing behavior in typically developing children and adolescents

Mental health problems often emerge in adolescence and are associated with reduced gray matter thickness or volume in the prefrontal cortex (PFC) and limbic system and reduced fractional anisotropy (FA) and increased mean diffusivity (MD) of white matter linking these regions. However, few studies have investigated whether internalizing and externalizing behavior are associated with brain structure in children and adolescents without mental health disorders, which is important for understanding the progression of symptoms. 67 T1-weighted and diffusion tensor imaging datasets were obtained from 48 typically developing participants aged 6-16 years (37M/30F; 19 participants had two visits). Volume was calculated in the prefrontal and limbic structures, and diffusion parameters were assessed in limbic white matter. Linear mixed effects models were used to compute associations between brain structure and internalizing and externalizing behavior, assessed using the Behavioral Assessment System for Children (BASC-2) Parent Rating Scale. Internalizing behavior was positively associated with MD of the bilateral cingulum. Gender interactions were found in the cingulum, with stronger positive relationships between MD and internalizing behavior in females. Externalizing behavior was negatively associated with FA of the left cingulum, and the left uncinate fasciculus showed an age-behavior interaction. No relationships between behavior and brain volumes survived multiple comparison correction. These results show altered limbic white matter FA and MD related to sub-clinical internalizing and externalizing behavior and further our understanding of neurological markers that may underlie risk for future mental health disorders.

Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms

Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain 'truly quantitative measures' and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research. Even though careful harmonisation of acquisition parameters can reduce variability, inter-protocol differences become almost inevitable with improvements in hardware and sequence design over time, even within a site. In this work, we present a benchmark diffusion MRI database of the same subjects acquired on three distinct scanners with different maximum gradient strength (40, 80, and 300 mT/m), and with 'standard' and 'state-of-the-art' protocols, where the latter have higher spatial and angular resolution. The dataset serves as a useful testbed for method development in cross-scanner/cross-protocol diffusion MRI harmonisation and quality enhancement. Using the database, we compare the performance of five different methods for estimating mappings between the scanners and protocols. The results show that cross-scanner harmonisation of single-shell diffusion data sets can reduce the variability between scanners, and highlight the promises and shortcomings of today's data harmonisation techniques.

A multiparametric analysis of white matter maturation during late childhood and adolescence

White matter development has been well described using diffusion tensor imaging (DTI), but the microstructural processes driving development remain unclear due to methodological limitations. Here, using neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT), and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT), we describe white matter development at the microstructural level in a longitudinal cohort of healthy 6-15 year olds. We evaluated age and gender-related trends in fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), orientation dispersion index (ODI), quantitative ihMT (qihMT), myelin volume fraction (VF_m ), and g-ratio. We found age-related increases of VF_m in most regions, showing ongoing myelination in vivo during late childhood and adolescence for the first time. No relationship was observed between qihMT and age, suggesting myelin volume increases are driven by increased water content. Age-related increases were observed for NDI, suggesting axonal packing is also occurring during this time. g-ratio decreased with age in the uncinate fasciculus, implying changes in communication efficiency are ongoing in this region. FA increased and MD decreased with age in most regions. Gender effects were present in the left cingulum for FA, and an age-by-gender interaction was found for MD in the left uncinate fasciculus. These findings suggest that FA and MD remain useful markers of gender-related processes, and gender differences are likely driven by factors other than myelin. We conclude that white matter development during late childhood and adolescence is driven by a combination of axonal packing and myelin volume increases.

SHORE-based detection and imputation of dropout in diffusion MRI

PURPOSE

In diffusion MRI, dropout refers to a strong attenuation of the measured signal that is caused by bulk motion during the diffusion encoding. When left uncorrected, dropout will be erroneously interpreted as high diffusivity in the affected direction. We present a method to automatically detect dropout, and to replace the affected measurements with imputed values.

METHODS

Signal dropout is detected by deriving an outlier score from a simple harmonic oscillator-based reconstruction and estimation (SHORE) fit of all measurements. The outlier score is defined to detect measurements that are substantially lower than predicted by SHORE in a relative sense, while being less sensitive to measurement noise in cases of weak baseline signal. A second SHORE fit is based on detected inliers only, and its predictions are used to replace outliers.

RESULTS

Our method is shown to reliably detect and accurately impute dropout in simulated data, and to achieve plausible results in corrupted in vivo dMRI measurements. Computational effort is much lower than with previously proposed alternatives.

CONCLUSIONS

Deriving a suitable outlier score from SHORE results in a fast and accurate method for detection and imputation of dropout in diffusion MRI. It requires measurements with multiple b values (such as multi-shell or DSI), but is independent from the models used for analysis (such as DKI, NODDI, deconvolution, etc.).

Reducing variability in along-tract analysis with diffusion profile realignment

Diffusion weighted magnetic resonance imaging (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than considering a region of interest or tract-averaged measurements. However, performing group analyses with this along-tract strategy requires correspondence between points of tract pathways across subjects. This is usually achieved by creating a new common space where the representative streamlines from every subject are resampled to the same number of points. If the underlying anatomy of some subjects was altered due to, e.g., disease or developmental changes, such information might be lost by resampling to a fixed number of points. In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR). Experiments on synthetic datasets show that DPR reduces the coefficient of variation for the mean diffusivity, fractional anisotropy and apparent fiber density when compared to the unaligned case. Using 100 in vivo datasets from the human connectome project, we simulated changes in mean diffusivity, fractional anisotropy and apparent fiber density. Independent Student's t-tests between these altered subjects and the original subjects indicate that regional changes are identified after realignment with the DPR algorithm, while preserving differences previously detected in the unaligned case. This new correction strategy contributes to revealing effects of interest which might be hidden by misalignment and has the potential to improve the specificity in longitudinal population studies beyond the traditional region of interest based analysis and along-tract analysis workflows.

Cortical Microinfarcts and White Matter Connectivity in Memory Clinic Patients

Background and purpose: Cerebral microinfarcts (CMIs) are associated with cognitive impairment and dementia. CMIs might affect cognitive performance through disruption of cerebral networks. We investigated in memory clinic patients whether cortical CMIs are clustered in specific brain regions and if presence of cortical CMIs is associated with reduced white matter (WM) connectivity in tracts projecting to these regions.

Methods:164 memory clinic patients with vascular brain injury with a mean age of 72 ± 11 years (54% male) were included. All underwent 3 tesla MRI, including a diffusion MRI and cognitive testing. Cortical CMIs were rated according to established criteria and their spatial location was marked. Diffusion imaging-based tractography was used to reconstruct WM connections and voxel based analysis (VBA) to assess integrity of WM directly below the cortex. WM connectivity and integrity were compared between patients with and without cortical CMIs for the whole brain and regions with a high CMI burden.

Results:30 patients (18%) had at least 1 cortical CMI [range 1–46]. More than 70% of the cortical CMIs were located in the superior frontal, middle frontal, and pre- and postcentral brain regions (covering 16% of the cortical surface). In these high CMI burden regions, presence of cortical CMIs was not associated with WM connectivity after correction for conventional neuroimaging markers of vascular injury. WM connectivity in the whole brain and WM voxels directly underneath the cortical surface did not differ between patients with and without cortical CMIs.

Conclusion:Cortical CMIs displayed a strong local clustering in highly interconnected frontal, pre- and postcentral brain regions. Nevertheless, WM connections projecting to these regions were not disproportionally impaired in patients with compared to patients without cortical CMIs. Alternative mechanisms, such as focal disturbances in cortical structure and functioning, may better explain CMI associated cognitive impairment.

Physical Performance in Memory Clinic Patients: The Potential Role of the White Matter Network

BACKGROUND/OBJECTIVES

Memory clinic patients commonly also have declined physical performance. This may be attributable to white matter injury, due to vascular damage or neurodegeneration. Quantifying white matter injury is made possible by new magnetic resonance imaging (MRI) techniques, including diffusion‐weighted imaging (DWI) of network connectivity. We investigated whether physical performance in memory clinic patients is related to white matter network connectivity.

DESIGN

Observational cross‐sectional study.

SETTING

Memory clinic.

PARTICIPANTS

Patients referred to a memory clinic with vascular brain injury on MRI (n = 90; average age = 72 years; 60% male; 34% with diagnosis Alzheimer disease).

MEASUREMENTS

We reconstructed structural brain networks from DWI with fiber tractography and used graph theory to calculate global efficiency, fractional anisotropy (FA), and mean diffusivity (MD) of the white matter, and nodal strength (mean FA or MD of all white matter tracts connected to a node). Assessment of physical performance included gait speed, chair stand time, and Short Physical Performance Battery (SPPB) score.

RESULTS

Lower global efficiency, lower FA, and higher MD correlated with poorer gait speed, SPPB scores, and chair stand times (R range = 0.23‐0.42). Global efficiency and FA explained 5% to 16% of the variance in gait speed, chair stand times, and SPPB scores, independent of age and sex. Moreover, global efficiency and FA explained an additional 4% to 5% of variance on top of lacunar infarcts and white matter hyperintensities. Regional analyses showed that, in particular, the connectivity strength of prefrontal, occipital, striatal, and thalamic nodes correlated with gait speed.

CONCLUSION

Poorer physical performance is related to disrupted white matter network connectivity in memory clinic patients with vascular brain injury. The associations of these network abnormalities are partially independent of visible vascular injury. J Am Geriatr Soc 67:1880–1887, 2019

Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2-7 days (acute), and >7-90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

The Superoanterior Fasciculus (SAF): A Novel White Matter Pathway in the Human Brain?

Fiber tractography (FT) using diffusion magnetic resonance imaging (dMRI) is widely used for investigating microstructural properties of white matter (WM) fiber-bundles and for mapping structural connections of the human brain. While studying the architectural configuration of the brain's circuitry with FT is not without controversy, recent progress in acquisition, processing, modeling, analysis, and visualization of dMRI data pushes forward the reliability in reconstructing WM pathways. Despite being aware of the well-known pitfalls in analyzing dMRI data and several other limitations of FT discussed in recent literature, we present the superoanterior fasciculus (SAF), a novel bilateral fiber tract in the frontal region of the human brain that-to the best of our knowledge-has not been documented. The SAF has a similar shape to the anterior part of the cingulum bundle, but it is located more frontally. To minimize the possibility that these FT findings are based on acquisition or processing artifacts, different dMRI data sets and processing pipelines have been used to describe the SAF. Furthermore, we evaluated the configuration of the SAF with complementary methods, such as polarized light imaging (PLI) and human brain dissections. The FT results of the SAF demonstrate a long pathway, consistent across individuals, while the human dissections indicate fiber pathways connecting the postero-dorsal with the antero-dorsal cortices of the frontal lobe.

Brain microstructural development in neonates with critical congenital heart disease: An atlas-based diffusion tensor imaging study

Background

Brain microstructural maturation progresses rapidly in the third trimester of gestation and first weeks of life, but typical microstructural development may be influenced by the presence of critical congenital heart disease (CHD).

Objective

The aim of this study was to investigate the pattern of white matter (WM) microstructural development in neonates with different types of critical CHD. The secondary aim was to examine whether there is an association between WM microstructural maturity and neonatal ischemic brain injury.

Methods

For this prospective, longitudinal cohort study, 74 term born neonates underwent diffusion tensor imaging (DTI) before (N = 56) and after (N = 71) cardiac surgery performed <30 days of life for transposition of the great arteries (TGA), single ventricle physiology with aortic arch obstruction (SVP-AO), left- (LVOTO) or right ventricle outflow tract obstruction (RVOTO). Microstructural integrity was investigated by fractional anisotropy (FA) and by mean diffusivity (MD) in 16 white matter (WM) structures in three WM regions with correction for postmenstrual age. Ischemic brain injury was defined as moderate-severe white matter injury or stroke.

Results

Before cardiac surgery, the posterior parts of the corona radiata and internal capsule showed significantly higher FA and lower MD compared to the anterior parts. Centrally-located WM structures demonstrated higher FA compared to peripherally-located structures. Neonates with TGA had higher FA in projection-, association- and commissural WM before surgery, when compared to other CHD groups. Neonates with LVOTO showed lower preoperative MD in these regions, and neonates with SVP-AO higher MD. Differences in FA/MD between CHD groups were most clear in centrally located WM structures. Between CHD groups, no differences in postoperative FA/MD or in change from pre- to postoperative FA/MD were seen. Neonatal ischemic brain injury was not associated with pre- or postoperative FA/MD.

Conclusions

Collectively, these findings revealed brain microstructural WM development to follow the same organized pattern in critical CHD as reported in healthy and preterm neonates, from posterior-to-anterior and central-to-peripheral. Neonates with TGA and LVOTO showed the most mature WM microstructure before surgery and SVP-AO the least mature. Degree of WM microstructural immaturity was not associated with ischemic brain injury.

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Preoperative white matter integrity related to critical CHD type.

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Largest difference across CHD types in most mature white matter structures.

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Pattern of white matter development not related to critical CHD type.

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White matter maturity not related to higher risk neonatal ischemic brain injury.

A combined diffusion-weighted and electroencephalography study on age-related differences in connectivity in the motor network during bimanual performance

We studied the relationship between age-related differences in inter- and intra-hemispheric structural and functional connectivity in the bilateral motor network. Our focus was on the correlation between connectivity and declined motor performance in older adults. Structural and functional connectivity were estimated using diffusion weighted imaging and resting-state electro-encephalography, respectively. A total of 48 young and older healthy participants were measured. In addition, motor performances were assessed using bimanual coordination tasks. To pre-select regions-of-interest (ROIs), a neural model was adopted that accounts for intra-hemispheric functional connectivity between dorsal premotor area (PMd) and primary motor cortex (M1) and inter-hemispheric connections between left and right M1 (M1_L and M1_R ). Functional connectivity was determined via the weighted phase-lag index (wPLI) in the source-reconstructed beta activity during rest. We quantified structural connectivity using kurtosis anisotropy (KA) values of tracts derived from diffusion tensor-based fiber tractography between the aforementioned areas. In the group of older adults, wPLI values between M1_L -M1_R were negatively associated with the quality of bimanual motor performance. The additional association between wPLI values of PMd_L --M1_L and PMd_R -M1_L supports that functional connectivity with the left hemisphere mediated (bimanual) motor control in older adults. The correlational analysis between the selected structural and functional connections revealed a strong association between wPLI values in the left intra-hemispheric PMd_L -M1_L pathway and KA values in M1_L -M1_R and PMd_R -M1_L pathways in the group of older adults. This suggests that weaker structural connections in older adults correlate with stronger functional connectivity and, hence, poorer motor performance.

Brain imaging correlates of mild cognitive impairment and early dementia in patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

The risk of mild cognitive impairment and dementia is increased in type 2 diabetes mellitus (T2DM). We aimed to identify the neuroanatomical correlates of mild cognitive impairment (MCI) and early dementia in patients with T2DM, using advanced multimodal MRI.

METHODS AND RESULTS

Twenty-five patients (≥70 years) with T2DM and MCI (n = 22) or early dementia (n = 3) were included. The reference group consisted of 23 patients with T2DM with intact cognition. All patients underwent a 3 T MRI. Brain volumes and white matter hyperintensity volumes were obtained with automated segmentation methods. White matter connectivity was assessed with diffusion tensor imaging and fiber tractography. Infarcts and microbleeds were rated visually. Compared to patients without cognitive impairment, those with impairment had a lower grey matter volume (effect size: -0.58, p=0.042), especially in the right temporal lobe and subcortical brain regions (effect sizes: -0.45 to -0.91, false discovery rate corrected p < 0.05). White matter volume (effect size: -0.47, p = 0.11) and white matter connectivity (effect size: 0.55, p = 0.054) were also reduced in patients with versus without cognitive impairment, albeit not statistically significant. White matter hyperintensity volumes and occurrence of other vascular lesions did not differ between the two patient groups.

CONCLUSION

In patients with T2DM, grey matter atrophy rather than vascular brain injury appears to be the primary imaging correlate of MCI and early dementia.

The Impacts of Tumor and Tumor Associated Epilepsy on Subcortical Brain Structures and Long Distance Connectivity in Patients With Low Grade Glioma

Low grade gliomas in cerebral cortex often cause symptoms related to higher cerebral functions such as attention, memory and executive function before treatment is initiated. Interestingly, focal tumors residing in one cortical region can lead to a diverse range of symptoms, indicating that the impact of a tumor is extended to multiple brain regions. We hypothesize that the presence of focal glioma in the cerebral cortex leads to alterations of distant subcortical areas and essential white matter tracts. In this study, we analyzed diffusion tensor imaging scans in glioma patients to study the effect of glioma on subcortical gray matter nuclei and long-distance connectivity. We found that the caudate nucleus, putamen and thalamus were affected by cortical glioma, displaying both volumetric and diffusion alterations. The cerebellar cortex contralateral to the tumor side also showed significant volume decrease. Additionally, tractography of the cortico-striatal and cortico-thalamic projections shows similar diffusion alterations. Tumor associated epilepsy might be an important contributing factor to the found alterations. Our findings indeed confirm concurrent structural and connectivity abrasions of brain areas distant from brain tumor, and provide insights into the pathogenesis of diverse neurological symptoms in glioma patients.

Associations between prenatal, childhood, and adolescent stress and variations in white-matter properties in young men

OBJECTIVE

Previous studies have shown that both pre- and post-natal adversities, the latter including exposures to stress during childhood and adolescence, explain variation in structural properties of white matter (WM) in the brain. While previous studies have examined effects of independent stress exposures within one developmental period, such as childhood, we examine effects of stress across development using data from a prospective longitudinal study. More specifically, we ask how stressful events during prenatal development, childhood, and adolescence relate to variation in WM properties in early adulthood in young men recruited from a birth cohort.

METHOD

Using data from 393 mother-son pairs from a community-based birth cohort from England (Avon Longitudinal Study of Parents and Children), we examined how stressful life events relate to variation in different structural properties of WM in the corpus callosum and across the whole brain in early adulthood in men aged 18-21 years. We distinguish between stress occurring during three developmental periods: a) prenatal maternal stress, b) postnatal stress within the first four years of life, c) stress during adolescence (age 12-16 years). To obtain a comprehensive quantification of variation in WM, we assess structural properties of WM using four different measures, namely fractional anisotropy (FA), mean diffusivity (MD), magnetization transfer ratio (MTR) and myelin water fraction (MWF).

RESULTS

The developmental model shows that prenatal stress is associated with lower MTR and MWF in the genu and/or splenium of the corpus callosum, and with lower MTR in global (lobar) WM. Stress during early childhood is associated with higher MTR in the splenium, and stress during adolescence is associated with higher MTR in the genu and lower MD in the splenium. We see no associations between postnatal stress and variation in global (lobar) WM.

CONCLUSIONS

The current study found evidence for independent effects of stress on WM properties during distinct neurodevelopmental periods. We speculate that these independent effects are due to differences in the developmental processes unfolding at different developmental time points. We suggest that associations between prenatal stress and WM properties may relate to abnormalities in neurogenesis, affecting the number and density of axons, while postnatal stress may interfere with processes related to myelination or radial growth of axons. Potential consequences of prenatal glucocorticoid exposure should be considered in obstetric care.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'.

Accelerated intermittent theta burst stimulation in major depression induces decreases in modularity: A connectome analysis

Accelerated intermittent theta burst stimulation (aiTBS) is a noninvasive neurostimulation technique that shows promise for improving clinical outcome in patients suffering from treatment-resistant depression (TRD). Although it has been suggested that aiTBS may evoke beneficial neuroplasticity effects in neuronal circuits, the effects of aiTBS on brain networks have not been investigated until now. Fifty TRD patients were enrolled in a randomized double-blind sham-controlled crossover trial involving aiTBS, applied to the left dorsolateral prefrontal cortex. Diffusion-weighted MRI data were acquired at each of three time points (T1 at baseline; T2 after the first week of real/sham aiTBS stimulation; and T3 after the second week of treatment). Graph analysis was performed on the structural connectivity to examine treatment-related changes in the organization of brain networks. Changes in depression severity were assessed using the Hamilton Depression Rating Scale (HDRS). Baseline data were compared with 60 healthy controls. We observed a significant reduction in depression symptoms over time (p < 0.001). At T1, both TRD patients and controls exhibited a small-world topology in their white matter networks. More importantly, the TRD patients demonstrated a significantly shorter normalized path length (p AUC = 0.01), and decreased assortativity (p AUC = 0.035) of the structural networks, compared with the healthy control group. Within the TRD group, graph analysis revealed a less modular network configuration between T1 and T2 in the TRD group who received real aiTBS stimulation in the first week (p < 0.013). Finally, there were no significant correlations between changes on HDRS scores and reduced modularity. Application of aiTBS in TRD is characterized by reduced modularity, already evident 4 days after treatment. These findings support the potential clinical application of such noninvasive brain stimulation in TRD.

A robust deconvolution method to disentangle multiple water pools in diffusion MRI

The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

Developmental origins of depression-related white matter properties: Findings from a prenatal birth cohort

Depression is the leading cause of years lost due to disability worldwide. Still, the mechanisms underlying its development are not well understood. This study aimed to evaluate white-matter properties associated with depressive symptomatology in young adulthood and their developmental origins. Diffusion tensor imaging and assessment of depressive symptomatology were conducted in 128 young adults (47% male, age 23-24) from a prenatal birth cohort (European Longitudinal Study of Pregnancy and Childhood). For a subset of these individuals, the database included information on prenatal stress (n = 93) and depressive symptoms during adolescence (assessed repeatedly at age 15 and 19). Depressive symptoms in young adulthood were associated with lower fractional anisotropy in the left and right cingulum and higher fractional anisotropy in the right corticospinal tract and superior longitudinal fasciculus. Further analyses revealed that prenatal stress and depressive symptomatology during adolescence were independent predictors of altered white-matter properties in the cingulum in young adulthood. We conclude that typically developing young adults with more depressive symptoms already exhibit tract-specific alterations in white-matter properties and that prenatal stress and depressive symptomatology during adolescence might contribute to their development.

Prediction of Isocitrate Dehydrogenase Genotype in Brain Gliomas with MRI: Single-Shell versus Multishell Diffusion Models

Purpose The primary aim of this prospective observational study was to assess whether diffusion MRI metrics correlate with isocitrate dehydrogenase (IDH) status in grade II and III gliomas. A secondary aim was to investigate whether multishell acquisitions with advanced models such as neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging offer greater diagnostic accuracy than diffusion-tensor imaging (DTI). Materials and Methods Diffusion MRI (b = 700 and 2000 sec/mm²) was performed preoperatively in 192 consecutive participants (113 male and 79 female participants; mean age, 46.18 years; age range, 14-77 years) with grade II (n = 62), grade III (n = 58), or grade IV (n = 72) gliomas. DTI, diffusion kurtosis imaging, and NODDI metrics were measured in regions with or without hyperintensity on diffusion MR images and compared among groups defined according to IDH genotype, 1p/19q codeletion status, and tumor grade by using Mann-Whitney tests. Results In grade II and III IDH wild-type gliomas, the maximum fractional anisotropy, kurtosis anisotropy, and restriction fraction were significantly higher and the minimum mean diffusivity was significantly lower than in IDH-mutant gliomas (P = .011, P = .002, P = .044, and P = .027, respectively); areas under the receiver operating characteristic curve ranged from 0.72 to 0.76. In IDH wild-type gliomas, no difference among grades II, III, and IV was found. In IDH-mutant gliomas, no difference between those with and those without 1p/19q loss was found. Conclusion Diffusion MRI metrics showed correlation with isocitrate dehydrogenase status in grade II and III gliomas. Advanced diffusion MRI models did not add diagnostic accuracy, supporting the inclusion of a single-shell diffusion-tensor imaging acquisition in brain tumor imaging protocols. Published under a CC BY 4.0 license. Online supplemental material is available for this article.

Multicenter reproducibility study of diffusion MRI and fiber tractography of the lumbosacral nerves

BACKGROUND

Diffusion tensor imaging (DTI) has been applied in the lumbar and sacral nerves in vivo, but information about the reproducibility of this method is needed before DTI can be used reliably in clinical practice across centers.

PURPOSE

In this multicenter study the reproducibility of DTI of the lumbosacral nerves in healthy volunteers was investigated.

STUDY TYPE

Prospective control series.

SUBJECTS

Twenty healthy subjects.

FIELD STRENGTH/SEQUENCE

3T MRI. 3D turbo spin echo, and 3.0 mm isotropic DTI scan.

ASSESSMENT

The DTI scan was performed three times (twice in the same session, intrascan reproducibility, and once after an hour, interscan reproducibility). At site 2, 1 week later, the protocol was repeated (interweek reproducibility). Fiber tractography (FT) of the lumbar and sacral nerves (L3-S2) was performed to obtain values for fractional anisotropy, mean, axial, and radial diffusivity.

STATISTICAL TESTS

Reproducibility was determined using the intraclass correlation coefficient (ICC), and power calculations were performed.

RESULTS

FT was successful and reproducible in all datasets. ICCs for all diffusion parameters were high for intrascan (ranging from 0.70-0.85), intermediate for interscan (ranging from 0.61-0.73), and interweek reliability (ranging from 0.58-0.62). There were small but significant differences between the interweek diffusivity values (P < 0.0005). Depending on the effect size, nerve location, and parameter of interest, power calculations showed that sample sizes between 10 and 232 subjects are needed for cross-sectional studies.

DATA CONCLUSION

We found that DTI and FT of the lumbosacral nerves have intermediate to high reproducibility within and between scans. Based on these results, 10-58 subjects are needed to find a 10% change in parameters in cross-sectional studies of the lumbar and sacral nerves. The small significant differences of the interweek comparison suggest that results from longitudinal studies need to be interpreted carefully, since small differences may also be caused by factors other than disease progression or therapeutic effects.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:951-963.

Weight loss, behavioral change, and structural neuroplasticity in children with obesity through a multidisciplinary treatment program

This study evaluated the effect of a multidisciplinary treatment program for children with obesity (OB) on motor competence, executive functioning (EF), and brain structure. Nineteen children with OB (7-11 years), who attended a multidisciplinary treatment program consisting of diet restriction, cognitive behavioral therapy, and physical activity, were compared with an age-matched control group of 24 children with a healthy weight (HW), who did not follow any treatment. For both groups, anthropometric measurements and tests of motor competence and EF were administered twice, with 5 months between pretest and posttest. Additionally, children's brain structure was assessed by performing a magnetic resonance imaging (MRI) scan at the pretest and posttest, which included a T1 anatomical scan, diffusion MRI scan, and magnetization transfer imaging scan. Compared to HW controls, children with OB lost a considerable amount of their body mass (p ≤ .001) and significantly improved their balance skills (p ≤ .001), while no transfer effects of the program were observed for EF. Furthermore, the program resulted in a significant increase in total (p ≤ .001) and cerebellar (p ≤ .001) gray matter volume in children with OB, while no change was observed in the HW controls. Finally, only weak to moderate (nonsignificant) correlations could be observed between structural brain alterations, weight-related changes, and behavioral improvements. Altogether, this is the first longitudinal study showing behavioral and structural brain alterations in response to a multidisciplinary weight loss program for children with OB. Our findings support the need for multidimensional intervention (and prevention) measures for children with OB to deal with this multifactorial health problem.

Fast and accurate Slicewise OutLIer Detection (SOLID) with informed model estimation for diffusion MRI data

The accurate characterization of the diffusion process in tissue using diffusion MRI is greatly challenged by the presence of artefacts. Subject motion causes not only spatial misalignments between diffusion weighted images, but often also slicewise signal intensity errors. Voxelwise robust model estimation is commonly used to exclude intensity errors as outliers. Slicewise outliers, however, become distributed over multiple adjacent slices after image registration and transformation. This challenges outlier detection with voxelwise procedures due to partial volume effects. Detecting the outlier slices before any transformations are applied to diffusion weighted images is therefore required. In this work, we present i) an automated tool coined SOLID for slicewise outlier detection prior to geometrical image transformation, and ii) a framework to naturally interpret data uncertainty information from SOLID and include it as such in model estimators. SOLID uses a straightforward intensity metric, is independent of the choice of the diffusion MRI model, and can handle datasets with a few or irregularly distributed gradient directions. The SOLID-informed estimation framework prevents the need to completely reject diffusion weighted images or individual voxel measurements by downweighting measurements with their degree of uncertainty, thereby supporting convergence and well-conditioning of iterative estimation algorithms. In comprehensive simulation experiments, SOLID detects outliers with a high sensitivity and specificity, and can achieve higher or at least similar sensitivity and specificity compared to other tools that are based on more complex and time-consuming procedures for the scenarios investigated. SOLID was further validated on data from 54 neonatal subjects which were visually inspected for outlier slices with the interactive tool developed as part of this study, showing its potential to quickly highlight problematic volumes and slices in large population studies. The informed model estimation framework was evaluated both in simulations and in vivo human data.

The cumulative effect of small vessel disease lesions is reflected in structural brain networks of memory clinic patients

Background and purpose

Mechanisms underlying cognitive impairment in patients with small vessel disease (SVD) are still unknown. We hypothesized that cognition is affected by the cumulative effect of multiple SVD-related lesions on brain connectivity. We therefore assessed the relationship between the total SVD burden on MRI, global brain network efficiency, and cognition in memory clinic patients with vascular brain injury.

Methods

173 patients from the memory clinic of the University Medical Center Utrecht underwent a 3 T brain MRI scan (including diffusion MRI sequences) and neuropsychological testing. MRI markers for SVD were rated and compiled in a previously developed total SVD score. Structural brain networks were reconstructed using fiber tractography followed by graph theoretical analysis. The relationship between total SVD burden score, global network efficiency and cognition was assessed using multiple linear regression analyses.

Results

Each point increase on the SVD burden score was associated with 0.260 [−0.404 - -0.117] SD units decrease of global brain network efficiency (p < .001). Global network efficiency was associated with information processing speed (standardized B = −0.210, p = .004) and attention and executive functioning (B = 0.164, p = .042), and mediated the relationship between SVD burden and information processing speed (p = .027) but not with executive functioning (p = .12).

Conclusion

Global network efficiency is sensitive to the cumulative effect of multiple manifestations of SVD on brain connectivity. Global network efficiency may therefore serve as a useful marker for functionally relevant SVD-related brain injury in clinical trials.

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Increasing small vessel disease burden (SVD) related to decreasing network efficiency.

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Network efficiency mediates association between SVD burden and processing speed.

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Cumulative effect of SVD might partly affect cognition through disrupted connectivity.

White matter network alterations in patients with depersonalization/derealization disorder

BACKGROUND

Depersonalization/derealization disorder (DPD) is a chronic and distressing condition characterized by detachment from oneself and/or the external world. Neuroimaging studies have associated DPD with structural and functional alterations in a variety of distinct brain regions. Such local neuronal changes might be mediated by altered interregional white matter connections. However, to our knowledge, no research on network characteristics in this patient population exists to date.

METHODS

We explored the structural connectome in 23 individuals with DPD and 23 matched, healthy controls by applying graph theory to diffusion tensor imaging data. Mean interregional fractional anisotropy (FA) was used to define the network weights. Group differences were assessed using network-based statistics and a link-based controlling procedure.

RESULTS

Our main finding refers to lower FA values within left temporal and right temporoparietal regions in individuals with DPD than in healthy controls when using a link-based controlling procedure. These links were also associated with dissociative symptom severity and could not be explained by anxiety or depression scores. Using network-based statistics, no significant results emerged. However, we found a trend for 1 subnetwork that may support the model of frontolimbic dysbalance suggested to underlie DPD symptomatology.

LIMITATIONS

To ensure ecological validity, patients with certain comorbidities or psychotropic medication were included in the study. Confirmatory replications are necessary to corroborate the results of this explorative investigation.

CONCLUSION

In patients with DPD, the structural connectivity between brain regions crucial for multimodal integration and emotion regulation may be altered. Aberrations in fibre tract communication seem to be not solely a secondary effect of local grey matter volume loss, but may present a primary pathophysiology in patients with DPD.

Mild cerebellar injury does not significantly affect cerebral white matter microstructural organization and neurodevelopmental outcome in a contemporary cohort of preterm infants

BackgroundPreterm birth is associated with an increased risk of cerebellar injury. The aim of this study was to assess the impact of cerebellar hemorrhages (CBH) on cerebral white matter microstructural tissue organization and cerebellar volume at term-equivalent age (TEA) in extremely preterm infants. Furthermore, we aimed to evaluate the association between CBH and neurodevelopmental outcome in late infancy.MethodsA total of 24 preterm infants with punctate CBH were included and each matched to two preterm control infants. T1-, T2-weighted images and diffusion-weighted imaging were acquired on a 3T magnetic resonance imaging (MRI) system. Regions of interest were drawn on a population-specific neonatal template and automatically registered to individual fractional anisotropy (FA) maps. Brain volumes were automatically computed. Neurodevelopmental outcome was assessed using the Bayley scales of Infant and Toddler Development at 2 years of corrected age.ResultsCBHs were not significantly related to FA in the posterior limb of the internal capsule and corpus callosum or to cerebellar volume. Infants with CBH did not have poorer neurodevelopmental outcome compared with control infants.ConclusionThese findings suggest that the impact of mild CBH on early macroscale brain development may be limited. Future studies are needed to assess the effects of CBH on long-term neurodevelopment.

Changes in brain morphology and microstructure in relation to early brain activity in extremely preterm infants

Background and ObjectiveTo investigate the relation of early brain activity with structural (growth of the cortex and cerebellum) and white matter microstructural brain development.MethodsA total of 33 preterm neonates (gestational age 26±1 weeks) without major brain abnormalities were continuously monitored with electroencephalography during the first 48 h of life. Rate of spontaneous activity transients per minute (SAT rate) and inter-SAT interval (ISI) in seconds per minute were calculated. Infants underwent brain magnetic resonance imaging ∼30 (mean 30.5; min: 29.3-max: 32.0) and 40 (41.1; 40.0-41.8) weeks of postmenstrual age. Increase in cerebellar volume, cortical gray matter volume, gyrification index, fractional anisotropy (FA) of posterior limb of the internal capsule, and corpus callosum (CC) were measured.ResultsSAT rate was positively associated with cerebellar growth (P=0.01), volumetric growth of the cortex (P=0.027), increase in gyrification (P=0.043), and increase in FA of the CC (P=0.037). ISI was negatively associated with cerebellar growth (P=0.002).ConclusionsIncreased early brain activity is associated with cerebellar and cortical growth structures with rapid development during preterm life. Higher brain activity is related to FA microstructural changes in the CC, a region responsible for interhemispheric connections. This study underlines the importance of brain activity for microstructural brain development.

Cerebellar Growth Impairment Characterizes School-Aged Children Born Preterm without Perinatal Brain Lesions

BACKGROUND AND PURPOSE

Infants born preterm are commonly diagnosed with structural brain lesions known to affect long-term neurodevelopment negatively. Yet, the effects of preterm birth on brain development in the absence of intracranial lesions remain to be studied in detail. In this study, we aim to quantify long term consequences of preterm birth on brain development in this specific group.

MATERIALS AND METHODS

Neonatal cranial sonography and follow-up T1-weighted MR imaging and DTI were performed to evaluate whether the anatomic characteristics of the cerebrum and cerebellum in a cohort of school-aged children (6-12 years of age) were related to gestational age at birth in children free of brain lesions in the perinatal period.

RESULTS

In the cohort consisting of 36 preterm (28-37 weeks' gestational age) and 66 term-born infants, T1-weighted MR imaging and DTI at 6-12 years revealed a reduction of cerebellar white matter volume (β = 0.387, P < .001), altered fractional anisotropy of cerebellar white matter (β = -0.236, P = .02), and a reduction of cerebellar gray and white matter surface area (β = 0.337, P < .001; β = 0.375, P < .001, respectively) in relation to birth age. Such relations were not observed for the cerebral cortex or white matter volume, surface area, or diffusion quantities.

CONCLUSIONS

The results of our study show that perinatal influences that are not primarily neurologic are still able to disturb long-term neurodevelopment, particularly of the developing cerebellum. Including the cerebellum in future neuroprotective strategies seems therefore essential.

Assessing diffusion kurtosis tensor estimation methods using a digital brain phantom derived from human connectome project data

PURPOSE

Diffusion kurtosis imaging (DKI) has gained popularity in recent years as an advanced diffusion-weighted MRI technique. This work aims to quantitatively compare the performance and accuracy of four DKI processing algorithms. For this purpose, a digital DKI brain phantom is developed.

METHODS

Data from the Human Connectome Project database were used to generate a DKI digital phantom. In a Monte Carlo Rician noise simulation, four DKI processing algorithms were compared based on their mean squared error, squared bias, and variance.

RESULTS

Algorithm performance was region-dependent and differed for each diffusion metric and noise level. Crossover between variance and squared bias error occurred between signal-to-noise ratios of 30 and 40.

CONCLUSION

Through the framework presented here, DKI algorithms can be quantitatively compared via a ground truth data set. Error maps are critical as algorithm performance varies spatially. Bias-plus-variance decomposition provides a more complete picture than MSE alone. In combination with refinements in acquisition in future studies, the accuracy and efficiency of DKI will continue to improve promoting clinical adoption.

Learning Morse Code Alters Microstructural Properties in the Inferior Longitudinal Fasciculus: A DTI Study

Learning relies on neuroplasticity, which has mainly been studied in gray matter (GM). However, there is mounting evidence indicating a critical role of white matter changes involved in learning processes. One of the most important learning processes in human development is language acquisition. However, due to the length of this learning process, it has been notoriously difficult to investigate the underlying neuroplastic changes. Here, we report a novel learning paradigm to assess the role of white matter plasticity for language acquisition. By acoustically presenting Morse Code (MC) using an in house developed audio book as a model for language-type learning, we generated a well-controlled learning environment that allows for the detection of subtle white matter changes related to language type learning in a much shorter time frame than usual language acquisition. In total 12 letters of the MC alphabet were learned within six learning session, which allowed study participants to perform a word recognition MC decoding task. In this study, we found that learning MC was associated with significant microstructural changes in the left inferior longitudinal fasciculus (ILF). The fractional anisotropy (FA) of this associative fiber bundle connecting the occipital and posterior temporal cortex with the temporal pole as well as the hippocampus and amygdala was increased. Furthermore, white matter plasticity was associated with task performance of MC decoding, indicating that the structural changes were related to learning efficiency. In conclusion, our findings demonstrate an important role of white matter neuroplasticity for acquiring a new language skill.

Differentiation of glioma malignancy grade using diffusion MRI

Modern diffusion MR protocols allow one to acquire the multi-shell diffusion data with high diffusion weightings in a clinically feasible time. In the present work we assessed three diffusion approaches based on diffusion and kurtosis tensor imaging (DTI, DKI), and neurite orientation dispersion and density imaging (NODDI) as possible biomarkers for human brain glioma grade differentiation based on the one diffusion protocol. We used three diffusion weightings (so called b-values) equal to 0, 1000, and 2500s/mm² with 60 non-coplanar diffusion directions in the case of non-zero b-values. The patient groups of the glioma grades II, III, and IV consist of 8 subjects per group. We found that DKI, and NODDI scalar metrics can be effectively used as glioma grade biomarkers with a significant difference (p<0.05) for grading between low- and high-grade gliomas, in particular, for glioma II versus glioma III grades, and glioma III versus glioma IV grades. The use of mean/axial kurtosis and intra-axonal fraction/orientation dispersion index metrics allowed us to obtain the most feasible and reliable differentiation criteria. For example, in the case of glioma grades II, III, and IV the mean kurtosis is equal to 0.31, 0.51, and 0.90, and the orientation dispersion index is equal to 0.14, 0.30, and 0.59, respectively. The limitations and perspectives of the biophysical diffusion models based on intra-/extra-axonal compartmentalisation for glioma differentiation are discussed.

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit

PURPOSE

To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue.

MATERIALS AND METHODS

Ten healthy volunteers were examined at 3T, with T2 -weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono-, bi-, and triexponential fit parameters (D1 , D2 , D3 , ffast2 , ffast3 , and finterm ) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( Radj2) and the Shapiro-Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared.

RESULTS

Fitting the diffusion signal was feasible for all models. The three-component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in Radj2 of the ROI containing high diffusion signals (ROIrest ), which was 0.42 ± 0.14, 0.61 ± 0.11, 0.77 ± 0.09, and 0.81 ± 0.08 for DTI, one-, two-, and three-component models, respectively, and in visual comparison of the fitted and measured S0 . None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the ffast component of the two and three-component models were significantly different (P < 0.001).

CONCLUSION

Triexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:228-239.

Skeletal muscle diffusion tensor-MRI fiber tracking: rationale, data acquisition and analysis methods, applications and future directions

The mechanical functions of muscles involve the generation of force and the actuation of movement by shortening or lengthening under load. These functions are influenced, in part, by the internal arrangement of muscle fibers with respect to the muscle's mechanical line of action. This property is known as muscle architecture. In this review, we describe the use of diffusion tensor (DT)-MRI muscle fiber tracking for the study of muscle architecture. In the first section, the importance of skeletal muscle architecture to function is discussed. In addition, traditional and complementary methods for the assessment of muscle architecture (brightness-mode ultrasound imaging and cadaver analysis) are presented. Next, DT-MRI is introduced and the structural basis for the reduced and anisotropic diffusion of water in muscle is discussed. The third section discusses issues related to the acquisition of skeletal muscle DT-MRI data and presents recommendations for optimal strategies. The fourth section discusses methods for the pre-processing of DT-MRI data, the available approaches for the calculation of the diffusion tensor and the seeding and propagating of fiber tracts, and the analysis of the tracking results to measure structural properties pertinent to muscle biomechanics. Lastly, examples are presented of how DT-MRI fiber tracking has been used to provide new insights into how muscles function, and important future research directions are highlighted. Copyright © 2016 John Wiley & Sons, Ltd.

A novel measure of reliability in Diffusion Tensor Imaging after data rejections due to subject motion

Diffusion Tensor Imaging (DTI) is commonly challenged by subject motion during data acquisition, which often leads to corrupted image data. Currently used procedure in DTI analysis is to correct or completely reject such data before tensor estimations, however assessing the reliability and accuracy of the estimated tensor in such situations has evaded previous studies. This work aims to define the loss of data accuracy with increasing image rejections, and to define a robust method for assessing reliability of the result at voxel level. We carried out simulations of every possible sub-scheme (N=1,073,567,387) of Jones30 gradient scheme, followed by confirming the idea with MRI data from four newborn and three adult subjects. We assessed the relative error of the most commonly used tensor estimates for DTI and tractography studies, fractional anisotropy (FA) and the major orientation vector (V1), respectively. The error was estimated using two measures, the widely used electric potential (EP) criteria as well as the rotationally variant condition number (CN). Our results show that CN and EP are comparable in situations with very few rejections, but CN becomes clearly more sensitive to depicting errors when more gradient vectors and images were rejected. The error in FA and V1 was also found depend on the actual FA level in the given voxel; low actual FA levels were related to high relative errors in the FA and V1 estimates. Finally, the results were confirmed with clinical MRI data. This showed that the errors after rejections are, indeed, inhomogeneous across brain regions. The FA and V1 errors become progressively larger when moving from the thick white matter bundles towards more superficial subcortical structures. Our findings suggest that i) CN is a useful estimator of data reliability at voxel level, and ii) DTI preprocessing with data rejections leads to major challenges when assessing brain tissue with lower FA levels, such as all newborn brain, as well as the adult superficial, subcortical areas commonly traced in precise connectivity analyses between cortical regions.

MRI shows thickening and altered diffusion in the median and ulnar nerves in multifocal motor neuropathy

Objectives

To study disease mechanisms in multifocal motor neuropathy (MMN) with magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) of the median and ulnar nerves.

Methods

We enrolled ten MMN patients, ten patients with amyotrophic lateral sclerosis (ALS) and ten healthy controls (HCs). Patients underwent MRI (in a prone position) and nerve conduction studies. DTI and fat-suppressed T2-weighted scans of the forearms were performed on a 3.0T MRI scanner. Fibre tractography of the median and ulnar nerves was performed to extract diffusion parameters: fractional anisotropy (FA), mean (MD), axial (AD) and radial (RD) diffusivity. Cross-sectional areas (CSA) were measured on T2-weighted scans.

Results

Forty-five out of 60 arms were included in the analysis. AD was significantly lower in MMN patients (2.20 ± 0.12 × 10^-3 mm²/s) compared to ALS patients (2.31 ± 0.17 × 10^-3 mm²/s; p < 0.05) and HCs (2.31± 0.17 × 10^-3 mm²/s; p < 0.05). Segmental analysis showed significant restriction of AD, RD and MD (p < 0.005) in the proximal third of the nerves. CSA was significantly larger in MMN patients compared to ALS patients and HCs (p < 0.01).

Conclusions

Thickening of nerves is compatible with changes in the myelin sheath structure, whereas lowered AD values suggest axonal dysfunction. These findings suggest that myelin and axons are diffusely involved in MMN pathogenesis.

Key Points

• Diffusion magnetic resonance imaging provides quantitative information about multifocal motor neuropathy (MMN).

• Diffusion tensor imaging allows non-invasive evaluation of the forearm nerves in MMN.

• Nerve thickening and lowered diffusion parameters suggests myelin and axonal changes.

• This study can help to provide insight into pathological mechanisms of MMN.

Electronic supplementary material

The online version of this article (doi:10.1007/s00330-016-4575-0) contains supplementary material, which is available to authorized users.

Comparison of image sensitivity between conventional tensor-based and fast diffusion kurtosis imaging protocols in a rodent model of acute ischemic stroke

Diffusion kurtosis imaging (DKI) can offer a useful complementary tool to routine diffusion MRI for improved stratification of heterogeneous tissue damage in acute ischemic stroke. However, its relatively long imaging time has hampered its clinical application in the emergency setting. A recently proposed fast DKI approach substantially shortens the imaging time, which may help to overcome the scan time limitation. However, to date, the sensitivity of the fast DKI protocol for the imaging of acute stroke has not been fully described. In this study, we performed routine and fast DKI scans in a rodent model of acute stroke, and compared the sensitivity of diffusivity and kurtosis indices (i.e. axial, radial and mean) in depicting acute ischemic lesions. In addition, we analyzed the contrast-to-noise ratio (CNR) between the ipsilateral ischemic and contralateral normal regions using both conventional and fast DKI methods. We found that the mean kurtosis shows a relative change of 47.1 ± 7.3% between the ischemic and contralateral normal regions, being the most sensitive parameter in revealing acute ischemic injury. The two DKI methods yielded highly correlated diffusivity and kurtosis measures and lesion volumes (R(2)  ⩾ 0.90, p < 0.01). Importantly, the fast DKI method exhibited significantly higher CNR of mean kurtosis (1.6 ± 0.2) compared with the routine tensor protocol (1.3 ± 0.2, p < 0.05), with its CNR per unit time (CNR efficiency) approximately doubled when the scan time was taken into account. In conclusion, the fast DKI method provides excellent sensitivity and efficiency to image acute ischemic tissue damage, which is essential for image-guided and individualized stroke treatment.

Choosing the polarity of the phase-encoding direction in diffusion MRI: Does it matter for group analysis?

Notorious for degrading diffusion MRI data quality are so-called susceptibility-induced off-resonance fields, which cause non-linear geometric image deformations. While acquiring additional data to correct for these distortions alleviates the adverse effects of this artifact drastically - e.g., by reversing the polarity of the phase-encoding (PE) direction - this strategy is often not an option due to scan time constraints. Especially in a clinical context, where patient comfort and safety are of paramount importance, acquisition specifications are preferred that minimize scan time, typically resulting in data obtained with only one PE direction. In this work, we investigated whether choosing a different polarity of the PE direction would affect the outcome of a specific clinical research study. To address this methodological question, fractional anisotropy (FA) estimates of FreeSurfer brain regions were obtained in civilian and combat controls, remitted posttraumatic stress disorder (PTSD) patients, and persistent PTSD patients before and after trauma-focused therapy and were compared between diffusion MRI data sets acquired with different polarities of the PE direction (posterior-to-anterior, PA and anterior-to-posterior, AP). Our results demonstrate that regional FA estimates differ on average in the order of 5% between AP and PA PE data. In addition, when comparing FA estimates between different subject groups for specific cingulum subdivisions, the conclusions for AP and PA PE data were not in agreement. These findings increase our understanding of how one of the most pronounced data artifacts in diffusion MRI can impact group analyses and should encourage users to be more cautious when interpreting and reporting study outcomes derived from data acquired along a single PE direction.

Diffusion tensor imaging of peripheral nerves in non-fixed post-mortem subjects

PURPOSE

While standard magnetic resonance imaging (MRI) sequences are increasingly employed in post-mortem (PM) examinations, more advanced techniques such as diffusion tensor imaging (DTI) remain unexplored in forensic sciences. Therefore, we studied the temporal stability and reproducibility of DTI and fiber tractography (FT) in non-fixed PM subjects. In addition, we investigated the lumbosacral nerves with PMDTI and compared their tissue characteristics to in vivo findings.

METHODS

MRI data were acquired on a 1.5T MRI scanner in seven PM subjects, consisting of six non-trauma deaths and one chronic trauma death, and in six living subjects. Inter-scan (within one session) and inter-session (between days) reproducibility of diffusion parameters, fractional anisotropy (FA), and mean diffusivity (MD), were evaluated for the lumbosacral nerves using Bland-Altman and Jones plots. Diffusion parameters in nerves L3-S2 were compared to living subjects using the non-parametric Mann-Whitney U test.

RESULTS

Reproducibility of diffusion values of inter-scan 95% limits of agreement ranged from -0.058 to 0.062 for FA, and (-0.037 to 0.052)×10(-3)mm(2)/s for MD. For the inter-session this was -0.0423 to 0.0423, and (-0.0442 to 0.0442)×10(-3)mm(2)/s for FA, and MD, respectively. Although PM subjects showed approximately four-fold lower diffusivity values compared to living subjects, FT results were comparable. The chronic trauma case showed disorganization and asymmetry of the nerves.

CONCLUSION

We demonstrated that DTI was reproducible in characterizing nervous tissue properties and FT in reconstructing the architecture of lumbosacral nerves in PM subjects. We showed differences in diffusion values between PM and in vivo and showed the ability of PMDTI and FT to reconstruct nerve lesions in a chronic trauma case. We expect that PMDTI and FT may become valuable in identification and documentation of PM nerve trauma or pathologies in forensic sciences.