High-frequency longitudinal white matter diffusion- and myelin-based MRI database: Reliability and variability.

Assessing the consistency of quantitative MRI measurements is critical for inclusion in longitudinal studies and clinical trials. Intraclass coefficient correlation and coefficient of variation were used to evaluate the different consistency aspects of diffusion- and myelin-based MRI measures. Multi-shell diffusion and inhomogeneous magnetization transfer data sets were collected from 20 healthy adults at a high-frequency of five MRI sessions. The consistency was evaluated across whole bundles and the track-profile along the bundles. The impact of the fiber populations on the consistency was also evaluated using the number of fiber orientations map. For whole and profile bundles, moderate to high reliability of diffusion and myelin measures were observed. We report higher reliability of measures for multiple fiber populations than single. The overall portrait of the most consistent measurements and bundles drawn from a wide range of MRI techniques presented here will be particularly useful for identifying reliable biomarkers capable of detecting, monitoring and predicting white matter changes in clinical applications and has the potential to inform patient-specific treatment strategies.

TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity.

Diffusion MRI tractography processing pipeline requires a large number of steps (typically 20+ steps). If parameters of these steps, number of threads, and random seed generators are not carefully controlled, the resulting tractography can easily be non-reproducible and non-replicable, even in test-test experiments. To handle these issues, we developed TractoFlow. TractoFlow is fully automatic from raw diffusion weighted images to tractography. The pipeline also outputs classical diffusion tensor imaging measures and several fiber orientation distribution function measures. TractoFlow supports the recent Brain Imaging Data Structure (BIDS) format as input and is based on two engines: Nextflow and Singularity. In this work, the TractoFlow pipeline is evaluated on three databases and shown to be efficient and reproducible from 98% to 100%, depending on parameter choices. Moreover, it is easy to use for non-technical users, with little to no installation requirements. TractoFlow is publicly available for academic research and is an important step forward for better structural brain connectivity mapping.

Quantification of apparent axon density and orientation dispersion in the white matter of youth born with congenital heart disease.

BACKGROUND: White matter alterations have previously been demonstrated in adolescents born with congenital heart disease (CHD) using diffusion tensor imaging (DTI). However, due to the non-specific nature of DTI metrics, it is difficult to interpret these findings in terms of their microstructural implications. This study investigated the use of neurite orientation dispersion and density imaging (NODDI), which involves the acquisition of advanced multiple b-value data over two shells and provides proxy measures of apparent axon density and orientation dispersion within white matter, as a complement to classic DTI measures. STUDY DESIGN: Youth aged 16 to 24 years born with complex CHD and healthy peers underwent brain magnetic resonance imaging. White matter tract volumes and tract-average values of DTI and NODDI metrics were compared between groups. Tract-average DTI and NODDI results were spatially confirmed using tract-based spatial statistics. RESULTS: There were widespread regions of lower tract-average neurite density index (NDI) in the CHD group as compared to the control group, particularly within long association tracts and in regions of the corpus callosum, accompanied by smaller white matter tract volumes and isolated clusters of lower fractional anisotropy (FA). There were no significant differences in orientation dispersion index (ODI) between groups. CONCLUSION: Lower apparent density of axonal packing, but not altered axonal orientation, is a key microstructural factor in the white matter abnormalities observed in youth born with CHD. These impairments in axonal packing may be an enduring consequence of early life brain injury and dysmaturation and may explain some of the long-term neuropsychological difficulties experienced by this at-risk group.

Limits to anatomical accuracy of diffusion tractography using modern approaches.

Diffusion MRI fiber tractography is widely used to probe the structural connectivity of the brain, with a range of applications in both clinical and basic neuroscience. Despite widespread use, tractography has well-known pitfalls that limits the anatomical accuracy of this technique. Numerous modern methods have been developed to address these shortcomings through advances in acquisition, modeling, and computation. To test whether these advances improve tractography accuracy, we organized the 3-D Validation of Tractography with Experimental MRI (3D-VoTEM) challenge at the ISBI 2018 conference. We made available three unique independent tractography validation datasets - a physical phantom and two ex vivo brain specimens - resulting in 176 distinct submissions from 9 research groups. By comparing results over a wide range of fiber complexities and algorithmic strategies, this challenge provides a more comprehensive assessment of tractography's inherent limitations than has been reported previously. The central results were consistent across all sub-challenges in that, despite advances in tractography methods, the anatomical accuracy of tractography has not dramatically improved in recent years. Taken together, our results independently confirm findings from decades of tractography validation studies, demonstrate inherent limitations in reconstructing white matter pathways using diffusion MRI data alone, and highlight the need for alternative or combinatorial strategies to accurately map the fiber pathways of the brain.

The role of the arcuate and middle longitudinal fasciculi in speech perception in noise in adulthood.

In this article, we used High Angular Resolution Diffusion Imaging (HARDI) with advanced anatomically constrained particle filtering tractography to investigate the role of the arcuate fasciculus (AF) and the middle longitudinal fasciculus (MdLF) in speech perception in noise in younger and older adults. Fourteen young and 15 elderly adults completed a syllable discrimination task in the presence of broadband masking noise. Mediation analyses revealed few effects of age on white matter (WM) in these fascicles but broad effects of WM on speech perception, independently of age, especially in terms of sensitivity and criterion (response bias), after controlling for individual differences in hearing sensitivity and head size. Indirect (mediated) effects of age on speech perception through WM microstructure were also found, after controlling for individual differences in hearing sensitivity and head size, with AF microstructure related to sensitivity, response bias and phonological priming, and MdLF microstructure more strongly related to response bias. These findings suggest that pathways of the perisylvian region contribute to speech processing abilities, with relatively distinct contributions for the AF (sensitivity) and MdLF (response bias), indicative of a complex contribution of both phonological and cognitive processes to age-related speech perception decline. These results provide new and important insights into the roles of these pathways as well as the factors that may contribute to elderly speech perception deficits. They also highlight the need for a greater focus to be placed on studying the role of WM microstructure to understand cognitive aging.

White matter degeneration profile in the cognitive cortico-subcortical tracts in Parkinson's disease.

BACKGROUND: In Parkinson's disease cognitive impairment is an early nonmotor feature, but it is still unclear why some patients are able to maintain their cognitive performance at normal levels, as quantified by neuropsychological tests, whereas others cannot. The objectives of this study were to perform a cross-sectional study and analyze the white matter changes in the cognitive and motor bundles in patients with Parkinson's disease. METHODS: Sixteen Parkinson's disease patients with normal cognitive performance, 19 with mild cognitive impairment (based on their performance of 1.5 standard deviations below the healthy population mean), and 16 healthy controls were compared with respect to their tractography patterns between the cortical cognitive / motor regions and subcortical structures, using high angular resolution diffusion imaging and constrained spherical deconvolution computation. RESULTS: Motor bundles showed decreased apparent fiber density in both PD groups, associated with a significant increase in diffusivity metrics, number of reconstructed streamlines, and track volumes, compared with healthy controls. By contrast, in the cognitive bundles, decreased fiber density in both Parkinson's groups was compounded by the absence of changes in diffusivity in patients with normal cognition, whereas patients with cognitive impairment had increased diffusivity metrics, lower numbers of reconstructed streamlines, and lower track volumes. CONCLUSIONS: Both PD groups showed similar patterns of white matter neurodegeneration in the motor bundles, whereas cognitive bundles showed a distinct pattern: Parkinson's patients with normal cognition had white matter diffusivity metrics similar to healthy controls, whereas in patients with cognitive impairment white matter showed a neurodegeneration pattern. © 2018 International Parkinson and Movement Disorder Society.

The Corticocortical Structural Connectivity of the Human Insula.

The insula is a complex structure involved in a wide range of functions. Tracing studies on nonhuman primates reveal a wide array of cortical connections in the frontal (orbitofrontal and prefrontal cortices, cingulate areas and supplementary motor area), parietal (primary and secondary somatosensory cortices) and temporal (temporal pole, auditory, prorhinal and entorhinal cortices) lobes. However, recent human tractography studies have not observed connections between the insula and the cingulate cortices, although these structures are thought to be functionally intimately connected. In this work, we try to unravel the structural connectivity between these regions and other known functionally connected structures, benefiting from a higher number of subjects and the latest state-of-the-art high angular resolution diffusion imaging (HARDI) tractography algorithms with anatomical priors. By performing an HARDI tractography analysis on 46 young normal adults, our study reveals a wide array of connections between the insula and the frontal, temporal, parietal and occipital lobes as well as limbic regions, with a rostro-caudal organization in line with tracing studies in macaques. Notably, we reveal for the first time in humans a clear structural connectivity between the insula and the cingulate, parahippocampal, supramarginal and angular gyri as well as the precuneus and occipital regions.

Fiber tractography using machine learning.

We present a fiber tractography approach based on a random forest classification and voting process, guiding each step of the streamline progression by directly processing raw diffusion-weighted signal intensities. For comparison to the state-of-the-art, i.e. tractography pipelines that rely on mathematical modeling, we performed a quantitative and qualitative evaluation with multiple phantom and in vivo experiments, including a comparison to the 96 submissions of the ISMRM tractography challenge 2015. The results demonstrate the vast potential of machine learning for fiber tractography.

The role of the pallidothalamic fibre tracts in deep brain stimulation for dystonia: A diffusion MRI tractography study.

BACKGROUND: Deep Brain Stimulation (DBS) of the Globus pallidus internus (GPi) is gold standard treatment in medically refractory dystonia. Recent evidence indicates that stimulation effects are also due to axonal modulation and affection of a fibre network. For the GPi, the pallidothalamic tracts are known to be the major motor efferent pathways. The aim of this study is to explore the anatomic vicinity of these tracts and DBS electrodes in dystonia applying diffusion tractography. METHODS: Diffusion MRI was acquired in ten patients presenting for DBS for dystonia. We applied both a conventionally used probabilistic tractography algorithm (FSL) as well as a probabilistic streamline tracking approach, based on constrained spherical deconvolution and particle filtering with anatomic priors, to the datasets. DBS electrodes were coregistered to the diffusion datasets. RESULTS: We were able to delineate the pallidothalamic tracts in all patients. Using the streamline approach, we were able to distinguish between the two sub-components of the tracts, the ansa lenticularis and the fasciculus lenticularis. Clinically efficient DBS electrodes displayed a close anatomic vicinity pathway of the pallidothalamic tracts, and their course was consistent with previous tracer labelling studies. Although we present only anatomic data, we interpret these findings as evidence of the possible involvement of fibre tracts to the clinical effect in DBS. Electrophysiological intraoperative recordings would be needed to complement our findings. In the future, a clear and individual delineation of the pallidothalamic tracts could optimize the stereotactic process of optimal electrode localization. Hum Brain Mapp 38:1224-1232, 2017. © 2016 Wiley Periodicals, Inc.

A new compression format for fiber tracking datasets.

A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications.

Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system.

Since 2015, research groups have sought to produce the ne plus ultra of tractography algorithms using the ISMRM 2015 Tractography Challenge as evaluation. In particular, since 2017, machine learning has made its entrance into the tractography world. The ISMRM 2015 Tractography Challenge is the most used phantom during tractography validation, although it contains limitations. Here, we offer a new scoring system for this phantom, where segmentation of the bundles is now based on manually defined regions of interest rather than on bundle recognition. Bundles are now more reliably segmented, offering more representative metrics for future users. New code is available online. Scores of the initial 96 submissions to the challenge are updated. Overall, conclusions from the 2015 challenge are confirmed with the new scoring, but individual tractogram scores have changed, and the data is much improved at the bundle- and streamline-level. This work also led to the production of a ground truth tractogram with less broken or looping streamlines and of an example of processed data, all available on the Tractometer website. This enhanced scoring system and new data should continue helping researchers develop and evaluate the next generation of tractography techniques.

Impact of follow ups, time interval and study duration in diffusion & myelin MRI clinical study in MS.

It is currently unknown how quantitative diffusion and myelin MRI designs affect the results of a longitudinal study. We used two independent datasets containing 6 monthly MRI measurements from 20 healthy controls and 20 relapsing-remitting multiple sclerosis (RR-MS) patients. Six designs were tested, including 3 MRI acquisitions, either over 6 months or over a shorter study duration, with balanced (same interval) or unbalanced (different interval) time intervals between MRI acquisitions. First, we show that in RR-MS patients, the brain changes over time obtained with 3 MRI acquisitions were similar to those observed with 5 MRI acquisitions and that designs with an unbalanced time interval showed the highest similarity, regardless of study duration. No significant brain changes were found in the healthy controls over the same periods. Second, the study duration affects the sample size in the RR-MS dataset; a longer study requires more subjects and vice versa. Third, the number of follow-up acquisitions and study duration affect the sensitivity and specificity of the associations with clinical parameters, and these depend on the white matter bundle and MRI measure considered. Together, this suggests that the optimal design depends on the assumption of the dynamics of change in the target population and the accuracy required to capture these dynamics. Thus, this work provides a better understanding of key factors to consider in a longitudinal study and provides clues for better strategies in clinical trial design.

Tractography in the study of the human brain: a neurosurgical perspective.

BACKGROUND: The brain functions as an integrated multi-networked organ. Complex neurocognitive functions are not attributed to a single brain area but depend on the dynamic interactions of distributed brain areas operating in large-scale networks. This is especially important in the field of neurosurgery where intervention within a spatially localized area may indirectly lead to unwanted effects on distant areas. As part of a preliminary integrated work on functional connectivity, we present our initial work on diffusion tensor imaging tractography to produce in vivo white matter tracts dissection. METHODS: Diffusion weighted data and high-resolution T1- weighted images were acquired from a healthy right-handed volunteer (25 years old) on a whole-body 3 T scanner. Two approaches were used to dissect the tractography results: 1) a standard region of interest technique and 2) the use of Brodmann's area as seeding points, which represents an innovation in terms of seeds initiation. RESULTS: Results are presented as tri-dimensional tractography images. The uncinate fasciculus, the inferior longitudinal fasciculus, the inferior fronto-occipital fasiculus, the corticospinal tract, the corpus callosum, the cingulum, and the optic radiations where studied by conventional seeding approach, while Broca's and Wernicke's areas, the primary motor as well as the primary visual cortices were used as seeding areas in the second approach. CONCLUSIONS: We report state-of-the-art tractography results of some of the major white matter bundles in a normal subject using DTI. Moreover, we used Brodmann's area as seeding areas for fiber tracts to study the connectivity of known major functional cortical areas.

A multi-scale probabilistic atlas of the human connectome.

The human brain is a complex system that can be efficiently represented as a network of structural connectivity. Many imaging studies would benefit from such network information, which is not always available. In this work, we present a whole-brain multi-scale structural connectome atlas. This tool has been derived from a cohort of 66 healthy subjects imaged with optimal technology in the setting of the Human Connectome Project. From these data we created, using extensively validated diffusion-data processing, tractography and gray-matter parcellation tools, a multi-scale probabilistic atlas of the human connectome. In addition, we provide user-friendly and accessible code to match this atlas to individual brain imaging data to extract connection-specific quantitative information. This can be used to associate individual imaging findings, such as focal white-matter lesions or regional alterations, to specific connections and brain circuits. Accordingly, network-level consequences of regional changes can be analyzed even in absence of diffusion and tractography data. This method is expected to broaden the accessibility and lower the yield for connectome research.

Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children.

Because of their high prevalence, heterogeneous clinical presentation, and wide-ranging sequelae, concussions are a challenging neurological condition, especially in children. Shearing forces transmitted across the brain during concussions often result in white matter damage. The neuropathological impact of concussions has been discerned from animal studies and includes inflammation, demyelination, and axonal loss. These pathologies can overlap during the sub-acute stage of recovery. However, due to the challenges of accurately modeling complex white matter structure, these neuropathologies have not yet been differentiated in children in vivo. In the present study, we leveraged recent advances in diffusion imaging modeling, tractography, and tractometry to better understand the neuropathology underlying working memory problems in concussion. Studying a sample of 16 concussed and 46 healthy youths, we used novel tractography methods to isolate 11 working memory tracks. Along these tracks, we measured fractional anisotropy, diffusivities, track volume, apparent fiber density, and free water fraction. In three tracks connecting the right thalamus to the right dorsolateral prefrontal cortex (DLPFC), we found microstructural differences suggestive of myelin alterations. In another track connecting the left anterior-cingulate cortex with the left DLPFC, we found microstructural changes suggestive of axonal loss. Structural differences and tractography reconstructions were reproduced using test-retest analyses. White matter structure in the three thalamo-prefrontal tracks, but not the cingulo-prefrontal track, appeared to play a key role in working memory function. The present results improve understanding of working memory neuropathology in concussions, which constitutes an important step toward developing neuropathologically informed biomarkers of concussion in children.

Fascicle- and Glucose-Specific Deterioration in White Matter Energy Supply in Alzheimer's Disease.

BACKGROUND: White matter energy supply to oligodendrocytes and the axonal compartment is crucial for normal axonal function. Although gray matter glucose hypometabolism is extensively reported in Alzheimer's disease (AD), glucose and ketones, the brain's two main fuels, are rarely quantified in white matter in AD. OBJECTIVE: Using a dual-tracer PET method combined with a fascicle-specific diffusion MRI approach, robust to white matter hyper intensities and crossing fibers, we aimed to quantify both glucose and ketone metabolism in specific white matter fascicles associated with mild cognitive impairment (MCI; n = 51) and AD (n = 13) compared to cognitively healthy age-matched controls (Controls; n = 14). METHODS: Eight white matter fascicles of the limbic lobe and corpus callosum were extracted and analyzed into fascicle profiles of five sections. Glucose (18F-fluorodeoxyglucose) and ketone (11C-acetoacetate) uptake rates, corrected for partial volume effect, were calculated along each fascicle. RESULTS: The only fascicle with significantly lower glucose uptake in AD compared to Controls was the left posterior cingulate segment of the cingulum (-22%; p = 0.016). Non-significantly lower glucose uptake in this fascicle was also observed in MCI. In contrast to glucose, ketone uptake was either unchanged or higher in sections of the fornix and parahippocampal segment of the cingulum in AD. CONCLUSION: To our knowledge, this is the first report of brain fuel uptake calculated along white matter fascicles in humans. Energetic deterioration in white matter in AD appears to be specific to glucose and occurs first in the posterior cingulum.

Tractography of the external capsule and cognition: A diffusion MRI study of cholinergic fibers.

INTRODUCTION: White matter changes (WMC) in the cholinergic tracts contribute to executive dysfunction in the context of cognitive aging. WMC in the external capsule have been associated with executive dysfunction. The objectives of this study were to: 1) Characterize the lateral cholinergic tracts (LCT) and the superior longitudinal fasciculus (SLF). 2) Evaluate the association between diffusion measures within those tracts and cognitive performance. METHODS: Neuropsychological testing and high angular resolution diffusion imaging (HARDI) of 34 healthy elderly participants was done, followed by anatomically constrained probabilistic tractography reconstruction robust to crossing fibers. The external capsule was manually segmented on a mean T1 image then merged with an atlas, allowing extraction of the LCT. Diffusion tensor imaging (DTI) and HARDI-based measures were obtained. RESULTS: Correlations between diffusion measures in the LCT and the time of completion of Stroop (left LCT radial and medial diffusivity), the Symbol Search score (right LCT apparent fiber density) and the motor part of Trail-B (left LCT axial and radial diffusivity) were observed. Correlations were also found with diffusion measures in the SLF. WMC burden was low, and no correlation was found with diffusion measures or cognitive performance. DISCUSSION: DTI and HARDI, with isolation of strategic white matter tracts for cognitive functions, represent complimentary tools to better understand the complex process of brain aging.

Structural and functional multi-platform MRI series of a single human volunteer over more than fifteen years.

We present MRI data from a single human volunteer consisting in over 599 multi-contrast MR images (T1-weighted, T2-weighted, proton density, fluid-attenuated inversion recovery, T2* gradient-echo, diffusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 different scanners (13 models, three manufacturers) over the course of 15+ years (cf. Data records). Data included planned data collection acquired within the Consortium pour l'identification précoce de la maladie Alzheimer - Québec (CIMA-Q) and Canadian Consortium on Neurodegeneration in Aging (CCNA) studies, as well as opportunistic data collection from various protocols. These multiple within- and between-centre scans over a substantial time course of a single, cognitively healthy volunteer can be useful to answer a number of methodological questions of interest to the community.

Free Water in White Matter Differentiates MCI and AD From Control Subjects.

Recent evidence shows that neuroinflammation plays a role in many neurological diseases including mild cognitive impairment (MCI) and Alzheimer's disease (AD), and that free water (FW) modeling from clinically acquired diffusion MRI (DTI-like acquisitions) can be sensitive to this phenomenon. This FW index measures the fraction of the diffusion signal explained by isotropically unconstrained water, as estimated from a bi-tensor model. In this study, we developed a simple but powerful whole-brain FW measure designed for easy translation to clinical settings and potential use as a priori outcome measure in clinical trials. These simple FW measures use a "safe" white matter (WM) mask without gray matter (GM)/CSF partial volume contamination (WM safe) near ventricles and sulci. We investigated if FW inside the WM safe mask, including and excluding areas of white matter damage such as white matter hyperintensities (WMHs) as shown on T2 FLAIR, computed across the whole white matter could be indicative of diagnostic grouping along the AD continuum. After careful quality control, 81 cognitively normal controls (NC), 103 subjects with MCI and 42 with AD were selected from the ADNIGO and ADNI2 databases. We show that MCI and AD have significantly higher FW measures even after removing all partial volume contamination. We also show, for the first time, that when WMHs are removed from the masks, the significant results are maintained, which demonstrates that the FW measures are not just a byproduct of WMHs. Our new and simple FW measures can be used to increase our understanding of the role of inflammation-associated edema in AD and may aid in the differentiation of healthy subjects from MCI and AD patients.

Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions.

Diffusion MRI (dMRI) fiber tractography has become a pillar of the neuroimaging community due to its ability to noninvasively map the structural connectivity of the brain. Despite widespread use in clinical and research domains, these methods suffer from several potential drawbacks or limitations. Thus, validating the accuracy and reproducibility of techniques is critical for sound scientific conclusions and effective clinical outcomes. Towards this end, a number of international benchmark competitions, or "challenges", has been organized by the diffusion MRI community in order to investigate the reliability of the tractography process by providing a platform to compare algorithms and results in a fair manner, and evaluate common and emerging algorithms in an effort to advance the state of the field. In this paper, we summarize the lessons from a decade of challenges in tractography, and give perspective on the past, present, and future "challenges" that the field of diffusion tractography faces.