Reducing variability in along-tract analysis with diffusion profile realignment

Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific investigation than considering a region of interest or tract-averaged measurements. However, performing group analyses with this along-tract strategy requires correspondence between points of tract pathways across subjects. This is usually achieved by creating a new common space where the representative streamlines from every subject are resampled to the same number of points. If the underlying anatomy of some subjects was altered due to, e.g. disease or developmental changes, such information might be lost by resampling to a fixed number of points. In this work, we propose to address the issue of possible misalignment, which might be present even after resampling, by realigning the representative streamline of each subject in this 1D space with a new method, coined diffusion profile realignment (DPR). Experiments on synthetic datasets show that DPR reduces the coefficient of variation for the mean diffusivity, fractional anisotropy and apparent fiber density when compared to the unaligned case. Using 100 in vivo datasets from the HCP, we simulated changes in mean diffusivity, fractional anisotropy and apparent fiber density. Pairwise Student's t-tests between these altered subjects and the original subjects indicate that regional changes are identified after realignment with the DPR algorithm, while preserving differences previously detected in the unaligned case. This new correction strategy contributes to revealing effects of interest which might be hidden by misalignment and has the potential to improve the specificity in longitudinal population studies beyond the traditional region of interest based analysis and along-tract analysis workflows.Comment: v4: peer-reviewed round 2 v3 : deleted some old text from before peer-review which was mistakenly included v2 : peer-reviewed version v1: preprint as submitted to journal NeuroImag

Visualisation en imagerie par résonance magnétique de diffusion : tractographie en temps réel des fibres de la matière blanche du cerveau

L'imagerie par résonance magnétique de diffusion est une technique non-invasive permettant de mesurer la diffusion des molécules d'eau selon plusieurs directions. Le résultat d'une telle acquisition contient de l'information implicite sur les structures microbiologiques qui composent le cerveau humain. La tractographie consiste à déterminer et visualiser, en trois dimensions, l'ensemble des connections neuronales de la matière blanche du cerveau en suivant la diffusion préférentielle de l'eau présente en chaque voxel. Les fibres de la matière blanche sont responsables de connecter les différentes aires fonctionnelles du cerveau entre-elles. En présence d'une tumeur, elles peuvent se réorganiser de multiples façons et refaire des connections pour assurer le suivi des fonctions importantes. L'imagerie du câblage cérébral est utilisée lors d'interventions neurochirurgicales afin d'aider le neurochirurgien à planifier son angle d'attaque pour réséquer le maximum de la tumeur sans léser la fonction du patient. La tractographie prend donc tout son sens pour le neurochirurgien avant et pendant l'opération. Dans ce mémoire, il sera question de tractographie en temps réel. La plupart des algorithmes de tractographie utilisent des paramètres fixes et prédéfinis pour l'ensemble du cerveau. Nous croyons que ces paramètres devraient être accessibles et modifiables afin de voir l'impact que ceux-ci ont sur la reconstruction des connections cérébrales. Nous proposons une méthode de visualisation de fibres en temps réel, permettant de calculer et d'afficher instantanément le résultat d'un nouvel algorithme de tractographie qui sera confronté aux méthodes existantes. Le nouveau module permet d'effectuer la tractographie des fibres de la matière blanche de manière interactive en offrant la possibilité d'ajuster les paramètres impliqués dans le processus de tractographie. Il a notamment été introduit plus d'une vingtaine de fois lors d'interventions neurochirurgicales au Centre Hospitalier Universitaire de Sherbrooke, grâce à la supervision du Dr. David Fortin. La tractographie en temps réel a changé la manière dont les données sont préparées en vue d'une intervention en bloc opératoire. Dans un contexte où le temps entre le traitement des données et l'intervention chirurgicale est une contrainte majeure, l'élimination de l'étape de tractographie du processus de prétraitement est un avantage non-négligeable

Neural Spherical Harmonics for structurally coherent continuous representation of diffusion MRI signal

We present a novel way to model diffusion magnetic resonance imaging (dMRI) datasets, that benefits from the structural coherence of the human brain while only using data from a single subject. Current methods model the dMRI signal in individual voxels, disregarding the intervoxel coherence that is present. We use a neural network to parameterize a spherical harmonics series (NeSH) to represent the dMRI signal of a single subject from the Human Connectome Project dataset, continuous in both the angular and spatial domain. The reconstructed dMRI signal using this method shows a more structurally coherent representation of the data. Noise in gradient images is removed and the fiber orientation distribution functions show a smooth change in direction along a fiber tract. We showcase how the reconstruction can be used to calculate mean diffusivity, fractional anisotropy, and total apparent fiber density. These results can be achieved with a single model architecture, tuning only one hyperparameter. In this paper we also demonstrate how upsampling in both the angular and spatial domain yields reconstructions that are on par or better than existing methods.Comment: 12 pages, 6 figures, accepted for cdMRI workshop at MICCAI 202

Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware

Introduction Surgical resection is an effective treatment for temporal lobe epilepsy but can result in visual field defects. This could be minimized if surgeons knew the exact location of the anterior part of the optic radiation (OR), the Meyer's loop. To this end, there is increasing prevalence of image-guided surgery using diffusion MRI tractography. Despite considerable effort in developing analysis methods, a wide discrepancy in Meyer's loop reconstructions is observed in the literature. Moreover, the impact of differences in image acquisition on Meyer's loop tractography remains unclear. Here, while employing the same state-of-the-art analysis protocol, we explored the extent to which variance in data acquisition leads to variance in OR reconstruction. Methods Diffusion MRI data were acquired for the same thirteen healthy subjects using standard and state-of-the-art protocols on three scanners with different maximum gradient amplitudes (MGA): Siemens Connectom (MGA = 300 mT/m); Siemens Prisma (MGA = 80 mT/m) and GE Excite-HD (MGA = 40 mT/m). Meyer's loop was reconstructed on all subjects and its distance to the temporal pole (ML-TP) was compared across protocols. Results A significant effect of data acquisition on the ML-TP distance was observed between protocols (p < .01 to 0.0001). The biggest inter-acquisition discrepancy for the same subject across different protocols was 16.5 mm (mean: 9.4 mm, range: 3.7–16.5 mm). Conclusion We showed that variance in data acquisition leads to substantive variance in OR tractography. This has direct implications for neurosurgical planning, where part of the OR is at risk due to an under-estimation of its location using conventional acquisition protocols

Voxlines: Streamline Transparency through Voxelization and View-Dependent Line Orders

As tractography datasets continue to grow in size, there is a need for improved visualization methods that can capture structural patterns occurring in large tractography datasets. Transparency is an increasingly important aspect of finding these patterns in large datasets but is inaccessible to tractography due to performance limitations. In this paper, we propose a rendering method that achieves performant rendering of transparent streamlines, allowing for exploration of deeper brain structures interactively. The method achieves this through a novel approximate order-independent transparency method that utilizes voxelization and caching view-dependent line orders per voxel. We compare our transparency method with existing tractography visualization software in terms of performance and the ability to capture deeper structures in the dataset.Comment: 12 pages. 4 figures. Accepted at Computational Diffusion MRI Workshop (CDMRI) at Medical Image Computing and Computer Assisted Intervention (MICCAI) 202

Multimodal principal component analysis to identify major features of white matter structure and links to reading

The role of white matter in reading has been established by diffusion tensor imaging (DTI), but DTI cannot identify specific microstructural features driving these relationships. Neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT) can be used to link more specific aspects of white matter microstructure and reading due to their sensitivity to axonal packing and fiber coherence (NODDI) and myelin (ihMT and mcDESPOT). We applied principal component analysis (PCA) to combine DTI, NODDI, ihMT and mcDESPOT measures (10 in total), identify major features of white matter structure, and link these features to both reading and age. Analysis was performed for nine reading-related tracts in 46 neurotypical 6–16 year olds. We identified three principal components (PCs) which explained 79.5% of variance in our dataset. PC1 probed tissue complexity, PC2 described myelin and axonal packing, while PC3 was related to axonal diameter. Mixed effects regression models did not identify any significant relationships between principal components and reading skill. Bayes factor analysis revealed that the absence of relationships was not due to low power. Increasing PC1 in the left arcuate fasciculus with age suggest increases in tissue complexity, while increases of PC2 in the bilateral arcuate, inferior longitudinal, inferior fronto-occipital fasciculi, and splenium suggest increases in myelin and axonal packing with age. Multimodal white matter imaging and PCA provide microstructurally informative, powerful principal components which can be used by future studies of development and cognition. Our findings suggest major features of white matter undergo development during childhood and adolescence, but changes are not linked to reading during this period in our typically-developing sample

To put an end to car dependence - Final report of the scoping review of the literature on the modal shift from the car to alternative modes 2010-2020

This research answers the following question: what are the main modal shift strategies discussed in the literature of the last 10 years? It also undertakes to analyze the impacts of each of the strategies present in the literature. It presents a scoping review of the literature aiming to draw an up-to-date portrait of the abundant literature on modal shift in order to synthesize it and present it in an organized manner and draw conclusions for future research and transport and development policies aimed at reducing automobile dependence and inducing a modal shift from the automobile to alternative modes of transport. We reviewed 2,872 studies published between 2010 and 2020 and retained 108 that we analyzed in detail. More than two thirds of studies report positive results of modal shift from the car towards alternative mobility. This leads us to believe that it is possible to implement public policies to facilitate modal shift and thus help reduce car dependence. A large majority of research on public transport reports positive examples. However, for studies on active transportation, we note that almost all of the research (92%) reports successes. By paying attention to the degree of coercion of the interventions investigated in the literature, we see that the “carrot” measures which seek to induce the modal shift by offering a benefit are more successful than the “stick” type measures which aim to restrict certain choices (pricing, tolls, reduction of parking spaces). However, research on the “carrot and stick” combination approach reports the most positive results. This leads us to conclude that research on this type of intervention should continue to be developed, even encouraged, and to suggest that public decision-makers take into account the beneficial effects for modal shift resulting from the combination of the two types of interventions simultaneously “carrot and stick”

Impact of b-value on estimates of apparent fibre density

Recent advances in diffusion magnetic resonance imaging (dMRI) analysis techniques have improved our understanding of fibre-specific variations in white matter microstructure. Increasingly, studies are adopting multi-shell dMRI acquisitions to improve the robustness of dMRI-based inferences. However, the impact of b-value choice on the estimation of dMRI measures such as apparent fibre density (AFD) derived from spherical deconvolution is not known. Here, we investigate the impact of b-value sampling scheme on estimates of AFD. First, we performed simulations to assess the correspondence between AFD and simulated intra-axonal signal fraction across multiple b-value sampling schemes. We then studied the impact of sampling scheme on the relationship between AFD and age in a developmental population (n=78) aged 8-18 (mean=12.4, SD=2.9 years) using hierarchical clustering and whole brain fixel-based analyses. Multi-shell dMRI data were collected at 3.0T using ultra-strong gradients (300 mT/m), using 6 diffusion-weighted shells ranging from 0 – 6000 s/mm2. Simulations revealed that the correspondence between estimated AFD and simulated intra-axonal signal fraction was improved with high b-value shells due to increased suppression of the extra-axonal signal. These results were supported by in vivo data, as sensitivity to developmental age-relationships was improved with increasing b-value (b=6000 s/mm2, median R2 = .34; b=4000 s/mm2, median R2 = .29; b=2400 s/mm2, median R2 = .21; b=1200 s/mm2, median R2 = .17) in a tract-specific fashion. Overall, estimates of AFD and age-related microstructural development were better characterised at high diffusion-weightings due to improved correspondence with intra-axonal properties

Pour en finir avec la dépendance automobile : rapport final de l’étude de la portée de la littérature sur le transfert modal de la voiture aux modes alternatifs 2010-2020

Cette recherche répond à la question suivante : quelles sont les principales stratégies de transfert modal discutées dans la littérature des 10 dernières années. Elle entreprend aussi d’analyser les impacts de chacune des stratégies présentes dans littérature. Elle présente une étude de la portée de la littérature visant à dresser un portrait à jour de l’abondante littérature sur le transfert modal afin de la synthétiser et de la présenter de façon organisée et d’en tirer des constats pour la recherche future et les politiques de transport et d’aménagement visant à réduire la dépendance automobile et à induire un transfert modal de l’automobile vers les modes de transports alternatifs. Nous avons révisé 2872 études publiées entre 2010-2020 et en avons retenu 108 que nous avons analysées en détail. Plus de deux tiers des études rapportent des résultats positifs de transfert modal de la voiture au profit des mobilités alternatives. Ce qui nous porte à croire qu’il est possible de mettre en place des politiques publiques afin de faciliter le transfert modal et d’ainsi contribuer à réduire la dépendance à l’automobile. Parmi les recherches portant sur les transports en commun, une grande majorité rapporte des exemples positifs. Cependant, du côté des études portant sur le transport actif, nous notons que la presque totalité des recherches (92 %) rapporte des succès. En portant attention au degré de coercition des interventions enquêtées dans la littérature, on constate que les mesures « carotte » qui cherchent à induire le transfert modal en offrant un bénéfice ont plus de succès que les mesures de type « bâton » qui visent à restreindre certains choix (tarification, péage, diminution des espaces de stationnement). Cependant, les recherches portant sur la combinaison « carotte et bâton » rapportent les résultats les plus positifs. Ceci nous amène à conclure que la recherche sur ce type d’intervention devrait continuer à être développée, voire encouragée, et à suggérer aux décideurs publics de tenir compte des effets bénéfiques pour le transfert modal provenant de la combinaison des deux types d’interventions simultanément « carotte et bâton »