Test-retest reliability of structural brain networks from diffusion MRI

Structural brain networks constructed from diffusion MRI (dMRI) and tractography have been demonstrated in healthy volunteers and more recently in various disorders affecting brain connectivity. However, few studies have addressed the reproducibility of the resulting networks. We measured the test–retest properties of such networks by varying several factors affecting network construction using ten healthy volunteers who underwent a dMRI protocol at 1.5 T on two separate occasions. Each T1-weighted brain was parcellated into 84 regions-of-interest and network connections were identified using dMRI and two alternative tractography algorithms, two alternative seeding strategies, a white matter waypoint constraint and three alternative network weightings. In each case, four common graph-theoretic measures were obtained. Network properties were assessed both node-wise and per network in terms of the intraclass correlation coefficient (ICC) and by comparing within- and between-subject differences. Our findings suggest that test–retest performance was improved when: 1) seeding from white matter, rather than grey; and 2) using probabilistic tractography with a two-fibre model and sufficient streamlines, rather than deterministic tensor tractography. In terms of network weighting, a measure of streamline density produced better test–retest performance than tract-averaged diffusion anisotropy, although it remains unclear which is a more accurate representation of the underlying connectivity. For the best performing configuration, the global within-subject differences were between 3.2% and 11.9% with ICCs between 0.62 and 0.76. The mean nodal within-subject differences were between 5.2% and 24.2% with mean ICCs between 0.46 and 0.62. For 83.3% (70/84) of nodes, the within-subject differences were smaller than between-subject differences. Overall, these findings suggest that whilst current techniques produce networks capable of characterising the genuine between-subject differences in connectivity, future work must be undertaken to improve network reliability

Altered white matter connectivity associated with visual hallucinations following occipital stroke

Introduction: Visual hallucinations that arise following vision loss stem from aberrant functional activity in visual cortices and an imbalance of activity across associated cortical and subcortical networks subsequent to visual pathway damage. We sought to determine if structural changes in white matter connectivity play a role in cases of chronic visual hallucinations associated with visual cortical damage. Methods: We performed diffusion tensor imaging (DTI) and probabilistic fiber tractography to assess white matter connectivity in a patient suffering from continuous and disruptive phosphene (simple) visual hallucinations for more than 2 years following right occipital stroke. We compared these data to that of healthy age-matched controls. Results: Probabilistic tractography to reconstruct white matter tracts suggests regeneration of terminal fibers of the ipsilesional optic radiations in the patient. However, arrangement of the converse reconstruction of these tracts, which were seeded from the ipsilesional visual cortex to the intrahemispheric lateral geniculate body, remained disrupted. We further observed compromised structural characteristics, and changes in diffusion (measured using diffusion tensor indices) of white matter tracts in the patient connecting the visual cortex with frontal and temporal regions, and also in interhemispheric connectivity between visual cortices. Conclusions: Cortical remapping and the disruption of communication between visual cortices and remote regions are consistent with our previous functional magnetic resonance imaging (fMRI) data showing imbalanced functional activity of the same regions in this patient (Rafique et al, 2016, Neurology, 87, 1493–1500). Long-term adaptive and disruptive changes in white matter connectivity may account for the rare nature of cases presenting with chronic and continuous visual hallucinations.York University Librarie

Beyond Crossing Fibers: Tractography Exploiting Sub-voxel Fibre Dispersion and Neighbourhood Structure

In this paper we propose a novel algorithm which leverages models of white matter fibre dispersion to improve tractography. Tractography methods exploit directional information from diffusion weighted magnetic resonance (DW-MR) imaging to infer connectivity between different brain regions. Most tractography methods use a single direction (e.g. the principal eigenvector of the diffusion tensor) or a small set of discrete directions (e.g. from the peaks of an orientation distribution function) to guide streamline propagation. This strategy ignores the effects of within-bundle orientation dispersion, which arises from fanning or bending at the sub-voxel scale, and can lead to missing connections. Various recent DW-MR imaging techniques estimate the fibre dispersion in each bundle directly and model it as a continuous distribution. Here we introduce an algorithm to exploit this information to improve tractography. The algorithm further uses a particle filter to probe local neighbourhood structure during streamline propagation. Using information gathered from neighbourhood structure enables the algorithm to resolve ambiguities between converging and diverging fanning structures, which cannot be distinguished from isolated orientation distribution functions. We demonstrate the advantages of the new approach in synthetic experiments and in vivo data. Synthetic experiments demonstrate the effectiveness of the particle filter in gathering and exploiting neighbourhood information in recovering various canonical fibre configurations and experiments with in vivo brain data demonstrate the advantages of utilising dispersion in tractography, providing benefits in practical situations. © 2013 Springer-Verlag

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments

MRI Tractography of Corticospinal Tract and Arcuate Fasciculus in High-Grade Gliomas Performed by Constrained Spherical Deconvolution: Qualitative and Quantitative Analysis

BACKGROUND AND PURPOSE: MR imaging tractography is increasingly used to perform noninvasive presurgical planning for brain gliomas. Recently, constrained spherical deconvolution tractography was shown to overcome several limitations of commonly used DTI tractography. The purpose of our study was to evaluate WM tract alterations of both the corticospinal tract and arcuate fasciculus in patients with high-grade gliomas, through qualitative and quantitative analysis of probabilistic constrained spherical deconvolution tractography, to perform reliable presurgical planning. MATERIALS AND METHODS: Twenty patients with frontoparietal high-grade gliomas were recruited and evaluated by using a 3T MR imaging scanner with both morphologic and diffusion sequences (60 diffusion directions). We performed probabilistic constrained spherical deconvolution tractography and tract quantification following diffusion tensor parameters: fractional anisotropy; mean diffusivity; linear, planar, and spherical coefficients. RESULTS: In all patients, we obtained tractographic reconstructions of the medial and lateral portions of the corticospinal tract and arcuate fasciculus, both on the glioma-affected and nonaffected sides of the brain. The affected lateral corticospinal tract and the arcuate fasciculus showed decreased fractional anisotropy ( z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) and linear coefficient ( z = 2.51, n = 20, P = .006; z = 2.52, n = 20, P = .006) along with increased spherical coefficient ( z = −2.51, n = 20, P = .006; z = −2.52, n = 20, P = .006). Mean diffusivity values were increased only in the lateral corticospinal tract ( z = −2.53, n = 20, P = .006). CONCLUSIONS: In this study, we demonstrated that probabilistic constrained spherical deconvolution can provide essential qualitative and quantitative information in presurgical planning, which was not otherwise achievable with DTI. These findings can have important implications for the surgical approach and postoperative outcome in patients with glioma

New insights into cortico-basal-cerebellar connectome: clinical and physiological considerations

The current model of the basal ganglia system based on the 'direct', 'indirect' and 'hyperdirect' pathways provides striking predictions about basal ganglia function that have been used to develop deep brain stimulation approaches for Parkinson's disease and dystonia. The aim of this review is to challenge this scheme in light of new tract tracing information that has recently become available from the human brain using MRI-based tractography, thus providing a novel perspective on the basal ganglia system. We also explore the implications of additional direct pathways running from cortex to basal ganglia and between basal ganglia and cerebellum in the pathophysiology of movement disorders

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means

Combining tractography and cortical measures to test system-specific hypotheses in multiple sclerosis

The objective was to test three motor system-specific hypotheses in multiple sclerosis patients: (i) corticospinal tract and primary motor cortex imaging measures differ between multiple sclerosis patients and controls; (ii) in patients, these measures correlate with disability; (iii) in patients, corticospinal tract measures correlate with measures of the ipsilateral primary motor cortex