Impacts des étapes de pré-traitement des données de diffusion sur la tractographie - Imagerie de diffusion

Ce mémoire présente l'ensemble des étapes de pré-traitement appliquées aux images provenant de l'imagerie par résonance magnétique de diffusion afin de conseiller les meilleurs paramètres dans une étude de tractographie. L'imagerie de diffusion nous donne l'information locale des déplacements moyens des molécules d'eau dans le cerveau. Cette information nous permet d'inférer l'architecture de la matière blanche. La reconstruction du signal de diffusion fait appel à différentes méthodes plus ou moins aptes à restituer la complexité des configurations de fibres. Dans ce mémoire, nous proposons une nouvelle méthode de reconstruction du phénomène de diffusion basée sur la décomposition en ondelettes sphériques. Ensuite, en combinant ces informations à tous les points du cerveau nous reconstruisons le réseau de fibres de la matière blanche par un algorithme de tractographie déterministe. Afin d'initier cet algorithme, nous proposons une nouvelle méthode d'initialisation dans le but de mieux gérer la complexité des configurations de fibres au sein d'un seul voxel. Les fibres reconstruites sont très difficiles à évaluer dans le cerveau car nous ne connaissons pas la configuration réelle des fibres. Pour être en mesure d'évaluer nos méthodes de reconstruction, nous utilisons un fantôme calquant la complexité des configurations de fibres trouvées dans le cerveau. Dans ce mémoire, nous proposons un ensemble de métriques et un système de notations permettant d'évaluer automatiquement la qualité des résultats d'une tractographie. Nous concluons l'étude concernant les données synthétiques par un ensemble de conseils sur les paramètres à utiliser afin d'obtenir des résultats de tractographie optimaux. Finalement, nous évaluons qualitativement les résultats de tractographie issus de données réelles afin de confirmer nos choix sur les données fantômes

The challenge of mapping the human connectome based on diffusion tractography

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations

Test-retest reliability of diffusion measures extracted along white matter language fiber bundles using HARDI-based tractography

High angular resolution diffusion imaging (HARDI)-based tractography has been increasingly used in longitudinal studies on white matter macro- and micro-structural changes in the language network during language acquisition and in language impairments. However, test-retest reliability measurements are essential to ascertain that the longitudinal variations observed are not related to data processing. The aims of this study were to determine the reproducibility of the reconstruction of major white matter fiber bundles of the language network using anatomically constrained probabilistic tractography with constrained spherical deconvolution based on HARDI data, as well as to assess the test-retest reliability of diffusion measures extracted along them. Eighteen right-handed participants were scanned twice, one week apart. The arcuate, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculi were reconstructed in the left and right hemispheres and the following diffusion measures were extracted along each tract: fractional anisotropy, mean, axial, and radial diffusivity, number of fiber orientations, mean length of streamlines, and volume. All fiber bundles showed good morphological overlap between the two scanning timepoints and the test-retest reliability of all diffusion measures in most fiber bundles was good to excellent. We thus propose a fairly simple, but robust, HARDI-based tractography pipeline reliable for the longitudinal study of white matter language fiber bundles, which increases its potential applicability to research on the neurobiological mechanisms supporting language

Structural and functional multiplatform 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, fuid-attenuated inversion recovery, T2* gradient-echo, difusion, susceptibility-weighted, arterial-spin labelled, and resting state BOLD functional connectivity imaging) acquired in over 73 sessions on 36 diferent 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’identifcation 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

Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography

High angular resolution diffusion imaging (HARDI)-based tractography has been increasingly used in longitudinal studies on white matter macro- and micro-structural changes in the language network during language acquisition and in language impairments. However, test-retest reliability measurements are essential to ascertain that the longitudinal variations observed are not related to data processing. The aims of this study were to determine the reproducibility of the reconstruction of major white matter fiber bundles of the language network using anatomically constrained probabilistic tractography with constrained spherical deconvolution based on HARDI data, as well as to assess the test-retest reliability of diffusion measures extracted along them. Eighteen right-handed participants were scanned twice, one week apart. The arcuate, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculi were reconstructed in the left and right hemispheres and the following diffusion measures were extracted along each tract: fractional anisotropy, mean, axial, and radial diffusivity, number of fiber orientations, mean length of streamlines, and volume. All fiber bundles showed good morphological overlap between the two scanning timepoints and the test-retest reliability of all diffusion measures in most fiber bundles was good to excellent. We thus propose a fairly simple, but robust, HARDI-based tractography pipeline reliable for the longitudinal study of white matter language fiber bundles, which increases its potential applicability to research on the neurobiological mechanisms supporting language

Plasticity in the Sensitivity to Light in Aging: Decreased Non-visual Impact of Light on Cognitive Brain Activity in Older Individuals but No Impact of Lens Replacement

Beyond its essential visual role, light, and particularly blue light, has numerous non-visual effects, including stimulating cognitive functions and alertness. Non-visual effects of light may decrease with aging and contribute to cognitive and sleepiness complaints in aging. However, both the brain and the eye profoundly change in aging. Whether the stimulating effects light on cognitive brain functions varies in aging and how ocular changes may be involved is not established. We compared the impact of blue and orange lights on non-visual cognitive brain activity in younger (23.6 ± 2.5 years), and older individuals with their natural lenses (NL; 66.7 ± 5.1 years) or with intraocular lens (IOL) replacement following cataract surgery (69.6 ± 4.9 years). Analyses reveal that blue light modulates executive brain responses in both young and older individuals. Light effects were, however, stronger in young individuals including in the hippocampus and frontal and cingular cortices. Light effects did not significantly differ between older-IOL and older-NL while regression analyses indicated that differential brain engagement was not underlying age-related differences in light effects. These findings show that, although its impact decreases, light can stimulate cognitive brain activity in aging. Since lens replacement did not affect light impact, the brain seems to adapt to the progressive decrease in retinal light exposure in aging

Impacts des étapes de pré-traitement des données de diffusion sur la tractographie - Imagerie de diffusion

Ce mémoire présente l'ensemble des étapes de pré-traitement appliquées aux images provenant de l'imagerie par résonance magnétique de diffusion afin de conseiller les meilleurs paramètres dans une étude de tractographie. L'imagerie de diffusion nous donne l'information locale des déplacements moyens des molécules d'eau dans le cerveau. Cette information nous permet d'inférer l'architecture de la matière blanche. La reconstruction du signal de diffusion fait appel à différentes méthodes plus ou moins aptes à restituer la complexité des configurations de fibres. Dans ce mémoire, nous proposons une nouvelle méthode de reconstruction du phénomène de diffusion basée sur la décomposition en ondelettes sphériques. Ensuite, en combinant ces informations à tous les points du cerveau nous reconstruisons le réseau de fibres de la matière blanche par un algorithme de tractographie déterministe. Afin d'initier cet algorithme, nous proposons une nouvelle méthode d'initialisation dans le but de mieux gérer la complexité des configurations de fibres au sein d'un seul voxel. Les fibres reconstruites sont très difficiles à évaluer dans le cerveau car nous ne connaissons pas la configuration réelle des fibres. Pour être en mesure d'évaluer nos méthodes de reconstruction, nous utilisons un fantôme calquant la complexité des configurations de fibres trouvées dans le cerveau. Dans ce mémoire, nous proposons un ensemble de métriques et un système de notations permettant d'évaluer automatiquement la qualité des résultats d'une tractographie. Nous concluons l'étude concernant les données synthétiques par un ensemble de conseils sur les paramètres à utiliser afin d'obtenir des résultats de tractographie optimaux. Finalement, nous évaluons qualitativement les résultats de tractographie issus de données réelles afin de confirmer nos choix sur les données fantômes

A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved; a 20-year perspective

Combining MRI modalities is a growing trend in neurosciences. It provides opportunities to investigate the brain architecture supporting cognitive functions. Integrating fMRI activation to guide dMRI tractography offers potential advantages over standard tractography methods. A quick glimpse of the literature on this topic reveals that this technique is challenging, and no consensus or “best practices” currently exist, at least not within a single document. We present the first attempt to systematically analyze and summarize the literature of 80 studies that integrated task-based fMRI results to guide tractography, over the last two decades. We report 19 findings that cover challenges related to sample size, microstructure modelling, seeding methods, multimodal space registration, false negatives/positives, specificity/validity, gray/white matter interface and more. These findings will help the scientific community (1) understand the strengths and limitations of the approaches, (2) design studies using this integrative framework, and (3) motivate researchers to fill the gaps identified. We provide references toward best practices, in order to improve the overall result's replicability, sensitivity, specificity, and validity

Network-level prediction of set-shifting deterioration after lower-grade glioma resection

International audienceOBJECTIVE The aim of this study was to predict set-shifting deterioration after resection of low-grade glioma. METHODS The authors retrospectively analyzed a bicentric series of 102 patients who underwent surgery for low-grade glioma. The difference between the completion times of the Trail Making Test parts B and A (TMT B-A) was evaluated preoperatively and 3–4 months after surgery. High dimensionality of the information related to the surgical cavity topography was reduced to a small set of predictors in four different ways: 1) overlap between surgical cavity and each of the 122 cortical parcels composing Yeo’s 17-network parcellation of the brain; 2) Tractotron: disconnection by the cavity of the major white matter bundles; 3) overlap between the surgical cavity and each of Yeo’s networks; and 4) disconets: signature of structural disconnection by the cavity of each of Yeo’s networks. A random forest algorithm was implemented to predict the postoperative change in the TMT B-A z-score. RESULTS The last two network-based approaches yielded significant accuracies in left-out subjects (area under the receiver operating characteristic curve [AUC] approximately equal to 0.8, p approximately equal to 0.001) and outperformed the two alternatives. In single tree hierarchical models, the degree of damage to Yeo corticocortical network 12 (CC 12) was a critical node: patients with damage to CC 12 higher than 7.5% (cortical overlap) or 7.2% (disconets) had much higher risk to deteriorate, establishing for the first time a causal link between damage to this network and impaired set-shifting. CONCLUSIONS The authors’ results give strong support to the idea that network-level approaches are a powerful way to address the lesion-symptom mapping problem, enabling machine learning–powered individual outcome predictions

Functional network and structural connections involved in picture naming

We mapped the left hemisphere cortical regions and fiber bundles involved in picture naming in adults by integrating task-based fMRI with dMRI tractography. We showed that a ventral pathway that “maps image and sound to meaning” involves the middle occipital, inferior temporal, superior temporal, inferior frontal gyri, and the temporal pole where a signal exchange is made possible by the inferior fronto-occipital, inferior longitudinal, middle longitudinal, uncinate fasciculi, and the extreme capsule. A dorsal pathway that “maps sound to speech” implicates the inferior temporal, superior temporal, inferior frontal, precentral gyri, and the supplementary motor area where the arcuate fasciculus and the frontal aslant ensure intercommunication. This study provides a neurocognitive model of picture naming and supports the hypothesis that the ventral indirect route passes through the temporal pole. This further supports the idea that the inferior and superior temporal gyri may play pivotal roles within the dual-stream framework of language