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Alan Connelly

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YNIMG Journal 2021 Journal Article

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis

  • Arush Honnedevasthana Arun
  • Alan Connelly
  • Robert E. Smith
  • Fernando Calamante

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

YNIMG Journal 2020 Journal Article

Early childhood development of white matter fiber density and morphology

  • Dennis Dimond
  • Christiane S. Rohr
  • Robert E. Smith
  • Thijs Dhollander
  • Ivy Cho
  • Catherine Lebel
  • Deborah Dewey
  • Alan Connelly

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 percent 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.

YNICL Journal 2020 Journal Article

In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data

  • Remika Mito
  • Thijs Dhollander
  • Ying Xia
  • David Raffelt
  • Olivier Salvado
  • Leonid Churilov
  • Christopher C. Rowe
  • Amy Brodtmann

White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.

YNIMG Journal 2020 Journal Article

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

  • Dennis Dimond
  • Stella Heo
  • Amanda Ip
  • Christiane S. Rohr
  • Ryann Tansey
  • Kirk Graff
  • Thijs Dhollander
  • Robert E. Smith

Background 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. Methods 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. Results 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. Conclusions 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.

YNIMG Journal 2019 Journal Article

Connectomes from streamlines tractography: Assigning streamlines to brain parcellations is not trivial but highly consequential

  • Chun-Hung Yeh
  • Robert E. Smith
  • Thijs Dhollander
  • Fernando Calamante
  • Alan Connelly

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.

YNIMG Journal 2019 Journal Article

Is removal of weak connections necessary for graph-theoretical analysis of dense weighted structural connectomes from diffusion MRI?

  • Oren Civier
  • Robert Elton Smith
  • Chun-Hung Yeh
  • Alan Connelly
  • Fernando Calamante

Recent advances in diffusion MRI tractography permit the generation of dense weighted structural connectomes that offer greater insight into brain organization. However, these efforts are hampered by the lack of consensus on how to extract topological measures from the resulting graphs. Here we evaluate the common practice of removing the graphs’ weak connections, which is primarily intended to eliminate spurious connections and emphasize strong connections. Because this processing step requires arbitrary or heuristic-based choices (e. g. , setting a threshold level below which connections are removed), and such choices might complicate statistical analysis and inter-study comparisons, in this work we test whether removing weak connections is indeed necessary. To this end, we systematically evaluated the effect of removing weak connections on a range of popular graph-theoretical metrics. Specifically, we investigated if (and at what extent) removal of weak connections introduces a statistically significant difference between two otherwise equal groups of healthy subjects when only applied to one of the groups. Using data from the Human Connectome Project, we found that removal of weak connections had no statistical effect even when removing the weakest ∼70–90% connections. Removing yet a larger extent of weak connections, thus reducing connectivity density even further, did produce a predictably significant effect. However, metric values became sensitive to the exact connectivity density, which has ramifications regarding the stability of the statistical analysis. This pattern persisted whether connections were removed by connection strength threshold or connectivity density, and for connectomes generated using parcellations at different resolutions. Finally, we showed that the same pattern also applies for data from a clinical-grade MRI scanner. In conclusion, our analysis revealed that removing weak connections is not necessary for graph-theoretical analysis of dense weighted connectomes. Because removal of weak connections provides no practical utility to offset the undesirable requirement for arbitrary or heuristic-based choices, we recommend that this step is avoided in future studies.

YNIMG Journal 2019 Journal Article

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

  • J-Donald Tournier
  • Robert Smith
  • David Raffelt
  • Rami Tabbara
  • Thijs Dhollander
  • Maximilian Pietsch
  • Daan Christiaens
  • Ben Jeurissen

MRtrix3 is an open-source, cross-platform software package for medical image processing, analysis and visualisation, 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.

YNICL Journal 2018 Journal Article

Fibre-specific white matter changes in multiple sclerosis patients with optic neuritis

  • Sanuji Gajamange
  • David Raffelt
  • Thijs Dhollander
  • Elaine Lui
  • Anneke van der Walt
  • Trevor Kilpatrick
  • Joanne Fielding
  • Alan Connelly

Long term irreversible disability in multiple sclerosis (MS) is thought to be primarily driven by axonal degeneration. Axonal degeneration leads to degenerative atrophy, therefore early markers of axonal degeneration are required to predict clinical disability and treatment efficacy. Given that additional pathologies such as inflammation, demyelination and oedema are also present in MS, it is essential to develop axonal markers that are not confounded by these processes. The present study investigated a novel method for measuring axonal degeneration in MS based on high angular resolution diffusion magnetic resonance imaging. Unlike standard methods, this novel method involved advanced acquisition and modelling for improved axonal sensitivity and specificity. Recent work has developed analytical methods, two novel axonal markers, fibre density and cross-section, that can be estimated for each fibre direction in each voxel (termed a "fixel"). This technique, termed fixel-based analysis, thus simultaneously estimates axonal density and white matter atrophy from specific white matter tracts. Diffusion-weighted imaging datasets were acquired for 17 patients with a history of acute unilateral optic neuritis (35.3 ± 10.2 years, 11 females) and 14 healthy controls (32.7 ± 4.8 years, 8 females) on a 3 T scanner. Fibre density values were compared to standard diffusion tensor imaging parameters (fractional anisotropy and mean diffusivity) in lesions and normal appearing white matter. Group comparisons were performed for each fixel to assess putative differences in fibre density and fibre cross-section. Fibre density was observed to have a comparable sensitivity to fractional anisotropy for detecting white matter pathology in MS, but was not affected by crossing axonal fibres. Whole brain fixel-based analysis revealed significant reductions in fibre density and fibre cross-section in the inferior fronto-occipital fasciculus (including the optic radiations) of patients compared to controls. We interpret this result to indicate that this fixel-based approach is able to detect early loss of fibre density and cross-section in the optic radiations in MS patients with a history of optic neuritis. Fibre-specific markers of axonal degeneration should be investigated further for use in early stage therapeutic trials, or to monitor axonal injury in early stage MS.

YNIMG Journal 2017 Journal Article

Investigating white matter fibre density and morphology using fixel-based analysis

  • David A. Raffelt
  • J.-Donald Tournier
  • Robert E. Smith
  • David N. Vaughan
  • Graeme Jackson
  • Gerard R. Ridgway
  • Alan Connelly

Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e. g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel (‘fixels’), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e. g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.

YNIMG Journal 2016 Journal Article

Correction for diffusion MRI fibre tracking biases: The consequences for structural connectomic metrics

  • Chun-Hung Yeh
  • Robert E. Smith
  • Xiaoyun Liang
  • Fernando Calamante
  • Alan Connelly

Diffusion MRI streamlines tractography has become a major technique for inferring structural networks through reconstruction of brain connectome. However, quantification of structural connectivity based on the number of streamlines interconnecting brain grey matter regions is known to be problematic in a number of aspects, such as the ill-posed nature of streamlines terminations and the non-quantitative nature of streamline counts. This study investigates the effects of state-of-the-art connectome construction methods on the subsequent analyses of structural brain networks using graph theoretical approaches. Our results demonstrate that the characteristics of structural connectivity, including connectome variability, global network metrics, small-world attributes and network hubs, alter significantly following the improvement in biological accuracy of streamlines tractograms provided by anatomically-constrained tractography (ACT) and spherical-deconvolution informed filtering of tractograms (SIFT). Importantly, the commonly-used correction for connection density based on scaling the contribution of each streamline to the connectome by its inverse length is shown to provide incomplete correction, highlighting the necessity for the use of advanced tractogram reconstruction techniques in structural connectomics research.

YNIMG Journal 2015 Journal Article

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

  • David A. Raffelt
  • Robert E. Smith
  • Gerard R. Ridgway
  • J-Donald Tournier
  • David N. Vaughan
  • Stephen Rose
  • Robert Henderson
  • Alan Connelly

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.

YNIMG Journal 2015 Journal Article

Fourier Tract Sampling (FouTS): A framework for improved inference of white matter tracts from diffusion MRI by explicitly modelling tract volume

  • Thomas G. Close
  • Jacques-Donald Tournier
  • Leigh A. Johnston
  • Fernando Calamante
  • Iven Mareels
  • Alan Connelly

Diffusion MRI tractography algorithm development is increasingly moving towards global techniques to incorporate “downstream” information and conditional probabilities between neighbouring tracts. Such approaches also enable white matter to be represented more tangibly than the abstract lines generated by the most common approaches to fibre tracking. However, previously proposed algorithms still use fibre-like models of white matter corresponding to thin strands of white matter tracts rather than the tracts themselves, and therefore require many components for accurate representations, which leads to poorly constrained inverse problems. We propose a novel tract-based model of white matter, the ‘Fourier tract’, which is able to represent rich tract shapes with a relatively low number of parameters, and explicitly decouples the spatial extent of the modelled tract from its ‘Apparent Connection Strength (ACS)’. The Fourier tract model is placed within a novel Bayesian framework, which relates the tract parameters directly to the observed signal, enabling a wide range of acquisition schemes to be used. The posterior distribution of the Bayesian framework is characterised via Markov-chain Monte-Carlo sampling to infer probable values of the ACS and spatial extent of the imaged white matter tracts, providing measures that can be directly applied to many research and clinical studies. The robustness of the proposed tractography algorithm is demonstrated on simulated basic tract configurations, such as curving, twisting, crossing and kissing tracts, and sections of more complex numerical phantoms. As an illustration of the approach in vivo, fibre tracking is performed on a central section of the brain in three subjects from 60 direction HARDI datasets.

YNIMG Journal 2015 Journal Article

Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping

  • Fernando Calamante
  • Robert E. Smith
  • Jacques-Donald Tournier
  • David Raffelt
  • Alan Connelly

A biological parameter that would be valuable to be able to extract from diffusion MRI data is the local white matter axonal density. Track-density imaging (TDI) has been used as if it could provide such a measure; however, this has been the subject of controversy, primarily due to the fact that track-count quantitation is highly sensitive to tracking biases and errors. The spherical-deconvolution informed filtering of tractograms (SIFT) post-processing method was recently introduced to minimise tractography biases, and thus provides a more biologically meaningful measure that could be used in track-count mapping (i. e. TDI following SIFT). The TDI intensity following SIFT ideally corresponds to the orientational average of the fibre orientation distribution (FOD), which corresponds to the total Apparent Fibre Density (AFDtotal) within the AFD framework; in fact, AFDtotal provides a direct measure of local fibre density at native resolution that does not rely on fibre-tracking. In this study, we demonstrate problems associated with quantitative TDI investigations, which can be avoided by using SIFT processing or directly by using AFDtotal maps. We also characterise the intra- and inter-subject reproducibility of TDI maps (with and without SIFT pre-processing) and AFDtotal maps. It is shown that SIFT improves the quantitative characteristics of TDI, but is still vastly inferior to the properties of the AFDtotal parameter itself, because the latter does not require tracking. While standard TDI might be preferable in applications when high anatomical contrast is required, particularly when combined with super-resolution, for voxel-wise quantitation of total tract density (i. e. without tract orientation information) at native resolution, the total AFD maps are preferable to TDI or other related track-count maps. Regardless of the track-count measure, it should be noted that all of these voxel-averaged approaches discard important information that is retained in fibre-specific approaches such as AFD.

YNIMG Journal 2015 Journal Article

Reproducibility of multiphase pseudo-continuous arterial spin labeling and the effect of post-processing analysis methods

  • Amir Fazlollahi
  • Pierrick Bourgeat
  • Xiaoyun Liang
  • Fabrice Meriaudeau
  • Alan Connelly
  • Olivier Salvado
  • Fernando Calamante

Arterial spin labeling (ASL) is an emerging MRI technique for non-invasive measurement of cerebral blood flow (CBF). Compared to invasive perfusion imaging modalities, ASL suffers from low sensitivity due to poor signal-to-noise ratio (SNR), susceptibility to motion artifacts and low spatial resolution, all of which limit its reliability. In this work, the effects of various state of the art image processing techniques for addressing these ASL limitations are investigated. A processing pipeline consisting of motion correction, ASL motion correction imprecision removal, temporal and spatial filtering, partial volume effect correction, and CBF quantification was developed and assessed. To further improve the SNR for pseudo-continuous ASL (PCASL) by accounting for errors in tagging efficiency, the data from multiphase (MP) acquisitions were analyzed using a novel weighted-averaging scheme. The performances of each step in terms of SNR and reproducibility were evaluated using test–retest ASL data acquired from 12 young healthy subjects. The proposed processing pipeline was shown to improve the within-subject coefficient of variation and regional reproducibility by 17% and 16%, respectively, compared to CBF maps computed following motion correction but without the other processing steps. The CBF measurements of MP-PCASL compared to PCASL had on average 23% and 10% higher SNR and reproducibility, respectively.

YNIMG Journal 2015 Journal Article

SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography

  • Robert E. Smith
  • Jacques-Donald Tournier
  • Fernando Calamante
  • Alan Connelly

Diffusion MRI streamlines tractography allows for the investigation of the brain white matter pathways non-invasively. However a fundamental limitation of this technology is its non-quantitative nature, i. e. the density of reconstructed connections is not reflective of the density of underlying white matter fibres. As a solution to this problem, we have previously published the “spherical-deconvolution informed filtering of tractograms (SIFT)” method, which determines a subset of the streamlines reconstruction such that the streamlines densities throughout the white matter are as close as possible to fibre densities estimated using the spherical deconvolution diffusion model; this permits the use of streamline count as a valid biological marker of connection density. Particular aspects of its performance may have however limited its uptake in the diffusion MRI research community. Here we present an alternative to this method, entitled SIFT2, which provides a more logically direct and computationally efficient solution to the streamlines connectivity quantification problem: by determining an appropriate cross-sectional area multiplier for each streamline rather than removing streamlines altogether, biologically accurate measures of fibre connectivity are obtained whilst making use of the complete streamlines reconstruction.

YNIMG Journal 2015 Journal Article

The effects of SIFT on the reproducibility and biological accuracy of the structural connectome

  • Robert E. Smith
  • Jacques-Donald Tournier
  • Fernando Calamante
  • Alan Connelly

Diffusion MRI streamlines tractography is increasingly being used to characterise and assess the structural connectome of the human brain. However, issues pertaining to quantification of structural connectivity using streamlines reconstructions are well-established in the field, and therefore the validity of any conclusions that may be drawn from these analyses remains ambiguous. We recently proposed a post-processing method entitled “SIFT: Spherical-deconvolution Informed Filtering of Tractograms” as a mechanism for reducing the biases in quantitative measures of connectivity introduced by the streamlines reconstruction method. Here, we demonstrate the advantage of this approach in the context of connectomics in three steps. Firstly, we carefully consider the model imposed by the SIFT method, and the implications this has for connectivity quantification. Secondly, we investigate the effects of SIFT on the reproducibility of structural connectome construction. Thirdly, we compare quantitative measures extracted from structural connectomes derived from streamlines tractography, with and without the application of SIFT, to published estimates drawn from post-mortem brain dissection. The combination of these sources of evidence demonstrates the important role the SIFT methodology has for the robust quantification of structural connectivity of the brain using diffusion MRI.

YNIMG Journal 2014 Journal Article

Graph analysis of resting-state ASL perfusion MRI data: Nonlinear correlations among CBF and network metrics

  • Xiaoyun Liang
  • Alan Connelly
  • Fernando Calamante

Human connectome mapping is important to understand both normal brain function and disease-related dysfunction. Although blood-oxygen-level-dependent (BOLD) fMRI has been the most commonly used method for human connectome mapping, arterial spin labeling (ASL) is an fMRI technique to measure cerebral blood flow (CBF) directly and noninvasively, and thus provides a more direct quantitative correlate of neural activity. In this study, investigations on properties of CBF networks using ASL perfusion data have been conducted on 10 healthy subjects. As with BOLD fMRI studies, the extracted networks exhibited small-world network properties. In addition, highly connected brain regions are shown to overlap mostly with hub regions detected from BOLD fMRI studies. Taken together, this demonstrates the capability of ASL fMRI for mapping the brain connectome. Furthermore, a sigmoid model was then employed to fit the extracted network metrics vs. CBF measurements. Interestingly, the relationships between 4 specific network metrics and region-wise CBF demonstrate that consistently nonlinear patterns exist across all subjects. In contrast to the positive nonlinear pattern of other network metrics (degree, vulnerability, and eigenvector centrality), the characteristic path length shows a negative nonlinear pattern, reflecting the mechanism underlying the small-world properties. To our knowledge, this is the first study to unravel the intrinsic relationships between specific network metrics and CBF estimates. This should have diagnostic and therapeutic implications for those studies focusing on patients who suffer from abnormal functional connectivity.

YNIMG Journal 2014 Journal Article

Identification and interpretation of microstructural abnormalities in motor pathways in adolescents born preterm

  • Samuel Groeschel
  • J-Donald Tournier
  • Gemma B. Northam
  • Torsten Baldeweg
  • John Wyatt
  • Brigitte Vollmer
  • Alan Connelly

There has been extensive interest in assessing the long-term effects of preterm birth on brain white matter microstructure using diffusion MRI. Our aim in this study is to explore diffusion MRI differences between adolescents born preterm and term born controls, with a specific interest in characterising how such differences are manifested in white matter regions containing predominantly single or crossing fibre populations. Probabilistic high angular resolution tractography together with large deformation spatial normalisation were used to objectively investigate diffusion tensor parameters at regular intervals along fibre tracts of 45 adolescents born before 33weeks of gestation and 30 term-born typically developing adolescents. Diffusion parameters were significantly different between preterms and controls at several levels along the cortico-spinal, thalamo-cortical and transcallosal pathways. Within the predominantly single fibre regions of the corpus callosum and internal capsule, in the preterms mean diffusivity (MD) was found to be increased while fractional anisotropy (FA) was decreased compared to controls. In contrast, however, where these pathways traversed the centrum semiovale, FA and MD were both significantly increased. The major contributor to reduced FA in preterms in predominantly single fibre regions was the increased radial eigenvalue (i. e. increased radial diffusivity). In predominantly crossing-fibre regions, the tensor eigenvalues are not meaningful, and the observed increase in FA is likely to be due to a decrease in anisotropy in one of the contributing fibre bundles. Similar differences (although less pronounced) were observed after excluding preterms with radiological signs of preterm brain injury from the sample. In summary, white matter microstructure was found to be altered in motor pathways in adolescents born preterm. Disruption of white matter (WM) microstructure in a single fibre region with resulting higher radial diffusivity leads to lower FA, whereas selective disruption of one fibre population in a crossing fibre region is observed to lead to higher FA. These findings challenge the common simplistic interpretation of FA as a measure of WM tract integrity.

YNIMG Journal 2014 Journal Article

Lesion segmentation from multimodal MRI using random forest following ischemic stroke

  • Jhimli Mitra
  • Pierrick Bourgeat
  • Jurgen Fripp
  • Soumya Ghose
  • Stephen Rose
  • Olivier Salvado
  • Alan Connelly
  • Bruce Campbell

Understanding structure–function relationships in the brain after stroke is reliant not only on the accurate anatomical delineation of the focal ischemic lesion, but also on previous infarcts, remote changes and the presence of white matter hyperintensities. The robust definition of primary stroke boundaries and secondary brain lesions will have significant impact on investigation of brain–behavior relationships and lesion volume correlations with clinical measures after stroke. Here we present an automated approach to identify chronic ischemic infarcts in addition to other white matter pathologies, that may be used to aid the development of post-stroke management strategies. Our approach uses Bayesian–Markov Random Field (MRF) classification to segment probable lesion volumes present on fluid attenuated inversion recovery (FLAIR) MRI. Thereafter, a random forest classification of the information from multimodal (T1-weighted, T2-weighted, FLAIR, and apparent diffusion coefficient (ADC)) MRI images and other context-aware features (within the probable lesion areas) was used to extract areas with high likelihood of being classified as lesions. The final segmentation of the lesion was obtained by thresholding the random forest probabilistic maps. The accuracy of the automated lesion delineation method was assessed in a total of 36 patients (24 male, 12 female, mean age: 64. 57±14. 23yrs) at 3months after stroke onset and compared with manually segmented lesion volumes by an expert. Accuracy assessment of the automated lesion identification method was performed using the commonly used evaluation metrics. The mean sensitivity of segmentation was measured to be 0. 53±0. 13 with a mean positive predictive value of 0. 75±0. 18. The mean lesion volume difference was observed to be 32. 32%±21. 643% with a high Pearson's correlation of r =0. 76 (p <0. 0001). The lesion overlap accuracy was measured in terms of Dice similarity coefficient with a mean of 0. 60±0. 12, while the contour accuracy was observed with a mean surface distance of 3. 06mm±3. 17mm. The results signify that our method was successful in identifying most of the lesion areas in FLAIR with a low false positive rate.

YNIMG Journal 2014 Journal Article

Mapping somatosensory connectivity in adult mice using diffusion MRI tractography and super-resolution track density imaging

  • Kay Richards
  • Fernando Calamante
  • Jacques-Donald Tournier
  • Nyoman D. Kurniawan
  • Farnoosh Sadeghian
  • Alexander R. Retchford
  • Gabriel Davis Jones
  • Christopher A. Reid

In this study we combined ultra-high field diffusion MRI fiber tracking and super-resolution track density imaging (TDI) to map the relay locations and connectivity of the somatosensory pathway in paraformaldehyde fixed, C57Bl/6J mouse brains. Super-resolution TDI was used to achieve 20μm isotropic resolution to inform the 3D topography of the relay locations including thalamic barreloids and brainstem barrelettes, not described previously using MRI methodology. TDI-guided mapping results for thalamo-cortical connectivity were consistent with thalamo-cortical projections labeled using virus mediated fluorescent protein expression. Trigemino-thalamic TDI connectivity maps were concordant with results obtained using anterograde dye tracing from brainstem to thalamus. Importantly, TDI mapping overcame the constraint of tissue distortion observed in mechanically sectioned tissue, enabling 3D reconstruction and long-range connectivity data. In conclusion, our results showed that diffusion micro-imaging at ultra-high field MRI revealed the stereotypical pattern of somatosensory connectivity and is a valuable tool to complement histologic methods, achieving 3D spatial preservation of whole brain networks for characterization in mouse models of human disease.

YNIMG Journal 2014 Journal Article

Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data

  • Ben Jeurissen
  • Jacques-Donald Tournier
  • Thijs Dhollander
  • Alan Connelly
  • Jan Sijbers

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.

YNIMG Journal 2014 Journal Article

Quantification of track-weighted imaging (TWI): Characterisation of within-subject reproducibility and between-subject variability

  • Lisa Willats
  • David Raffelt
  • Robert E. Smith
  • J.-Donald Tournier
  • Alan Connelly
  • Fernando Calamante

Recently several novel image contrasts derived from whole-brain fibre tracking-data (tractograms) have been introduced. The novel contrasts of these track-weighted imaging (TWI) methods may provide important information for clinical neuroscience studies. However, before they can be used reliably to generate quantitative measures, it is important to characterise their within-subject reproducibility, and between-subject variability. In this work we compute the within-subject reproducibility (intra-scan, intra-session and inter-session), and between-subject variability of TWI for a number of different TWI contrasts across multiple subjects. The results are used in simple voxel-wise power calculations within illustrative regions of interest to provide guidelines for required sample sizes and observable effect sizes for individual subjects and between groups. It was found that the required sample sizes and observable effect sizes varied considerably between different TWI maps and for different ROIs. For some TWI contrast and ROI combinations, the power calculations yielded clinically practical values. These results provide important information concerning the potential usefulness and sensitivity of TWI maps for individual diagnosis, longitudinal studies and group comparisons, as well as for study designs.

YNIMG Journal 2013 Journal Article

SIFT: Spherical-deconvolution informed filtering of tractograms

  • Robert E. Smith
  • Jacques-Donald Tournier
  • Fernando Calamante
  • Alan Connelly

Diffusion MRI allows the structural connectivity of the whole brain (the ‘tractogram’) to be estimated in vivo non-invasively using streamline tractography. The biological accuracy of these data sets is however limited by the inherent biases associated with the reconstruction method. Here we propose a method to retrospectively improve the accuracy of these reconstructions, by selectively filtering out streamlines from the tractogram in a manner that improves the fit between the streamline reconstruction and the underlying diffusion images. This filtering is guided by the results of spherical deconvolution of the diffusion signal, hence the acronym SIFT: spherical-deconvolution informed filtering of tractograms. Data sets processed by this algorithm show a marked reduction in known reconstruction biases, and improved biological plausibility. Emerging methods in diffusion MRI, particularly those that aim to characterise and compare the structural connectivity of the brain, should benefit from the improved accuracy of the reconstruction.

YNIMG Journal 2013 Journal Article

Track-weighted functional connectivity (TW-FC): A tool for characterizing the structural–functional connections in the brain

  • Fernando Calamante
  • Richard A.J. Masterton
  • Jacques-Donald Tournier
  • Robert E. Smith
  • Lisa Willats
  • David Raffelt
  • Alan Connelly

MRI provides a powerful tool for studying the functional and structural connections in the brain non-invasively. The technique of functional connectivity (FC) exploits the intrinsic temporal correlations of slow spontaneous signal fluctuations to characterise brain functional networks. In addition, diffusion MRI fibre-tracking can be used to study the white matter structural connections. In recent years, there has been considerable interest in combining these two techniques to provide an overall structural–functional description of the brain. In this work we applied the recently proposed super-resolution track-weighted imaging (TWI) methodology to demonstrate how whole-brain fibre-tracking data can be combined with FC data to generate a track-weighted (TW) FC map of FC networks. The method was applied to data from 8 healthy volunteers, and illustrated with (i) FC networks obtained using a seeded connectivity-based analysis (seeding in the precuneus/posterior cingulate cortex, PCC, known to be part of the default mode network), and (ii) with FC networks generated using independent component analysis (in particular, the default mode, attention, visual, and sensory-motor networks). TW-FC maps showed high intensity in white matter structures connecting the nodes of the FC networks. For example, the cingulum bundles show the strongest TW-FC values in the PCC seeded-based analysis, due to their major role in the connection between medial frontal cortex and precuneus/posterior cingulate cortex; similarly the superior longitudinal fasciculus was well represented in the attention network, the optic radiations in the visual network, and the corticospinal tract and corpus callosum in the sensory-motor network. The TW-FC maps highlight the white matter connections associated with a given FC network, and their intensity in a given voxel reflects the functional connectivity of the part of the nodes of the network linked by the structural connections traversing that voxel. They therefore contain a different (and novel) image contrast from that of the images used to generate them. The results shown in this study illustrate the potential of the TW-FC approach for the fusion of structural and functional data into a single quantitative image. This technique could therefore have important applications in neuroscience and neurology, such as for voxel-based comparison studies.

YNIMG Journal 2012 Journal Article

A generalised framework for super-resolution track-weighted imaging

  • Fernando Calamante
  • Jacques-Donald Tournier
  • Robert E. Smith
  • Alan Connelly

Track-density imaging (TDI) was recently introduced as a method to achieve super-resolution imaging using whole-brain fibre-tracking data (the so called tractogram). A similar approach to achieve super-resolution was later applied for average pathlength mapping (APM). These two methods have in common that the tractogram information is used to create an image with novel contrast and super-resolution properties. In this study, we present a generalised framework for creating super-resolution track-weighted imaging (TWI), where the intensity of the map can be made dependent on any specific property of the streamlines or their set of spatial coordinates. Furthermore, each contrast can be determined by a number of characteristics that are under user control. It is shown that TDI and APM represent specific cases of this generalised framework, and that this framework opens up the possibility of generating a large range of images with novel image contrasts. Finally, it is shown that the same super-resolution principles as those introduced in the original TDI method are also applicable to any of these new images.

YNIMG Journal 2012 Journal Article

Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information

  • Robert E. Smith
  • Jacques-Donald Tournier
  • Fernando Calamante
  • Alan Connelly

Diffusion MRI streamlines tractography suffers from a number of inherent limitations, one of which is the accurate determination of when streamlines should be terminated. Use of an accurate streamlines propagation mask from segmentation of an anatomical image confines the streamlines to the volume of the brain white matter, but does not take full advantage of all of the information available from such an image. We present a modular addition to streamlines tractography, which makes more effective use of the information available from anatomical image segmentation, and the known properties of the neuronal axons being reconstructed, to apply biologically realistic priors to the streamlines generated; we refer to this as “Anatomically-Constrained Tractography”. Results indicate that some of the known false positives associated with tractography algorithms are prevented, such that the biological accuracy of the reconstructions should be improved, provided that state-of-the-art streamlines tractography methods are used.

YNIMG Journal 2012 Journal Article

Apparent Fibre Density: A novel measure for the analysis of diffusion-weighted magnetic resonance images

  • David Raffelt
  • J.-Donald Tournier
  • Stephen Rose
  • Gerard R. Ridgway
  • Robert Henderson
  • Stuart Crozier
  • Olivier Salvado
  • Alan Connelly

This article proposes a new measure called Apparent Fibre Density (AFD) for the analysis of high angular resolution diffusion-weighted images using higher-order information provided by fibre orientation distributions (FODs) computed using spherical deconvolution. AFD has the potential to provide specific information regarding differences between populations by identifying not only the location, but also the orientations along which differences exist. In this work, analytical and numerical Monte-Carlo simulations are used to support the use of the FOD amplitude as a quantitative measure (i. e. AFD) for population and longitudinal analysis. To perform robust voxel-based analysis of AFD, we present and evaluate a novel method to modulate the FOD to account for changes in fibre bundle cross-sectional area that occur during spatial normalisation. We then describe a novel approach for statistical analysis of AFD that uses cluster-based inference of differences extended throughout space and orientation. Finally, we demonstrate the capability of the proposed method by performing voxel-based AFD comparisons between a group of Motor Neurone Disease patients and healthy control subjects. A significant decrease in AFD was detected along voxels and orientations corresponding to both the corticospinal tract and corpus callosal fibres that connect the primary motor cortices. In addition to corroborating previous findings in MND, this study demonstrates the clear advantage of using this type of analysis by identifying differences along single fibre bundles in regions containing multiple fibre populations.

YNIMG Journal 2012 Journal Article

Comment on time-varying eddy currents effects on diffusion-weighting echo-planar imaging

  • Fernando Calamante
  • Alan Connelly

This commentary addresses the recent paper entitled “Dynamic correction of artifacts due to susceptibility effects and time-varying eddy currents in diffusion tensor imaging” (Truong et al. , 2011) and discusses their findings in relation to previous studies from the late 1990s that showed equivalent findings regarding the complex time-varying nature of eddy currents during the imaging readout. The similarities between the findings from these studies are highlighted, and their possible implications for present commonly used eddy current reduction methods are discussed.

YNIMG Journal 2012 Journal Article

Super-resolution track-density imaging studies of mouse brain: Comparison to histology

  • Fernando Calamante
  • Jacques-Donald Tournier
  • Nyoman D. Kurniawan
  • Zhengyi Yang
  • Erika Gyengesi
  • Graham J. Galloway
  • David C. Reutens
  • Alan Connelly

The recently proposed track-density imaging (TDI) technique was introduced as a means to achieve super-resolution using diffusion MRI. This technique is able to increase the spatial resolution of the reconstructed images beyond the acquired MRI resolution by incorporating information from whole-brain fibre-tracking results. It not only achieves super-resolution, but also provides very high anatomical contrast with a new MRI contrast mechanism. However, the anatomical information-content of this novel contrast mechanism has not yet been assessed. In this work, we perform such a study using diffusion MRI of ex vivo mouse brains acquired at 16. 4T, to compare the results of the super-resolution TDI technique with histological staining (myelin and Nissl stains) in the same brains. Furthermore, a modified version of the directionally-encoded colour TDI map using short-tracks is introduced, which reduces the TDI intensity dynamic range, and therefore enhances the directionality colour-contrast. Good agreement was observed between structures visualised in the super-resolution TDI maps and in the histological sections, supporting the anatomical information-content of the images generated using the TDI technique. The results therefore show that the TDI methodology does provide meaningful and rich anatomical contrast, in addition to achieving super-resolution. Furthermore, this study is the first to show the application of TDI to mouse brain imaging: the high-resolution, high-quality images demonstrate the useful complementary information that can be achieved using super-resolution TDI.

YNIMG Journal 2011 Journal Article

Symmetric diffeomorphic registration of fibre orientation distributions

  • David Raffelt
  • J-Donald Tournier
  • Jurgen Fripp
  • Stuart Crozier
  • Alan Connelly
  • Olivier Salvado

Registration of diffusion-weighted images is an important step in comparing white matter fibre bundles across subjects, or in the same subject at different time points. Using diffusion-weighted imaging, Spherical Deconvolution enables multiple fibre populations within a voxel to be resolved by computing the fibre orientation distribution (FOD). In this paper, we present a novel method that employs FODs for the registration of diffusion-weighted images. Registration was performed by optimising a symmetric diffeomorphic non-linear transformation model, using image metrics based on the mean squared difference, and cross-correlation of the FOD spherical harmonic coefficients. The proposed method was validated by recovering known displacement fields using FODs represented with maximum harmonic degrees (l max ) of 2, 4 and 6. Results demonstrate a benefit in using FODs at l max =4 compared to l max =2. However, a decrease in registration accuracy was observed when l max =6 was used; this was likely caused by noise in higher harmonic degrees. We compared our proposed method to fractional anisotropy driven registration using an identical code base and parameters. FOD registration was observed to perform significantly better than FA in all experiments. The cross-correlation metric performed significantly better than the mean squared difference. Finally, we demonstrated the utility of this method by computing an unbiased group average FOD template that was used for probabilistic fibre tractography. This work suggests that using crossing fibre information aids in the alignment of white matter and could therefore benefit several methods for investigating population differences in white matter, including voxel based analysis, tensor based morphometry, atlas based segmentation and labelling, and group average fibre tractography.

YNIMG Journal 2011 Journal Article

Track density imaging (TDI): Validation of super resolution property

  • Fernando Calamante
  • Jacques-Donald Tournier
  • Robin M. Heidemann
  • Alfred Anwander
  • Graeme D. Jackson
  • Alan Connelly

We have recently introduced a novel MRI methodology, so-called super resolution track-density imaging (TDI), which produces high-quality white matter images, with high spatial resolution and exquisite anatomical contrast not available from other MRI modalities. This method achieves super resolution by utilising the long-range information contained in the diffusion MRI fibre tracks. In this study, we validate the super resolution property of the TDI method by using in vivo diffusion MRI data acquired at ultra-high magnetic field strength (7T), and in silico diffusion MRI data from a well-characterised numerical phantom. Furthermore, an alternative version of the TDI technique is described, which mitigates the track length weighting of the TDI map intensity. For the in vivo data, high-resolution diffusion images were down-sampled to simulate low-resolution data, for which the high-resolution images serve as a gold standard. For the in silico data, the gold standard is given by the known simulated structures of the numerical phantom. Both the in vivo and in silico data show that the structures that could be identified in the TDI maps only after using super resolution were consistent with the corresponding structures identified in the reference maps. This supports the claim that the structures identified by the super resolution step are accurate, thus providing further evidence for the important potential role of the super resolution TDI methodology in neuroscience.

YNIMG Journal 2010 Journal Article

The effect of finite diffusion gradient pulse duration on fibre orientation estimation in diffusion MRI

  • Chun-Hung Yeh
  • J-Donald Tournier
  • Kuan-Hung Cho
  • Ching-Po Lin
  • Fernando Calamante
  • Alan Connelly

An essential step for fibre-tracking is the accurate estimation of neuronal fibre orientations within each imaging voxel, and a number of methods have been proposed to reconstruct the orientation distribution function based on sampling three-dimensional q-space. In the q-space formalism, very short (infinitesimal) gradient pulses are the basic requirement to obtain the true spin displacement probability density function. On current clinical MR systems however, the diffusion gradient pulse duration (δ) is inevitably finite due to the limit on the achievable gradient intensity. The failure to satisfy the short gradient pulse (SGP) requirement has been a recurrent criticism for fibre orientation estimation based on the q-space approach. In this study, the influence of a finite δ on the DW signal measured as a function of gradient direction is described theoretically and demonstrated through simulations and experimental models. Our results suggest that the current practice of using long δ for DW imaging on human clinical MR scanners, which is enforced by hardware limitations, might in fact be beneficial for estimating fibre orientations. For a given b-value, the prolongation of δ is advantageous for estimating fibre orientations for two reasons: first, it leads to a boost in DW signal in the transverse plane of the fibre. Second, it stretches out the shape of the measured diffusion profile, which improves the contrast between DW orientations. This is especially beneficial for resolving crossing fibres, as this contrast is essential to discriminate between different fibre directions.

YNIMG Journal 2010 Journal Article

Track-density imaging (TDI): Super-resolution white matter imaging using whole-brain track-density mapping

  • Fernando Calamante
  • Jacques-Donald Tournier
  • Graeme D. Jackson
  • Alan Connelly

Neuroimaging advances have given rise to major progress in neurosciences and neurology, as ever more subtle and specific imaging methods reveal new aspects of the brain. One major limitation of current methods is the spatial scale of the information available. We present an approach to gain spatial resolution using post-processing methods based on diffusion MRI fiber-tracking, to reveal structures beyond the resolution of the acquired imaging voxel; we term such a method as super-resolution track-density imaging (TDI). A major unmet challenge in imaging is the identification of abnormalities in white matter as a cause of illness; super-resolution TDI is shown to produce high-quality white matter images, with high spatial resolution and outstanding anatomical contrast. A unique property of these maps is demonstrated: their spatial resolution and signal-to-noise ratio can be tailored depending on the chosen image resolution and total number of fiber-tracks generated. Super-resolution TDI should greatly enhance the study of white matter in disorders of the brain and mind.

YNIMG Journal 2009 Journal Article

A software tool to generate simulated white matter structures for the assessment of fibre-tracking algorithms

  • Thomas G. Close
  • Jacques-Donald Tournier
  • Fernando Calamante
  • Leigh A. Johnston
  • Iven Mareels
  • Alan Connelly

The assessment of Diffusion-Weighted MRI (DW-MRI) fibre-tracking algorithms has been limited by the lack of an appropriate ‘gold standard’. Practical limitations of alternative methods and physical models have meant that numerical simulations have become the method of choice in practice. However, previous numerical phantoms have consisted of separate fibres embedded in homogeneous backgrounds, which do not capture the true nature of white matter. In this paper we describe a method that is able to randomly generate numerical structures consisting of densely packed bundles of fibres, which are much more representative of human white matter, and simulate the DW-MR images that would arise from them under many imaging conditions. User-defined parameters may be adjusted to produce structures with a range of complexities that spans the levels we would expect to find in vivo. These structures are shown to contain many different features that occur in human white matter and which could confound fibre-tracking algorithms, such as tract kissing and crossing. Furthermore, combinations of such features can be sampled by the random generation of many different structures with consistent levels of complexity. The proposed software provides means for quantitative assessment via direct comparison between tracking results and the exact location of the generated fibres. This should greatly improve our understanding of algorithm performance and therefore prove an important tool for fibre tracking development.

YNIMG Journal 2008 Journal Article

Resolving crossing fibres using constrained spherical deconvolution: Validation using diffusion-weighted imaging phantom data

  • J.-Donald Tournier
  • Chun-Hung Yeh
  • Fernando Calamante
  • Kuan-Hung Cho
  • Alan Connelly
  • Ching-Po Lin

Diffusion-weighted imaging can potentially be used to infer the connectivity of the human brain in vivo using fibre-tracking techniques, and is therefore of great interest to neuroscientists and clinicians. A key requirement for fibre tracking is the accurate estimation of white matter fibre orientations within each imaging voxel. The diffusion tensor model, which is widely used for this purpose, has been shown to be inadequate in crossing fibre regions. A number of approaches have recently been proposed to address this issue, based on high angular resolution diffusion-weighted imaging (HARDI) data. In this study, an experimental model of crossing fibres, consisting of water-filled plastic capillaries, is used to thoroughly assess three such techniques: constrained spherical deconvolution (CSD), super-resolved CSD (super-CSD) and Q-ball imaging (QBI). HARDI data were acquired over a range of crossing angles and b-values, from which fibre orientations were computed using each technique. All techniques were capable of resolving the two fibre populations down to a crossing angle of 45°, and down to 30° for super-CSD. A bias was observed in the fibre orientations estimated by QBI for crossing angles other than 90°, consistent with previous simulation results. Finally, for a 45° crossing, the minimum b-value required to resolve the fibre orientations was 4000s/mm2 for QBI, 2000s/mm2 for CSD, and 1000s/mm2 for super-CSD. The quality of estimation of fibre orientations may profoundly affect fibre tracking attempts, and the results presented provide important additional information regarding performance characteristics of well-known methods.

YNIMG Journal 2007 Journal Article

Cortical abnormalities and language function in young patients with basal ganglia stroke

  • Alison Rowan
  • Faraneh Vargha-Khadem
  • Fernando Calamante
  • Jacques-Donald Tournier
  • Fenella J. Kirkham
  • Wui K. Chong
  • Torsten Baldeweg
  • Alan Connelly

We examined MRI abnormalities and language function in young patients with infarctions apparently confined to the basal ganglia to establish whether impaired performance was attributable to basal ganglia damage per se or to additional cerebral abnormalities. Seventeen stroke patients (10 with left- and 7 with right-hemispheric damage) and seventeen controls participated. MRI included perfusion imaging and voxel-based morphometry analyses of T1-weighted and diffusion data sets. Language was assessed using the CELF-III test. Analysis of CELF-III scores showed a main effect of presence or absence of stroke, with patients performing more poorly than controls. There was no evidence of differences between the left- and right-hemisphere groups. However individual patients with left-hemisphere lesions showed large variations in performance. In the patients with left-hemisphere damage, voxel-based morphometry showed significant relationships between language function and gray matter density in cortical language areas. The white matter analyses also showed correlations with language function, and in addition there were hemodynamic abnormalities in cortical language areas in the three patients with poorest language function. We suggest that language impairments following basal ganglia damage may be attributable primarily to abnormalities in cortical language areas that are too subtle to detect on conventional structural MRI.

YNIMG Journal 2007 Journal Article

Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution

  • J-Donald Tournier
  • Fernando Calamante
  • Alan Connelly

Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.

YNIMG Journal 2005 Journal Article

Extra-hippocampal grey matter density abnormalities in paediatric mesial temporal sclerosis

  • Francesca Cormack
  • David G. Gadian
  • Faraneh Vargha-Khadem
  • J. Helen Cross
  • Alan Connelly
  • Torsten Baldeweg

The aim of this study was to identify grey matter density abnormalities in children with temporal lobe epilepsy and mesial temporal sclerosis. Magnetic resonance T1 weighted 3D datasets were obtained in children with temporal lobe epilepsy (20 left and 10 right sided, mean age 11. 9 years, range 6. 6–17. 5) and compared to scans obtained from age-matched controls (n = 22, mean age 12. 8 years, range 7. 1–17. 5) using voxel-based morphometry. This method detected reduced grey matter ipsilateral to the seizure focus not only in the hippocampus, but also in the lateral temporal lobe and in extra-temporal regions including the thalamus, posterior cingulate cortex and cerebellum. Bilateral differences were present in the frontal and parietal opercular cortices and lateral temporal regions. These grey matter density reductions broadly reflect the pattern of hippocampal connections and may be caused by the disruption of cortical development by the recurrent seizures, as well as by loss of functional input from the sclerotic hippocampus.

YNIMG Journal 2004 Journal Article

Cortical lateralization during verb generation: a combined ERP and fMRI study

  • Alison Rowan
  • Frédérique Liégeois
  • Faraneh Vargha-Khadem
  • David Gadian
  • Alan Connelly
  • Torsten Baldeweg

Lateralization of scalp-recorded event-related potentials (ERPs) and functional MRI (fMRI) activation was investigated using a verb generation task in 10 healthy right-handed adults. ERPs showed an early transient positivity in the left inferior temporal region (500–1250 ms) following auditory presentation of the stimulus noun. A sustained slow cortical negativity of later onset (1250–3000 ms) was then recorded, most pronounced over left inferior frontal regions. fMRI data were in agreement with both ERP effects, showing left lateralized activation in inferior and superior temporal as well as inferior frontal cortices. Lateralized ERP effects occurred during the verb generation task but not during passive word listening or during word- and nonword repetition. Thus, ERPs and fMRI provided convergent evidence regarding language lateralization, with ERPs revealing the temporal sequence of posterior to anterior cortical activation during semantic retrieval.

YNIMG Journal 2004 Journal Article

Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution

  • J.-Donald Tournier
  • Fernando Calamante
  • David G. Gadian
  • Alan Connelly

Diffusion-weighted magnetic resonance imaging can provide information related to the arrangement of white matter fibers. The diffusion tensor is the model most commonly used to derive the orientation of the fibers within a voxel. However, this model has been shown to fail in regions containing several fiber populations with distinct orientations. A number of alternative models have been suggested, such as multiple tensor fitting, q-space, and Q-ball imaging. However, each of these has inherent limitations. In this study, we propose a novel method for estimating the fiber orientation distribution directly from high angular resolution diffusion-weighted MR data without the need for prior assumptions regarding the number of fiber populations present. We assume that all white matter fiber bundles in the brain share identical diffusion characteristics, thus implicitly assigning any differences in diffusion anisotropy to partial volume effects. The diffusion-weighted signal attenuation measured over the surface of a sphere can then be expressed as the convolution over the sphere of a response function (the diffusion-weighted attenuation profile for a typical fiber bundle) with the fiber orientation density function (ODF). The fiber ODF (the distribution of fiber orientations within the voxel) can therefore be obtained using spherical deconvolution. The properties of the technique are demonstrated using simulations and on data acquired from a volunteer using a standard 1. 5-T clinical scanner. The technique can recover the fiber ODF in regions of multiple fiber crossing and holds promise for applications such as tractography.

YNIMG Journal 2003 Journal Article

Diffusion-weighted magnetic resonance imaging fibre tracking using a front evolution algorithm

  • J.-Donald Tournier
  • Fernando Calamante
  • David G Gadian
  • Alan Connelly

A novel technique is presented for estimating white matter connectivity in vivo using diffusion-weighted magnetic resonance imaging. The concept of a fibre orientation density function (ODF) is described, which characterises the uncertainty in the orientation of the underlying white matter fibres, given the set of diffusion-weighted signal intensities at the point of interest. The proposed algorithm is based on the evolution of a front from a seed region, using the information provided by the fibre ODF. Each point reached by the front is assigned an index of connectivity with the seed region. The algorithm was used to track various major white matter fibre pathways in two data sets acquired on the same healthy adult volunteer over separate occasions. Example tracks are shown to illustrate some of the properties of the algorithm, such as robustness to noise and branching capability. Finally, the dependence of the algorithm on the model used to derive the fibre ODF is discussed.

YNIMG Journal 1996 Journal Article

Quantitative Comparison of Functional Magnetic Resonance Imaging with Positron Emission Tomography Using a Force-Related Paradigm

  • Christian Dettmers
  • Alan Connelly
  • Klaus M Stephan
  • Robert Turner
  • Karl J Friston
  • Richard S.J Frackowiak
  • David G Gadian

The intention of our study was to compare functional magnetic resonance imaging (fMRI) with positron emission tomography (PET). We used the same force-related motor paradigm for both techniques, which allows for quantification of stimulus intensity. Regional cerebral blood flow (rCBF) was determined with PET in six male subjects (age 30±3) using the slow bolus injection technique and oxygen-15-labeled water. Scans were collected during six different conditions: at rest and during repetitive Morse key press at 1 Hz, with the right index finger at a range of different forces. In a second series of experiments fMRI data were acquired under similar conditions in six volunteers in a single slice parallel to and 51 ± 3 mm dorsal to the anterior and posterior commissure (AC–PC). A conventional 1. 5-T clinical magnetic resonance (MR) system and the FLASH technique were used. The data obtained in both series of experiments were subjected to the same statistical analyses. Statistical parametric maps (SPM) were generated by two different approaches: a correlation between peak force and rCBF or fMRI signal and using a categorical comparison of force exerted with rest. SPMs were coregistered with anatomical MR images. PET and fMRI measurements demonstrated activation in the primary motor cortex (M1) and posterior supplementary motor cortex in all subjects. Correlation analysis demonstrated foci in the M1 in four subjects with PET and in only one subject with fMRI. Locations of activation peaks differed by 2 to 8 mm between imaging methods. The relationship between fMRI signal or rCBF and peak force was logarithmic. The maximum increase in fMRI signal was 5. 0% ± 0. 9 at 60% of the maximum voluntary contraction while the corresponding increase in rCBF was 13. 7% ± 1. 2. The ratio of percentage rCBF change to percentage fMRI signal change was very similar across all force levels. The high degree of correspondence between PET and fMRI data provides good cross-validation for the two techniques.

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