270 research outputs found

    Assessment of white matter microstructure in stroke patients using NODDI

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    pre-printDiffusion weighted imaging (DWI) is widely used to study changes in white matter following stroke. In various studies employing diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI) modalities, it has been shown that fractional anisotropy (FA), mean diffusivity (MD), and generalized FA (GFA) can be used as measures of white matter tract integrity in stroke patients. However, these measures may be non-specific, as they do not directly delineate changes in tissue microstructure. Multi-compartment models overcome this limitation by modeling DWI data using a set of indices that are directly related to white matter microstructure. One of these models which is gaining popularity, is neurite orientation dispersion and density imaging (NODDI). his model uses conventional single or multi-shell HARDI data to describe fiber orientation dispersion as well as densities of different tissue types in the imaging voxel. In this paper, we apply for the first time the NODDI model to 4-shell HARDI stroke data. By computing NODDI indices over the entire brain in two stroke patients, and comparing tissue regions in ipsilesional and contralesional hemispheres, we demonstrate that NODDI modeling provides specific information on tissue microstructural changes. We also introduce an information theoretic analysis framework to investigate the non-local effects of stroke in the white matter. Our initial results suggest that the NODDI indices might be more specific markers of white matter reorganization following stroke than other measures previously used in studies of stroke recovery

    Diffusion tensor model links to neurite orientation dispersion and density imaging at high b-value in cerebral cortical gray matter

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    Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture

    Diffusion-Weighted Imaging: Recent Advances and Applications

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    Quantitative diffusion imaging techniques enable the characterization of tissue microstructural properties of the human brain “in vivo”, and are widely used in neuroscientific and clinical contexts. In this review, we present the basic physical principles behind diffusion imaging and provide an overview of the current diffusion techniques, including standard and advanced techniques as well as their main clinical applications. Standard diffusion tensor imaging (DTI) offers sensitivity to changes in microstructure due to diseases and enables the characterization of single fiber distributions within a voxel as well as diffusion anisotropy. Nonetheless, its inability to represent complex intravoxel fiber topologies and the limited biological specificity of its metrics motivated the development of several advanced diffusion MRI techniques. For example, high-angular resolution diffusion imaging (HARDI) techniques enabled the characterization of fiber crossing areas and other complex fiber topologies in a single voxel and supported the development of higher-order signal representations aiming to decompose the diffusion MRI signal into distinct microstructure compartments. Biophysical models, often known by their acronym (e.g., CHARMED, WMTI, NODDI, DBSI, DIAMOND) contributed to capture the diffusion properties from each of such tissue compartments, enabling the computation of voxel-wise maps of axonal density and/or morphology that hold promise as clinically viable biomarkers in several neurological and neuroscientific applications; for example, to quantify tissue alterations due to disease or healthy processes. Current challenges and limitations of state-of-the-art models are discussed, including validation efforts. Finally, novel diffusion encoding approaches (e.g., b-tensor or double diffusion encoding) may increase the biological specificity of diffusion metrics towards intra-voxel diffusion heterogeneity in clinical settings, holding promise in neurological applications

    Neurite imaging reveals microstructural variations in human cerebral cortical gray matter

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    We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture

    Clinical application of novel marker for cerebral small vessel disease

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    Impact of arterial stiffness on white matter microstructure in the elderly

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    La rigidité artérielle fait référence à la perte d'élasticité principalement dans les grandes artères telles que l'aorte et les carotides. On sait que la rigidité artérielle chroniquement élevée contribue à des modifications vasculaires cérébrales telles que des lésions parenchymateuses de la substance blanche cérébrale via une modification du flux sanguin cérébral. En particulier, parmi les structures perfusées par les artérioles fournies par les artères cérébrales antérieure et moyenne, le corps calleux, la capsule interne, la corona radiata et le faisceau longitudinal supérieur sont les plus vulnérables à l’hypoperfusion. Des études antérieures ont montré que l'augmentation de la rigidité artérielle évaluée par la vitesse de l'onde de pouls carotide-fémorale (cfPWV) est associée à une diminution de l'anisotropie fractionnelle (FA) et à une augmentation de la diffusivité radiale (RD). On a émis l'hypothèse que les altérations au niveau des régions vulnérables de la substance blanche (par exemple, le corps calleux, la capsule interne) seraient probablement liées à la démyélinisation axonale. Cependant, bien que la RD a auparavant été corrélée avec la démyélinisation axonale, l'imagerie de diffusion est principalement aveugle à la myéline. En revanche, l'imagerie par transfert de magnétisation (MT) est une métrique adaptée pour estimer la fraction volumique de myéline. De plus, malgré leur sensibilité à l'organisation des fibres axonales, les métriques de tenseur de diffusion (DTI) telles que les FA et RD manquent de spécificité pour la microstructure tissulaire individuelle. Des modèles microstructuraux plus avancés tels que l’imagerie dispersion et de l'orientation des neurites (NODDI) fournissent des outils pour disséquer les changements microstructuraux derrière les mesures DTI. Dans l'article 1, nous avons utilisé les métriques de DTI et basé sur le MT pour examiner de plus près l'interaction entre la rigidité artérielle et la microstructure de la substance blanche chez les personnes âgées de plus de 65 ans. Nous avons constaté que la mesure de référence absolue de la rigidité artérielle, la mesure de la vitesse de l'onde de pouls entre l’artère fémorale et carotidienne (cfPWV) était associée à l'organisation axonale des fibres telle que reflétée par FA et RD plutôt qu'à la démyélinisation dans les régions de la substance blanche qui ont été précédemment désignées comme vulnérables à rigidité artérielle. Dans notre deuxième article, nous avons utilisé le modèle NODDI pour approfondir la relation entre le cfPWV et l'organisation axonale. Nos résultats ont montré que la cfPWV est positivement associée à la diffusion extracellulaire de l'eau (ISOVF), ce qui signifie que la rigidité artérielle peut entraîner une dispersion axonale, diminuant la contrainte de directionnalité de l'eau le long des axones. En outre, nous avons constaté que la rigidité artérielle est associée à une augmentation de la densité des fibres dans le corps calleux tel que mesuré par l’ICVF, ce qui pourrait suggérer que les personnes à risque plus élevé de déclin cognitif présentent des mécanismes compensatoires précoces avant l'apparition de signes cliniques de déclin cognitif. Compte tenu de la forte interaction entre la rigidité artérielle et le déclin à la fois de la structure du cerveau et des fonctions cérébrales, on peut envisager un avenir meilleur où la rigidité artérielle sera mesurée dans la pratique clinique de routine afin d'identifier les personnes à risque plus élevé d’altérations de la substance blanche et de déclin cognitif. Ces personnes pourraient bénéficier de programmes multi-interventionnels visant à préserver la structure et la fonction cérébrale. Un seuil de rigidité artérielle est donc nécessaire pour identifier ces individus. L'article 3 présente la première estimation d'une valeur seuil de cfPWV à laquelle la rigidité artérielle affecte la microstructure de la substance blanche chez les personnes âgées. Nos résultats suggèrent que le seuil actuel de 10 m / s de cfPWV adopté par la Société européenne d'hypertension n'est peut-être pas le seuil optimal pour diviser les individus en groupes à risque neurovasculaire élevé et faible. Au lieu de cela, nos résultats suggèrent que le seuil de cfPWV est plus susceptible d’être autour de 8,5 m / s. Bien que le cfPWV offre une excellente valeur pronostique chez les adultes, il reste malheureusement principalement utilisé dans la recherche en raison du besoin d'experts formés pour cette mesure. À l'inverse, la mesure de l'indice de rigidité artérielle (ASI) à l'aide de la pléthysmographie suscite un intérêt croissant ces dernières années en raison de son approche simple à utiliser. Dans l'article 4, nous avons étudié la relation entre l'ASI et la pression pulsée (PP) qui est une mesure indirecte de la rigidité artérielle, avec la FA et les lésions de la substance blanche chez les participants du UK Biobank. Nous avons constaté que la PP prédit mieux l'intégrité de la substance blanche que l'ASI chez les participants de moins de 75 ans. Cette constatation implique que l'ASI de la pléthysmographie ne semble pas être une mesure fiable de la rigidité artérielle chez les personnes âgées. Des études futures sont évidemment nécessaires pour valider nos résultats, en particulier notre seuil de cfPWV. Une fois ce seuil validé, nous envisageons un avenir radieux où la mesure du cfPWV sera non seulement utilisée pour aider à sélectionner les personnes qui bénéficieraient le plus d'un programme multi-interventionnel visant à préserver l'intégrité cérébrale, mais pourrait également être utilisée pour surveiller l’effet d’une telle intervention.Arterial stiffness refers to the loss of elasticity mainly in large arteries such as the aorta and carotids. Chronically elevated arterial stiffness contributes to cerebrovascular changes such as cerebral white matter parenchymal damage via an alteration of cerebral blood flow. In particular, among the areas perfused by arterioles supplied by the anterior and middle cerebral arteries, the corpus callosum, the internal capsule, the corona radiata, and the superior longitudinal fasciculus are more vulnerable to cerebral hypoperfusion. Previous studies have shown that increased arterial stiffness as assessed by carotid-femoral pulse wave velocity (cfPWV) is associated with a decrease in fractional anisotropy (FA) and increase in radial diffusivity (RD). It was hypothesized that alterations in vulnerable white matter tracts (e.g. corpus callosum, internal capsule) are likely to be related to axonal demyelination. However, while RD was previously correlated with axonal demyelination, diffusion imaging is mostly blind to myelin. In contrast magnetization transfer (MT) imaging is a tailored metric to estimate myelin volume fraction. Moreover, despite their sensitivity to axon fiber organization, diffusion tensor metrics (DTI) such as FA and RD lack specificity for individual tissue microstructure. More advanced microstructural model such as neurite orientation dispersion and density imaging (NODDI) give tools to disecate the microstructural changes behind DTI metrics. In Article 1 we used DTI and MT based metric to look more closely at the interplay between arterial stiffness and white matter microstructure in older adults > 65 years old. We found that the gold standard measure of arterial stiffness, the measure of carotid femoral pulse wave velocity (cfPWV) was associated with axonal fiber organization as reflected by FA and RD rather than demyelination in the white matter regions that have been previously denoted as vulnerable to arterial stiffness. In our second Article, we used the NODDI model to take a further look at the relationship between cfPWV and axonal organization. Our results showed that cfPWV is positively associated with the extracellular water diffusion (ISOVF) which means that arterial stiffness may result in axonal dispersion, lessening the constraint of water directionality along axons. In addition, we found that arterial stiffness is associated with increased fibers density in the corpus callosum as measured by ICVF which could suggest that individuals at higher risk for cognitive decline demonstrate early compensatory mechanisms before the appearance of clinical signs of cognitive decline. Considering the strong interplay between arterial stiffness and decline both in brain structure and function, one can envision a bright future where arterial stiffness would be measured in routine clinical practice in order to identify individuals at higher risk for white matter changes and cognitive decline. Such individuals could benefit from multi-interventions programs aiming to preserve brain structure and function. A cut-off arterial stiffness is thus needed to identify these individuals. Article 3 presents the first estimation of an cfPWV cut-off value at which arterial stiffness impacts the white matter microstructure in older adults. Our results suggested that the current 10 m/s cfPWV cut-off adopted by the European Society of Hypertension may not be the optimal threshold to split individuals into high and low neurovascular risk groups. Instead, our findings suggest that the cfPWV cut-off is more likely to fall around 8.5 m/s. While cfPWV provides excellent prognostic value in adults, it remains unfortunately mainly used in research due to the need of trained experts. Conversely, measure of arterial stiffness index (ASI) using plethysmography is getting increased interest in the last few years due to its simple-to-use approach. In article 4, we investigated the relationship between ASI and pulse pressure (PP), an indirect measure of arterial stiffness, with FA and white matter lesions in participants of the UK Biobank. We found that PP better predicts white matter integrity compared to ASI in participants younger than 75 years old. This finding implies that ASI from plethysmography may not be a reliable measure of arterial stiffness in older adults. Future studies are obviously needed to validate our results, in particular our cfPWV cut-off. Once such cut-off will be validated, the present author envision a bright future where measure of cfPWV will not only be used to help selecting individuals that would most benefit from a multi intervention program aiming to preserve brain integrity, but could also be used to monitor the effect of such intervention

    White Matter Integrity and Processing Speed in Sickle Cell Anemia

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    Objective The purpose of this retrospective cross-sectional study was to investigate whether changes in white matter integrity are related to slower processing speed in sickle cell anemia. Methods Thirty-seven patients with silent cerebral infarction, 46 patients with normal MRI, and 32 sibling controls (age range 8–37 years) underwent cognitive assessment using the Wechsler scales and 3-tesla MRI. Tract-based spatial statistics analyses of diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters were performed. Results Processing speed index (PSI) was lower in patients than controls by 9.34 points (95% confi- dence interval: 4.635–14.855, p = 0.0003). Full Scale IQ was lower by 4.14 scaled points (95% confidence interval: −1.066 to 9.551, p = 0.1), but this difference was abolished when PSI was included as a covariate (p = 0.18). There were no differences in cognition between patients with and without silent cerebral infarction, and both groups had lower PSI than controls (both p < 0.001). In patients, arterial oxygen content, socioeconomic status, age, and male sex were identified as predictors of PSI, and correlations were found between PSI and DTI scalars (fractional anisotropy r = 0.614, p < 0.00001; r = −0.457, p < 0.00001; mean diffusivity r = −0.341, p = 0.0016; radial diffusivity r = −0.457, p < 0.00001) and NODDI parameters (intracellular volume fraction r = 0.364, p = 0.0007) in widespread regions. Conclusion Our results extend previous reports of impairment that is independent of presence of infarction and may worsen with age. We identify processing speed as a vulnerable domain, with deficits potentially mediating difficulties across other domains, and provide evidence that reduced processing speed is related to the integrity of normal-appearing white matter using microstructure parameters from DTI and NODDI

    Probing brain microstructure with multidimensional diffusion MRI: Encoding, interpretation, and the role of exchange

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    Diffusion MRI (dMRI) is a non-invasive probe of human brain microstructure. It is a long-standing promise to use dMRI for ‘in vivo histology’ and estimate tissue quantities. However, this faces several challenges. First, the microstructure models used for dMRI data are based on assumptions that may cause erroneous interpretations. Also, probing neurites in gray matter assumes high microscopic diffusion anisotropy in both axons and dendrites, which is not supported by evidence. Furthermore, dMRI data analysis typically ignores diffusional exchange between microscopic environments. This thesis investigates and addresses these challenges using ‘multidimensional’ dMRI techniques that vary additional sequence encoding parameters to obtain new information on the tissue. In Paper I, we optimized an acquisition protocol for filter exchange imaging (FEXI). We found slow rates of diffusional exchange in normal brain tissue. In patients with gliomas and meningiomas, faster exchange was tentatively associated with higher tumor grade. In Paper II, we used tensor-valued diffusion encoding to test the NODDI microstructure model. The NODDI assumptions were contradicted by independent data and parameter estimates were found to be biased in normal brain and in gliomas. The CODIVIDE model combined data acquired with different b-tensor shapes to remove NODDI assumptions and reduce the susceptibility to bias. In Paper III, we used tensor-valued diffusion encoding with multiple echo times to investigate challenges in estimating neurite density. We found that microscopic anisotropy in the brain reflected axons but not dendrites. We could not separate the densities and T2 values of a two-component model in normal brain, but we did detect different component T2 values in white matter lesions. Microstructure models ranked regions from normal brain and white matter lesions inconsistently with respect to neurite density. In Paper IV, we optimized an acquisition protocol for tensor-valued diffusion encoding with multiple echo times. The data allowed removing all assumptions on diffusion and T2 relaxation from a two-component model. This increased the measurable parameters from two to six and reduced their susceptibility to bias. Data from the normal brain showed different component T2 values and contradicted common model assumptions. In Paper V, we used tensor-valued diffusion encoding in malformations of cortical development. Lesions that appeared gray matter-like in T1- and T2-weighted contrasts featured white matter-like regions with high microscopic diffusion anisotropy. We interpreted these regions as myelin-poor white matter with a high axonal content. By primarily reflecting axons and not dendrites or myelin, microscopic anisotropy may differentiate tissue where alterations to myelin confound conventional MRI contrasts. In Paper VI, we used SDE with multiple diffusion times in patients with acute ischemic stroke. Subacute lesions exhibited elevated diffusional exchange that predicted later infarction. MD reduction was partially reversible and did not predict infarction. Diffusional exchange may improve definition of ischemic core and identify additional patients for late revascularization
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