Biology subjects

Dhollander, T.

Publications and source records attributed to Dhollander, T..

12 recordsLinked to original sources

bioRxiv2021

Timing of selective basal ganglia white matter loss in Huntington's disease

ObjectivesTo investigate the timeframe prior to symptom onset when cortico-basal ganglia white matter (WM) loss begins in premanifest Huntingtons disease (preHD), and which striatal and thalamic sub-region WM tracts are most vulnerable. MethodsWe performed fixel-based analysis, which allows resolution of crossing WM fibres at the voxel level, on diffusion tractography derived WM tracts of striatal and thalamic sub-regions in two independent cohorts; TrackON-HD, which included 72 preHD (approx. 11 years before disease onset) and 85 controls imaged at three time points over two years; and the HD young adult study (HD-YAS), which included 54 preHD (approx. 25 years before disease onset) and 53 controls, imaged at one time point. Group differences in fibre density and cross section (FDC) were investigated. ResultsWe found no significant group differences in cortico-basal ganglia sub-region FDC in preHD gene carriers 25 years before onset. In gene carriers 11 years before onset, there were reductions in striatal (limbic and caudal motor) and thalamic (premotor, motor and sensory) FDC at baseline, with no significant change over 2 years. Caudal motor-striatal, pre-motor-thalamic, and primary motor-thalamic FDC at baseline, showed significant correlations with the Unified Huntingtons disease rating scale (UHDRS) total motor score (TMS). Limbic cortico-striatal FDC and apathy were also significantly correlated. ConclusionsOur findings suggest that the initiation of disease modifying therapies 25 years before onset could protect these important brain networks from undergoing neurodegeneration and highlight selectively vulnerable sub-regions of the striatum and thalamus that may be important targets for future therapies.

neuroscience↗

bioRxiv2020

QSIPrep: An integrative platform for preprocessing and reconstructing diffusion MRI

Diffusion-weighted magnetic resonance imaging (dMRI) has become the primary method for non-invasively studying the organization of white matter in the human brain. While many dMRI acquisition sequences have been developed, they all sample q-space in order to characterize water diffusion. Numerous software platforms have been developed for processing dMRI data, but most work on only a subset of sampling schemes or implement only parts of the processing workflow. Reproducible research and comparisons across dMRI methods are hindered by incompatible software, diverse file formats, and inconsistent naming conventions. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing upon a diverse set of software suites to capitalize upon their complementary strengths, QSIPrep automatically applies best practices for dMRI preprocessing, including denoising, distortion correction, head motion correction, coregistration, and spatial normalization. Throughout, QSIPrep provides both visual and quantitative measures of data quality as well as "glass-box" methods reporting. Taken together, these features facilitate easy implementation of best practices for processing of diffusion images while simultaneously ensuring reproducibility.

bioinformatics↗

bioRxiv2020

A Connectome-Based Approach to Assess Motor Outcome after Neonatal Arterial Ischemic Stroke

Objectivestudies 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 Methods30 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. Resultssignificant 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. Interpretationusing 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.

bioengineering↗

bioRxiv2020

Fibre-specific laterality of white matter in left and right language dominant people

Despite the typical symmetrical appearance of the human brain, several functional and structural asymmetries have been reported. Language is the most commonly described lateralised cognitive function, relying relatively more on the left hemisphere in over 90% of the population. This is in line with white matter studies which have revealed leftwards lateralisation of the arcuate fasciculus, a white matter tract that connects important language-related regions. Most research to date examining the structure-function relationship of language lateralisation only included people showing a left language hemisphere dominance. As such, the reported correlations do not allow for inferences of relationships between the directions of functional and structural lateralisation of language. In this work, we applied a state-of-the-art "fixel-based" analysis approach, which allows to statistically analyse white matter micro- and macrostructure on a fibre-specific level. To study lateralisation using this framework, we defined a bespoke fibre-specific laterality index which allowed us to examine whole-brain white matter asymmetries in samples of participants with left and right language dominance (LLD and RLD respectively). Both groups showed similar extensive and intricate patterns of significant white matter lateralisation. Few group differences were found between both groups, with a similar leftwards lateralisation of the arcuate fasciculus, regardless of functional language lateralisation of the participants. A significant group difference of lateralisation was detected in the forceps minor, with a leftwards lateralisation in LLD and rightwards lateralisation for the RLD group. In conclusion, we showed that fixel-based analysis of fibre-specific lateralisation indices is an effective approach to study white matter asymmetries. Our results suggest that the lateralisation of language functioning and the arcuate fasciculus are driven by independent biases. The exact relationship between forceps minor asymmetry and language dominance could be an interesting subject of future studies.

neuroscience↗

bioRxiv2020

Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia

Fronto-temporal dementia (FTD) is a neurodegenerative disease characterized by focal atrophy of the gray matter (GM), especially in the frontal and temporal regions. Recent studies suggest a framework where white matter (WM) atrophy plays an important role in FTD pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of GM atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Here, by leveraging the sensitivity of advanced diffusion MRI modelling and metrics to precise white matter microstructural properties, we aim to clarify the relative contributions of WM fibers and GM atrophy to the cognitive symptoms typically found in FTD. A total of 155 participant from the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI) were analysed, including 68 normal elderly controls (CN), 28 behavioral variants (BV), 26 sematic variants (SV) and 30 progressive non fluent aphasia variants (PNFA) of FTD. Diffusion MRI analysis was performed using two complementary techniques: whole brain fixel-based analysis (FBA) and structural connectivity based on probabilistic tractography. Whole brain GM atrophy was assessed using voxel-based morphometry (VBM). Using a common factor analysis to extract a semantic and an executive factor, we aim to test the relative contribution of WM and GM of specific tracts in predicting cognition. We found that semantic symptoms were mainly dependent on short-range WM fiber disruption, while damage to long-range WM fibers was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. Our results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep white matter disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.

neuroscience↗

bioRxiv2019

Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood

BackgroundThe brains 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. MethodsTwo sets of diffusion weighted images (DWI) 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. Paired t-tests were used to assess interhemispheric differences in tract-wise NDI and ODI values and longitudinal changes in cross-sectional and 12-month longitudinal analyses, respectively. ResultsMaturational 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 higher cross-sectional NDI and ODI values in the right as compared to the left hemisphere for most tracts, but no hemispheric asymmetry for longitudinal changes. ConclusionsThese 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 not longitudinal changes, suggests that rightward asymmetry of neurite density and orientation dispersion is established prior to age 4.

neuroscience↗

bioRxiv2019

Test-retest reliability and long-term stability of 3-tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

PurposeSeveral recent studies have utilized a 3-tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion-weighted MRI data. The three tissue compartments, comprising white matter-, grey 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 has not yet been evaluated.\n\nMethodsThis study examined estimates of whole brain microstructure for the three tissue compartments, in three separate test-retest cohorts. Each cohort has different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to three months in the longest interval. Each cohort was also collected with different acquisition parameters.\n\nResultsThe 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 grey 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.\n\nConclusionThe 3-tissue CSD 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 utilizing 3-tissue CSD techniques to track changes in microstructure across a variety of brain pathologies.

neuroscience↗

bioRxiv2019

Modeling brain dynamics after tumor resection using The Virtual Brain

Brain tumor patients scheduled for tumor resection often face significant uncertainty, as the outcome of neurosurgery is difficult to predict at the individual patient level. Recently, computational modeling of brain activity using so-called brain network models has been introduced as a promising tool for this purpose. However, brain network models first have to be validated, before they can be used to predict brain dynamics. In prior work, we optimized individual brain network model parameters to maximize the fit with empirical brain activity. In this study, we extend this line of research by examining the stability of fitted parameters before and after tumor resection, and compare it with baseline parameter variability using data from healthy control subjects. Based on these findings, we perform the first \"virtual neurosurgery\" analyses to evaluate the potential of brain network modeling in predicting brain dynamics after tumor resection.\n\nWe find that brain network model parameters are relatively stable over time in brain tumor patients who underwent tumor resection, compared with baseline variability in healthy control subjects. In addition, we identify several robust associations between individually optimized model parameters, structural network topology and cognitive performance from pre-to post-operative assessment. Concerning the virtual neurosurgery analyses, we obtain promising results in some patients, whereas the predictive accuracy of the currently applied model is poor in others. These findings reveal interesting avenues for future research, as well as important limitations that warrant further investigation.

neuroscience↗

bioRxiv2019

Early childhood development of white matter fiber density and morphology

Early childhood is an important period for cognitive and brain development, though white matter changes specific to this period remain understudied. Here we utilize a novel analytic approach to quantify and track developmental changes in white matter micro- and macro-structure, calculated from individually oriented fiber-bundle populations, termed \"fixels\". Fixel-based analysis and mixed-effects models were used to assess tract-wise changes in fiber density and bundle morphology in 73 girls scanned at baseline (ages 4.09-7.02, mean=5.47, SD=0.81), 6-month (N=7), and one-year follow-up (N=42). For comparison, we also assessed changes in commonly utilized diffusion tensor metrics: fractional anisotropy (FA), and mean, radial and axial diffusivity (MD, RD, AD). Maturational increases in fixel-metrics were seen in most major white matter tracts, with the most rapid increases in the corticospinal tract and slowest or non-significant increases in the genu of the corpus callosum and uncinate fasciculi. As expected, we observed developmental increases in FA and decreases in MD, RD and AD, though percentage changes were smaller relative to fixel-metrics. The majority of tracts showed more substantial morphological than microstructural changes. These findings highlight early childhood as a period of dynamic white matter maturation, characterized by large increases in macroscopic fiber bundle size, mild changes in axonal density, and parallel, albeit less substantial, changes in diffusion tensor metrics.

neuroscience↗

bioRxiv2019

Evaluating the performance of 3-tissue constrained spherical deconvolution pipelines for within-tumor tractography

The use of diffusion MRI (dMRI) for assisting in the planning of neurosurgery has become increasingly common practice, allowing to non-invasively map white matter pathways via tractography techniques. Limitations of earlier pipelines based on the diffusion tensor imaging (DTI) model have since been revealed and improvements were made possible by constrained spherical deconvolution (CSD) pipelines. CSD allows to resolve a full white matter (WM) fiber orientation distribution (FOD), which can describe so-called \"crossing fibers\": complex local geometries of WM tracts, which DTI fails to model. This was found to have a profound impact on tractography results, with substantial implications for presurgical decision making and planning. More recently, CSD itself has been extended to allow for modeling of other tissue compartments in addition to the WM FOD, typically resulting in a 3-tissue CSD model. It seems likely this may improve the capability to resolve WM FODs in the presence of infiltrating tumor tissue. In this work, we evaluated the performance of 3-tissue CSD pipelines, with a focus on within-tumor tractography. We found that a technique named single-shell 3-tissue CSD (SS3T-CSD) successfully allowed tractography within infiltrating gliomas, without increasing existing single-shell dMRI acquisition requirements.

neuroscience↗

bioRxiv2019

In vivo microstructural heterogeneity of white matter lesions in Alzheimer’s disease using tissue compositional analysis of diffusion MRI data

White matter hyperintensities (WMH) are commonly observed in elderly individuals, and are typically more prevalent in Alzheimers disease subjects than in healthy subjects. These lesions can be identified on fluid attenuated inversion recovery (FLAIR) MRI, on which they are hyperintense compared to their surroundings. These MRI-visible lesions appear homogeneously hyperintense despite known heterogeneity in their pathological underpinnings, and are commonly regarded as surrogate markers of small vessel disease in in vivo studies. Consequently, the extent to which these lesions contribute to Alzheimers disease remains unclear, likely due to the somewhat limited way in which these lesions are assessed in vivo. Diffusion MRI is sensitive to white matter microstructure, and might thus be used to investigate microstructural changes within WMH. In this study, we applied a method called single-shell 3-tissue constrained spherical deconvolution, which models white matter microstructure while also accounting for other tissue compartments, to investigate WMH in vivo. Diffusion MRI data and FLAIR images were obtained from Alzheimers disease (n = 48) and healthy elderly control (n = 94) subjects from the Australian Imaging, Biomarkers and Lifestyle study of ageing. WMH were automatically segmented and classified as periventricular or deep lesions from FLAIR images based on their continuity with the lateral ventricles, and the 3-tissue profile of different classes of WMH was characterised by three metrics, which together characterised the relative tissue profile in terms of the white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our findings revealed that periventricular and deep lesion classes could be distinguished from one another, and from normal-appearing white matter based on their 3-tissue profile, with substantially higher free water content in periventricular lesions than deep. Given the higher lesion load of periventricular lesions in Alzheimers disease patients, the 3-tissue profile of these WMH could be interpreted as reflecting the more deleterious pathological underpinnings that are associated with disease. However, when alternatively classifying lesion sub-regions in terms of distance contours from the ventricles to account for potential heterogeneity within confluent lesions, we found that the highest fluid content was present in lesion areas most proximal to the ventricles, which were common to both Alzheimers disease subjects and healthy controls. We argue that whatever classification scheme is used when investigating WMH, failure to account for heterogeneity within lesions may result in classification-scheme dependent conclusions. Future studies of WMH in Alzheimers Disease would benefit from inclusion of microstructural information when characterising lesions.

neuroscience↗

bioRxiv2019

MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation

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

neuroscience↗