scholarly journals Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract

2019 ◽  
Author(s):  
Francois Rheault ◽  
Alessandro De Benedictis ◽  
Alessandro Daducci ◽  
Chiara Maffei ◽  
Chantal M.W Tax ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Large Scale ◽  
Pyramidal Tract ◽  
Brain Structures ◽  
Extraction Techniques ◽  
Human Errors ◽  
Human Subjectivity ◽  
Virtual Dissection ◽  
Voxel Representation

AbstractInvestigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called “virtual dissection”. Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. The contribution of this study is to provide the first large-scale, international, multi-center variability assessment of the “virtual dissection” of the pyramidal tract (PyT). Eleven (11) experts and thirteen (13) non-experts in neuroanatomy and “virtual dissection” were asked to perform 30 PyT segmentation and their results were compared using various voxel-wise and streamline-wise measures. Overall the voxel representation is always more reproducible than streamlines (≈70% and ≈35% overlap respectively) and distances between segmentations are also lower for voxel-wise than streamline-wise measures (¾3mm and ¾ûmm respectively). This needs to be seriously considered before using tract-based measures (e.g. bundle volume versus streamline count) for an analysis. We show and argue that future bundle segmentation protocols need to be designed to be more robust to human subjectivity. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction techniques in this era of open and collaborative science.

scholarly journals Neurobiological underpinnings of rapid white matter plasticity during intensive reading instruction

2020 ◽  
Author(s):  
Elizabeth Huber ◽  
Aviv Mezer ◽  
Jason D. Yeatman
Keyword(s):  
White Matter ◽  
Reading Instruction ◽  
Diffusion Mri ◽  
Large Scale ◽  
Mean Diffusivity ◽  
Quantitative Mri ◽  
Diffusion Kurtosis Imaging ◽  
Control Group ◽  
Intensive Reading ◽  
Diffusion Kurtosis

AbstractHuman white matter is remarkably plastic. Yet it is challenging to infer the biological underpinnings of this plasticity using non-invasive measurements like diffusion MRI. Here we capitalize on metrics derived from diffusion kurtosis imaging (DKI) to interpret previously reported changes in mean diffusivity throughout the white matter during an 8-week, intensive reading intervention. We then use an independent quantitative MRI measurement of R1 (1/T1 relaxation time) in the same white matter regions; since R1 closely tracks variation in myelin content, it provides complementary information about white matter microstructure. Behavioral measures, multi-shell diffusion MRI data, and quantitative T1 data were collected at regular intervals during the intervention in a group of 33 children with reading difficulties (7-12 years old), and over the same period in an age-matched non-intervention control group. Changes in DKI parameters modeled over the intervention were consistent with increased hindrance in the extra-axonal space, rather than a large-scale change in axon density and/or myelination. Supporting this interpretation, analysis of R1 values did not suggest a change in myelin, although R1 estimates were correlated with individual differences in reading skill. Together, these results suggest that large-scale changes in diffusivity observed over a short timescale during an intensive educational experience are most likely to reflect changes occurring in the extra-axonal space, in line with recent work highlighting the role of glial cells in experience-dependent plasticity and learning.

scholarly journals An atlas of white matter anatomy, its variability, and reproducibility based on Constrained Spherical Deconvolution of diffusion MRI

2021 ◽  
Author(s):  
Ahmed M. Radwan ◽  
Stefan Sunaert ◽  
Kurt G. Schilling ◽  
Maxime Descoteaux ◽  
Bennett A. Landman ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Single Subject ◽  
Constrained Spherical Deconvolution ◽  
Spherical Deconvolution ◽  
Pyramidal Tracts ◽  
Human Connectome Project ◽  
Subject Specific ◽  
Virtual Dissection

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the first segment of the superior longitudinal fasciculus, fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a highly reproducible parcellation-based dissection protocol, as well as being an educational resource for applied neuroimaging and clinical professionals.

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

2020 ◽  
Author(s):  
Melissa Savard ◽  
Tharick A. Pascoal ◽  
Thijs Dhollander ◽  
Yasser Iturria-Medina ◽  
Paolo Vitali ◽  
...  
Keyword(s):  
Risk Factors ◽  
White Matter ◽  
Diffusion Mri ◽  
Short Range ◽  
Large Scale ◽  
Structural Connectivity ◽  
Executive Dysfunction ◽  
Cognitive Symptoms ◽  
Whole Brain ◽  
Relative Contribution

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

scholarly journals A Measure of Whole-Brain White Matter Topography

2019 ◽  
Author(s):  
Junyan Wang ◽  
Yonggang Shi
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
Large Scale ◽  
Uk Biobank ◽  
Reliable Measure ◽  
Whole Brain ◽  
Brain White Matter ◽  
Human Connectome Project ◽  
Natural Coordinate System ◽  
Natural Coordinate

The unprecedentedly high-quality large-scale brain imaging datasets, from such as the Human Connectome Project (HCP) and UK-Biobank, provide a unique opportunity for measuring the white matter topography of the human brain. By leveraging the multi-shell diffusion MRI data from the original young adult HCP, we systematically develop a reliable measure of the whole-brain white matter topography, and we coin it topographic vector. As the main result, we find that the three most dominant dimensions of the topographic vectors strongly and linearly correlate with the coordinates of the corresponding streamlines of the whole-brain tractograms. Our results support the earlier prescient hypothesis that brain development follows a “base-plan” established by three (main) chemotactic gradients of early embryogenesis, and they implicate that the whole brain white matter tracts can be represented by vectors of a natural coordinate system.

What Has Direct Cortical and Subcortical Electrostimulation Taught Us about Neurolinguistics?

2019 ◽  
pp. 185-211
Author(s):  
Hugues Duffau
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Great Accuracy ◽  
Subcortical White Matter ◽  
Cerebral Lesions ◽  
Physiological Basis ◽  
Postoperative Mri ◽  
The Brain

Investigating the neural and physiological basis of language is one of the most important challenges in neurosciences. Direct electrical stimulation (DES), usually performed in awake patients during surgery for cerebral lesions, is a reliable tool for detecting both cortical and subcortical (white matter and deep grey nuclei) regions crucial for cognitive functions, especially language. DES transiently interacts locally with a small cortical or axonal site, but also nonlocally, as the focal perturbation will disrupt the entire subnetwork sustaining a given function. Thus, in contrast to functional neuroimaging, DES represents a unique opportunity to identify with great accuracy and reproducibility, in vivo in humans, the structures that are actually indispensable to the function, by inducing a transient virtual lesion based on the inhibition of a subcircuit lasting a few seconds. Currently, this is the sole technique that is able to directly investigate the functional role of white matter tracts in humans. Thus, combining transient disturbances elicited by DES with the anatomical data provided by pre- and postoperative MRI enables to achieve reliable anatomo-functional correlations, supporting a network organization of the brain, and leading to the reappraisal of models of language representation. Finally, combining serial peri-operative functional neuroimaging and online intraoperative DES allows the study of mechanisms underlying neuroplasticity. This chapter critically reviews the basic principles of DES, its advantages and limitations, and what DES can reveal about the neural foundations of language, that is, the large-scale distribution of language areas in the brain, their connectivity, and their ability to reorganize.

Clustering of short association white matter fibers calculated from diffusion MRI

2014 ◽  
Author(s):  
C. Roman ◽  
D. Le Bihan ◽  
C. Poupon ◽  
P. Guevara ◽  
A. Lebois ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri

scholarly journals Diffusion MRI data, sulcal anatomy, and tractography for eight species from the Primate Brain Bank

2021 ◽  
Author(s):  
Katherine L. Bryant ◽  
Dirk Jan Ardesch ◽  
Lea Roumazeilles ◽  
Lianne H. Scholtens ◽  
Alexandre A. Khrapitchev ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Large Scale ◽  
Structural Mri ◽  
Relative Volume ◽  
Primate Species ◽  
Brain Bank ◽  
Cingulum Bundle ◽  
Primate Brain ◽  
Multiple Levels ◽  
Comparative Neuroscience

AbstractLarge-scale comparative neuroscience requires data from many species and, ideally, at multiple levels of description. Here, we contribute to this endeavor by presenting diffusion and structural MRI data from eight primate species that have not or rarely been described in the literature. The selected samples from the Primate Brain Bank cover a prosimian, New and Old World monkeys, and a great ape. We present preliminary labelling of the cortical sulci and tractography of the optic radiation, dorsal part of the cingulum bundle, and dorsal parietal–frontal and ventral temporal-frontal longitudinal white matter tracts. Both dorsal and ventral association fiber systems could be observed in all samples, with the dorsal tracts occupying much less relative volume in the prosimian than in other species. We discuss the results in the context of known primate specializations and present hypotheses for further research. All data and results presented here are available online as a resource for the scientific community.

scholarly journals Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

2021 ◽  
Author(s):  
Thomaz R. Mostardeiro ◽  
Ananya Panda ◽  
Robert J. Witte ◽  
Norbert G. Campeau ◽  
Kiaran P. McGee ◽  
...  
Keyword(s):  
White Matter ◽  
Statistical Significance ◽  
Relaxation Times ◽  
Brain Structures ◽  
Centrum Semiovale ◽  
In Vivo Evaluation ◽  
Whole Brain ◽  
Mean Values ◽  
Caudate Head

Abstract Purpose MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. Materials and methods A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T1 and T2 estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test. Results MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T1 (r2 = 0.99) and T2 (r2 = 0.97). MRF T1 relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T2 relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001) Conclusions Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

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