In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

Novel insights into axon diameter and myelin content in late childhood and adolescence.

White matter microstructural development in late childhood and adolescence is driven predominantly by increasing axon density and myelin thickness. Ex vivo studies suggest that the increase in axon diameter drives developmental increases in axon density observed with pubertal onset. In this cross-sectional study, 50 typically developing participants aged 8-18 years were scanned using an ultra-strong gradient magnetic resonance imaging scanner. Microstructural properties, including apparent axon diameter $({d}_a)$, myelin content, and g-ratio, were estimated in regions of the corpus callosum. We observed age-related differences in ${d}_a$, myelin content, and g-ratio. In early puberty, males had larger ${d}_a$ in the splenium and lower myelin content in the genu and body of the corpus callosum, compared with females. Overall, this work provides novel insights into developmental, pubertal, and cognitive correlates of individual differences in apparent axon diameter and myelin content in the developing human brain.

Surface-based tracking for short association fibre tractography.

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities.

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.

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

Long-term development of white matter fibre density and morphology up to 13 years after preterm birth: A fixel-based analysis.

BACKGROUND: It is well documented that infants born very preterm (VP) are at risk of brain injury and altered brain development in the neonatal period, however there is a lack of long-term, longitudinal studies on the effects of VP birth on white matter development over childhood. Most previous studies were based on voxel-averaged, non-fibre-specific diffusion magnetic resonance imaging (MRI) measures, such as fractional anisotropy. In contrast, the novel diffusion MRI analysis framework, fixel-based analysis (FBA), enables whole-brain analysis of microstructural and macrostructural properties of individual fibre populations at a sub-voxel level. We applied FBA to investigate the long-term implications of VP birth and associated perinatal risk factors on fibre development in childhood and adolescence. METHODS: Diffusion images were acquired for a cohort of VP (born <30 weeks' gestation) and full-term (FT, ≥37 weeks' gestation) children at two timepoints: mean (SD) 7.6 (0.2) years (n â€‹= â€‹138 VP and 32 FT children) and 13.3 (0.4) years (n â€‹= â€‹130 VP and 45 FT children). 103 VP and 21 FT children had images at both ages for longitudinal analysis. At every fixel (individual fibre population within an image voxel) across the white matter, we compared FBA metrics (fibre density (FD), cross-section (FC) and a combination of these properties (FDC)) between VP and FT groups cross-sectionally at each timepoint, and longitudinally between timepoints. We also examined associations between known perinatal risk factors and FBA metrics in the VP group. RESULTS: Compared with FT children, VP children had lower FD, FC and FDC throughout the white matter, particularly in the corpus callosum, tapetum, inferior fronto-occipital fasciculus, fornix and cingulum at ages 7 and 13 years, as well as the corticospinal tract and anterior limb of the internal capsule at age 13 years. VP children also had slower FDC development in the corpus callosum and corticospinal tract between ages 7 and 13 years compared with FT children. Within VP children, earlier gestational age at birth, lower birth weight z-score, and neonatal brain abnormalities were associated with lower FD, FC and FDC throughout the white matter at both ages. CONCLUSIONS: VP birth and concomitant perinatal risk factors are associated with fibre tract-specific alterations to axonal development in childhood and adolescence.

Impact of b-value on estimates of apparent fibre density.

Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre-specific variations in white matter microstructure. Increasingly, studies are adopting multi-shell dMRI acquisitions to improve the robustness of dMRI-based inferences. However, the impact of b-value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b-value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra-axonal signal fraction across multiple b-value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n = 78) aged 8-18 (mean = 12.4, SD = 2.9 years) using hierarchical clustering and whole brain fixel-based analyses. Multi-shell dMRI data were collected at 3.0T using ultra-strong gradients (300 mT/m), using 6 diffusion-weighted shells ranging from b = 0 to 6,000 s/mm2 . Simulations revealed that the correspondence between estimated AFD and simulated intra-axonal signal fraction was improved with high b-value shells due to increased suppression of the extra-axonal signal. These results were supported by in vivo data, as sensitivity to developmental age-relationships was improved with increasing b-value (b = 6,000 s/mm2 , median R2 = .34; b = 4,000 s/mm2 , median R2 = .29; b = 2,400 s/mm2 , median R2 = .21; b = 1,200 s/mm2 , median R2 = .17) in a tract-specific fashion. Overall, estimates of AFD and age-related microstructural development were better characterised at high diffusion-weightings due to improved correspondence with intra-axonal properties.

Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain.

Various diffusion MRI (dMRI) measures have been proposed for characterising tissue microstructure over the last 15 years. Despite the growing number of experiments using different dMRI measures in assessments of white matter, there has been limited work on: 1) examining their covariance along specific pathways; and on 2) combining these different measures to study tissue microstructure. Indeed, it quickly becomes intractable for existing analysis pipelines to process multiple measurements at each voxel and at each vertex forming a streamline, highlighting the need for new ways to visualise or analyse such high-dimensional data. In a sample of 36 typically developing children aged 8-18 years, we profiled various commonly used dMRI measures across 22 brain pathways. Using a data-reduction approach, we identified two biologically-interpretable components that capture 80% of the variance in these dMRI measures. The first derived component captures properties related to hindrance and restriction in tissue microstructure, while the second component reflects characteristics related to tissue complexity and orientational dispersion. We then demonstrate that the components generated by this approach preserve the biological relevance of the original measurements by showing age-related effects across developmentally sensitive pathways. In summary, our findings demonstrate that dMRI analyses can benefit from dimensionality reduction techniques, to help disentangling the neurobiological underpinnings of white matter organisation.

Development of white matter fibre density and morphology over childhood: A longitudinal fixel-based analysis.

PURPOSE: White matter fibre development in childhood involves dynamic changes to microstructural organisation driven by increasing axon diameter, density, and myelination. However, there is a lack of longitudinal studies that have quantified advanced diffusion metrics to identify regions of accelerated fibre maturation, particularly across the early pubertal period. We applied a novel longitudinal fixel-based analysis (FBA) framework, in order to estimate microscopic and macroscopic white matter changes over time. METHODS: Diffusion-weighted imaging (DWI) data were acquired for 59 typically developing children (27 female) aged 9-13 years  at two time-points approximately 16 months apart (time-point 1: 10.4 ±â€¯0.4 years, time-point 2: 11.7 ±â€¯0.5 years). Whole brain FBA was performed using the connectivity-based fixel enhancement method, to assess longitudinal changes in fibre microscopic density and macroscopic morphological measures, and how these changes are related to sex, pubertal stage, and pubertal progression. Follow-up analyses were performed in sub-regions of the corpus callosum to confirm the main findings using a Bayesian repeated measures approach. RESULTS: There was a statistically significant increase in fibre density over time localised to medial and posterior commissural and association fibres, including the forceps major and bilateral superior longitudinal fasciculus. Increases in fibre cross-section were substantially more widespread. The rate of fibre development was not associated with age or sex. In addition, there was no significant relationship between pubertal stage or progression and longitudinal fibre development over time. Follow-up Bayesian analyses were performed to confirm the findings, which supported the null effect of the longitudinal pubertal comparison. CONCLUSION: Using a novel longitudinal fixel-based analysis framework, we demonstrate that white matter fibre density and fibre cross-section increased within a 16-month scan rescan period in specific regions. The observed increases might reflect increasing axonal diameter or axon count. Pubertal stage or progression did not influence the rate of fibre development in the early stages of puberty. Future work should focus on quantifying these measures across a wider age range to capture the full spectrum of fibre development across the pubertal period.

Neurite density index is sensitive to age related differences in the developing brain.

PURPOSE: White matter development during childhood and adolescence is characterised by increasing white matter coherence and organisation. Commonly used scalar metrics, such as fractional anisotropy (FA), are sensitive to multiple mechanisms of white matter change and therefore unable to distinguish between mechanisms that change during development. We investigate the relationship between age and neurite density index (NDI) from neurite orientation dispersion and density imaging (NODDI), and the age-classification accuracy of NDI compared with FA, in a developmental cohort. METHOD: Diffusion-weighted imaging data from 72 children and adolescents between the ages of 4-19 was collected (M=10.42, SD=3.99, 36 male). We compared NODDI metrics against conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD] and radial diffusivity [RD]) in terms of their relationship to age. An ROC analysis was also performed to assess the ability of each metric to classify older and younger participants. RESULTS: NDI exhibited a stronger relationship with age (median R2=.60) compared with MD (median R2=.39), FA (median R2=.27), AD (median R2=.14), and RD (median R2=.35) in a high proportion of white matter tracts. When participants were divided into an older and younger group, NDI achieved the best classification (median area under the curve [AUC]=.89), followed by MD (median AUC=.81), FA (median AUC=.80), RD (median AUC=.81), and AD (median AUC=.64). CONCLUSION: Our results demonstrate the sensitivity of NDI to age-related differences in white matter microstructural organisation over development. Importantly, NDI is more sensitive to such developmental changes compared to commonly used DTI metrics. This knowledge provides justification for implementing NODDI metrics in developmental studies.

White matter alterations at pubertal onset.

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 3.0T (60 diffusion gradient directions, b-value=2800s/mm2). 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.

Short-term white matter alterations in Alzheimer's disease characterized by diffusion tensor imaging.

PURPOSE: To investigate whether there are any white matter changes in a 6-month follow-up of mild-moderate Alzheimer's patients using diffusion tensor imaging (DTI). MATERIALS AND METHODS: We recruited 18 mild-moderate Alzheimer's disease patients and they underwent magnetic resonance imaging (MRI) at recruitment and at 6-month follow-up. Diffusion MRI images were processed using DTI-ToolKit to create a population-based tensor template. This template was integrated with a voxel-wise and atlas-based analysis in FSL to determine the magnitude and location of change in diffusion metrics over the 6-month follow-up period. RESULTS: There were significant widespread changes in diffusion metrics across the entire white matter skeleton (P < 0.001), 95% confidence interval (CI) difference in fractional anisotropy: -0.007 (-0.011, -0.002), mean diffusivity: 0.040 (0.023, 0.058), axial diffusivity: 0.015 (0.008, 0.022), radial diffusivity: 0.012 (0.006, 0.019), as well as regions of interest in the splenium and superior longitudinal fasciculus. CONCLUSION: Our findings show that diffusion metrics are altered in a 6-month follow-up period of mild-moderate Alzheimer's patients, supporting the potential of DTI metrics to act as sensitive biomarkers for disease progression even over a relatively short time interval, and the potential utility to be applied to clinical trials of putative disease-modifying therapies.

Developmental brain trajectories in children with ADHD and controls: a longitudinal neuroimaging study.

BACKGROUND: The symptom profile and neuropsychological functioning of individuals with Attention Deficit/Hyperactivity Disorder (ADHD), change as they enter adolescence. It is unclear whether variation in brain structure and function parallels these changes, and also whether deviations from typical brain development trajectories are associated with differential outcomes. This paper describes the Neuroimaging of the Children's Attention Project (NICAP), a comprehensive longitudinal multimodal neuroimaging study. Primary aims are to determine how brain structure and function change with age in ADHD, and whether different trajectories of brain development are associated with variations in outcomes including diagnostic persistence, and academic, cognitive, social and mental health outcomes. METHODS/DESIGN: NICAP is a multimodal neuroimaging study in a community-based cohort of children with and without ADHD. Approximately 100 children with ADHD and 100 typically developing controls will be scanned at a mean age of 10 years (range; 9-11years) and will be re-scanned at two 18-month intervals (ages 11.5 and 13 years respectively). Assessments include a structured diagnostic interview, parent and teacher questionnaires, direct child cognitive/executive functioning assessment and magnetic resonance imaging (MRI). MRI acquisition techniques, collected at a single site, have been selected to provide optimized information concerning structural and functional brain development. DISCUSSION: This study will allow us to address the primary aims by describing the neurobiological development of ADHD and elucidating brain features associated with differential clinical/behavioral outcomes. NICAP data will also be explored to assess the impact of sex, ADHD presentation, ADHD severity, comorbidities and medication use on brain development trajectories. Establishing which brain regions are associated with differential clinical outcomes, may allow us to improve predictions about the course of ADHD.

The developing hippocampus: Microstructural evolution through childhood and adolescence.

The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.

Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography.

In response to a growing interest in refining brain connectivity assessments, this study focuses on integrating white matter fiber-specific microstructural properties into structural connectomes. Spanning ages 8-19 years in a developmental sample, it explores age-related patterns of microstructure-informed network properties at both local and global scales. First, the diffusion-weighted signal fraction associated with each tractography-reconstructed streamline was constructed. Subsequently, the convex optimization modeling for microstructure-informed tractography (COMMIT) approach was employed to generate microstructure-informed connectomes from diffusion MRI data. To complete the investigation, network characteristics within eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks) were evaluated. The findings underscore a consistent increase in global efficiency across child and adolescent development within the visual, somatomotor, and default mode networks (p < 0.005). Additionally, mean strength exhibits an upward trend in the somatomotor and visual networks (p < 0.001). Notably, nodes within the dorsal and ventral visual pathways manifest substantial age-dependent changes in local efficiency, aligning with existing evidence of extended maturation in these pathways. The outcomes strongly support the notion of a prolonged developmental trajectory for visual association cortices. This study contributes valuable insights into the nuanced dynamics of microstructure-informed brain connectivity throughout different developmental stages.

There is a growing interest in incorporating biologically relevant white matter properties into the analysis of brain networks to obtain a more quantitative assessment of brain connectivity. In a developmental sample aged 8­19 years, we studied age-related patterns of local and global network properties. We generated microstructure-informed connectomes using diffusion MRI data, and computed network characteristics in eight functionally defined networks (visual, somatomotor, dorsal attention, ventral attention, limbic, fronto-parietal, default mode, and subcortical networks). The findings reveal that throughout child and adolescent development, global efficiency increases in the visual, somatomotor, and default mode networks, and mean strength increases in the somatomotor and visual networks. Nodes belonging to the dorsal and ventral visual pathways demonstrate the largest age-dependence in local efficiency, supporting previous evidence of protracted maturation of dorsal and ventral visual pathways. The results provide compelling evidence that there is a prolonged development of visual association cortices.

MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression.

Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss with age. However, the underlying cellular mechanisms remain elusive with conventional neuroimaging. Recent advances in MRI hardware and new biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. This study used ultra-strong gradient MRI to obtain high-resolution, in vivo estimates of cortical neurite and soma microstructure in sample of typically developing children and adolescents. Cortical neurite signal fraction, attributed to neuronal and glial processes, increased with age (mean R2 fneurite=.53, p<3.3e-11, 11.91% increase over age), while apparent soma radius decreased (mean R2 Rsoma=.48, p<4.4e-10, 1% decrease over age) across domain-specific networks. To complement these findings, developmental patterns of cortical gene expression in two independent post-mortem databases were analysed. This revealed increased expression of genes expressed in oligodendrocytes, and excitatory neurons, alongside a relative decrease in expression of genes expressed in astrocyte, microglia and endothelial cell-types. Age-related genes were significantly enriched in cortical oligodendrocytes, oligodendrocyte progenitors and Layer 5-6 neurons (pFDR<.001) and prominently expressed in adolescence and young adulthood. The spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes suggest that ongoing cortical myelination processes contribute to adolescent cortical development. These findings highlight the role of intra-cortical myelination in cortical maturation during adolescence and into adulthood.

Advanced tractography-guided laser ablation of a perirolandic long-term epilepsy-associated tumor: illustrative case.

BACKGROUND: Microsurgical resection of drug-resistant epilepsy-associated perirolandic lesions can lead to postoperative motor impairment. Magnetic resonance imaging (MRI)-guided laser interstitial thermal therapy (MRgLITT) has emerged as a less invasive alternative, offering reduced surgical risks and improved neurological outcomes. Electrophysiological tools routinely used for motor mapping in resective microsurgery are incompatible with intraoperative MRI. The utilization of advanced neuroimaging adjuncts for eloquent brain mapping during MRgLITT is imperative. The authors present the case of a 17-year-old athlete who underwent MRgLITT for a perirolandic long-term epilepsy-associated tumor (LEAT). They performed probabilistic multi-tissue constrained spherical deconvolution (MT-CSD) tractography to delineate the corticospinal tract (CST) for presurgical planning and intraoperative image guidance. The CST tractography was integrated into neuronavigation and MRgLITT workstation software to guide the ablation while monitoring the CST throughout the procedure. OBSERVATIONS: The integration of CST tractography into neuronavigation workstation planning and laser ablation workstation thermoablation is feasible and practical, facilitating complete ablation of a deep-seated perirolandic LEAT while preserving motor function. LESSONS: Probabilistic MT-CSD tractography enhanced MRgLITT planning as well as intraprocedural CST visualization and preservation, leading to a favorable functional outcome. The limitations of tractography and the predictability of thermal output distribution compared to the gold standard of microsurgical resection merit further discussion. https://thejns.org/doi/10.3171/CASE24139.

White matter fiber morphology in persisting postconcussive symptoms and posttraumatic headache after pediatric concussion: a fixel-based analysis.

OBJECTIVE: Posttraumatic headache (PTH) represents the most common acute and persistent postconcussive symptom (PCS) in children after concussion, yet there remains a lack of valid and objective biomarkers to facilitate risk stratification and early intervention in this patient population. Fixel-based analysis of diffusion-weighted imaging, which overcomes constraints of traditional diffusion tensor imaging analyses, can improve the sensitivity and specificity of detecting white matter changes postconcussion. The aim of this study was to investigate whole-brain and tract-based differences in white matter morphology, including fiber density (FD) and fiber bundle cross-section (FC) area in children with PCSs and PTH at 2 weeks after concussion. METHODS: This prospective longitudinal study recruited children aged 5-18 years who presented to the emergency department of a tertiary pediatric hospital with a concussion sustained within the previous 48 hours. Participants underwent diffusion-weighted MRI at 2 weeks postinjury. Whole-brain white matter statistical analysis was performed at the level of each individual fiber population within an image voxel (fixel) to compute FD, FC, and a combined metric (FD and bundle cross-section [FDC]) using connectivity-based fixel enhancement. Tract-based Bayesian analysis was performed to examine FD in 23 major white matter tracts. RESULTS: Comparisons of 1) recovered (n = 27) and symptomatic (n = 16) children, and those with 2) PTH (n = 13) and non-PTH (n = 30; overall mean age 12.99 ± 2.70 years, 74% male) found no fiber-specific white matter microstructural differences in FD, FC, or FDC at 2 weeks postconcussion, when adjusting for age and sex (family-wise error rate corrected p value > 0.05). Tract-based Bayesian analysis showed evidence of no effect of PTH on FD in 10 major white matter tracts, and evidence of no effect of recovery group on FD in 3 white matter tracts (Bayes factor < 1/3). CONCLUSIONS: Using whole-brain fixel-wise and tract-based analyses, these findings indicate that fiber-specific properties of white matter microstructure are not different between children with persisting PCSs compared with recovered children 2 weeks after concussion. These data extend the limited research on white matter fiber-specific morphology while overcoming limitations inherent to traditional diffusion models. Further validation of our findings with a large-scale cohort is warranted.

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders.

Structural brain MRI has proven invaluable in understanding movement disorder pathophysiology. However, most work has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong spherical tensor encoding diffusion-weighted MRI, a persistent MRI signal was seen in healthy cerebellar grey matter even at high diffusion-weightings (b ​≥ 10,000 s/mm2). Quantifying the proportion of this signal (denoted fs), previously ascertained to originate from inside small spherical spaces, provides a potential proxy for cell body density. In this work, this approach was applied for the first time to a clinical cohort, including patients with diagnosed movement disorders in which the cerebellum has been implicated in symptom pathophysiology. Five control participants (control group 1, median age 24.5 years (20-39 years), imaged at two timepoints, demonstrated consistency in measurement of all three measures - MD (Mean Diffusivity) fs, and Ds (dot diffusivity)- with intraclass correlation coefficients (ICC) of 0.98, 0.86 and 0.76, respectively. Comparison with an older control group (control group 2 (n = 5), median age 51 years (43-58 years)) found no significant differences, neither with morphometric nor microstructural (MD (p = 0.36), fs (p = 0.17) and Ds (p = 0.22)) measures. The movement disorder cohort (Parkinson's Disease, n = 5, dystonia, n = 5. Spinocerebellar Ataxia 6, n = 5) when compared to the age-matched control cohort (Control Group 2) identified significantly lower MD (p < 0.0001 and p < 0.0001) and higher fs values (p < 0.0001 and p < 0.0001) in SCA6 and dystonia cohorts respectively. Lobar division of the cerebellum found these same differences in the superior and inferior posterior lobes, while no differences were seen in either the anterior lobes or with Ds measurements. In contrast to more conventional measures from diffusion tensor imaging, this framework provides enhanced specificity to differences in restricted spherical spaces in grey matter (including small cells) by eliminating signals from cerebrospinal fluid and axons. In the context of human and animal histopathology studies, these findings potentially implicate the cerebellar Purkinje and granule cells as contributors to the observed signal differences, with both cell types having been implicated in several neurological disorders through both postmortem and animal model studies. This novel microstructural imaging approach shows promise for improving movement disorder diagnosis, prognosis, and treatment.

Childhood conduct problems are associated with reduced white matter fibre density and morphology.

Childhood conduct problems are an important public health issue as these children are at-risk of adverse outcomes. Studies using diffusion Magnetic Resonance Imaging (dMRI) have found that conduct problems in adults are characterised by abnormal white-matter microstructure within a range of white matter pathways underpinning socio-emotional processing, while evidence within children and adolescents has been less conclusive based on non-specific diffusion tensor imaging metrics. Fixel-based analysis (FBA) provides measures of fibre density and morphology that are more sensitive to developmental changes in white matter microstructure. The current study used FBA to investigate whether childhood conduct problems were related both cross-sectionally and longitudinally to microstructural alterations within the fornix, inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and the uncinate fasciculus (UF). dMRI data was obtained for 130 children across two time-points in a community sample with high levels of externalising difficulties (age: time-point 1 = 9.47 - 11.86 years, time-point 2 = 10.67 -13.45 years). Conduct problems were indexed at each time-point using the Conduct Problems subscale of the parent-informant Strengths and Difficulties Questionnaire (SDQ). Conduct problems were related to lower fibre density in the fornix at both time-points, and in the ILF at time-point 2. We also observed lower fibre cross-section in the UF at time-point 1. The change in conduct problems did not predict longitudinal changes in white-matter microstructure across time-points. The current study suggests that childhood conduct problems are related to reduced fibre-specific microstructure within white matter fibre pathways implicated in socio-emotional functioning.