987 resultados para Diffusion-weighted imaging
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Enriched by a decade of remarkable developments, matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) has witnessed a phenomenal expansion. Initially introduced for the mapping of peptides and intact proteins from mammalian tissue sections, MALDI IMS applications now extend to a wide range of molecules including peptides, lipids, metabolites and xenobiotics. Technology and methodology are quickly evolving to push the limits of the technique forward. Within a short period of time, numerous protocols and concepts have been developed and introduced in tissue section preparation, nonexhaustively including in situ tissue chemistries and solvent-free matrix depositions. Considering the past progress and current capabilities, this Review aims to cover the different aspects and challenges of tissue section preparation for MALDI IMS.
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Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.
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Methods like Event History Analysis can show the existence of diffusion and part of its nature, but do not study the process itself. Nowadays, thanks to the increasing performance of computers, processes can be studied using computational modeling. This thesis presents an agent-based model of policy diffusion mainly inspired from the model developed by Braun and Gilardi (2006). I first start by developing a theoretical framework of policy diffusion that presents the main internal drivers of policy diffusion - such as the preference for the policy, the effectiveness of the policy, the institutional constraints, and the ideology - and its main mechanisms, namely learning, competition, emulation, and coercion. Therefore diffusion, expressed by these interdependencies, is a complex process that needs to be studied with computational agent-based modeling. In a second step, computational agent-based modeling is defined along with its most significant concepts: complexity and emergence. Using computational agent-based modeling implies the development of an algorithm and its programming. When this latter has been developed, we let the different agents interact. Consequently, a phenomenon of diffusion, derived from learning, emerges, meaning that the choice made by an agent is conditional to that made by its neighbors. As a result, learning follows an inverted S-curve, which leads to partial convergence - global divergence and local convergence - that triggers the emergence of political clusters; i.e. the creation of regions with the same policy. Furthermore, the average effectiveness in this computational world tends to follow a J-shaped curve, meaning that not only time is needed for a policy to deploy its effects, but that it also takes time for a country to find the best-suited policy. To conclude, diffusion is an emergent phenomenon from complex interactions and its outcomes as ensued from my model are in line with the theoretical expectations and the empirical evidence.Les méthodes d'analyse de biographie (event history analysis) permettent de mettre en évidence l'existence de phénomènes de diffusion et de les décrire, mais ne permettent pas d'en étudier le processus. Les simulations informatiques, grâce aux performances croissantes des ordinateurs, rendent possible l'étude des processus en tant que tels. Cette thèse, basée sur le modèle théorique développé par Braun et Gilardi (2006), présente une simulation centrée sur les agents des phénomènes de diffusion des politiques. Le point de départ de ce travail met en lumière, au niveau théorique, les principaux facteurs de changement internes à un pays : la préférence pour une politique donnée, l'efficacité de cette dernière, les contraintes institutionnelles, l'idéologie, et les principaux mécanismes de diffusion que sont l'apprentissage, la compétition, l'émulation et la coercition. La diffusion, définie par l'interdépendance des différents acteurs, est un système complexe dont l'étude est rendue possible par les simulations centrées sur les agents. Au niveau méthodologique, nous présenterons également les principaux concepts sous-jacents aux simulations, notamment la complexité et l'émergence. De plus, l'utilisation de simulations informatiques implique le développement d'un algorithme et sa programmation. Cette dernière réalisée, les agents peuvent interagir, avec comme résultat l'émergence d'un phénomène de diffusion, dérivé de l'apprentissage, où le choix d'un agent dépend en grande partie de ceux faits par ses voisins. De plus, ce phénomène suit une courbe en S caractéristique, poussant à la création de régions politiquement identiques, mais divergentes au niveau globale. Enfin, l'efficacité moyenne, dans ce monde simulé, suit une courbe en J, ce qui signifie qu'il faut du temps, non seulement pour que la politique montre ses effets, mais également pour qu'un pays introduise la politique la plus efficace. En conclusion, la diffusion est un phénomène émergent résultant d'interactions complexes dont les résultats du processus tel que développé dans ce modèle correspondent tant aux attentes théoriques qu'aux résultats pratiques.
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Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.
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The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.
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BACKGROUND: Acute treatment of ischemic stroke patients presenting more than eight-hours after symptom onset remains limited and largely unproven. Partial aortic occlusion using the NeuroFlo catheter can augment cerebral perfusion in animals. We investigated the safety and feasibility of employing this novel catheter to treat ischemic stroke patients eight-hours to 24 h following symptom onset. METHODS: A multicenter, single-arm trial enrolled ischemic stroke patients at nine international academic medical centers. Eligibility included age 18-85 years old, National Institutes of Health stroke scale (NIHSS) score between four and 20, within eight-hours to 24 h after symptom onset, and perfusion-diffusion mismatch confirmed by magnetic resonance imaging. The primary outcome was all adverse events occurring from baseline to 30 days posttreatment. Secondary outcomes included stroke severity on neurological indices through 90 days. This study is registered with ClinicalTrials.gov, number NCT00436592. RESULTS: A total of 26 patients were enrolled. Of these, 25 received treatment (one excluded due to aortic morphology); five (20%) died. Favorable neurological outcome at 90 days (modified Rankin score 0-2 vs. 3-6) was associated with lower baseline NIHSS (P < 0·001) and with longer duration from symptom discovery to treatment. There were no symptomatic intracranial hemorrhages or parenchymal hematomas. Asymptomatic intracranial hemorrhage was visible on computed tomography in 32% and only on microbleed in another 20%. CONCLUSIONS: Partial aortic occlusion using the NeuroFlo catheter, a novel collateral therapeutic strategy, appears safe and feasible in stroke patients eight-hours to 24 h after symptom onset.
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A simple and time efficient technique to illustrate specimens is described and demonstrated with Paleogene radiolarians. This method produces Scanning Electron Microscope (SEM) and composite focal depth Transmitted Light Microscope (TLM) images for single radiolarian specimens. We propose the use of this technique to clarify radiolarian taxonomy. This technique has distinct advantages over previously published time consuming techniques that can also require toxic materials.
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Messages à retenir: Connaître le principe physique de l'imagerie de diffusion (DWI) à l'IRM adaptée à l'exploration des tumeurs du foie.Savoir la bonne technique d'acquisition des séquences pour évaluer la diffusion du parenchyme hépatique ainsi que des lésions focales intra -hépatiques les plusfréquentes.Apprendre l'utilité de la DWI pour évaluer le succès d'un traitement médical oncologique ou interventionnel .Discuter les avantages et les pièges liés à la DWI hépatique susceptibles d'influencer l'interprétation des tumeurs hépatiques. Résumé: Le principe d'imagerie de diffusion (DWI) à l'IRM repose sur la mobilité des molécules d'eau dans les différents tissus. Ce «mouvement Brownien» dépend de lacellularité tissulaire , des membranes cellulaires intactes et de la vascularisation . L'augmentation de ces paramètres précités résulte en une restriction de ladiffusion moléculaire, caractérisée par un hypersignal, puis quantifié par le calcul d'un coefficient apparent de diffusion (ADC). Basée sur des séquenceséchoplanaires pondérées en T2, la technique d'acquisition est rapide et non-invasive, donc souvent intégrée à l'IRM hépatique de routine. La DWI s'est révéléetrès sensible pour la détection de tumeurs hépatiques, même à un diamètre infracentimétrique. Néanmoins, sans être très spécifique, elle ne donne pas d'information certaine sur le caractère bénin ou malin, et elle doit être interprétée avec les autres séquences d'IRM et dans le contexte clinique donné. L'informationdiagnostique résultant de la DWI est morphologique et fonctionnelle, ce qui permet d'évaluer le succès de traitements oncologiques, notamment en absence dechangement de taille ou persistance de prise de contraste des lésions hépatiques. Très sensibles aux mouvements respiratoires, la DWI hépatique peut êtreaccompagnée d'artéfacts, qui influencent le calcul de l'ADC dont la valeur dépend de la machine IRM utilisée.
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Determining groundwater flow paths of infiltrated river water is necessary for studying biochemical processes in the riparian zone, but their characterization is complicated by strong temporal and spatial heterogeneity. We investigated to what extent repeat 3D surface electrical resistance tomography (ERT) can be used to monitor transport of a salt-tracer plume under close to natural gradient conditions. The aim is to estimate groundwater flow velocities and pathways at a site located within a riparian groundwater system adjacent to the perialpine Thur River in northeastern Switzerland. Our ERT time-lapse images provide constraints on the plume's shape, flow direction, and velocity. These images allow the movement of the plume to be followed for 35 m. Although the hydraulic gradient is only 1.43 parts per thousand, the ERT time-lapse images demonstrate that the plume's center of mass and its front propagate with velocities of 2x10(-4) m/s and 5x10(-4) m/s, respectively. These velocities are compatible with groundwater resistivity monitoring data in two observation wells 5 m from the injection well. Five additional sensors in the 5-30 m distance range did not detect the plume. Comparison of the ERT time-lapse images with a groundwater transport model and time-lapse inversions of synthetic ERT data indicate that the movement of the plume can be described for the first 6 h after injection by a uniform transport model. Subsurface heterogeneity causes a change of the plume's direction and velocity at later times. Our results demonstrate the effectiveness of using time-lapse 3D surface ERT to monitor flow pathways in a challenging perialpine environment over larger scales than is practically possible with crosshole 3D ERT.
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The primary goal of this study was to design a fluorescent E-selectin-targeted iodine-containing liposome for specific E-selectin imaging with the use of micro-CT. The secondary goal was to correlate the results of micro-CT imaging with other imaging techniques with cellular resolution, i.e., confocal and intravital microscopy. E-selectin-targeted liposomes were tested on endothelial cells in culture and in vivo in HT-29 tumor-bearing mice (n = 12). The liposomes contained iodine (as micro-CT contrast medium) and fluorophore (as optical contrast medium) for confocal and intravital microscopy. Optical imaging methods were used to confirm at the cellular level, the observations made with micro-CT. An ischemia-reperfusion model was used to trigger neovessel formation for intravital imaging. The E-selectin-targeted liposomes were avidly taken up by activated endothelial cells, whereas nontargeted liposomes were not. Direct binding of the E-selectin-targeted liposomes was proved by intravital microscopy, where bright spots clearly appeared on the activated vessels. Micro-CT imaging also demonstrated accumulation of the targeted lipsomes into subcutaneous tumor by an increase of 32 +/- 8 HU. Hence, internalization by activated endothelial cells was rapid and mediated by E-selectin. We conclude that micro-CT associated with specific molecular contrast agent is able to detect specific molecular markers on activated vessel walls in vivo.
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Introduction : DTI has proven to be an exquisite biomarker of tissue microstructure integrity. This technique has been successfully applied to schizophrenia in showing that fractional anisotropy (FA, a marker of white matter integrity) is diminished in several areas of the brain (Kyriakopoulos M et al (2008)). New ways of representing diffusion data emerged recently and achieved to create structural connectivity maps in healthy brains (Hagmann P et al. (2008)). These maps have the capacity to study alterations over the entire brain at the connection and network level. This is of high interest in complex disconnection diseases like schizophrenia. We report on the specific network alterations of schizophrenic patients. Methods : 13 patients with chronic schizophrenia were recruited from in-patient, day treatment, out-patient clinics. Comparison subjects were recruited and group-matched to patients on age, sex, handedness, and parental social economic-status. This study was approved by the local IRB and subjects had to give informed written consent. They were scanned with a 3T clinical MRI scanner. DTI and high-resolution anatomical T1w imaging were performed during the same session. The path from diffusion MRI to a multi-resolution structural connection matrices of the entire brain is a five steps process that was performed in a similar way as described in Hagmann P et al. (2008). (1) DTI and T1w MRI of the brain, (2) segmentation of white and gray matter, (3) white matter tractography, (4) segmentation of the cortex into 242 ROIs of equal surface area covering the entire cortex (Fig 1), (5) the connection network was constructed by measuring for each ROI to ROI connection the related average FA along the corresponding tract. Results : For every connection between 2 ROIs of the network we tested the hypothesis H0: "average FA along fiber pathway is larger or equal in patients than in controls". H0 was rejected for connections where average FA in a connection was significantly lower in patients than in controls. Threshold p-value was 0.01 corrected for multiple comparisons with false discovery rate. We identified consistently that temporal, occipito-temporal, precuneo-temporal as well as frontal inferior and precuneo-cingulate connections were altered (Fig 2: significant connections in yellow). This is in agreement with the known literature, which showed across several studies that FA is diminished in several areas of the brain. More precisely, abnormalities were reported in the prefrontal and temporal white matter and to some extent also in the parietal and occipital regions. The alterations reported in the literature specifically included the corpus callosum, the arcuate fasciculus and the cingulum bundle, which was the case here as well. In addition small world indexes are significantly reduced in patients (p<0.01) (Fig. 3). Conclusions : Using connectome mapping to characterize differences in structural connectivity between healthy and diseased subjects we were able to show widespread connectional alterations in schizophrenia patients and systematic small worldness decrease, which is a marker of network desorganization. More generally, we described a method that has the capacity to sensitively identify structure alterations in complex disconnection syndromes where lesions are widespread throughout the connectional network.
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Electromagnetic fields arising from magnetic resonance imaging (MRI) can cause various clinically relevant functional disturbances in patients with cardiac pacemakers. Consequently, an implanted pacemaker is generally considered a contraindication for an MRI scan. With approximately 60 million MRI scans performed worldwide per year, MRI may be indicated for an estimated majority of pacemaker patients during the lifetime of their pacemakers. The availability of MR conditional pacemakers with CE labelling is of particular advantage since they allow the safe use of pacemakers in MRI. In this article the current state of knowledge on pacemakers and MR imaging is discussed. We present the results of a survey conducted among Swiss radiologists to assess current practice in patients with pacemakers.