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Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities., (Copyright © 2021. Published by Elsevier Inc.)

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

Purpose: Several recent studies have used a three-tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion-weighted MRI data. The three tissue compartments, consisting of white matter, gray matter, and CSF-like (free water) signals, are potentially useful in the evaluation of brain microstructure in a range of pathologies. However, the reliability and long-term stability of these metrics have not yet been evaluated., Methods: This study examined estimates of whole-brain microstructure for the three tissue compartments, in three separate test-retest cohorts. Each cohort had different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to 3 months in the longest interval. Each cohort was also collected with different acquisition parameters., Results: The CSF-like compartment displayed the greatest reliability across all cohorts, with intraclass correlation coefficient (ICC) values being above 0.95 in each cohort. White matter-like and gray matter-like compartments both demonstrated very high reliability in the immediate cohort (both ICC > 0.90); however, this declined in the 3-month interval cohort to both compartments having ICC > 0.80. Regional CSF-like signal fraction was examined in bilateral hippocampus and had an ICC > 0.80 in each cohort., Conclusion: The three-tissue constrained spherical deconvolution techniques provide reliable and stable estimates of tissue-microstructure composition, up to 3 months longitudinally in a control population. This forms an important basis for further investigations using three-tissue constrained spherical deconvolution techniques to track changes in microstructure across a variety of brain pathologies., (© 2020 International Society for Magnetic Resonance in Medicine.)

Since its inception 30 years ago, diffusion-weighted magnetic resonance imaging (dMRI) has advanced to become a common component of routine clinical MRI examinations. Diffusion-weighted magnetic resonance offers a way to measure anisotropic diffusion in-vivo, which has led to the development of techniques capable of characterising the orientation of diffusion within living tissue. These modelling techniques can be used to investigate the microstructure and connectivity of white matter tracts within the human brain. Such techniques have been used to study many neural networks within the human body. There is, however, a notable paucity of research utilising dMRI techniques to investigate the white matter tracts of the auditory brainstem. In this review we provide a brief introduction to the basic principles of dMRI analysis and consider some of the difficulties associated with applying dMRI techniques to study the auditory pathways of the brainstem. We also consider aspects of current dMRI methodologies relevant to the auditory brainstem to inform future research in this area., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Differences in brain networks and underlying white matter abnormalities have been suggested to underlie symptoms of autism spectrum disorder (ASD). However, robustly characterizing microstructural white matter differences has been challenging. In the present study, we applied an analytic technique that calculates structural metrics specific to differently-oriented fiber bundles within a voxel, termed "fixels". Fixel-based analyses were used to compare diffusion-weighted magnetic resonance imaging data from 25 individuals with ASD (mean age = 16.8 years) and 27 typically developing age-matched controls (mean age = 16.9 years). Group comparisons of fiber density (FD) and bundle morphology were run on a fixel-wise, tract-wise, and global white matter (GWM) basis. We found that individuals with ASD had reduced FD, suggestive of decreased axonal count, in several major white matter tracts, including the corpus callosum (CC), bilateral inferior frontal-occipital fasciculus, right arcuate fasciculus, and right uncinate fasciculus, as well as a GWM reduction. Secondary analyses assessed associations with social impairment in participants with ASD, and showed that lower FD in the splenium of the CC was associated with greater social impairment. Our findings suggest that reduced FD could be the primary microstructural white matter abnormality in ASD., (© The Author(s) 2019. Published by Oxford University Press.)

Diffusion-weighted imaging and tractography provide a unique, non-invasive technique to study the macroscopic structure and connectivity of brain white matter in vivo. Global tractography methods aim at reconstructing the full-brain fiber configuration that best explains the measured data, based on a generative signal model. In this work, we incorporate a multi-shell multi-tissue model based on spherical convolution, into a global tractography framework, which allows to deal with partial volume effects. The required tissue response functions can be estimated from and hence calibrated to the data. The resulting track reconstruction is quantitatively related to the apparent fiber density in the data. In addition, the fiber orientation distribution for white matter and the volume fractions of gray matter and cerebrospinal fluid are produced as ancillary results. Validation results on simulated data demonstrate that this data-driven approach improves over state-of-the-art streamline and global tracking methods, particularly in the valid connection rate. Results in human brain data correspond to known white matter anatomy and show improved modeling of partial voluming. This work is an important step toward detecting and quantifying white matter changes and connectivity in healthy subjects and patients., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Constrained spherical deconvolution (CSD) has become one of the most widely used methods to extract white matter (WM) fibre orientation information from diffusion-weighted MRI (DW-MRI) data, overcoming the crossing fibre limitations inherent in the diffusion tensor model. It is routinely used to obtain high quality fibre orientation distribution function (fODF) estimates and fibre tractograms and is increasingly used to obtain apparent fibre density (AFD) measures. Unfortunately, CSD typically only supports data acquired on a single shell in q-space. With multi-shell data becoming more and more prevalent, there is a growing need for CSD to fully support such data. Furthermore, CSD can only provide high quality fODF estimates in voxels containing WM only. In voxels containing other tissue types such as grey matter (GM) and cerebrospinal fluid (CSF), the WM response function may no longer be appropriate and spherical deconvolution produces unreliable, noisy fODF estimates. The aim of this study is to incorporate support for multi-shell data into the CSD approach as well as to exploit the unique b-value dependencies of the different tissue types to estimate a multi-tissue ODF. The resulting approach is dubbed multi-shell, multi-tissue CSD (MSMT-CSD) and is compared to the state-of-the-art single-shell, single-tissue CSD (SSST-CSD) approach. Using both simulations and real data, we show that MSMT-CSD can produce reliable WM/GM/CSF volume fraction maps, directly from the DW data, whereas SSST-CSD has a tendency to overestimate the WM volume in voxels containing GM and/or CSF. In addition, compared to SSST-CSD, MSMT-CSD can substantially increase the precision of the fODF fibre orientations and reduce the presence of spurious fODF peaks in voxels containing GM and/or CSF. Both effects translate into more reliable AFD measures and tractography results with MSMT-CSD compared to SSST-CSD., (Copyright © 2014 Elsevier Inc. All rights reserved.)

In the field of diffusion weighted imaging (DWI), it is common to fit one of many available models to the acquired data. A hybrid diffusion imaging (HYDI) approach even allows to reconstruct different models and measures from a single dataset. Methods for DWI atlas construction (and registration) are as plenty as the number of available models. Therefore, it would be nice if we were able to perform atlas building before model reconstruction. In this work, we present a method for atlas construction of DWI data in q-space: we developed a new multi-subject multi-channel diffeomorphic matching algorithm, which is combined with a recently proposed DWI retransformation method in q-space. We applied our method to HYDI data of 10 healthy subjects. From the resulting atlas, we also reconstructed some advanced models. We hereby demonstrate the feasibility of q-space atlas building, as well as the quality, advantages and possibilities of such an atlas.

Background: Age‐related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single‐shell 3‐tissue constrained spherical deconvolution (SS3T‐CSD), a novel technique that models diffusion data in terms of gray matter (TG), white matter (Tw), and cerebrospinal fluid (TC), to differentiate WMSA from normal‐appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. Methods: A total of 189 individuals from the GENIC cohort were included. MRI data, including T1‐weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T‐CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3‐tissue signal fractions (Tw, TG, and TC), and neuropsychological variables. Results: Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p <.001). Age was negatively associated with Tw in normal‐appearing white matter (p <.001) and positively associated with TG in both WMSA (p <.01) and normal‐appearing white matter (p <.001). Age was also significantly associated with WMSA volume (p <.001). Higher processing speed was associated with lower Tw and higher TG, in normal‐appearing white matter (p <.01 and p <.001, respectively), as well as increased WMSA volume (p <.001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal‐appearing white matter (p <.05). High cholesterol and hypertension were associated with higher WMSA volume (p <.05). Conclusion: The microstructural heterogeneity within normal‐appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3‐tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3‐tissue metrics. Finally, the 3‐tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance. [ABSTRACT FROM AUTHOR]

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia. [ABSTRACT FROM AUTHOR]

Diffusion magnetic resonance imaging studies often investigate white matter (WM) microstructural degeneration in aging by probing WM regions that exhibit negative age associations of fractional anisotropy (FA). However, WM regions in which FA is unassociated with age are not necessarily "spared" in aging. Besides the confound of inter-participant heterogeneity, FA conflates all intravoxel fiber populations and does not allow the detection of individual fiber-specific age associations. In this study of 541 healthy adults aged 36–100 years, we use fixel-based analysis to investigate age associations among each "fixel" within a voxel, representing individual fiber populations. We find age associations of fixel-based measures that indicate age-related differences in individual fiber populations amid complex fiber architectures. Different crossing fiber populations exhibit different slopes of age associations. Our findings may provide evidence of selective degeneration of intravoxel WM fibers in aging, which does not necessarily manifest as a change in FA and therefore escapes notice if conventional voxel-based analyses are relied upon alone. [ABSTRACT FROM AUTHOR]

We present a dataset of magnetic resonance imaging (MRI) data (T1, diffusion, BOLD) acquired in 25 brain tumor patients before the tumor resection surgery, and six months after the surgery, together with the tumor masks, and in 11 controls (recruited among the patients' caregivers). The dataset also contains behavioral and emotional scores obtained with standardized questionnaires. To simulate personalized computational models of the brain, we also provide structural connectivity matrices, necessary to perform whole-brain modelling with tools such as The Virtual Brain. In addition, we provide blood-oxygen-level-dependent imaging time series averaged across regions of interest for comparison with simulation results. An average resting state hemodynamic response function for each region of interest, as well as shape maps for each voxel, are also contributed. Measurement(s) BOLD signal • Diffusion Anisotropy Technology Type(s) Functional Magnetic Resonance Imaging • Diffusion Weighted Imaging Factor Type(s) Surgery Sample Characteristic - Organism Homo sapiens [ABSTRACT FROM AUTHOR]

The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development. [ABSTRACT FROM AUTHOR]

Attentional lapses interfere with goal‐directed behaviors, which may result in harmless (e.g., not hearing instructions) or severe (e.g., fatal car accident) consequences. Task‐related functional MRI (fMRI) studies have shown a link between attentional lapses and activity in the frontoparietal network. Activity in this network is likely to be mediated by the organization of the white matter fiber pathways that connect the regions implicated in the network, such as the superior longitudinal fasciculus I (SLF‐I). In the present study, we investigate the relationship between susceptibility to attentional lapses and relevant white matter pathways in 36 healthy adults (23 females, Mage = 31.56 years). Participants underwent a diffusion MRI (dMRI) scan and completed the global–local task to measure attentional lapses, similar to previous fMRI studies. Applying the fixel‐based analysis framework for fiber‐specific analysis of dMRI data, we investigated the association between attentional lapses and variability in microstructural fiber density (FD) and macrostructural (morphological) fiber‐bundle cross section (FC) in the SLF‐I. Our results revealed a significant negative association between higher total number of attentional lapses and lower FD in the left SLF‐I. This finding indicates that the variation in the microstructure of a key frontoparietal white matter tract is associated with attentional lapses and may provide a trait‐like biomarker in the general population. However, SLF‐I microstructure alone does not explain propensity for attentional lapses, as other factors such as sleep deprivation or underlying psychological conditions (e.g., sleep disorders) may also lead to higher susceptibility in both healthy people and those with neurological disorders. Our findings provide evidence of associations between white matter microstructure and susceptibility to attentional lapses using the highly sensitive fixel‐based analysis. We complement previous fMRI evidence to provide a more complete understanding of neural substrates underlying attentional lapses by implicating the superior longitudinal fasciculus‐I, an important attention‐based white matter tract. [ABSTRACT FROM AUTHOR]

Objective: Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome. Methods: Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1‐weighted and diffusion‐weighted imaging. Results: Significant disconnections in the lesioned and contra‐lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients. Interpretation: Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS. [ABSTRACT FROM AUTHOR]

In complex everyday environments, action selection is critical for optimal goal-directed behavior. This refers to the process of choosing a proper action from the range of possible alternatives. The neural mechanisms underlying action selection and how these are affected by normal aging remain to be elucidated. In the present cross-sectional study, we studied processes of effector selection during a multilimb reaction time task in a lifespan sample of healthy human adults (N = 89; 20-75 years; 48 males, 41 females). Participants were instructed to react as quickly and accurately as possible to visually cued stimuli representing single-limb or combined upper and/or lower limb motions. Diffusion MRI was used to study structural connectivity between prefrontal and striatal regions as critical nodes for action selection. Behavioral findings revealed that increasing age was associated with slowing of action selection performance. At the neural level, aging had a negative impact on prefrontostriatal connectivity. Importantly, mediation analyses revealed that the negative association between action selection performance and age was mediated by prefronto-striatal connectivity, specifically the connections between left rostral medial frontal gyrus and left nucleus accumbens as well as right frontal pole and left caudate. These results highlight the potential role of prefronto-striatal white matter decline in poorer action selection performance of older adults. [ABSTRACT FROM AUTHOR]

There have been many studies demonstrating children born very preterm exhibit brain white matter microstructural alterations, which have been related to neurodevelopmental difficulties. These prior studies have often been based on diffusion MRI modelling and analysis techniques, which commonly focussed on white matter microstructural properties in children born very preterm. However, there have been relatively fewer studies investigating the free-water content of the white matter, and also the microstructure and free-water content of the cortical grey matter, in children born very preterm. These biophysical properties of the brain change rapidly during fetal and neonatal brain development, and therefore such properties are likely also adversely affected by very preterm birth. In this study, we investigated the relationship of very preterm birth (<30 weeks' gestation) to both white matter and cortical grey matter microstructure and free-water content in childhood using advanced diffusion MRI analyses. A total of 130 very preterm participants and 45 full-term control participants underwent diffusion MRI at age 13 years. Diffusion tissue signal fractions derived by Single-Shell 3-Tissue Constrained Spherical Deconvolution were used to investigate brain tissue microstructural and free-water composition. The tissue microstructural and free-water composition metrics were analysed using a voxel-based analysis and cortical region-of-interest analysis approach. Very preterm 13-year-olds exhibited reduced white matter microstructural density and increased free-water content across widespread regions of the white matter compared with controls. Additionally, very preterm 13-year-olds exhibited reduced microstructural density and increased free-water content in specific temporal, frontal, occipital and cingulate cortical regions. These brain tissue composition alterations were strongly associated with cerebral white matter abnormalities identified in the neonatal period, and concurrent adverse cognitive and motor outcomes in very preterm children. The findings demonstrate brain microstructural and free-water alterations up to thirteen years from neonatal brain abnormalities in very preterm children that relate to adverse neurodevelopmental outcomes. [ABSTRACT FROM AUTHOR]

When using diffusion MRI streamlines tractograms to construct structural connectomes, ideally, each streamline should connect exactly 2 regions-of-interest (i.e. network nodes) as defined by a given brain parcellation scheme. However, the ill-posed nature of termination criteria in many tractography algorithms can cause streamlines apparently being associated with zero, one, or more than two grey matter (GM) nodes; streamlines that terminate in white matter or cerebrospinal fluid may even end up being assigned to nodes if the definitions of these nodes are not strictly constrained to genuine GM areas, resulting in a misleading connectome in non-trivial ways. Based on both in-house MRI data and state-of-the-art data provided by the Human Connectome Project, this study investigates the actual influence of streamline-to-node assignment methods, and their interactions with fibre-tracking terminations and brain parcellations, on the construction of pairwise regional connectivity and subsequent connectomic measures. Our results show that the frequency of generating successful pairwise connectivity is heavily affected by the convoluted interactions between the applied strategies for connectome construction, and that minor changes in the mechanism can cause significant variations in the within- and between-module connectivity strengths as well as in the commonly-used graph theory metrics. Our data suggest that these fundamental processes should not be overlooked in structural connectomics research, and that improved data quality is not in itself sufficient to solve the underlying problems associated with assigning streamlines to brain nodes. We demonstrate that the application of advanced fibre-tracking techniques that are designed to correct for inaccuracies of track terminations with respect to anatomical information at the fibre-tracking stage is advantageous to the subsequent connectome construction process, in which pairs of parcellation nodes can be more robustly identified from streamline terminations via a suitable assignment mechanism. • The process of assigning streamlines to brain nodes can be a significant problem. • Using over-dilated node images may result in biologically unrealistic connections. • Connectome topology is significantly affected by connection construction mechanisms. • Improved data quality cannot fix the underlying issues of connectome construction. • Advanced tractography methods can improve the construction of pairwise connections. [ABSTRACT FROM AUTHOR]

Recent neurodevelopmental research supports the contribution of pubertal stage to local and global grey and white matter remodelling. Little is known, however, about white matter microstructural alterations at pubertal onset. This study investigated differences in white matter properties between pre-pubertal and pubertal children using whole brain fixel-based analysis (FBA) of the microscopic density and macroscopic cross-section of fibre bundles. Diffusion-weighted imaging data were acquired for 74 typically developing children ( M =10.4, SD =.43 years, 31 female) at 3.0 T (60 diffusion gradient directions, b-value=2800 s/mm 2 ). Group comparisons of fibre density (FD) and fibre cross-section (FC) were made between age-matched pre-pubertal and pubertal groups, and post-hoc analyses were performed on regions of interest (ROIs) defined in the splenium, body and genu of the corpus callosum. Significant fixel-wise differences in FD were observed between the pubertal groups, where the pubertal group had significantly higher FD compared with age-matched pre-pubertal children, localised to the posterior corpus callosum. Post-hoc analyses on mean FD in the corpus callosum ROIs revealed group differences between the pubertal groups in the splenium, but not body or genu. The observed higher apparent fibre density in the splenium suggests that pubertal onset coincides with white matter differences explained by increasing axon diameter. This may be an important effect to account for over pubertal development, particularly for group studies where age-matched clinical and typical populations may be at various stages of puberty. [ABSTRACT FROM AUTHOR]

Age-related microstructural differences have been detected using diffusion tensor imaging (DTI). Although DTI is sensitive to the effects of aging, it is not specific to any underlying biological mechanism, including demyelination. Combining multiexponential T2 relaxation (MET2) and multishell diffusion MRI (dMRI) techniques may elucidate such processes. Multishell dMRI and MET2 data were acquired from 59 healthy participants aged 17–70 years. Whole-brain and regional age-associated correlations of measures related to multiple dMRI models (DTI, diffusion kurtosis imaging [DKI], neurite orientation dispersion and density imaging [NODDI]) and myelin-sensitive MET2 metrics were assessed. DTI and NODDI revealed widespread increases in isotropic diffusivity with increasing age. In frontal white matter, fractional anisotropy linearly decreased with age, paralleled by increased “neurite” dispersion and no difference in myelin water fraction. DKI measures and neurite density correlated well with myelin water fraction and intracellular and extracellular water fraction. DTI estimates remain among the most sensitive markers for age-related alterations in white matter. NODDI, DKI, and MET2 indicate that the initial decrease in frontal fractional anisotropy may be due to increased axonal dispersion rather than demyelination. [ABSTRACT FROM AUTHOR]

• NAWM converting to WMHs include fluid-like properties and increased tissue water. • GM-like signal features relate to isotropic microstructure and hindered diffusion. • Growing WMHs had similar microstructural tissue compositions to WMHs at baseline. • NAWM microstructure was related to WMH volume burden. • Higher fluid-like properties in NAWM were found in patients with greater WMH load. Using advanced diffusion MRI, we aimed to assess the microstructural properties of normal-appearing white matter (NAWM) preceding conversion to white matter hyperintensities (WMHs) using 3-tissue diffusion signal compositions in ischemic stroke. Data were obtained from the Cognition and Neocortical Volume After Stroke (CANVAS) study. Diffusion-weighted MR and high-resolution structural brain images were acquired 3- (baseline) and 12-months (follow-up) post-stroke. WMHs were automatically segmented and longitudinal assessment at 12-months was used to retrospectively delineate NAWM voxels at baseline converting to WMHs. NAWM voxels converting to WMHs were further dichotomized into either: "growing" WMHs if NAWM adhered to existing WMH voxels, or "isolated de-novo" WMHs if NAWM was unconnected to WMH voxels identified at baseline. Microstructural properties were assessed using 3-tissue diffusion signal compositions consisting of white matter-like (WM-like: T W), gray matter-like (GM-like: T G), and cerebrospinal fluid-like (CSF-like: T C) signal fractions. Our findings showed that NAWM converting to WMHs already exhibited similar changes in tissue compositions at baseline to WMHs with lower T W and increased T C (fluid-like, i.e. free-water) and T G compared to persistent NAWM. We also found that microstructural properties of persistent NAWM were related to overall WMH burden with greater free-water content in patients with high WMH load. These findings suggest that NAWM preceding conversion to WMHs are accompanied by greater fluid-like properties indicating increased tissue water content. Increased GM-like properties may indicate a more isotropic microstructure of tissue reflecting a degree of hindered diffusion in NAWM regions vulnerable to WMH development. These results support the usefulness of microstructural compositions as a sensitive marker of NAWM vulnerability to WMH pathogenesis. [ABSTRACT FROM AUTHOR]

The brain's white matter undergoes profound changes during early childhood, which are believed to underlie the rapid development of cognitive and behavioral skills during this period. Neurite density, and complexity of axonal projections, have been shown to change across the life span, though changes during early childhood are poorly characterized. Here, we utilize neurite orientation dispersion and density imaging (NODDI) to investigate maturational changes in tract-wise neurite density index (NDI) and orientation dispersion index (ODI) during early childhood. Additionally, we assess hemispheric asymmetry of tract-wise NDI and ODI values, and longitudinal changes. Two sets of diffusion weighted images with different diffusion-weighting were collected from 125 typically developing children scanned at baseline (N = 125; age range = 4.14–7.29; F/ M = 73/52), 6-month (N = 8; F/ M = 8/0), and 12-month (N = 52; F/ M = 39/13) timepoints. NODDI and template-based tractography using constrained spherical deconvolution were utilized to calculate NDI and ODI values for major white matter tracts. Mixed-effects models controlling for sex, handedness, and in-scanner head motion were utilized to assess developmental changes in tract-wise NDI and ODI. Additional mixed-effects models were used to assess interhemispheric differences in tract-wise NDI and ODI values and hemispheric asymmetries in tract-wise development. Maturational increases in NDI were seen in all major white matter tracts, though we did not observe the expected tract-wise pattern of maturational rates (e.g. fast commissural/projection and slow frontal/temporal tract change). ODI did not change significantly with age in any tract. We observed greater NDI and ODI values in the right as compared to the left hemisphere for most tracts, but no hemispheric asymmetry for rate of change with age. These findings suggest that neurite density, but not orientation dispersion, increases with age during early childhood. In relation to NDI growth trends reported in infancy and late-childhood, our results suggest that early childhood may be a transitional period for neurite density maturation wherein commissural/projection fibers are approaching maturity, maturation in long range association fibers is increasing, and changes in limbic/frontal fibers remain modest. Rightward asymmetry in NDI and ODI values, but no asymmetry in developmental changes, suggests that rightward asymmetry of neurite density and orientation dispersion is established prior to age 4. [ABSTRACT FROM AUTHOR]

White matter hyperintensities (WMHs) are frequently observed on brain scans of older individuals and are associated with cognitive impairment and vascular brain burden. Recent studies have shown that WMHs may only represent an extreme end of a diffuse pathological spectrum of white matter (WM) degeneration. The present study investigated the microstructural characteristics of WMHs using an advanced diffusion MRI modelling approach known as Single-Shell 3-Tissue Constrained Spherical Deconvolution (SS3T-CSD), which provides information on different tissue compartments within each voxel. The SS3T-CSD method may provide complementary information in the interpretation of pathological tissue through the tissue-specific microstructural compositions of WMHs. Data were obtained from stroke patients enrolled in the Cognition and Neocortical Volume After Stroke (CANVAS) study, a study examining brain volume and cognition after stroke. WMHs were segmented using an automated method, based on fluid attenuated inversion recovery (FLAIR) images. Automated tissue segmentation was used to identify normal-appearing white matter (NAWM). WMHs were classified into juxtaventricular, periventricular and deep lesions, based on their distance from the ventricles (3–10 ​mm). We aimed to compare in stroke participants the microstructural composition of the different lesion classes of WMHs and compositions of NAWM to assess the in-vivo heterogeneity of these lesions. Results showed that the 3-tissue composition significantly differed between WMHs classes and NAWM. Specifically, the 3-tissue compositions for juxtaventricular and periventricular WMHs both exhibited a relatively greater fluid-like (free water) content, which is compatible with a presence of interstitial fluid accumulation, when compared to deep WMHs. These findings provide evidence of microstructural heterogeneity of WMHs in-vivo and may support new insights for understanding the role of WMH development in vascular neurodegeneration. • SS3T-CSD reveals in-vivo microstructural heterogeneity of WMHs in stroke. • WMHs in stroke are distinguished from NAWM in terms of 3-tissue compositions. • Compositions of WMHs may reflect underlying pathological changes in-vivo. • This highlights the value of SS3T-CSD as a method for the assessment of WMHs. [ABSTRACT FROM AUTHOR]

Age-related differences in bimanual motor performance have been extensively documented, but their underlying neural mechanisms remain less clear. Studies applying diffusion MRI in the aging population have revealed evidence for age-related white matter variations in the corpus callosum (CC) which are related to bimanual motor performance. However, the diffusion tensor model used in those studies is confounded by partial volume effects in voxels with complex fiber geometries which are present in up to 90% of white matter voxels, including the bilateral projections of the CC. A recently developed whole-brain analysis framework, known as fixel-based analysis (FBA), enables comprehensive statistical analyses of white matter quantitative measures in the presence of such complex fiber geometries. To investigate the contribution of age-related fiber-specific white matter variations to age-related differences in bimanual performance, a cross-sectional lifespan sample of healthy human adults (N ​= ​95; 20–75 years of age) performed a bimanual tracking task. Furthermore, diffusion MRI data were acquired and the FBA metrics associated with fiber density, cross-section, and combined fiber density and cross-section were estimated. Whole-brain FBA revealed significant negative associations between age and fiber density, cross-section, and combined metrics of multiple white matter tracts, including the bilateral projections of the CC, indicative of white matter micro- and macrostructural degradation with age. More importantly, mediation analyses demonstrated that age-related variations in the combined (fiber density and cross-section) metric of the genu, but not splenium, of the CC contributed to the observed age-related differences in bimanual coordination performance. These findings highlight the contribution of variations in interhemispheric communication between prefrontal (non-motor) cortices to age-related differences in motor performance. • Negative age-motor performance association amplifies with higher task complexity. • Aging is negatively associated with fiber density and cross-section. • Age-related variations in anterior interhemispheric tract mediate motor behavior. [ABSTRACT FROM AUTHOR]