Segmentation of Fetal Pericerebral Spaces Based on Reconstructed High-Resolution MRI

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Correlation of Diffusion and Metabolic Alterations in Different Clinical Forms of Multiple Sclerosis

Diffusion tensor imaging (DTI) and MR spectroscopic imaging (MRSI) provide greater sensitivity than conventional MRI to detect diffuse alterations in normal appearing white matter (NAWM) of Multiple Sclerosis (MS) patients with different clinical forms. Therefore, the goal of this study is to combine DTI and MRSI measurements to analyze the relation between diffusion and metabolic markers, T2-weighted lesion load (T2-LL) and the patients clinical status. The sensitivity and specificity of both methods were then compared in terms of MS clinical forms differentiation. MR examination was performed on 71 MS patients (27 relapsing remitting (RR), 26 secondary progressive (SP) and 18 primary progressive (PP)) and 24 control subjects. DTI and MRSI measurements were obtained from two identical regions of interest selected in left and right centrum semioval (CSO) WM. DTI metrics and metabolic contents were significantly altered in MS patients with the exception of N-acetyl-aspartate (NAA) and NAA/Choline (Cho) ratio in RR patients. Significant correlations were observed between diffusion and metabolic measures to various degrees in every MS patients group. Most DTI metrics were significantly correlated with the T2-LL while only NAA/Cr ratio was correlated in RR patients. A comparison analysis of MR methods efficiency demonstrated a better sensitivity/specificity of DTI over MRSI. Nevertheless, NAA/Cr ratio could distinguish all MS and SP patients groups from controls, while NAA/Cho ratio differentiated PP patients from controls. This study demonstrated that diffusivity changes related to microstructural alterations were correlated with metabolic changes and provided a better sensitivity to detect early changes, particularly in RR patients who are more subject to inflammatory processes. In contrast, the better specificity of metabolic ratios to detect axonal damage and demyelination may provide a better index for identification of PP patients

Microstructural Changes in the Striatum and Their Impact on Motor and Neuropsychological Performance in Patients with Multiple Sclerosis

Grey matter (GM) damage is a clinically relevant feature of multiple sclerosis (MS) that has been previously assessed with diffusion tensor imaging (DTI). Fractional anisotropy (FA) of the basal ganglia and thalamus might be increased in MS patients, and correlates with disability scores. Despite the established role of the striatum and thalamus in motor control, mood and cognition, the impact of DTI changes within these structures on motor and neuropsychological performance has not yet been specifically addressed in MS. We investigated DTI metrics of deep GM nuclei and their potential association with mobility and neuropsychological function. DTI metrics from 3T MRI were assessed in the caudate, putamen, and thalamus of 30 MS patients and 10 controls. Sixteen of the patients underwent neuropsychological testing. FA of the caudate and putamen was higher in MS patients compared to controls. Caudate FA correlated with Expanded Disability Status Scale score, Ambulation Index, and severity of depressive symptomatology. Putamen and thalamus FA correlated with deficits in memory tests. In contrast, cerebral white matter (WM) lesion burden showed no significant correlation with any of the disability, mobility and psychometric parameters. Our findings support evidence of FA changes in the basal ganglia in MS patients, as well as deep GM involvement in disabling features of MS, including mobility and cognitive impairment. Deep GM FA appears to be a more sensitive correlate of disability than WM lesion burden

Detection and longitudinal follow-up of white and gray matter abnormalities in multiple sclerosis by regional and statistical approaches of diffusion tensor imaging

Si l’imagerie par résonance magnétique (IRM) montre la charge lésionnelle qui reflète le caractère inflammatoire de la sclérose en plaques (SEP), il n’existe pas de marqueur permettant de prédire son évolution ou de caractériser les phénomènes de neurodégénérescence. Par conséquent, cette étude a pour objectif premièrement d’identifier des marqueurs de l’intégrité tissulaire par IRM de tenseur de diffusion (DTI), permettant de détecter les dommages tissulaires de type inflammatoire et/ou dégénératif, et deuxièmement de caractériser leur évolution par une analyse longitudinale, chez des patients de différentes formes cliniques. A cette fin, nous avons proposé une première approche régionale des substances blanche (SB) et grise (SG) sous-corticale et une deuxième approche statistique globale analysant par TBSS les variations d’anisotropie de la SB et par VBM la densité de la SG. Les résultats obtenus dans la SB montrent des variations de la fraction d’anisotropie (FA), et des diffusivités radiales et axiales reflétant respectivement une atteinte myélinique et une atteinte axonale alors que la SG présente une augmentation de la FA suggérant une atteinte dendritique neuronale. L’analyse par TBSS et VBM montre des anomalies touchant plutôt les régions sous-corticales chez les patients rémittents qui s’étendent aux régions corticales chez les patients de forme progressive. Longitudinalement, on retrouve essentiellement des changements de FA dans la SB et d’atrophie de la SG chez les patients rémittents. Ces travaux montrent que la DTI constitue une méthode sensible pour une meilleure détection et compréhension des altérations cérébrales et de leur évolution dans la SEP.If magnetic resonance imaging (MRI) shows the inflammatory nature of multiple sclerosis (MS) lesions, there is no marker capable of predicting its evolution or characterizing neurodegeneration. Therefore, the aim of this work was first, to identify markers of tissue integrity by diffusion tensor MRI (DTI) for the detection of inflammatory and/or degenerative tissue damages, and second, to characterize their changes with time using a longitudinal analysis of patients with different clinical forms. To this end, we first proposed a regional approach based on several white (WM) and gray (GM) matter regions of interest, and second, a statistical approach for the analysis of global WM anisotropy changes (TBSS) and GM density changes (VBM). WM analysis showed variations of the fractional anisotropy (FA), and radial and axial diffusivities, reflecting myelin and axonal damage respectively, while the GM analysis showed increased FA suggesting neuronal dendritic loss. TBSS and VBM analysis showed abnormalities affecting mostly subcortical regions in patients with relapsing-remitting (RR) MS which extended to cortical regions in patients with progressive MS. Longitudinally, we mainly observed WM FA changes and GM atrophy in RR patients. This work showed that DTI is a sensitive method for the detection and a better understanding of brain alterations and their progression in M

Détection et suivi longitudinal des anomalies de la substance blanche et de la substance grise dans la sclérose en plaques par des approches régionales et statistiques d’IRM de tenseur de diffusion

If magnetic resonance imaging (MRI) shows the inflammatory nature of multiple sclerosis (MS) lesions, there is no marker capable of predicting its evolution or characterizing neurodegeneration. Therefore, the aim of this work was first, to identify markers of tissue integrity by diffusion tensor MRI (DTI) for the detection of inflammatory and/or degenerative tissue damages, and second, to characterize their changes with time using a longitudinal analysis of patients with different clinical forms. To this end, we first proposed a regional approach based on several white (WM) and gray (GM) matter regions of interest, and second, a statistical approach for the analysis of global WM anisotropy changes (TBSS) and GM density changes (VBM). WM analysis showed variations of the fractional anisotropy (FA), and radial and axial diffusivities, reflecting myelin and axonal damage respectively, while the GM analysis showed increased FA suggesting neuronal dendritic loss. TBSS and VBM analysis showed abnormalities affecting mostly subcortical regions in patients with relapsing-remitting (RR) MS which extended to cortical regions in patients with progressive MS. Longitudinally, we mainly observed WM FA changes and GM atrophy in RR patients. This work showed that DTI is a sensitive method for the detection and a better understanding of brain alterations and their progression in MSSi l’imagerie par résonance magnétique (IRM) montre la charge lésionnelle qui reflète le caractère inflammatoire de la sclérose en plaques (SEP), il n’existe pas de marqueur permettant de prédire son évolution ou de caractériser les phénomènes de neurodégénérescence. Par conséquent, cette étude a pour objectif premièrement d’identifier des marqueurs de l’intégrité tissulaire par IRM de tenseur de diffusion (DTI), permettant de détecter les dommages tissulaires de type inflammatoire et/ou dégénératif, et deuxièmement de caractériser leur évolution par une analyse longitudinale, chez des patients de différentes formes cliniques. A cette fin, nous avons proposé une première approche régionale des substances blanche (SB) et grise (SG) sous-corticale et une deuxième approche statistique globale analysant par TBSS les variations d’anisotropie de la SB et par VBM la densité de la SG. Les résultats obtenus dans la SB montrent des variations de la fraction d’anisotropie (FA), et des diffusivités radiales et axiales reflétant respectivement une atteinte myélinique et une atteinte axonale alors que la SG présente une augmentation de la FA suggérant une atteinte dendritique neuronale. L’analyse par TBSS et VBM montre des anomalies touchant plutôt les régions sous-corticales chez les patients rémittents qui s’étendent aux régions corticales chez les patients de forme progressive. Longitudinalement, on retrouve essentiellement des changements de FA dans la SB et d’atrophie de la SG chez les patients rémittents. Ces travaux montrent que la DTI constitue une méthode sensible pour une meilleure détection et compréhension des altérations cérébrales et de leur évolution dans la SEP

Graph Theory-Based Brain Connectivity for Automatic Classification of Multiple Sclerosis Clinical Courses

Purpose: In this work, we introduce a method to classify Multiple Sclerosis (MS) patients into four clinical profiles using structural connectivity information. For the first time, we try to solve this question in a fully automated way using a computer-based method. The main goal is to show how the combination of graph-derived metrics with machine learning techniques constitutes a powerful tool for a better characterization and classification of MS clinical profiles.Materials and methods: Sixty-four MS patients (12 Clinical Isolated Syndrome (CIS), 24 Relapsing Remitting (RR), 24 Secondary Progressive (SP), and 17 Primary Progressive (PP)) along with 26 healthy controls (HC) underwent MR examination. T1 and diffusion tensor imaging (DTI) were used to obtain structural connectivity matrices for each subject. Global graph metrics, such as density and modularity, were estimated and compared between subjects’ groups. These metrics were further used to classify patients using tuned Support Vector Machine (SVM) combined with Radial Basic Function (RBF) kernel.Results: When comparing MS patients to HC subjects, a greater assortativity, transitivity and characteristic path length as well as a lower global efficiency were found. Using all graph metrics, the best F-Measures (91.8%, 91.8%, 75.6% and 70.6%) were obtained for binary (HC-CIS, CIS-RR, RR-PP) and multi-class (CIS-RR-SP) classification tasks, respectively. When using only one graph metric, the best F-Measures (83.6%, 88.9% and 70.7%) were achieved for modularity with previous binary classification tasks.Conclusion: Based on a simple DTI acquisition associated with structural brain connectivity analysis, this automatic method allowed an accurate classification of different MS patients’ clinical profiles

Tracking successive Wallerian degenerations in a relapsing-remitting multiple sclerosis patient

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A new MRI marker of ataxia with oculomotor apraxia

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Analyse de la connectivité structurelle cérébrale par la théorie des graphes : une nouvelle caractérisation physio-pathologique des formes cliniques de sclérose en plaques

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Brain Structural Connectivity in Different Clinical Forms of Multiple Sclerosis

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