Changes in Resting-State Neural Activity and Nerve Fibres in Ischaemic Stroke Patients with Hemiplegia.

Many neuroimaging studies have reported that stroke induces abnormal brain activity. However, little is known about resting-state networks (RSNs) and the corresponding white matter changes in stroke patients with hemiplegia. Here, we utilized functional magnetic resonance imaging (fMRI) to measure neural activity and related fibre tracts in 14 ischaemic stroke patients with hemiplegia and 12 healthy controls. Fractional amplitude of low-frequency fluctuations (fALFF) calculation and correlation analyses were used to assess the relationship between regional neural activity and movement scores. Tractography was performed using diffusion tensor imaging (DTI) data to analyse the fibres passing through the regions of interest. Compared with controls, stroke patients showed abnormal functional connectivity (FC) between some brain regions in the RSNs. The fALFF was increased in the contralesional parietal lobe, with the regional fALFF being correlated with behavioural scores in stroke patients. Additionally, the passage of fibres across regions with reduced FC in the RSNs was increased in stroke patients. This study suggests that structural remodelling of functionally relevant white matter tracts is probably an adaptive response that compensates for injury to the brain.

The Brainstem Cavernoma Case Series: A Formula for Surgery and Surgical Technique.

Background and Objectives: Cavernous malformations (CM) are vascular malformations with low blood flow. The removal of brainstem CMs (BS) is associated with high surgical morbidity, and there is no general consensus on when to treat deep-seated BS CMs. The aim of this study is to compare the surgical outcomes of a series of deep-seated BS CMs with the surgical outcomes of a series of superficially located BS CMs operated on at the Department of Neurosurgery, College of Tuebingen, Germany. Materials and Methods: A retrospective evaluation was performed using patient charts, surgical video recordings, and outpatient examinations. Factors were identified in which surgical intervention was performed in cases of BS CMs. Preoperative radiological examinations included MRI and diffusion tensor imaging (DTI). For deep-seated BS CMs, a voxel-based 3D neuronavigation system and electrophysiological mapping of the brainstem surface were used. Results: A total of 34 consecutive patients with primary superficial (n = 20/58.8%) and deep-seated (n = 14/41.2%) brainstem cavernomas (BS CM) were enrolled in this comparative study. Complete removal was achieved in 31 patients (91.2%). Deep-seated BS CMs: The mean diameter was 14.7 mm (range: 8.3 to 27.7 mm). All but one of these lesions were completely removed. The median follow-up time was 5.8 years. Two patients (5.9%) developed new neurologic deficits after surgery. Superficial BS CMs: The median diameter was 14.9 mm (range: 7.2 to 27.3 mm). All but two of the superficial BS CMs could be completely removed. New permanent neurologic deficits were observed in two patients (5.9%) after surgery. The median follow-up time in this group was 3.6 years. Conclusions: The treatment of BS CMs remains complex. However, the results of this study demonstrate that with less invasive posterior fossa approaches, brainstem mapping, and neuronavigation combined with the use of a blunt "spinal cord" dissection technique, deep-seated BS CMs can be completely removed in selected cases, with good functional outcomes comparable to those of superficial BS CM.

Uncrossed corticospinal tract in health and genetic disorders: Review, case report, and clinical implications.

BACKGROUND AND PURPOSE: Crossing pathologies of the corticospinal tract (CST) are rare and often associated with genetic disorders. However, they can be present in healthy humans and lead to ipsilateral motor deficits when a lesion to motor areas occurs. Here, we review historical and current literature of CST crossing pathologies and present a rare case of asymmetric crossing of the CST. METHODS: Description of the case and systematic review of the literature were based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The PubMed database was searched for peer-reviewed articles in English since 1950. All articles on ipsilateral stroke, uncrossed CST, and associated neurologic disorders were screened. Furthermore, a literature review between the years 1850 and 1980 including articles in other languages, books, opinions, and case studies was conducted. RESULTS: Only a few descriptions of CST crossing pathologies exist in healthy humans, whereas they seem to be more common in genetic disorders such as horizontal gaze palsy with progressive scoliosis or congenital mirror movements. Our patient presented with aphasia and left-sided hemiparesis. Computed tomographic (CT) scan revealed a perfusion deficit in the left middle cerebral artery territory, which was confirmed by diffusion-weighted magnetic resonance imaging (MRI), so that thrombolysis was administered. Diffusion tensor imaging with fibre tracking revealed an asymmetric CST crossing. CONCLUSIONS: The knowledge of CST crossing pathologies is essential if a motor deficit occurs ipsilateral to the lesion side. An ipsilateral deficit should not lead to exclusion or delay of therapeutic options in patients with suspected stroke. Here, a combined evaluation of CT perfusion imaging and MRI diffusion imaging may be of advantage.

Track-weighted imaging methods: extracting information from a streamlines tractogram.

A whole-brain streamlines data-set (so-called tractogram) generated from diffusion MRI provides a wealth of information regarding structural connectivity in the brain. Besides visualisation strategies, a number of post-processing approaches have been proposed to extract more detailed information from the tractogram. One such approach is based on exploiting the information contained in the tractogram to generate track-weighted (TW) images. In the track-weighted imaging (TWI) approach, a very large number of streamlines are often generated throughout the brain, and an image is then computed based on properties of the streamlines themselves (e.g. based on the number of streamlines in each voxel, or their average length), or based on the values of an associated image (e.g. a diffusion anisotropy map, a T2 map) measured at the coordinates of the streamlines. This review article describes various approaches used to generate TW images and discusses the flexible formalism that TWI provides to generate a range of images with very different contrast, as well as the super-resolution properties of the resulting images. It also explains how this approach provides a powerful means to study structural and functional connectivity simultaneously. Finally, a number of key issues for its practical implementation are discussed.

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

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.

Resection of highly language-eloquent brain lesions based purely on rTMS language mapping without awake surgery.

BACKGROUND: The resection of left-sided perisylvian brain lesions harbours the risk of postoperative language impairment. Therefore the individual patient's language distribution is investigated by intraoperative direct cortical stimulation (DCS) during awake surgery. Yet, not all patients qualify for awake surgery. Non-invasive language mapping by repetitive navigated transcranial magnetic stimulation (rTMS) has frequently shown a high correlation in comparison with the results of DCS language mapping in terms of language-negative brain regions. The present study analyses the extent of resection (EOR) and functional outcome of patients who underwent left-sided perisylvian resection of brain lesions based purely on rTMS language mapping. METHODS: Four patients with left-sided perisylvian brain lesions (two gliomas WHO III, one glioblastoma, one cavernous angioma) underwent rTMS language mapping prior to surgery. Data from rTMS language mapping and rTMS-based diffusion tensor imaging fibre tracking (DTI-FT) were transferred to the intraoperative neuronavigation system. Preoperatively, 5 days after surgery (POD5), and 3 months after surgery (POM3) clinical follow-up examinations were performed. RESULTS: No patient suffered from a new surgery-related aphasia at POM3. Three patients underwent complete resection immediately, while one patient required a second rTMS-based resection some days later to achieve the final, complete resection. CONCLUSIONS: The present study shows for the first time the feasibility of successfully resecting language-eloquent brain lesions based purely on the results of negative language maps provided by rTMS language mapping and rTMS-based DTI-FT. In very select cases, this technique can provide a rescue strategy with an optimal functional outcome and EOR when awake surgery is not feasible.

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

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.

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

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.

Optimal preservation of porcine cardiac tissue prior to diffusion tensor magnetic resonance imaging.

The effects of ex vivo preservation techniques on the quality of diffusion tensor magnetic resonance imaging in hearts are poorly understood, and the optimal handling procedure prior to investigation remains to be determined. Therefore, 24 porcine hearts were examined in six groups treated with different preservation techniques, including chemical fixation and freezing. Diffusion properties of each heart were assessed with diffusion tensor imaging in terms of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da) and radial diffusivity (Dr). Tractography was performed to visualize the course of the cardiomyocytes, assuming greater diffusivity in the longitudinal than the transverse axis of individual cardiomyocytes. Significant differences in MD, Da and Dr were found, as well as in FA between groups (P < 0.001). Freezing of specimens resulted in the lowest mean FA of 0.21 (0.06) and highest Dr of 8.92 (1.5) mm2 s(-1) . The highest mean FA was found to be 0.43 (0.11) in hearts perfusion-fixed with formalin. Calculated tractographies were indistinguishable among groups except in frozen specimens, where no fibres could be tracked. Perfusion fixation with formalin provided the best tractography, but immersion fixation yielded diffusion data most similar to fresh hearts. These findings suggest that parameters derived from diffusion tensor imaging in ex vivo hearts are sensitive to fixation and storage methods. In particular, freezing of specimens should be avoided prior to diffusion tensor imaging investigation due to significant changes in diffusion parameters and subsequent image deteriorations.

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

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.

MRI tractography-guided PET image reconstruction regularisation using connectome-based nonlocal means filtering.

Positron emission tomography (PET) molecular biomarkers and diffusion magnetic resonance imaging (dMRI) derived information show associations and highly complementary information in a number of neurodegenerative conditions, including Alzheimer's disease. Diffusion MRI provides valuable information about the microstructure and structural connectivity (SC) of the brain which could guide and improve the PET image reconstruction when such associations exist. However, this potental has not been previously explored. In the present study, we propose a CONNectome-based non-local means one-atep late maximuma posteriori(CONN-NLM-OSLMAP) method, which allows diffusion MRI-derived connectivity information to be incorporated into the PET iterative image reconstruction process, thus regularising the estimated PET images. The proposed method was evaluated using a realistic tau-PET/MRI simulated phantom, demonstrating more effective noise reduction and lesion contrast improvement, as well as the lowest overall bias compared with both a median filter applied as an alternative regulariser and CONNectome-based non-local means as a post-reconstruction filter. By adding complementary SC information from diffusion MRI, the proposed regularisation method offers more useful and targeted denoising and regularisation, demonstrating the feasibility and effectiveness of integrating connectivity information into PET image reconstruction.

Diffusion MRI tractography for neurosurgery: the basics, current state, technical reliability and challenges.

Diffusion magnetic resonance imaging (dMRI) tractography is currently the only imaging technique that allows for non-invasive delineation and visualisation of white matter (WM) tractsin vivo,prompting rapid advances in related fields of brain MRI research in recent years. One of its major clinical applications is for pre-surgical planning and intraoperative image guidance in neurosurgery, where knowledge about the location of WM tracts nearby the surgical target can be helpful to guide surgical resection and optimise post-surgical outcomes. Surgical injuries to these WM tracts can lead to permanent neurological and functional deficits, making the accuracy of tractography reconstructions paramount. The quality of dMRI tractography is influenced by many modifiable factors, ranging from MRI data acquisition through to the post-processing of tractography output, with the potential of error propagation based on decisions made at each and subsequent processing steps. Research over the last 25 years has significantly improved the anatomical accuracy of tractography. An updated review about tractography methodology in the context of neurosurgery is now timely given the thriving research activities in dMRI, to ensure more appropriate applications in the clinical neurosurgical realm. This article aims to review the dMRI physics, and tractography methodologies, highlighting recent advances to provide the key concepts of tractography-informed neurosurgery, with a focus on the general considerations, the current state of practice, technical challenges, potential advances, and future demands to this field.

Morphological determinants of bite force capacity in insects: a biomechanical analysis of polymorphic leaf-cutter ants.

The extraordinary success of social insects is partially based on division of labour, i.e. individuals exclusively or preferentially perform specific tasks. Task preference may correlate with morphological adaptations so implying task specialization, but the extent of such specialization can be difficult to determine. Here, we demonstrate how the physical foundation of some tasks can be leveraged to quantitatively link morphology and performance. We study the allometry of bite force capacity in Atta vollenweideri leaf-cutter ants, polymorphic insects in which the mechanical processing of plant material is a key aspect of the behavioural portfolio. Through a morphometric analysis of tomographic scans, we show that the bite force capacity of the heaviest colony workers is twice as large as predicted by isometry. This disproportionate 'boost' is predominantly achieved through increased investment in muscle volume; geometrical parameters such as mechanical advantage, fibre length or pennation angle are likely constrained by the need to maintain a constant mandibular opening range. We analyse this preference for an increase in size-specific muscle volume and the adaptations in internal and external head anatomy required to accommodate it with simple geometric and physical models, so providing a quantitative understanding of the functional anatomy of the musculoskeletal bite apparatus in insects.

Diffusion MRI in the brain - Theory and concepts.

Over the past two decades, diffusion MRI has become an essential tool in neuroimaging investigations. This is due to its sensitivity to the motion of water molecules as they diffuse through the microstructural environment, allowing diffusion MRI to be used as a 'probe' of tissue microstructure. Furthermore, this sensitivity is strongly direction-dependent, notably in brain white matter, due to the alignment of structures that restrict or hinder the motion of water molecules, notably axonal membranes. This provides a means of inferring the orientation of fibres in vivo, and by use of appropriate fibre-tracking algorithms, of delineating the path of white matter tracts in the brain. The ability to perform so-called tractography in humans in vivo non-invasively is unique to diffusion MRI, and is now used in applications such as neurosurgery planning and more broadly within investigations of brain connectomics. This review describes the theory and concepts of diffusion MRI and describes its most important areas of application in the brain, with a strong focus on tractography.

The Seven Deadly Sins of Measuring Brain Structural Connectivity Using Diffusion MRI Streamlines Fibre-Tracking.

There is great interest in the study of brain structural connectivity, as white matter abnormalities have been implicated in many disease states. Diffusion magnetic resonance imaging (MRI) provides a powerful means to characterise structural connectivity non-invasively, by using a fibre-tracking algorithm. The most widely used fibre-tracking strategy is based on the step-wise generation of streamlines. Despite their popularity and widespread use, there are a number of practical considerations that must be taken into account in order to increase the robustness of streamlines tracking results, particularly when these methods are used to study brain structural connectivity, and the connectome. This review article describes what we consider the 'seven deadly sins' of mapping structural connections using diffusion MRI streamlines fibre-tracking, with particular emphasis on 'sins' that can be practically avoided and they can have an important impact in the results. It is shown that there are important 'deadly sins' to be avoided at every step of the pipeline, such as during data acquisition, during data modelling to estimate local fibre architecture, during the fibre-tracking process itself, and during quantification of the tracking results. The recommendations here are intended to inform users on potential important shortcomings of their current tracking protocols, as well as to guide future users on some of the key issues and decisions that must be faced when designing their processing pipelines.

A multimodal data-set of a unidirectional glass fibre reinforced polymer composite.

A unidirectional (UD) glass fibre reinforced polymer (GFRP) composite was scanned at varying resolutions in the micro-scale with several imaging modalities. All six scans capture the same region of the sample, containing well-aligned fibres inside a UD load-carrying bundle. Two scans of the cross-sectional surface of the bundle were acquired at a high resolution, by means of scanning electron microscopy (SEM) and optical microscopy (OM), and four volumetric scans were acquired through X-ray computed tomography (CT) at different resolutions. Individual fibres can be resolved from these scans to investigate the micro-structure of the UD bundle. The data is hosted at https://doi.org/10.5281/zenodo.1195879 and it was used in Emerson et al. (2018) [1] to demonstrate that precise and representative characterisations of fibre geometry are possible with relatively low X-ray CT resolutions if the analysis method is robust to image quality.

Track-weighted dynamic functional connectivity (TW-dFC): a new method to study time-resolved functional connectivity.

Interest in the study of brain connectivity is growing, particularly in understanding the dynamics of the structural/functional connectivity relation. Structural and functional connectivity are most often analysed independently of each other. Track-weighted functional connectivity (TW-FC) was recently proposed as a means to combine structural/functional connectivity information into a single image. We extend here TW-FC in two important ways: first, all the functional data are used without having to define a prior functional network (cf. TW-FC generates a map for a pre-specified network); second, we incorporate time-resolved connectivity information, thus allowing dynamic characterisation of functional connectivity. We refer to this technique as track-weighted dynamic functional connectivity (TW-dFC), which fuses structural/functional connectivity data into a four-dimensional image, providing a new approach to investigate dynamic connectivity. The structural connectivity information effectively 'constrains' the extremely large number of possible connections in the functional connectivity data (i.e. each voxel's connection to every other voxel), thus providing a way of reducing the problem's dimensionality while still maintaining key data features. The methodology is demonstrated in data from eight healthy subjects, and independent component analysis was subsequently applied to parcellate the corpus callosum, as an illustration of a possible application. TW-dFC maps demonstrate that different white matter pathways can have very different temporal characteristics, corresponding to correlated fluctuations in the grey matter regions they link. A realistic parcellation of the corpus callosum was generated, which was qualitatively similar to topography previously reported. TW-dFC, therefore, provides a complementary new tool to investigate the dynamic nature of brain connectivity.

Perpendicular fibre tracking for neural fibre bundle analysis using diffusion MRI.

Information on the directionality and structure of axonal fibres in neural tissue can be obtained by analysing diffusion-weighted MRI data sets. Several fibre tracking algorithms have been presented in the literature that trace the underlying field of principal orientations of water diffusion, which correspond to the local primary eigenvectors of the diffusion tensor field. However, the majority of the existing techniques ignore the secondary and tertiary orientations of diffusion, which contain significant information on the local patterns of diffusion. In this paper, we introduce the idea of perpendicular fibre tracking and present a novel dynamic programming method that traces surfaces, which are locally perpendicular to the axonal fibres. This is achieved by using a cost function, with geometric and fibre orientation constraints, that is evaluated dynamically for every voxel in the image domain starting from a given seed point. The proposed method is tested using synthetic and real DW-MRI data sets. The results conclusively demonstrate the accuracy and effectiveness of our method.