Connectivity-based Fixel Enhancement Research Articles

Cerebral white matter damage in patients with end stage kidney disease associates with cognitive impairment

Abstract Background and hypothesis Damages in brain white matter often occurs in individuals with chronic kidney disease, which might be related to their cognitive decline. This study aims to investigate tract specific white matter damage in patients with end stage renal disease by using fixel based analysis. Methods Images of 31 end stage renal disease patients and 16 normal controls (aged: 61.1 ± 10.4 years; 11 men) were acquired from a 1.5 T MR scanner. The patients were subsequently divided into with normal cognition (N = 17, aged: 66.9 ± 7.2 years; 10 men) and cognitive impairment (N = 14, aged: 72.4 ± 9.4 years; 7 men). Cognitive assessment, neurologic, hematologic and biochemical samples were collected. Fixel-based analysis was used to examine the tract-specific damage within white matter. Differences between groups were evaluated through connectivity-based fixel enhancement and non-parametric permutation testing. Correlation with biomarkers was conducted through general linear model. Significance was determined with familywise error-corrected p-value < 0.05. Results Reduced fixel-based metrics were observed in specific tract located the cerebral peduncle, internal capsule, corpus callosum, fornix, and superior corona radiata in patients when compared to normal controls, indicating a reduction in fiber content. The fibers crossing the corpus callosum and the fornix/stria terminalis are particularly vulnerable sites, which can be associated with the decrease in both Mini-Mental State Examination (R2 ranged between 0.420 and 0.556) and Montreal Cognitive Assessment (R2 ranged between 0.425 and 0.509), as well as the plasma concentration of calcium (R2 ranged between 0.207 and 0.322). The plasma concentration of indoxyl sulfate was associated with the descending tracts from right posterior limb of internal capsule to cerebral peduncle (R2 ranged between 0.262 and 0.335). Conclusions Tract specific white matter damage can be noticed in the patients with end stage renal disease, and can be associated with their cognitive decline.

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

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. 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. 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). 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.

Structural connectivity at term equivalent age and language in preterm children at 2 years corrected.

We previously reported interhemispheric structural hyperconnectivity bypassing the corpus callosum in children born extremely preterm (<28 weeks) versus term children. This increased connectivity was positively associated with language performance at 4-6 years of age in our prior work. In the present study, we aim to investigate whether this extracallosal connectivity develops in extremely preterm infants at term equivalent age by leveraging a prospective cohort study of 350 very and extremely preterm infants followed longitudinally in the Cincinnati Infant Neurodevelopment Early Prediction Study. For this secondary analysis, we included only children born extremely preterm and without significant brain injury (n = 95). We use higher-order diffusion modelling to assess the degree to which extracallosal pathways are present in extremely preterm infants and predictive of later language scores at 22-26 months corrected age. We compare results obtained from two higher-order diffusion models: generalized q-sampling imaging and constrained spherical deconvolution. Advanced MRI was obtained at term equivalent age (39-44 weeks post-menstrual age). For structural connectometry analysis, we assessed the level of correlation between white matter connectivity at the whole-brain level at term equivalent age and language scores at 2 years corrected age, controlling for post-menstrual age, sex, brain abnormality score and social risk. For our constrained spherical deconvolution analyses, we performed connectivity-based fixel enhancement, using probabilistic tractography to inform statistical testing of the hypothesis that fibre metrics at term equivalent age relate to language scores at 2 years corrected age after adjusting for covariates. Ninety-five infants were extremely preterm with no significant brain injury. Of these, 53 had complete neurodevelopmental and imaging data sets that passed quality control. In the connectometry analyses adjusted for covariates and multiple comparisons (P < 0.05), the following tracks were inversely correlated with language: bilateral cerebellar white matter and middle cerebellar peduncles, bilateral corticospinal tracks, posterior commissure and the posterior inferior fronto-occipital fasciculus. No tracks from the constrained spherical deconvolution/connectivity-based fixel enhancement analyses remained significant after correction for multiple comparisons. Our findings provide critical information about the ontogeny of structural brain networks supporting language in extremely preterm children. Greater connectivity in more posterior tracks that include the cerebellum and connections to the regions of the temporal lobes at term equivalent age appears to be disadvantageous for language development.

Fixel based analysis of white matter alterations in Mild cognitive impairment and Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is the leading cause of dementia, and is associated with altered white matter (WM) microstructures in the brain (Clerx et al., 2012; Jack Jr et al., 2013). Diffusion weighted imaging (DWI) is a non‐invasive method of examining white matter alterations in AD and Mild cognitive Impairment (MCI). DWI based Fixel‐based analysis (FBA) is a novel method that enables the investigation of fibre specific WM alterations at the microscopic level. In this study, we investigated fibre tract‐specific changes in the whole‐brain WM, in individuals with MCI and AD using DWI based FBA.MethodN = 102 participants (&gt;70 years) from the University of California Davis Alzheimer’s Disease Research Center were included in this study, including 34 individuals with AD, 34 with MCI, and 34 control subjects. DWI data were obtained on a 3T Siemens TimTrio scanner (resolution = 2mm, 60 directions, at b = 1000s/mm2) and pre‐processed using MRtrix3 (Tournier et al., 2019). Single‐Shell 3‐tissue CSD (SS3T‐CSD) was performed to obtain Fibre Orientation Distributions (FODs) related to WM as well as for gray matter and cerebrospinal fluid compartments in all voxels, using MRtrix3Tissue. A study‐specific unbiased FOD template was generated and used for FBA processing. Whole‐brain FBA maps, including fibre density (FD), fibre cross‐section (FC), and combination of fibre density and cross‐section (FDC), were generated. Statistical analyses were performed using connectivity based fixel enhancement at each fixel using general linear model (Raffelt et al., 2015)(Figure1).ResultThe whole‐brain FBA showed significant reduction in FD in individuals with AD compared to MCI, in regions including splenium of corpus callosum, fornix, and the left uncinate fasciculus (Figure2). Furthermore, AD individuals showed significant reduction in FD in the left uncinate fasciculus compared to controls. We observed subtle reduction in FD and FDC metrics (although not statistically significant after FWE corrections) in regions including corpus callosum, forceps majors, and uncinate fasciculus in AD(Figure3). We did not observe significant difference in FC between groups.ConclusionFBA‐derived measures demonstrated sensitivity in detecting microstructural white matter alterations in AD. These findings highlight the utility of FBA as a promising tool for providing valuable insights into pathophysiologic changes in AD.

Inter-individual performance differences in the stop-signal task are associated with fibre-specific microstructure of the fronto-basal-ganglia circuit in healthy children

Previous Diffusion Tensor Imaging (DTI) studies in children suggest that developmental improvements in inhibitory control is largely mediated by the degree of white matter organisation within a right-lateralised network of fronto-basal-ganglia regions. Recent advances in diffusion imaging analysis now permit greater biological specificity, both in identifying specific fibre populations within a voxel, as well as in the underlying microstructural properties of that white matter. In the present work, employing a novel fixel-based analysis (FBA) framework, we aimed to comprehensively investigate microstructure within the fronto-basal-ganglia circuit in childhood, and its contribution to inhibition performance. Diffusion MRI data were obtained from 43 healthy children and adolescents aged 9–11 years (10.42 ± .41 years, 18 females). Response inhibition for each participant was assessed using the Stop-signal Task (SST) and quantified as a Stop–Signal Reaction Time (SSRT). All steps relevant to FBA were implemented in MRtrix3Tissue, a fork of the MRtrix3 software library. The fronto-basal-ganglia circuit were delineated using probabilistic tractography to identify the tracts connecting the subthalamic nucleus, pre-supplementary motor area and the inferior frontal gyrus. Connectivity-based fixel enhancement (CFE) was then used to assess the association between fibre density (FD) and fibre cross-section (FC) with inhibitory ability. Significant negative associations were identified for FD in both the right and left fronto-basal-ganglia circuit whereby greater FD was associated with better inhibition performance (e.g., reduced SSRTs). This effect was specifically localised to clusters of fixels within white matter proximal to the right subthalamic nucleus. We did not report any meaningful associations between SSRT and FC. Whilst findings are broadly consistent with prior DTI evidence, current results suggest that SSRT is predominantly facilitated by subcortical microstructure of the connections projecting from the subthalamic nucleus to the cortical regions of the network. Our findings extend current understanding of the role of white matter in childhood response inhibition.

Manual dexterity in late childhood is associated with maturation of the corticospinal tract

PurposeDespite the important role of manual dexterity in child development, the neurobiological mechanisms associated with manual dexterity in childhood remain unclear. We leveraged fixel-based analysis (FBA) to examine the longitudinal association between manual dexterity and the development of white matter structural properties in the corticospinal tract (CST). MethodsHigh angular diffusion weighted imaging (HARDI) data were acquired for 44 right-handed typically developing children (22 female) aged 9-13 across two timepoints (timepoint 1: mean age 10.5 years ± 0.5 years, timepoint 2: 11.8 ± 0.5 years). Manual dexterity was assessed using the Grooved Pegboard Test, a widely used measure of manual dexterity. FBA-derived measures of fiber density and morphology were generated for the CST at each timepoint. Connectivity-based fixel enhancement and mixed linear modelling were used to examine the longitudinal association between manual dexterity and white matter structural properties of the CST. ResultsLongitudinal mixed effects models showed that greater manual dexterity of the dominant hand was associated with increased fiber cross-section in the contralateral CST. Analyses further demonstrated that the rate of improvement in manual dexterity was associated with the rate of increase in fiber cross-section in the contralateral CST between the two timepoints. ConclusionOur longitudinal data suggest that the development of manual dexterity in late childhood is associated with maturation of the CST. These findings significantly enhance our understanding of the neurobiological systems that subserve fine motor development and provide an important step toward mapping normative trajectories of fine motor function against microstructural and morphological development in childhood.

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

PurposeWhite 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. MethodsDiffusion-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 ± 0.4 years, time-point 2: 11.7 ± 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. ResultsThere 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. ConclusionUsing 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.

Low Rank plus Sparse decomposition of ODFs for improved detection of group-level differences and variable correlations in white matter

A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF).Recent advances in MRI acquisition make it possible to use high quality diffusion weighted protocols (multi-shell, large number of gradient directions) for routine in vivo study of white matter architecture. The dimensionality of these data sets is however often reduced to simplify statistical analysis. While these approaches may detect large group differences, they do not fully capitalize on all acquired image volumes. Incorporation of all available diffusion information in the analysis however risks biasing the outcome by outliers.Here we propose a statistical analysis method operating on the ODF, either the diffusion ODF or fiber ODF. To avoid outlier bias and reliably detect voxelwise group differences and correlations with demographic or behavioral variables, we apply the Low-Rank plus Sparse (L+S) matrix decomposition on the voxelwise ODFs which separates the sparse individual variability in the sparse matrix S whilst recovering the essential ODF features in the low-rank matrix L.We demonstrate the performance of this ODF L+S approach by replicating the established negative association between global white matter integrity and physical obesity in the Human Connectome dataset. The volume of positive findings p<0.01,227cm3, agrees with and expands on the volume found by TBSS (17 cm3), Connectivity based fixel enhancement (15 cm3) and Connectometry (212 cm3). In the same dataset we further localize the correlations of brain structure with neurocognitive measures such as fluid intelligence and episodic memory.The presented ODF L+S approach will aid in the full utilization of all acquired diffusion weightings leading to the detection of smaller group differences in clinically relevant settings as well as in neuroscience applications.

Changes in Apparent Fiber Density and Track-Weighted Imaging Metrics in White Matter following Experimental Traumatic Brain Injury.

Traumatic brain injury (TBI) has been assessed with diffusion tensor imaging (DTI), a commonly used magnetic resonance imaging (MRI) marker for white matter integrity. However, given that the DTI model only fits a single fiber orientation, results can become confounded in regions of "crossing" white matter fibers. In contrast, constrained spherical deconvolution estimates a fiber orientation distribution directly from high angular resolution diffusion-weighted images. Consequently, constrained spherical deconvolution-based measures, such as apparent fiber density (AFD) and track-weighted imaging (TWI) metrics (including tract density imaging, average pathlength mapping, and mean curvature), may be more sensitive than DTI metrics to white matter injury post-TBI. As such, this study administered the lateral fluid percussion injury (FPI) model of TBI, assessed for changes in AFD and TWI metrics, and compared these results to the DTI metrics, fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). Rats received either an FPI (n = 11) or sham injury (n = 9) and after a recovery period of 12 weeks underwent MRI. AFD was calculated as described previously and statistical testing was performed using connectivity-based fixel enhancement. TWI and DTI metrics were assessed using voxel-wise nonparametric permutation testing. We found that rats given an FPI had significantly reduced AFD, tract density, average pathlength, and mean curvature when compared to sham-injured rats and significant changes in DTI metrics, including reduced FA and increased MD, RD, and AD. However, the latter DTI metrics identified fewer voxels affected by TBI. Additionally, analysis of AFD with connectivity-based fixel enhancement was the only method that identified damage within the corticospinal tract of rats given an FPI. These results support the use of constrained spherical deconvolution, in conjunction with DTI metrics, to better assess disease progression and treatment post-TBI.

Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres

In brain regions containing crossing fibre bundles, voxel-average diffusion MRI measures such as fractional anisotropy (FA) are difficult to interpret, and lack within-voxel single fibre population specificity. Recent work has focused on the development of more interpretable quantitative measures that can be associated with a specific fibre population within a voxel containing crossing fibres (herein we use fixel to refer to a specific fibre population within a single voxel). Unfortunately, traditional 3D methods for smoothing and cluster-based statistical inference cannot be used for voxel-based analysis of these measures, since the local neighbourhood for smoothing and cluster formation can be ambiguous when adjacent voxels may have different numbers of fixels, or ill-defined when they belong to different tracts. Here we introduce a novel statistical method to perform whole-brain fixel-based analysis called connectivity-based fixel enhancement (CFE). CFE uses probabilistic tractography to identify structurally connected fixels that are likely to share underlying anatomy and pathology. Probabilistic connectivity information is then used for tract-specific smoothing (prior to the statistical analysis) and enhancement of the statistical map (using a threshold-free cluster enhancement-like approach). To investigate the characteristics of the CFE method, we assessed sensitivity and specificity using a large number of combinations of CFE enhancement parameters and smoothing extents, using simulated pathology generated with a range of test-statistic signal-to-noise ratios in five different white matter regions (chosen to cover a broad range of fibre bundle features). The results suggest that CFE input parameters are relatively insensitive to the characteristics of the simulated pathology. We therefore recommend a single set of CFE parameters that should give near optimal results in future studies where the group effect is unknown. We then demonstrate the proposed method by comparing apparent fibre density between motor neurone disease (MND) patients with control subjects. The MND results illustrate the benefit of fixel-specific statistical inference in white matter regions that contain crossing fibres.