Transcranial color-coded sonography in the management of patients with cervical and intracranial arterial stenosis

peer reviewedLe progrès technique en imagerie a permis le développement de l’écho-Doppler transcrânien en mode duplex ou triplex. A côté des autres techniques de neuro-imagerie, son intérêt dans la pathologie vasculaire cérébrale va grandissant. Le présent article a pour but de présenter cette technique en détaillant ses indications actuelles chez les patients présentant des sténoses artérielles cervicales et intra-crâniennes

Dynamic functional network connectivity using distance correlation

Investigations about the intrinsic brain organization in resting-state are critical for the understanding of healthy, pathological and pharmacological cerebral states. Recent studies on fMRI suggest that resting state activity is organized on large scale networks of coordinated activity, in the so called, Resting State Networks (RSNs). The assessment of the interactions among these functional networks plays an important role for the understanding of different brain pathologies. Current methods to quantify these interactions commonly assume that the underlying coordination mechanisms are stationary and linear through the whole recording of the resting state phenomena. Nevertheless, recent evidence suggests that rather than stationary, these mechanisms may exhibit a rich set of time-varying repertoires. In addition, these approaches do not consider possible non-linear relationships maybe linked to feed-back communication mechanisms between RSNs. In this work, we introduce a novel approach for dynamical functional network connectivity for functional magnetic resonance imaging (fMRI) resting activity, which accounts for non-linear dynamic relationships between RSNs. The proposed method is based on a windowed distance correlations computed on resting state time-courses extracted at single subject level. We showed that this strategy is complementary to the current approaches for dynamic functional connectivity and will help to enhance the discrimination capacity of patients with disorder of consciousness

Functional imaging and radiotherapy

peer reviewedLes progrès technologiques réalisés par l’image- rie médicale l’ont placée au centre de la prise en charge des patients oncologiques, tant au niveau du diagnostic, du pro - nostic et du suivi que dans la prise en charge thérapeutique. En effet, l’imagerie représente, à l’heure actuelle, la pierre angulaire des traitements de radiothérapie. Les objectifs du radiothérapeute sont d’irradier le plus précisément possible la tumeur à dose curative, tout en évitant les organes sains. Pour y arriver, le radiothérapeute utilise de façon routinière l’imagerie anatomique (Scanner et IRM). Depuis quelques années, le développement des différentes imageries métabo - liques et fonctionnelles, comme l’imagerie par émission de positons (PET-CT) et la résonnance magnétique fonctionnelle, ouvrent de nouvelles possibilités thérapeutiques grâce aux informations qu’elles apportent sur la biologie des tumeurs. Cet article décrit, de manière non exhaustive, les différentes imageries anatomiques et métaboliques à la disposition du radiothérapeute

Neuroimaging after coma.

Following coma, some patients will recover wakefulness without signs of consciousness (only showing reflex movements, i.e., the vegetative state) or may show non-reflex movements but remain without functional communication (i.e., the minimally conscious state). Currently, there remains a high rate of misdiagnosis of the vegetative state (Schnakers et. al. BMC Neurol, 9:35, 8) and the clinical and electrophysiological markers of outcome from the vegetative and minimally conscious states remain unsatisfactory. This should incite clinicians to use multimodal assessment to detect objective signs of consciousness and validate para-clinical prognostic markers in these challenging patients. This review will focus on advanced magnetic resonance imaging (MRI) techniques such as magnetic resonance spectroscopy, diffusion tensor imaging, and functional MRI (fMRI studies in both "activation" and "resting state" conditions) that were recently introduced in the assessment of patients with chronic disorders of consciousness

Reduction of resting state network segregation is linked to disorders of consciousness

Recent evidence suggests that healthy brain is organized on large-scale in regions spatially distant and partially temporally synchronized. These regions commonly are called Resting State Networks (RSNs). Many RSNs has been identified in multiples spatial scales in healthy subjects and their interactions has been used to define the functional network connectivity (FNC). The main idea in FNC is that the dynamic shown in the interactions among RSNs in control subjects, can change in pathological and pharmacological conditions. However, this hypothesis assumes that functional structure of healthy brain, remains in other brain states or conditions. In this work, we proposed a novel methodology in order to find the new brain functional structure for disorders of consciousness conditions, based on multi-objective optimization approach. Particularly, we find the best partition of RSNs set, that maximize two modularity measures (Kapur and Otsu measures). Our results suggest that the brain segregation level, may be linked to consciousness level

Multivariate functional network connectivity for disorders of consciousness

Recent evidence suggests that healthy brain is organized on large-scale spatially distant brain regions, which are temporally synchronized. These regions are known as resting state networks (RSNs). The level of interaction among these functional entities has been studied in the so called functional network connectivity (FNC). FNC aims to quantify the level of interaction between pairs of RSNs, which commonly emerge at similar spatial scale. Nevertheless, the human brain is a complex functional structure which is partitioned into functional regions that emerge at multiple spatial scales. In this work, we propose a novel multivariate FNC strategy to study interactions among communities of RSNs, these communities may emerge at different spatial scales. For this, first a community or hyperedge detection strategy was used to conform groups of RSNs with a similar behavior. Following, a distance correlation measurement was employed to quantify the level of interaction between these communities. The proposed strategy was evaluated in the characterization of patients with disorders of consciousness, a highly challenging problem in the clinical setting. The results suggest that the proposed strategy may improve the capacity of characterization of these brain altered conditions

Automatic identification of resting state networks: An extended version of multiple template-matching

Functional magnetic resonance imaging in resting state (fMRI-RS) constitutes an informative protocol to investigate several pathological and pharmacological conditions. A common approach to study this data source is through the analysis of changes in the so called resting state networks (RSNs). These networks correspond to well-defined functional entities that have been associated to different low and high brain order functions. RSNs may be characterized by using Independent Component Analysis (ICA). ICA provides a decomposition of the fMRI-RS signal into sources of brain activity, but it lacks of information about the nature of the signal, i.e., if the source is artifactual or not. Recently, a multiple template-matching (MTM) approach was proposed to automatically recognize RSNs in a set of Independent Components (ICs). This method provides valuable information to assess subjects at individual level. Nevertheless, it lacks of a mechanism to quantify how much certainty there is about the existence/absence of each network. This information may be important for the assessment of patients with severely damaged brains, in which RSNs may be greatly affected as a result of the pathological condition. In this work we propose a set of changes to the original MTM that improves the RSNs recognition task and also extends the functionality of the method. The key points of this improvement is a standardization strategy and a modification of method\u27s constraints that adds flexibility to the approach. Additionally, we also introduce an analysis to the trustworthiness measurement of each RSN obtained by using template-matching approach. This analysis consists of a thresholding strategy applied over the computed Goodness-of-Fit (GOF) between the set of templates and the ICs. The proposed method was validated on 2 two independent studies (Baltimore, 23 healthy subjects and Liege, 27 healthy subjects) with different configurations of MTM. Results suggest that the method will provide complementary information for characterization of RSNs at individual level

DTI based structural damage characterization for Disorders of Consciousness

peer reviewe

Natalizumab induces a rapid improvement of disability status and ambulation after failure of previous therapy in relapsing-remitting multiple sclerosis.

peer reviewedBackground: Natalizumab (Tysabri) is a monoclonal antibody that was recently approved for the treatment of relapsing-remitting multiple sclerosis (RRMS). Our primary objective was to analyse the efficacy of natalizumab on disability status and ambulation after switching patients with RRMS from other disease-modifying treatments (DMTs). Methods: A retrospective, observational study was carried out. All patients (n = 45) initiated natalizumab after experiencing at least 1 relapse in the previous year under interferon-beta (IFNB) or glatiramer acetate (GA) treatments. The patients also had at least 1 gadolinium-enhancing (Gd+) lesion on their baseline brain MRI. Expanded Disability Status Scale (EDSS) scores, and performance on the Timed 25-Foot Walk Test and on the Timed 100-Metre Walk Test were prospectively collected every 4 weeks during 44 weeks of natalizumab treatment. Brain MRI scans were performed after 20 and 44 weeks of treatment. Results: Sixty-two per cent of patients showed no clinical and no radiological signs of disease activity, and 29% showed a rapid and confirmed EDSS improvement over 44 weeks of natalizumab therapy. Patients with improvement on the EDSS showed similar levels of baseline EDSS and active T1 lesions, but had a significantly higher number of relapses, and 92% of them had experienced relapse-mediated sustained EDSS worsening in the previous year. A clinically meaningful improvement in ambulation speed was observed in approximately 30% of patients. Conclusions: These results indicate that natalizumab silences disease activity and rapidly improves disability status and walking performance, possibly through delayed relapse recovery in patients with RRMS who had shown a high level of disease activity under other DMTs

Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

INTRODUCTION: The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure \u27resting state\u27 cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. OBJECTIVE: We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. METHODS: We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. RESULTS: The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. CONCLUSIONS: The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map