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Non‐invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI
Magnetic Resonance in Medicine
Abstract
A technique for assessing in vivo fiber connectivity in the human brain is presented. The method utilizes a novel connectivity algorithm that operates in three spatial dimensions and uses estimates of fiber tract orientation and tissue anisotropy, obtained from diffusion tensor magnetic resonance imaging, to establish the pathways of fiber tracts. Sample in vivo connectivity images from healthy human brain are presented that demonstrate connections in the white matter tracts. White matter connectivity information is potentially of interest in the study of a range of neurological, psychiatric, and developmental disorders and shows promise for following the natural history of disease. Magn Reson Med 42:37–41, 1999. © 1999 Wiley-Liss, Inc.
... Changes in FA and/or AD of the superior (including temporal aspects) and inferior longitudinal fasciculi in the patient (Table 1) are therefore not surprising given the disruption to diffusivity at the stroke site (Figure 1), and consequent changes in tractography between regions concerned with these fasciculi (Figures 2-3). Altered FA suggests changes to white matter microstructure (Jones, Simmons, Williams, & Horsfield, 1999) indicative of change in aspects of connectivity (Jones, Knösche, & Turner, 2013). AD measures are considered variable in white matter changes and pathology; however, a decrease is observed in axonal injury/damage (Song et al., 2002). ...
... Reduced FA of the contralesional anterior thalamic radiation in the patient (Table 1), which connects the anterior and dorsomedial thalamic nuclei with the prefrontal cortex (Wakana et al., 2004), suggests changes to white matter microstructure and connectivity of this tract (Jones et al., 1999(Jones et al., , 2013. Thalamic degeneration is previously implicated in visual hallucinations (Manford & Andermann, 1998), consistent with its involvement in this patient. ...
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.
... Two main techniques to do so are typically diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI). The dMRI estimates the axonal orientations which are consecutively used to calculate white matter fiber tracts between brain regions, i.e., structural connectivity, using tractography algorithms [10,11]. The rs-fMRI data are used to calculate functional connectivity as the correlation between temporal changes in the blood-oxygen-level-dependent (BOLD) signal of spatially distinct brain regions [12,13]. ...
In population-based cohort studies, magnetic resonance imaging (MRI) is vital for examining brain structure and function. Advanced MRI techniques, such as diffusion-weighted MRI (dMRI) and resting-state functional MRI (rs-fMRI), provide insights into brain connectivity. However, biases in MRI data acquisition and processing can impact brain connectivity measures and their associations with demographic and clinical variables. This study, conducted with 5110 participants from The Maastricht Study, explored the relationship between brain connectivity and various image quality metrics (e.g., signal-to-noise ratio, head motion, and atlas–template mismatches) that were obtained from dMRI and rs-fMRI scans. Results revealed that in particular increased head motion (R2 up to 0.169, p < 0.001) and reduced signal-to-noise ratio (R2 up to 0.013, p < 0.001) negatively impacted structural and functional brain connectivity, respectively. These image quality metrics significantly affected associations of overall brain connectivity with age (up to −59%), sex (up to −25%), and body mass index (BMI) (up to +14%). Associations with diabetes status, educational level, history of cardiovascular disease, and white matter hyperintensities were generally less affected. This emphasizes the potential confounding effects of image quality in large population-based neuroimaging studies on brain connectivity and underscores the importance of accounting for it.
... Its extension to diffusion tensor imaging (DTI), based on estimating the components of the apparent diffusion coefficient along multiple directions, enables to determine tissue microstructure anisotropies which are very useful for tracking brain connectivity [34][35][36][37][38][39]. Nevertheless, there are cases where the anisotropy of the apparent diffusion tensor is small, as occurs in wide compartments or in fiber crossing regions in brain, and the application of DTI it is thus limited [37,[40][41][42]. ...
Magnetic resonance imaging is a powerful, non invasive tool for medical diagnosis. The low sensitivity for detecting the nuclear spin signals, typically limits the image resolution to several tens of micrometers in preclinical systems and millimeters in clinical scanners. Other sources of information, derived from diffusion processes of intrinsic molecules as water in the tissues, allow getting morphological information at micrometric and submicrometric scales as potential biomarkers of several pathologies. Here we consider extracting this morphological information by probing the distribution of internal magnetic field gradients induced by the heterogeneous magnetic susceptibility of the medium. We use a cumulant expansion to derive the dephasing on the spin signal induced by the molecules that explore these internal gradients while diffuse. Based on the cumulant expansion, we define internal gradient distributions tensors (IGDT) and propose modulating gradient spin echo sequences to probe them. These IGDT contain microstructural morphological information that characterize porous media and biological tissues. We evaluate the IGDT effects on the magnetization decay with typical conditions of brain tissue and show their effects can be experimentally observed. Our results thus provide a framework for exploiting IGDT as quantitative diagnostic tools.
... Recent advances in neuroscientific methods have opened up new avenues for probing the relationship between structure and function. Diffusion magnetic resonance imaging (dMRI) tractography (Jones et al. 1999;Conturo et al. 1999) enables in vivo investigation of the brain's white matter connections across large samples. By following the direction of the greatest diffusivity of water molecules, one can extract orientational information and virtually reconstruct the CST (Jones 2008). ...
Probing the brain structure–function relationship is at the heart of modern neuroscientific explorations, enabled by recent advances in brain mapping techniques. This study aimed to explore the anatomical blueprint of corticospinal excitability and shed light on the structure–function relationship within the human motor system. Using diffusion magnetic resonance imaging tractography, based on the spherical deconvolution approach, and transcranial magnetic stimulation (TMS), we show that anatomical inter-individual variability of the corticospinal tract (CST) modulates the corticospinal excitability and conductivity. Our findings show for the first time the relationship between increased corticospinal excitability and conductivity in individuals with a bigger CST (i.e., number of streamlines), as well as increased corticospinal microstructural organization (i.e., fractional anisotropy). These findings can have important implications for the understanding of the neuroanatomical basis of TMS as well as the study of the human motor system in both health and disease.
... MRI data were collected at 3T (Philips Achieva) using a thirty-two channel receive-only head RF coil. A diffusionweighted spin-echo echo-planar imaging sequence was used to acquire high angular resolution diffusion weighted images (HARDI) (Jones et al., 1999). One hundred twenty-eight gradient orientations and six unweighted (b = 0 s/mm2) images were acquired with the following parameters: TR/TE = 10000/76 ms, b = 1,000 s/mm 2 , 60 slices, slice thickness = 2 mm, FOV = 224 × 224, acquisition matrix = 112 × 112, resulting in data acquired with a 2 mm 3 isotropic resolution. ...
The ability to generate probabilistic expectancies regarding when and where sensory stimuli will occur, is critical to derive timely and accurate inferences about updating contexts. However, the existence of specialized neural networks for inferring predictive relationships between events is still debated. Using graph theoretical analysis applied to structural connectivity data, we tested the extent of brain connectivity properties associated with spatio-temporal predictive performance across 29 healthy subjects. Participants detected visual targets appearing at one out of three locations after one out of three intervals; expectations about stimulus location (spatial condition) or onset (temporal condition) were induced by valid or invalid symbolic cues. Connectivity matrices and centrality/segregation measures, expressing the relative importance of, and the local interactions among specific cerebral areas respect to the behavior under investigation, were calculated from whole-brain tractography and cortico-subcortical parcellation. Results: Response preparedness to cued stimuli relied on different structural connectivity networks for the temporal and spatial domains. Significant covariance was observed between centrality measures of regions within a subcortical-fronto-parietal-occipital network -comprising the left putamen, the right caudate nucleus, the left frontal operculum, the right inferior parietal cortex, the right paracentral lobule and the right superior occipital cortex-, and the ability to respond after a short cue-target delay suggesting that the local connectedness of such nodes plays a central role when the source of temporal expectation is explicit. When the potential for functional segregation was tested, we found highly clustered structural connectivity across the right superior, the left middle inferior frontal gyrus and the left caudate nucleus as related to explicit temporal orienting. Conversely, when the interaction between explicit and implicit temporal orienting processes was considered at the long interval, we found that explicit processes were related to centrality measures of the bilateral inferior parietal lobule. Degree centrality of the same region in the left hemisphere covaried with behavioral measures indexing the process of attentional re-orienting. These results represent a crucial step forward the ordinary predictive processing description, as we identified the patterns of connectivity characterizing the brain organization associated with the ability to generate and update temporal expectancies in case of contextual violations.
... Brain MRI data were acquired with a 1.5-Tesla scanner (GE Healthcare, Milwaukee, Wisconsin) using an eight-channel head coil during a 30-min brain imaging protocol that was previously described in detail (Ikram et al. 2011;Jones et al. 1999). Two trained technicians performed all examinations in a standardized way. ...
To determine the association between meditation and yoga practice, experienced stress, and amygdala and hippocampal volume in a large population-based study. This study was embedded within the population-based Rotterdam Study and included 3742 participants for cross-sectional association. Participants filled out a questionnaire assessing meditation practice, yoga practice, and experienced stress, and underwent a magnetic resonance scan of the brain. 2397 participants underwent multiple brain scans, and were assessed for structural change over time. Amygdala and hippocampal volumes were regions of interest, as these are structures that may be affected by meditation. Multivariable linear regression analysis and mixed linear models were performed adjusted for age, sex, educational level, intracranial volume, cardiovascular risk, anxiety, depression and stress. 15.7% of individuals participated in at least one form of practice. Those who performed meditation and yoga practices reported significantly more stress (mean difference 0.2 on a 1–5 scale, p < .001) and more depressive symptoms (mean difference 1.03 on CESD, p = .015). Partaking in meditation and yoga practices was associated with a significantly lower right amygdala volume (β = − 31.8 mm³, p = .005), and lower left hippocampus volume (β = − 75.3 mm³, p = .025). Repeated measurements using linear mixed models showed a significant effect over time on the right amygdala of practicing meditation and yoga (β = − 24.4 mm³, SE 11.3, p = .031). Partaking in meditation and yoga practice is associated with more experienced stress while it also helps cope with stress, and is associated with smaller right amygdala volume.
22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12–15 years) and those undergoing typical development (8–18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6–52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.
Aging is associated with changes in the central nervous system and leads to reduced life quality. Here, we investigated the age-related differences in the CNS underlying motor performance deficits using magnetic resonance spectroscopy and diffusion MRI. MRS measured N-acetyl aspartate (NAA), choline (Cho), and creatine (Cr) concentrations in the sensorimotor and occipital cortex, whereas dMRI quantified apparent fiber density (FD) in the same voxels to evaluate white matter microstructural organization. We found that aging was associated with increased reaction time and reduced FD and NAA concentration in the sensorimotor voxel. Both FD and NAA mediated the association between age and reaction time. The NAA concentration was found to mediate the association between age and FD in the sensorimotor voxel. We propose that the age-related decrease in NAA concentration may result in reduced axonal fiber density in the sensorimotor cortex which may ultimately account for the response slowness of older participants.
Although very well adapted to brain study, Magnetic Resonance Imaging (MRI) remains limited by the facilities and capabilities required to acquire data, especially for non-human primates. Addressing the data gaps resulting from these limitations requires making data more accessible and open. In contempt of the regular use of Saimiri sciureus in neuroscience research, in vivo diffusion has yet to be openly available for this species. Here we built and made openly available a unique new resource consisting of a high-resolution, multishell diffusion-weighted dataset in the anesthetized Saimiri sciureus. The data were acquired on 11 individuals with an 11.7 T MRI scanner (isotropic resolution of 400 µm³). This paper presents an overview of our dataset and illustrates some of its possible use through example analyses. To assess the quality of our data, we analyzed long-range connections (whole-brain tractography), microstructure (Neurite Orientation Dispersion and Density Imaging), and axon diameter in the corpus callosum (ActiveAx). Constituting an essential new resource for primate evolution studies, all data are openly available.
The BTBR T⁺Itpr3tf/J (BTBR/J) strain is one of the most valid models of idiopathic autism, serving as a potent forward genetics tool to dissect the complexity of autism. We found that a sister strain with an intact corpus callosum, BTBR TF/ArtRbrc (BTBR/R), showed more prominent autism core symptoms but moderate ultrasonic communication/normal hippocampus-dependent memory, which may mimic autism in the high functioning spectrum. Intriguingly, disturbed epigenetic silencing mechanism leads to hyperactive endogenous retrovirus (ERV), a mobile genetic element of ancient retroviral infection, which increases de novo copy number variation (CNV) formation in the two BTBR strains. This feature makes the BTBR strain a still evolving multiple-loci model toward higher ASD susceptibility. Furthermore, active ERV, analogous to virus infection, evades the integrated stress response (ISR) of host defense and hijacks the transcriptional machinery during embryonic development in the BTBR strains. These results suggest dual roles of ERV in the pathogenesis of ASD, driving host genome evolution at a long-term scale and managing cellular pathways in response to viral infection, which has immediate effects on embryonic development. The wild-type Draxin expression in BTBR/R also makes this substrain a more precise model to investigate the core etiology of autism without the interference of impaired forebrain bundles as in BTBR/J.
Clinical MR Neuroimaging, second edition, provides radiologists, neuroscientists and researchers with a clear understanding of each physiological MR methodology and their applications to the major neurological diseases. Section 1 describes the physical principles underlying each technique and their associated artefacts and pitfalls. Subsequent sections review the application of MRI in a range of clinical disorders: cerebrovascular disease, neoplasia, infection/inflammation/demyelination disorders, seizures, psychiatric/neurodegenerative conditions, and trauma. This new edition includes all recent advances and applications, with greatly increased coverage of permeability imaging, susceptibility imaging, iron imaging, MR spectroscopy and fMRI. All illustrations are completely new, taking advantage of the latest scan capabilities to give images of the highest possible quality. In addition, over 35 new case studies have been included. Editors and contributors are the leading neuroimaging experts worldwide; their unique combination of technical knowledge and clinical expertise makes Clinical MR Neuroimaging the leading text on the subject.
There is a growing body of evidence which suggests that neural disconnectivity is a core pathophysiological feature of autism spectrum disorder (ASD). Brain structural connectivity, a measure of the micro- and macrostructural organization of brain white matter, is typically examined using diffusion-weighted magnetic resonance imaging (DW-MRI). There are multiple DW-MRI analytic approaches including voxel-based analyses, diffusion tractography, and connectomics. A large body of DW-MRI research using these methods has reported atypical organization of white matter microstructural organization in diverse brain regions and white matter tracts in individuals with ASD. The developmental trajectory of white matter is atypical in ASD and appears to be influenced not only by age but also by sex.
Hemispheric lateralization of white matter is abnormal in ASD. The behavioral correlates of disrupted white matter organization require further study, but many studies have reported association between atypical structural connectivity and core features of ASD.
This is the last chapter of the book. This chapter is conceived with the only purpose of analyzing all (or almost all) the imaging modalities and techniques that can be used in the future to identify structural derangements in the ankle-foot derived from diabetes mellitus type 2 (DMT2). As a complication of DMT2, Charcot neuroarthropathy (or diabetic foot) has a complex and enigmatic pathophysiology. Its clinical and radiological manifestations remain ambiguous and oftentimes lead to unfortunate misinterpretations. Charcot neuroarthropathy per se demands understanding and comprehension, which can be obtained only through sophisticated imaging techniques. High efficacy and specificity must be condition sine qua non to visualize and diagnose neuro-myo-arthropathic lesions associated with Charcot foot. Undoubtedly, the modalities discussed herein carry the potentials to improve radiologists’ and other professionals’ ability to understand DMT2-induced Charcot neuro-myo-arthropathy (or diabetic foot).
Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.
Diffusion MRI (dMRI) is a unique tool in the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
Objective:
In the diagnosis of HTLV-1-associated myelopathy (HAM), while magnetic resonance imaging (MRI) is essential to exclude other diseases, its power is limited regarding HAM diagnosis, as only 30% of affected patients present with spinal cord atrophy. Diffusion tensor imaging (DTI) may enable the detection of damage in the white matter microstructure. Here, we quantitatively assess spinal cord damage using DTI and evaluate conventional MRI parameters of the spinal cord in HTLV-1-infected individuals.
Methods:
This cross-sectional study involved 33 HTLV-1 carriers, 28 patients with definite-HAM, and 11 seronegative healthy subjects (HS). Region-of-interest (ROI)-based fractional anisotropy (FA) and mean diffusivity (MD) measurements were performed in the upper thoracic and lumbar regions of the spinal cord. Thoracic index was defined as 1/ (anteroposterior diameter × transverse diameter) measured at the fifth 5th vertebral level. Receiver operating characteristic (ROC) curve analysis was used to determine optimal cutoff FA, MD, and thoracic index values.
Results:
Spinal cord atrophy was observed in 15 (53.6%) patients with definite-HAM. The area under the ROC curve in the thoracic spinal cord was 0.824 (95% CI, 0.716-0.932), 0.839 (95% CI: 0.736-0.942), and 0.838 (95% CI: 0.728-0.949) for FA, MD, and the thoracic index, respectively. Lower FA and higher MD values were observed in the definite-HAM group compared to HTLV-1 carriers and HS at the T5 vertebral level (p < 0.01).
Interpretation:
Complementary to conventional MRI, DTI analysis of the spinal cord and thoracic index determination can offer additional insight that may prove useful in the diagnosis of HAM.
Adolescent depression is characterized by heightened inflammation and altered connectivity of fronto-cingulate-limbic tracts, including the genu of the corpus callosum (CCG) and the uncinate fasciculus (UF). No studies, however, have yet examined the association between inflammation, measured by peripheral levels of cytokines, and white matter connectivity of fronto-cingulate-limbic tracts in adolescents. Here, 56 depressed adolescents (32 females, 3 non-binary; 16.23±1.28 years) and 19 controls (10 females; 15.72±1.17 years) completed a diffusion-weighted MRI scan at 3 Tesla. We conducted deterministic tractography to segment bilateral corpus callosum (genu and splenium) and UF and computed mean fractional anisotropy (FA) in each tract. A subset of participants (43 depressed and 17 healthy controls) also provided dried blood spot samples from which we assayed interleukin 6 (IL-6) and tumor necrosis alpha (TNF-ɑ) using a Luminex multiplex array. Depressed participants did not differ from controls in FA of the corpus callosum or UF (all FDR-corrected ps>0.056) but exhibited higher levels of inflammation than did controls (IL-6: β=0.91, FDR-corrected p=0.006; TNF-α: β=0.76, FDR-corrected p=0.006). Although diagnostic group did not moderate the associations between inflammatory cytokines and FA in the CCG and UF, across both groups, greater peripheral inflammation was associated with lower FA in the CCG (IL-6: β=-0.38; FDR-corrected p=0.044; TNF-ɑ: β=-0.41, FDR-corrected p=0.044). This study is the first to examine associations between peripheral inflammation and white matter microstructure of fronto-cingulate-limbic tracts in depressed and nondepressed adolescents. Future mechanistic studies are needed to confirm our findings; nevertheless, our results suggest that heightened inflammation is an important component of neurophenotypes that are relevant to adolescent depression.
Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.
Magnetic resonance imaging (MRI) is more sensitive than computed tomography (CT) in detecting structural and functional abnormalities of the brain, providing superior structural resolution and tissue contrast. Modalities like positron emission tomography (PET), single-photon emission tomography (SPECT), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) inform us about functional aspects of the brain related to brain metabolism, receptor binding, cerebral blood flow, certain pathological molecular accumulations, and certain molecular changes. Diffusion tensor imaging (DTI) is an MRI method to delineate axonal tracts, utilizing a particular type of diffusion-weighted sequence that measures microstructural water diffusion properties within the brain.
Diffusion MRI (dMRI) tractography is currently the only imaging technique that allows for non-invasive delineation and visualisation of white matter (WM) tracts in vivo prompting rapid advances in related fields of brain MRI research in recent years. One of its major clinical applications is for pre-surgery 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 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 the 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.
The evolution of the folded cortical surface is an iconic feature of the human brain shared by a subset of mammals and considered pivotal for the emergence of higher-order cognitive functions. While our understanding of the neurodevelopmental processes involved in corticogenesis has greatly advanced over the past 70 years of brain research, the fundamental mechanisms that result in gyrification, along with its originating cytoarchitectural location, remain largely unknown. This review brings together numerous approaches to this basic neurodevelopmental problem, constructing a narrative of how various models, techniques and tools have been applied to the study of gyrification thus far. After a brief discussion of core concepts and challenges within the field, we provide an analysis of the significant discoveries derived from the parallel use of model organisms such as the mouse, ferret, sheep and non-human primates, particularly with regard to how they have shaped our understanding of cortical folding. We then focus on the latest developments in the field and the complementary application of newly emerging technologies, such as cerebral organoids, advanced neuroimaging techniques, and atomic force microscopy. Particular emphasis is placed upon the use of novel computational and physical models in regard to the interplay of biological and physical forces in cortical folding.
Diffusion weighted imaging has further pushed the boundaries of neuroscience by allowing us to peer farther into the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We will briefly summarize key questions, that have historically been raised in neuroscience, concerning the brain's white matter. We will then expand on the benefits of diffusion weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this article will highlight the invaluable contribution of diffusion weighted imaging in neuroscience, present its limitations and put forth new challenges for the future generations who may wish to exploit this powerful technology to gain novel insights.
Background
Diffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed.
Methods
A multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers was evaluated.
Results
The SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above.
Conclusion
The single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals). Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have little impact on optic nerve fiber integrity of chimpanzees, in contrast to results for both macaque monkeys and humans.
Diffusion MRI can probe neural fiber orientations through an in vivo measurement of water diffusion on a subvoxel scale, ultimately enabling tracking structural connections in the brain. This chapter introduces the principles behind resolving fiber orientations in diffusion MRI and provides an overview of the models and techniques that have advanced this field over the years. We will first introduce the concept of q→-space as the fundamental descriptor of the diffusion propagator. Subsequently, we will discuss the main developments toward practical, scan-time-efficient fiber orientation modeling, starting with diffusion tensor imaging and moving on to higher-order representations of increasingly complex fiber topologies. We will particularly discuss spherical deconvolution as the most widely adopted approach to modeling fiber orientation distributions. Finally, we will point out the major differences and similarities between the various techniques, distinguishing discrete versus continuous representations and model-based versus data-driven methods.
Water diffusion is the basis of several important contrast mechanisms in Magnetic Resonance Imaging (MRI) experiments. Diffusion MRI techniques are novel in that they provide the opportunity to non-invasively probe characteristics of biological tissue on the cellular size-scale. This chapter provides a definition of the diffusion coefficient and describes fundamental principles involved in using MRI to measure diffusion in vivo. The analysis of water diffusion anisotropy, the directional dependence of water diffusion, in brain tissue is reviewed as an example of the powerful inferences about cellular structure that can be made using diffusion MRI. In addition, the use of diffusion MRI in the detection and study of cerebral ischemia is reviewed. These two applications demonstrate the exquisite sensitivity of diffusion-based MRI contrast to cellular anatomy and physiology, and provide numerous examples of quantitative experimental measurements and analytical modeling approaches for interpreting diffusion MRI data.
“Tractography” refers to the process of digitally reconstructing the spatial trajectories of elongated thin structures based on a continuous field of local orientation data; most commonly in reference to white matter axons within the central nervous system based on a diffusion Magnetic Resonance Imaging (MRI) model. This technology provides a unique capacity to investigate the long-distance connectional structure of such biology both in vivo and noninvasively. This chapter describes the basic principles behind the near-ubiquitous “streamlines” approach to tractography (which has remained relatively unchanged for 20 years) as well as some modern advancements to such, with a particular emphasis on the quantitative capabilities of this technology.
In diffusion MRI, spherical deconvolution approaches can estimate local white matter (WM) fiber orientation distributions (FOD) which can be used to produce fiber tractography reconstructions. The applicability of spherical deconvolution to grey matter (GM), however, is still limited, despite its critical role as start/endpoint of WM fiber pathways. The advent of multi-shell diffusion MRI data offers additional contrast to model the GM signal but, to date, only isotropic models have been applied to GM. Evidence from both histology and high-resolution diffusion MRI studies suggests a marked anisotropic character of the diffusion process in GM, which could be exploited to improve the description of the cortical organization. In this study, we investigated whether performing spherical deconvolution with tissue specific models of both WM and GM can improve the characterization of the latter while retaining state-of-the-art performances in WM. To this end, we developed a framework able to simultaneously accommodate multiple anisotropic response functions to estimate multiple, tissue-specific, fiber orientation distributions (mFODs). As proof of principle, we used the diffusion kurtosis imaging model to represent the WM signal, and the neurite orientation dispersion and density imaging (NODDI) model to represent the GM signal. The feasibility of the proposed approach is shown with numerical simulations and with data from the Human Connectome Project (HCP). The performance of our method is compared to the current state of the art, multi-shell constrained spherical deconvolution (MSCSD). The simulations show that with our new method we can accurately estimate a mixture of two FODs at SNR≥50. With HCP data, the proposed method was able to reconstruct both tangentially and radially oriented FODs in GM, and performed comparably well to MSCSD in computing FODs in WM. When performing fiber tractography, the trajectories reconstructed with mFODs reached the cortex with more spatial continuity and for a longer distance as compared to MSCSD and allowed to reconstruct short trajectories tangential to the cortical folding. In conclusion, we demonstrated that our proposed method allows to perform spherical deconvolution of multiple anisotropic response functions, specifically improving the performances of spherical deconvolution in GM tissue.
Diffusion-weighted magnetic resonance imaging (DW-MRI) tractography is a non-invasive tool to probe neural connections and the structure of the white matter. It has been applied successfully in studies of neurological disorders and normal connectivity. Recent work has revealed that tractography produces a high incidence of false-positive connections, often from “bottleneck” white matter configurations. The rich literature in histological connectivity analysis studies in the macaque monkey enables quantitative evaluation of the performance of tractography algorithms. In this study, we use the intricate connections of frontal, cingulate, and parietal areas, well established by the anatomical literature, to derive a symmetrical histological connectivity matrix composed of 59 cortical areas. We evaluate the performance of fifteen diffusion tractography algorithms, including global, deterministic, and probabilistic state-of-the-art methods for the connectivity predictions of 1,711 distinct pairs of areas, among which 680 are reported connected by the literature. The diffusion connectivity analysis was performed on a different ex-vivo macaque brain, acquired using multi-shell DW-MRI protocol, at high spatial and angular resolutions. Across all tested algorithms, the true-positive and true-negative connections were dominant over false-positives and false-negative connections, respectively. Moreover, three-quarters of streamlines had endpoints location in agreement with histological data, on average. Furthermore, probabilistic streamline tractography algorithms show the best performances in predicting which areas are connected. Altogether, we propose a method for quantitative evaluation of tractography algorithms, which aims at improving the sensitivity and the specificity of diffusion-based connectivity analysis. Overall, those results confirm the usefulness of tractography in predicting connectivity, although errors are produced. Many of the errors result from bottleneck white matter configurations near the cortical grey matter and should be the target of future implementation of methods.
Background
Multi‐b‐valued/multi‐shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal‐to‐noise ratio and has potentially long scan times.
Purpose
To investigate the effects of model‐based denoising with no loss of spatial resolution on multi‐shell breast diffusion MRI; to determine the effects of downsampling on multi‐shell diffusion; and to quantify these effects in multi‐b‐valued (three directions per b‐value) acquisitions.
Study Type
Prospective (“fully‐sampled” multi‐shell) and retrospective longitudinal (multi‐b).
Subjects
One normal subject (multi‐shell) and 10 breast cancer subjects imaging at four timepoints (multi‐b).
Field Strength/Sequence
3T multi‐shell acquisition and 1.5T multi‐b acquisition.
Assessment
The “fully‐sampled” multi‐shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi‐b‐valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity.
Statistical Tests
Parametric paired t‐ test (P < 0.05 considered statistically significant) on mean and coefficient of variation of each metric—the apparent diffusion coefficient (ADC) from all b‐values, fast ADC, slow ADC, and perfusion fraction. Paired and two‐sample t‐ tests for each metric comparing normal and tumor tissue.
Results
In the multi‐shell data, denoising effectively suppressed FA (–45% to –78%), with small biases in mean diffusivity (–5% in normal, +23% in tumor, and –4% in vascular compartments). In the multi‐b data, denoising resulted in small biases to the ADC metrics in tumor and normal contralateral tissue (by –3% to +11%), but greatly reduced the coefficient of variation for every metric (by –1% to –24%). Denoising improved differentiation of tumor and normal tissue regions in most metrics and timepoints; subjectively, image noise level and tumor conspicuity were improved in the fast ADC maps.
Data Conclusion
Model‐based denoising effectively suppressed erroneously high FA and improved the accuracy of diffusivity metrics.
Evidence Level
3
Technical Efficacy Stage
1
Objectives
Although hearing has been shown to interact with sleep, the underlying mechanisms for the interaction remain largely unclear. In the absence of knowledge about the neural pathways that are associated with hearing-sleep interaction, this study aimed to examine whether the auditory radiation, the final portion of the auditory pathway from the cochlea to the cerebral cortex, shows association with sleep duration.
Methods
Using Diffusion Tensor Imaging (DTI) data from enhanced Nathan Kline Institute-Rockland Sample (NKI-RS), we isolated the white matter tracts between the medial geniculate nucleus of the thalamus and Heschl’s gyrus in each individual subject (N = 465) using probabilistic tractography. As a measure of the white matter microstructure integrity, the mean fractional anisotropy (FA) of the whole auditory radiation was examined and tested for an association with sleep length in the Pittsburgh Sleep Assessment Index.
Results
A significant inverse-U shaped association was found between the auditory radiation FA and sleep duration.
Discussion
It is suggested that the auditory radiations are a part of the pathway mediating the sleep-hearing interaction. Although the current study does not resolve the causal relationship between hearing and sleep, it would be the first evidence that the auditory radiation is associated with sleep duration
The field of functional neurosurgery has evolved in tandem with advances in imaging techniques, from the invention of X-rays leading to ventriculography and angiography, which saw the development of stereotactic frames, to the development of conventional MRI techniques, which have allowed for direct surgical targeting and verification based on directly visualised anatomy. Developments in MRI connectivity methods have enabled the exploration of neural networks modulated by surgery. These techniques have been exploited to identify and segment targets not readily visible on conventional MRI, refine existing targets by mapping out functional subzones within the target and explore new diagnostic and therapeutic biomarkers. This chapter presents an overview of these connectivity techniques, with an exemplary focus on the application of diffusion connectivity in tremor surgery.
Purpose:
In diffusion MRI, the actual b-value played out on the scanner may deviate from the nominal value due to magnetic field imperfections. A simple image-based correction method for this problem is presented.
Methods:
The apparent diffusion constant (ADC) of a water phantom was measured voxel-wise along 64 diffusion directions at b = 1000 s/mm2 . The true diffusion constant of water was estimated, considering the phantom temperature. A voxel-wise correction factor, providing an effective b-value including any magnetic field deviations, was determined for each diffusion direction by relating the measured ADC to the true diffusion constant. To test the method, the measured b-value map was used to calculate the corrected voxel-wise ADC for additionally acquired diffusion data sets on the same water phantom and data sets acquired on a small water phantom at three different positions. Diffusion tensor was estimated by applying the measured b-value map to phantom and in vivo data sets.
Results:
The b-value-corrected ADC maps of the phantom showed the expected spatial uniformity as well as a marked improvement in consistency across diffusion directions. The b-value correction for the brain data resulted in a 5.8% and 5.5% decrease in mean diffusivity and angular differences of the primary diffusion direction of 2.71° and 0.73° inside gray and white matter, respectively.
Conclusion:
The actual b-value deviates significantly from its nominal setting, leading to a spatially variable error in the common diffusion outcome measures. The suggested method measures and corrects these artifacts.
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.
Genomic copy number variants (CNVs) are amongst the most highly penetrant genetic risk factors for neuropsychiatric disorders. The scarcity of carriers of individual CNVs and their phenotypical heterogeneity limits investigations of the associated neural mechanisms and endophenotypes. We applied a novel design based on CNV penetrance for schizophrenia (Sz) and developmental delay (DD) that allows us to identify structural sequelae that are most relevant to neuropsychiatric disorders. Our focus on brain structural abnormalities was based on the hypothesis that convergent mechanisms contributing to neurodevelopmental disorders would likely manifest in the macro- and microstructure of white matter and cortical and subcortical grey matter. Twenty one adult participants carrying neuropsychiatric risk CNVs (including those located at 22q11.2, 15q11.2, 1q21.1, 16p11.2 and 17q12) and 15 age- and gender-matched controls underwent T1-weighted structural, diffusion and relaxometry MRI. The macro- and microstructural properties of the cingulum bundles were associated with penetrance for both developmental delay and schizophrenia, in particular curvature along the anterior-posterior axis (Sz: pcorr = 0.026; DD: pcorr = 0.035) and intracellular volume fraction (Sz: pcorr = 0.019; DD: pcorr = 0.064). Further principal component analysis showed alterations in the interrelationships between the volumes of several midline white-matter structures (Sz: pcorr = 0.055; DD: pcorr = 0.027). In particular, the ratio of volumes in the splenium and body of the corpus callosum was significantly associated with both penetrance scores (Sz: p = 0.037; DD; p = 0.006). Our results are consistent with the notion that a significant alteration in developmental trajectories of midline white-matter structures constitutes a common neurodevelopmental aberration contributing to risk for schizophrenia and intellectual disability.
The chemical specificity of nuclear magnetic resonance (NMR) spectroscopy, observed through the chemical shift and scalar coupling patterns, allows the detection of more than 15 metabolites in vivo and more than 50 chemical compounds in bodily fluids in vitro. This chapter is dedicated to the description of dynamic processes in vivo that can be measured by NMR spectroscopy. It discusses the dynamics of T1 and T2 relaxation. When combined with the infusion of exogenous compounds, NMR allows the detection of metabolic fluxes noninvasively in vivo. The chapter also discusses deuterium metabolic imaging and advances in the application of hyperpolarization methods. Spin rotation relaxation arises from magnetic fields at the nucleus generated by coherent rotational motion of the entire molecule, which can couple with the nuclear spin. Saturation recovery is a faster alternative to inversion recovery in which enhanced acquisition speed is traded off against reduced dynamic range.
Despite a prevalence exceeding 1%, mechanisms underlying autism spectrum disorders (ASDs) are poorly understood, and targeted therapies and guiding parameters are urgently needed. We recently demonstrated that cerebellar dysfunction is sufficient to generate autistic-like behaviors in a mouse model of tuberous sclerosis complex (TSC). Here, using the mechanistic target of rapamycin (mTOR)-specific inhibitor rapamycin, we define distinct sensitive periods for treatment of autistic-like behaviors with sensitive periods extending into adulthood for social behaviors. We identify cellular and electrophysiological parameters that may contribute to behavioral rescue, with rescue of Purkinje cell survival and excitability corresponding to social behavioral rescue. In addition, using anatomic and diffusion-based MRI, we identify structural changes in cerebellar domains implicated in ASD that correlate with sensitive periods of specific autism-like behaviors. These findings thus not only define treatment parameters into adulthood, but also support a mechanistic basis for the targeted rescue of autism-related behaviors. : A mechanistic understanding of and establishment of time windows for effective therapy (sensitive periods) for autism-related behaviors remain unknown. Tsai et al. delineate specific time windows for treatment of specific autism-relevant behaviors and evaluate underlying cellular, electrophysiological, and anatomic mechanisms for these sensitive periods. Keywords: sensitive periods, autism, treatment, tuberous sclerosis, cerebellum, Purkinje cell
Despite the potential for better understanding functional neuroanatomy, the complex relationship between neuroimaging measures of brain structure and function has confounded integrative, multimodal analyses of brain connectivity. This is particularly true for task-related effective connectivity, which describes the causal influences between neuronal populations. Here, we assess whether measures of structural connectivity may usefully inform estimates of effective connectivity in larger scale brain networks. To this end, we introduce an integrative approach, capitalising on two recent statistical advances: Parametric Empirical Bayes, which provides group-level estimates of effective connectivity, and Bayesian model reduction, which enables rapid comparison of competing models. Crucially, we show that structural priors derived from high angular resolution diffusion imaging on a dynamic causal model of a 12-region network—based on functional MRI data from the same subjects—substantially improve model evidence (posterior probability 1.00). This provides definitive evidence that structural and effective connectivity depend upon each other in mediating distributed, large-scale interactions in the brain. Furthermore, this work offers novel perspectives for understanding normal brain architecture and its disintegration in clinical conditions.
Electronic supplementary material
The online version of this article (10.1007/s00429-018-1760-8) contains supplementary material, which is available to authorized users.
Epilepsy is a chronic neurologic disorder characterized by unpredictable, recurrent, unprovoked seizures. It is the fourth most common neurologic disorder and affects people of all ages. A substantial number of epilepsies are well controlled with the administration of suitable antiepileptic medication. However, approximately 20–30% of epilepsy cases can be medically intractable, and hence there is an increasing interest in surgical approaches for seizure abolition [1]. It follows that accurate lateralization and localization of the epileptogenic focus are significant prerequisites for determining surgical candidacy once the patient has been deemed medically intractable.
Clinical MR Neuroimaging, second edition, provides radiologists, neuroscientists and researchers with a clear understanding of each physiological MR methodology and their applications to the major neurological diseases. Section 1 describes the physical principles underlying each technique and their associated artefacts and pitfalls. Subsequent sections review the application of MRI in a range of clinical disorders: cerebrovascular disease, neoplasia, infection/inflammation/demyelination disorders, seizures, psychiatric/neurodegenerative conditions, and trauma. This new edition includes all recent advances and applications, with greatly increased coverage of permeability imaging, susceptibility imaging, iron imaging, MR spectroscopy and fMRI. All illustrations are completely new, taking advantage of the latest scan capabilities to give images of the highest possible quality. In addition, over 35 new case studies have been included. Editors and contributors are the leading neuroimaging experts worldwide; their unique combination of technical knowledge and clinical expertise makes Clinical MR Neuroimaging the leading text on the subject.
Since the realization that diffusion MRI can probe the microstructural organization and orientation of biological tissue in vivo and non‐invasively, a multitude of diffusion imaging methods have been developed and applied to study the living human brain. Diffusion tensor imaging was the first model to be widely adopted in clinical and neuroscience research, but it was also clear from the beginning that it suffered from limitations when mapping complex configurations, such as crossing fibres. In this review, we highlight the main steps that have led the field of diffusion imaging to move from the tensor model to the adoption of diffusion and fibre orientation density functions as a more effective way to describe the complexity of white matter organization within each brain voxel. Among several techniques, spherical deconvolution has emerged today as one of the main approaches to model multiple fibre orientations and for tractography applications. Here we illustrate the main concepts and the reasoning behind this technique, as well as the latest developments in the field. The final part of this review provides practical guidelines and recommendations on how to set up processing and acquisition protocols suitable for spherical deconvolution. Diffusion MRI can probe non‐invasively and in vivo the microstructural organization and the orientation of white matter in the human brain. Diffusion tensor imaging was the first model to be widely adopted in clinical and research applications, but it has also shown important limitations. Alternative methods have been developed to extract and better describe multiple populations of fibre orientations in the brain. Here we review these techniques, focusing particularly on spherical deconvolution, its principles and how this method can be practically applied in real studies.
Structure tensor informed fibre tractography (STIFT) based on informing tractography for diffusion‐weighted images at 3T and by utilising the structure tensor obtained from gradient‐recalled echo (GRE) images at 7T is able to delineate fibres when seed voxels are placed close to the fibre boundaries. However, incorporating data from two different field strengths limits the applicability of STIFT. In this study, STIFT was implemented with both diffusion‐weighted images and GRE images acquired at 3T. Instead of using the magnitude GRE data directly for STIFT as in the previous work, the utility of T2* maps and quantitative susceptibility maps derived from complex‐valued GRE data to improve fibre delineation was explored. Single‐seed tractography was performed and the results show that the optic radiation reconstructed with STIFT is more distinguishable from the inferior longitudinal fasciculus/inferior fronto‐occipital fasciculus complex when compared to standard diffusion‐weighted imaging tractography. We further investigated the quantitative effects of STIFT in a group of five healthy volunteers and evaluated its impact on measures of structural connectivity. The framework was extended to evaluate implementations of STIFT based on T2*‐weighted and quantitative susceptibility‐weighted images in a whole‐brain connectivity study. In terms of connectivity, no systematic differences were found between STIFT and diffusion‐weighted imaging tractography, suggesting that local improvements in tractography are not translated to the atlas‐based structural connectivity analysis. Nevertheless, the reduction in the number of statistically significant connections in the STIFT connectivity matrix suggests that STIFT can potentially reduce the false‐positive connections in fibre tractography.
Topographic regularity of axonal connections is commonly understood as the preservation of spatial relationships between nearby neurons and is a fundamental structural property of the brain. In particular the retinotopic mapping of the visual pathway can even be quantitatively computed. Inspired from this previously untapped anatomical knowledge, we propose a novel tractography method that preserves both topographic and geometric regularity. We make use of parameterized curves with Frenet-Serret frame and introduce a highly flexible mechanism for controlling geometric regularity. At the same time, we incorporate a novel local data support term in order to account for topographic organization. Unifying geometry with topographic regularity, we develop a Bayesian framework for generating highly organized streamlines that accurately follow neuroanatomy. We additionally propose two novel validation techniques to quantify topographic regularity. In our experiments, we studied the results of our approach with respect to connectivity, reproducibility and topographic regularity aspects. We present both qualitative and quantitative comparisons of our technique against three algorithms from MRtrix3. We show that our method successfully generates highly organized fiber tracks while capturing bundle anatomy that are geometrically challenging for other approaches.
The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non‐destructively and three‐dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7‐T preclinical scanner, we present a novel two‐coil system in which each coil is shielded, placed off‐isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal‐to‐noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil‐dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two‐coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade‐offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post‐processing techniques and biological variability impact mouse brain connectomics.
Background:
Anatomical awareness of brain's structural connectivity is mandatory for neurosurgeons, to select the most effective approaches for brain resections. Although standard micro-dissection is a validated technique to investigate the different white matter (WM) pathways and to verify results coming from tractography, the possibility of an interactive exploration of the specimens and of a reliable acquisition of quantitative information has not been described so far. Photogrammetry is a well-established technique allowing an accurate metrology on highly defined 3D-models. The aim of this work is to propose the application of photogrammetric technique for supporting the 3D-exploration and the quantitative analysis on the cerebral WM connectivity.
Methods:
The main peri-sylvian pathways, including the superior longitudinal fascicle (SLF) and the arcuate fascicle (AF) were exposed using the Klingler's technique. The photogrammetric acquisition followed each dissection step. The point-clouds were registered to a reference MRI of the specimen. All the acquisitions were co-registered into an open-source model.
Results:
We analyzed five steps, including: the cortical surface, the short intergyral fibers, the indirect posterior and anterior SLF, and the AF. The co-registration between the MRI mesh and the point-clouds models resulted highly accurate. Multiple measures of distances between specific cortical landmarks and WM tracts were collected on the photogrammetric model.
Conclusions:
Photogrammetry allows an accurate 3D-reproduction of WM anatomy, and the acquisition of unlimited quantitative data directly on the real specimen during the post-dissection analysis. These results open many new promising neuroscientific and educational perspectives, also for optimizing the quality of neurosurgical treatments.
The neural mechanisms of visual perceptual learning (VPL) remain unclear. Previously we found that activation in the primary visual cortex (V1) increased in the early encoding phase of training, but returned to baseline levels in the later retention phase. To examine neural changes during the retention phase, we measured structural and functional connectivity changes using MRI. After weeks of training on a texture discrimination task, the fractional anisotropy of the inferior longitudinal fasciculus, a major tract connecting visual and anterior areas, was increased, as well as the functional connectivity between V1 and anterior regions mediated by the ILF. These changes were strongly correlated with behavioral performance improvements. These results suggest a two-phase model of VPL in which localized functional changes in V1 in the encoding phase of training are followed by changes in both structural and functional connectivity in ventral visual processing, perhaps leading to the long-term stabilization of VPL.
Background
Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the association between executive, semantic and language production functions.
Findings
Here we provide, for the first time, a set of complementary solutions to measure the impact of a given lesion upon the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesion, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency.
Conclusions
The combination of structural and functional connectivity together with cortical thickness estimates reveals the remote effects of brain lesions, provide for the identification of the affected networks and strengthen our understanding of their relationship with cognitive and behavioural measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].
We present a technique to automatically characterize the geometry of important anatomical structures in diffusion weighted MRI (DWI) data. Our approach is based on the interpretation of diffusion data as a superimposition of multiple line fields that each form a continuum of space filling curves. Using a dense tractography computation, our method quantifies the spatial variations of the geometry of these curves and use the resulting measure to characterize salient structures as edges. Anatomically, these structures have a boundary-like nature and yield a clear picture of major fiber bundles. In particular, the application of our algorithm to high angular resolution imaging (HARDI) data yields a precise geometric description of subtle anatomical configurations associated with the local presence of multiple fiber orientations. We evaluate our technique and study its robustness to noise in the context of a phantom dataset and present results obtained with two diffusion weighted brain images.
INTRODUCTION Non-invasive assessment of tissue structure is an exciting application of diffusion tensor imaging (DTIL1). Here we propose an algorithm for visualising the structural connectivity of white matter via diffusion tensor imaging.
Purpose divergence (converging or diverging fiber pattern), (b) non-zero curl (circulating, open or closed fiber pattern), or (c) periodic or uniform fiber directional pattern. Fig 1 shows a fiber tract trajectory, r(s), calculated from such a test map in which all three Euler angles of D(x): φ (x), ϕ(x), and θ(x), varied continuously through the image volume. To propose a methodology to calculate continuous fiber-tract trajectories from measured diffusion tensor MRI data, and a rationale for determining fiber tract continuity. Introduction In normal and pathological tissues, fiber tract trajectories would provide valuable new microstructural information. In aging and development it would provide a means to follow changes in fiber-architecture. DT-MRI (1) is now the first noninvasive imaging modality capable of generating such fiber-tract trajectories. This is because in each voxel, the fiber tract direction is parallel to the eigenvector, ε 1 , associated with the largest eigenvalue, λ 1 , of the local diffusion tensor, D (1). However, ε 1 measured by DT-MRI are inherently discrete, noisy, voxel-averaged estimates of the "true" direction vectors (2). To date, it has not been feasible to reconstruct continuous fiber tract trajectories from the measured ε 1 . However, a new, efficient D-field processing methodology that we just developed, generates a continuous diffusion tensor field, D(x), from measured DT-MRI data (3) from which a continuous ε 1 -field map can be calculated. Then, the method below can be used to calculate fiber tract trajectories, and assess fiber tract continuity. Fig 1. Computed 3-d fiber tract trajectory from synthetic D(x) image.
Pattern formation and switching between self-organized states are often associated with instabilities in open, nonequilibrium systems. We describe an experiment which shows that systematically changing a control parameter induces qualitative changes in sensorimotor coordination and brain activity, as registered by a 37-SQUID (Superconducting Quantum Interference Device) array. Near the instability point, predicted features of nonequilibrium phase transitions (critical slowing down, fluctuation enhancement) are observed in both the psychophysical data and the brain signals obtained from single SQUID sensors. Further analysis reveals that activity from the entire array displays spatial patterns evolving in time. Such spatiotemporal patterns are characterized by the dynamics of only a few coherent spatial modes.
Schizophrenic patients tend to demonstrate reduced cerebral metabolism in frontal areas. Studies of human brain development reveal that synapses in the cerebral cortex are progressively reduced throughout childhood and adolescence, with parallel reductions in cerebral metabolism. This relationship is not surprising, since synaptic density is a primary factor determining regional metabolic requirements. The elimination of synapses in prefrontal cortex continues for a particularly long period of time, extending well into adolescence. Thus, reduced frontal metabolism in schizophrenic patients could be due to a developmental process--namely, elimination of synapses--gone too far. Animal studies indicate that developmentally induced reductions in synaptic density are due to the pruning of axonal collaterals rather than the death of neurons, which raises a critical question: Does excessive axonal pruning have specific pathological effects on cortical information processing? To answer this question, computer simulations of neural information processing systems were subjected to axonal pruning which reduced synaptic density. If pruning was conducted overzealously, cognitive pathology was induced that could, in humans, lead to the conscious experience of hallucinations, delusions, and Schneiderian symptoms.
Molecular diffusion and microcirculation in the capillary network result in a distribution of phases in a single voxel in the presence of magnetic field gradients. This distribution produces a spin-echo attenuation. The authors have developed a magnetic resonance (MR) method to image such intravoxel incoherent motions (IVIMs) by using appropriate gradient pulses. Images were generated at 0.5 T in a high-resolution, multisection mode. Diffusion coefficients measured on images of water and acetone phantoms were consistent with published values. Images obtained in the neurologic area from healthy subjects and patients were analyzed in terms of an apparent diffusion coefficient (ADC) incorporating the effect of all IVIMs. Differences were found between various normal and pathologic tissues. The ADC of in vivo water differed from the diffusion coefficient of pure water. Results were assessed in relation to water compartmentation in biologic tissues (restricted diffusion) and tissue perfusion. Nonuniform slow flow of cerebrospinal fluid appeared as a useful feature on IVIM images. Observation of these motions may significantly extend the diagnostic capabilities of MR imaging.
Converging evidence indicates that a profound reorganization of human brain function takes place during adolescence: the amount of deep sleep and the rate of brain metabolism fall sharply; the latency of certain event-related potentials declines; the capacity to recover function after brain injury diminishes; and adult problem-solving "power" appears. A reduction in cortical synaptic density has recently been observed and might account for all of these changes. Such synaptic "pruning" may be analogous to the programmed elimination of neural elements in very early development. A defect in this maturational process may underlie those cases of schizophrenia that emerge during adolescence.
We studied the effects of Wallerian degeneration in the cerebral peduncle shown by magnetic resonance imaging (MRI) following a supratentorial vascular lesion, to identify the somatotopic localisation of the descending cortical tracts. Patients with a lesion involving a large area of a cerebral hemisphere had an area of abnormal signal intensity in the whole cerebral peduncle, suggesting Wallerian degeneration of all the whole descending cortical tracts. With a small lesion confined to the precentral gyrus, corona radiata, or posterior limb of the internal capsule there was an abnormal signal at the centre of the peduncle, suggesting degeneration of the precentrospinal tract. Those with a small lesion confined to the paracentral gyrus had an abnormal area slightly lateral to the centre of the peduncle, suggesting degeneration of the parietospinal tract. Patients with a lesion of the parietal or temporal lobes, not including the paracentral or precentral gyri, corona radiata, or the posterior limb of the internal capsule, had an abnormal area laterally in the peduncle, suggesting degeneration of the parietopontine or temporopontine tract.
The distributed brain systems associated with performance of a verbal fluency task were identified in a nondirected correlational analysis of neurophysiological data obtained with positron tomography. This analysis used a recursive principal-component analysis developed specifically for large data sets. This analysis is interpreted in terms of functional connectivity, defined as the temporal correlation of a neurophysiological index measured in different brain areas. The results suggest that the variance in neurophysiological measurements, introduced experimentally, was accounted for by two independent principal components. The first, and considerably larger, highlighted an intentional brain system seen in previous studies of verbal fluency. The second identified a distributed brain system including the anterior cingulate and Wernicke's area that reflected monotonic time effects. We propose that this system has an attentional bias.
A disturbance in the frontal-striatal-thalamic circuitry has been proposed for schizophrenia, but this concept has been based primarily on indirect evidence from psychopharmacology and analogies with animal research. Diffusion tensor imaging, a new MRI technique that permits direct assessment of the large axon masses stretching from the prefrontal cortex to the striatum, was used to study white matter axon bundles. Diffusion tensor images, high-resolution structural MRI and positron emission tomography scans with 18-fluorodexoyglucose were obtained on five patients with schizophrenia and six age- and sex-matched normal controls. Significantly lower diffusion anisotropy in the white matter of the prefrontal cortex in schizophrenic patients than in normal controls was observed in statistical probability maps. Co-registered PET scans revealed significantly lower correlation coefficients between metabolic rates in the prefrontal cortex and striatum in patients than in controls. These twin findings provide convergent evidence for diminished fronto-striatal connectivity in schizophrenia.
We investigated frontal cognitive function in a group of 153 patients with multiple sclerosis and 100 healthy controls using a global scale composed by a set of items from the Luria-Nebraska Neuropsychological Battery (LNNB) which has been validated by Malloy and colleagues on frontally damaged patients. A second scale was built with LNNB items tapping parietal lobes function. Patients who were specifically impaired on the frontal scale (12%) had a shorter disease duration and were less physically disabled than those failing on the parietal tasks (8.5%) or those showing combined deficits (21.5%). Sixty-four patients were also tested on the Wisconsin Card Sorting Test (WCST). Twenty-seven (37.5%) patients were found to be impaired on the WCST, but the latter could not predict reliably their performance on the LNNB frontal scale. We also examined whether age of onset and disease duration could have had any effect on the cognitive performance of selected groups of patients. We found that relative to normals, deficits on the frontal scale were more severe in patients with a clinical onset around age 20 than in patients with a later onset (i.e., around 35), the two groups being comparable for duration and degree of disability. Furthermore, patients with a longstanding illness (> 10 years) were more affected on visuospatial processing and frontal control of language than those with a short duration (1.5 yrs). We propose that a greater disease activity interacting with contingent (developmental?) factors is responsible for the appearance of transient frontal deficits in several young MS patients. A differential involvement of long associative and connecting bundles is also proposed as a basis for understanding the pattern of cognitive deficits encountered in selected patient groups.
Quantitative measurements of perfusion and molecular diffusion were made in human white matter in two orientations of the motion-sensitization gradient to document anisotropy of these parameters. Measurements were localized to a 10 X 10-mm tissue column oriented in an anterior-to-posterior direction in the left cerebral hemisphere just above the body of the left ventricle. This region was selected because of the relatively high directionality of white matter fibers. In this study of five healthy volunteers, strong diffusion anisotropy was observed in all cases. Twofold or greater anisotropy was commonly observed, with the higher diffusion value associated with motion sensitivity along the fiber directions. By combining data from both gradient orientations in all cases, diffusion values of solid tissue ranged from 0.38 X 10(-3) mm2/sec to 1.12 X 10(-3) mm2/sec, and measured perfusion fractions were in the range of 2%-5% (excluding areas highly contaminated by cerebrospinal fluid). Little or no perfusion-fraction anisotropy was observed; however, perfusion measurements were limited by noise. Data were collected without cardiac gating by using a technique that offers good immunity to bulk tissue motion artifacts.
A pulsed magnetic field gradient spin echo technique was used to study the brain of two volunteers and eight patients. The pulsed gradients were applied both perpendicular and parallel to the image slice. Striking changes in signal intensity were demonstrated in white matter depending on the direction in which pulsed gradients were applied. These effects enabled specific white matter tracts to be identified depending on the direction of their fibres. Abnormalities were also demonstrated in these tracts in patients with a variety of diseases, including cases where only minor abnormalities were seen with conventional, highly T2-weighted sequences. The effects were attributed to anisotropically restricted diffusion within white matter. The technique may have application in a wide range of neurological disease and result in better localisation of lesions and improved detection of disease.
The diffusion behavior of intracranial water in the cat brain and spine was examined with the use of diffusion-weighted magnetic resonance (MR) imaging, in which the direction of the diffusion-sensitizing gradient was varied between the x, y, and z axes of the magnet. At very high diffusion-sensitizing gradient strengths, no clear evidence of anisotropic water diffusion was found in either cortical or subcortical (basal ganglia) gray matter. Signal intensities clearly dependent on orientation were observed in the cortical and deep white matter of the brain and in the white matter of the spinal cord. Greater signal attenuation (faster diffusion) was observed when the relative orientation of white matter tracts to the diffusion-sensitizing gradient was parallel as compared to that obtained with a perpendicular alignment. These effects were seen on both premortem and immediate postmortem images obtained in all axial, sagittal, and coronal views. Potential applications of this MR imaging technique included the stereospecific evaluation of white matter in the brain and spinal cord and in the characterization of demyelinating and dysmyelinating diseases.
Magnetic resonance (MR) imaging systems produce spatial distribution estimates of proton density, relaxation time, and flow, in a two dimensional matrix form that is analogous to that of the image data obtained from multispectral imaging satellites. Advanced NASA satellite image processing offers sophisticated multispectral analysis of MR images. Spin echo and inversion recovery pulse sequence images were entered in a digital format compatible with satellite images and accurately registered pixel by pixel. Signatures of each tissue class were automatically determined using both supervised and unsupervised classification. Overall tissue classification was obtained in the form of a theme map. In MR images of the brain, for example, the classes included CSF, gray matter, white matter, subcutaneous fat, muscle, and bone. These methods provide an efficient means of identifying subtle relationships in a multi-image MR study.
Several lines of evidence support the notion that a substantial reorganization of cortical connections, involving a programmed synaptic pruning, takes place during adolescence in humans. A review of neurobiological abnormalities in schizophrenia indicates that the neurobiological parameters that undergo peripubertal regressive changes may be abnormal in this disorder. An excessive pruning of the prefrontal corticocortical, and corticosubcortical synapses, perhaps involving the excitatory glutamatergic inputs to pyramidal neurons, may underlie schizophrenia. A reciprocal failure of pruning in certain subcortical structures, such as lenticular nuclei, may also occur. Several developmental trajectories, related to early brain insults as well as genetic factors affecting postnatal neurodevelopment, could lead to the illness. These models would have heuristic value and may be consistent with several known facts of the schizophrenic illness, such as its onset in adolescence and the gender differences in its onset and natural course. The relationship between these models and other etiological models of schizophrenia are summarized and approaches to test relevant hypotheses are discussed.
This paper describes a new NMR imaging modality--MR diffusion tensor imaging. It consists of estimating an effective diffusion tensor, Deff, within a voxel, and then displaying useful quantities derived from it. We show how the phenomenon of anisotropic diffusion of water (or metabolites) in anisotropic tissues, measured noninvasively by these NMR methods, is exploited to determine fiber tract orientation and mean particle displacements. Once Deff is estimated from a series of NMR pulsed-gradient, spin-echo experiments, a tissue's three orthotropic axes can be determined. They coincide with the eigenvectors of Deff, while the effective diffusivities along these orthotropic directions are the eigenvalues of Deff. Diffusion ellipsoids, constructed in each voxel from Deff, depict both these orthotropic axes and the mean diffusion distances in these directions. Moreover, the three scalar invariants of Deff, which are independent of the tissue's orientation in the laboratory frame of reference, reveal useful information about molecular mobility reflective of local microstructure and anatomy. Inherently tensors (like Deff) describing transport processes in anisotropic media contain new information within a macroscopic voxel that scalars (such as the apparent diffusivity, proton density, T1, and T2) do not.
Quantitative-diffusion-tensor MRI consists of deriving and displaying parameters that resemble histological or physiological stains, i.e., that characterize intrinsic features of tissue microstructure and microdynamics. Specifically, these parameters are objective, and insensitive to the choice of laboratory coordinate system. Here, these two properties are used to derive intravoxel measures of diffusion isotropy and the degree of diffusion anisotropy, as well as intervoxel measures of structural similarity, and fiber-tract organization from the effective diffusion tensor, D, which is estimated in each voxel. First, D is decomposed into its isotropic and anisotropic parts, [D] I and D - [D] I, respectively (where [D] = Trace(D)/3 is the mean diffusivity, and I is the identity tensor). Then, the tensor (dot) product operator is used to generate a family of new rotationally and translationally invariant quantities. Finally, maps of these quantitative parameters are produced from high-resolution diffusion tensor images (in which D is estimated in each voxel from a series of 2D-FT spin-echo diffusion-weighted images) in living cat brain. Due to the high inherent sensitivity of these parameters to changes in tissue architecture (i.e., macromolecular, cellular, tissue, and organ structure) and in its physiologic state, their potential applications include monitoring structural changes in development, aging, and disease.
We report a case of multiple sclerosis with visual form agnosia and callosal syndromes. Initially, the patient's visual recognition of object form was severely disturbed at the perceptual stage, in association with left-sided ideomotor apraxia and agraphia. Magnetic resonance imaging showed large white matter lesions in the bilateral frontal and occipital lobes, the latter extending to the occipitotemporal junction, and widespread corpus callosum lesions. Over the course of one year follow-up, neuropsychological examinations indicated that the patient's visual recognition defects occurred not only at the early substage of form perception, but also at the stage of reproducing the shape of objects from visual memory store. The present case suggests that neural connections between the striate cortex and occipitotemporal visual areas are crucial for both the perceptual and associative stages of visual object recognition.
The authors report NMR measurements of the changes in water diffusion brought about by in vivo Wallerian degeneration due to either crush- or tie-injuries in the sciatic nerve of the frog. Using a pulsed-gradient spin-echo sequence with a diffusion measurement time of 28 ms, the degree of diffusion coefficient anisotropy ¿D(longitudinal)/D(transverse)¿ 4 weeks after injury in both crush- and tie-injured nerves (2.3 +/- 0.4 and 1.7 +/- 0.1, respectively) is significantly less than in normal frog sciatic nerve (3.9 +/- 0.4). The decrease of anisotropy in the degenerated nerves is due to both a decrease in longitudinal diffusion and an increase in transverse diffusion. The changes in diffusion coefficients are compared with the degree of axonal and myelin breakdown observed in light and electron micrographs of the nerves.
To assess intrinsic properties of water diffusion in normal human brain by using quantitative parameters derived from the diffusion tensor, D, which are insensitive to patient orientation.
Maps of the principal diffusivities of D, of Trace(D), and of diffusion anisotropy indices were calculated in eight healthy adults from 31 multisection, interleaved echo-planar diffusion-weighted images acquired in about 25 minutes.
No statistically significant differences in Trace(D) (approximately 2,100 x 10(-6) mm2/sec) were found within normal brain parenchyma, except in the cortex, where Trace(D) was higher. Diffusion anisotropy varied widely among different white matter regions, reflecting differences in fiber-tract architecture. In the corpus callosum and pyramidal tracts, the ratio of parallel to perpendicular diffusivities was approximately threefold higher than previously reported, and diffusion appeared cylindrically symmetric. However, in other white matter regions, particularly in the centrum semiovale, diffusion anisotropy was low, and cylindrical symmetry was not observed. Maps of parameters derived from D were also used to segment tissues based on their diffusion properties.
A quantitative characterization of water diffusion in anisotropic, heterogeneously oriented tissues is clinically feasible. This should improve the neuroradiologic assessment of a variety of gray and white matter disorders.
An algorithm for correcting the distortions that occur in diffusion-weighted echo-planar images due to the strong diffusion-sensitizing gradients is presented. The dominant distortions may be considered to be only changes of scale coupled with a shear and linear translation in the phase-encoding direction. It is then possible to correct for them by using an algorithm in which each line of the image in the phase-encoding direction is considered in turn, with only one parameter (the scale) to be found by searching.
Indices of diffusion anisotropy calculated from diffusion coefficients acquired in two or three perpendicular directions are rotationally variant. In living monkey brain, these indices severely underestimate the degree of diffusion anisotropy. New indices calculated from the entire diffusion tensor are rotationally invariant (RI). They show that anisotropy is highly variable in different white matter regions depending on the degree of coherence of fiber tract directions. In structures with a regular, parallel fiber arrangement, water diffusivity in the direction parallel to the fibers (Dparallel approximately 1400-1800 x 10(-6) mm2/s) is almost 10 times higher than the average diffusivity in directions perpendicular to them (D + D)/2 [corrected] approximately 150-300 x 10(-6) mm2/s), and is almost three times higher than previously reported. In structures where the fiber pattern is less coherent (e.g., where fiber bundles merge), diffusion anisotropy is significantly reduced. However, RI anisotropy indices are still susceptible to noise contamination. Monte Carlo simulations show that these indices are statistically biased, particularly those requiring sorting of the eigenvalues of the diffusion tensor based on their magnitude. A new intervoxel anisotropy index is proposed that locally averages inner products between diffusion tensors in neighboring voxels. This "lattice" RI index has an acceptably low error variance and is less susceptible to bias than any other RI anisotropy index proposed to date.
Multiple lines of evidence suggest that the prefrontal cortex is a site of dysfunction in schizophrenia. In addition, one of the characteristics of this disorder is the tendency for clinical symptoms to appear first during late adolescence or early adulthood. Recent studies in nonhuman primates have shown that the connectivity of the prefrontal cortex is substantially refined during adolescence, suggesting that these developmental changes may be critical for the appearance of the clinical features of schizophrenia. This article reviews data demonstrating that these late developmental changes are selective for particular neural elements in the prefrontal cortex and that they are synaptically linked. It is suggested that these neural elements comprise a functional circuit that is likely to be especially vulnerable in schizophrenia, a hypothesis that can be directly tested in postmortem studies.
The authors propose a method for the 3-D reconstruction of the
brain from anisotropic magnetic resonance imaging (MRI) brain data. The
method essentially consists in two original algorithms both for
segmentation and for interpolation of the MRI data. The segmentation
process is performed in three steps. A gray level thresholding of the
white and gray matter tissue is performed on the brain MR raw data. A
global white matter segmentation is automatically performed with a
global 3-D connectivity algorithm which takes into account the
anisotropy of the MRI voxel. The gray matter is segmented with a local
3-D connectivity algorithm. Mathematical morphology tools are used to
interpolate slices. The whole process gives an isotropic binary
representation of both gray and white matter which are available for 3-D
surface rendering. The power and practicality of this method have been
tested on four brain datasets. The segmentation algorithm favorably
compares to a manual one. The interpolation algorithm was compared to
the shaped-based method both quantitatively and qualitatively
Exploring links between brain structure and function: combining diffusion tensor imaging (DTI) with functional magnetic resonance imaging (fMRI)
- D J Werring
- C A Clark
- Gjm Parker
- G J Barker
- M R Symms
- F Franconi
- D H Miller
- A J Thompson
Werring DJ, Clark CA, Parker GJM, Barker GJ, Symms MR, Franconi F,
Miller DH, Thompson AJ. Exploring links between brain structure and
function: combining diffusion tensor imaging (DTI) with functional
magnetic resonance imaging (fMRI). In: Proceedings of the ISMRM 6th
Annual Meeting, Sydney, 1998. p 1497.
Characterizing focal and distributed physiological changes with MRI and PET
- K J Friston
- P Jezzard
- Rsj Frackowiak
- R Turner
Friston KJ, Jezzard P, Frackowiak RSJ, Turner R. Characterizing focal
and distributed physiological changes with MRI and PET. In: Functional MRI of the brain. Berkeley, CA: Society of Magnetic Resonance in
Medicine; 1993. p 207-216.
Quantifying errors in fiber-tract direction and diffusion tensor field maps resulting from MR noise
- P J Basser
Basser PJ. Quantifying errors in fiber-tract direction and diffusion
tensor field maps resulting from MR noise. In: Proceedings of the
ISMRM 5th Annual Meeting, Vancouver, 1997. p 1740.
Diffusion MRI of wallerian degeneration. A new tool to investigate neural connectivity in vivo?
- C Pierpaoli
- A Barnett
- A Virta
- L Peniz
- R Chen
Pierpaoli C, Barnett A, Virta A, Peniz L, Chen R. Diffusion MRI of
wallerian degeneration. A new tool to investigate neural connectivity in
vivo? In: Proceedings of the ISMRM 6th Annual Meeting, Sydney, 1998.
p 1247.