Arnaud Le Troter

Tract-specific and age-related variations of the spinal cord microstructure: a multi-parametric MRI study using diffusion tensor imaging (DTI) and inhomogeneous magnetization transfer (ihMT).

Being able to finely characterize the spinal cord (SC) microstructure and its alterations is a key point when investigating neural damage mechanisms encountered in different central nervous system (CNS) pathologies, such as multiple sclerosis, amyotrophic lateral sclerosis or myelopathy.

Muscle Quantitative MR Imaging and Clustering Analysis in Patients with Facioscapulohumeral Muscular Dystrophy Type 1

Background Facioscapulohumeral muscular dystrophy type 1 (FSHD1) is the third most common inherited muscular dystrophy. Considering the highly variable clinical expression and the slow disease progression, sensitive outcome measures would be of interest. Methods and Findings Using muscle MRI, we assessed muscular fatty infiltration in the lower limbs of 35 FSHD1 patients and 22 healthy volunteers by two methods: a quantitative imaging (qMRI) combined with a dedicated automated segmentation method performed on both thighs and a standard T1-weighted four-point visual scale (visual score) on thighs and legs. Each patient had a clinical evaluation including manual muscular testing, Clinical Severity Score (CSS) scale and MFM scale. The intramuscular fat fraction measured using qMRI in the thighs was significantly higher in patients (21.9 ± 20.4%) than in volunteers (3.6 ± 2.8%) (p<0.001). In patients, the intramuscular fat fraction was significantly correlated with the muscular fatty infiltration in the thighs evaluated by the mean visual score (p<0.001). However, we observed a ceiling effect of the visual score for patients with a severe fatty infiltration clearly indicating the larger accuracy of the qMRI approach. Mean intramuscular fat fraction was significantly correlated with CSS scale (p≤0.01) and was inversely correlated with MMT score, MFM subscore D1 (p≤0.01) further illustrating the sensitivity of the qMRI approach. Overall, a clustering analysis disclosed three different imaging patterns of muscle involvement for the thighs and the legs which could be related to different stages of the disease and put forth muscles which could be of interest for a subtle investigation of the disease progression and/or the efficiency of any therapeutic strategy. Conclusion The qMRI provides a sensitive measurement of fat fraction which should also be of high interest to assess disease progression and any therapeutic strategy in FSHD1 patients.

Whole-brain quantitative mapping of metabolites using short echo three-dimensional proton MRSI.

To improve the extent over which whole brain quantitative three‐dimensional (3D) magnetic resonance spectroscopic imaging (MRSI) maps can be obtained and be used to explore brain metabolism in a population of healthy volunteers.

Single-trial EEG-informed fMRI reveals spatial dependency of BOLD signal on early and late IC-ERP amplitudes during face recognition.

Simultaneous EEG-fMRI has opened up new avenues for improving the spatio-temporal resolution of functional brain studies. However, this method usually suffers from poor EEG quality, especially for evoked potentials (ERPs), due to specific artifacts. As such, the use of EEG-informed fMRI analysis in the context of cognitive studies has particularly focused on optimizing narrow ERP time windows of interest, which ignores the rich diverse temporal information of the EEG signal. Here, we propose to use simultaneous EEG-fMRI to investigate the neural cascade occurring during face recognition in 14 healthy volunteers by using the successive ERP peaks recorded during the cognitive part of this process. N170, N400 and P600 peaks, commonly associated with face recognition, were successfully and reproducibly identified for each trial and each subject by using a group independent component analysis (ICA). For the first time we use this group ICA to extract several independent components (IC) corresponding to the sequence of activation and used single-trial peaks as modulation parameters in a general linear model (GLM) of fMRI data. We obtained an occipital-temporal-frontal stream of BOLD signal modulation, in accordance with the three successive IC-ERPs providing an unprecedented spatio-temporal characterization of the whole cognitive process as defined by BOLD signal modulation. By using this approach, the pattern of EEG-informed BOLD modulation provided improved characterization of the network involved than the fMRI-only analysis or the source reconstruction of the three ERPs; the latter techniques showing only two regions in common localized in the occipital lobe.

Nodal approach reveals differential impact of lateralized focal epilepsies on hub reorganization.

The impact of the hemisphere affected by impairment in models of network disease is not fully understood. Among such models, focal epilepsies are characterised by recurrent seizures generated in epileptogenic areas also responsible for wider network dysfunction between seizures. Previous work focusing on functional connectivity within circumscribed networks suggests a divergence of network integrity and compensatory capacity between epilepsies as a function of the laterality of seizure onset. We evaluated the ability of complex network theory to reveal changes in focal epilepsy in global and nodal parameters using graph theoretical analysis of functional connectivity data obtained with resting-state fMRI. Graphs of functional connectivity networks were derived from 19 right and 13 left focal epilepsy patients and 15 controls. Topological metrics (degree, local efficiency, global efficiency and modularity) were computed for a whole-brain, atlas-defined network. We also calculated a hub disruption index for each graph metric, measuring the capacity of the brain network to demonstrate increased connectivity in some nodes for decreased connectivity in others. Our data demonstrate that the patient group as a whole is characterised by network-wide pattern of reorganization, even while global parameters fail to distinguish between groups. Furthermore, multiple metrics indicate that epilepsies with differently lateralized epileptic networks are asymmetric in their burden on functional brain networks; with left epilepsy patients being characterised by reduced efficiency and modularity, while in right epilepsy patients we provide the first evidence that functional brain networks are characterised by enhanced connectivity and efficiency at some nodes whereas reduced in others.

Combined MRI and 31P-MRS Investigations of the ACTA1(H40Y) Mouse Model of Nemaline Myopathy Show Impaired Muscle Function and Altered Energy Metabolism

Nemaline myopathy (NM) is the most common disease entity among non-dystrophic skeletal muscle congenital diseases. Mutations in the skeletal muscle α-actin gene (ACTA1) account for ∼25% of all NM cases and are the most frequent cause of severe forms of NM. So far, the mechanisms underlying muscle weakness in NM patients remain unclear. Additionally, recent Magnetic Resonance Imaging (MRI) studies reported a progressive fatty infiltration of skeletal muscle with a specific muscle involvement in patients with ACTA1 mutations. We investigated strictly noninvasively the gastrocnemius muscle function of a mouse model carrying a mutation in the ACTA1 gene (H40Y). Skeletal muscle anatomy (hindlimb muscles and fat volumes) and energy metabolism were studied using MRI and 31Phosphorus magnetic resonance spectroscopy. Skeletal muscle contractile performance was investigated while applying a force-frequency protocol (from 1–150 Hz) and a fatigue protocol (80 stimuli at 40 Hz). H40Y mice showed a reduction of both absolute (−40%) and specific (−25%) maximal force production as compared to controls. Interestingly, muscle weakness was associated with an improved resistance to fatigue (+40%) and an increased energy cost. On the contrary, the force frequency relationship was not modified in H40Y mice and the extent of fatty infiltration was minor and not different from the WT group. We concluded that the H40Y mouse model does not reproduce human MRI findings but shows a severe muscle weakness which might be related to an alteration of intrinsic muscular properties. The increased energy cost in H40Y mice might be related to either an impaired mitochondrial function or an alteration at the cross-bridges level. Overall, we provided a unique set of anatomic, metabolic and functional biomarkers that might be relevant for monitoring the progression of NM disease but also for assessing the efficacy of potential therapeutic interventions at a preclinical level.

Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter

Abstract The spinal cord white and gray matter can be affected by various pathologies such as multiple sclerosis, amyotrophic lateral sclerosis or trauma. Being able to precisely segment the white and gray matter could help with MR image analysis and hence be useful in further understanding these pathologies, and helping with diagnosis/prognosis and drug development. Up to date, white/gray matter segmentation has mostly been done manually, which is time consuming, induces a bias related to the rater and prevents large‐scale multi‐center studies. Recently, few methods have been proposed to automatically segment the spinal cord white and gray matter. However, no single method exists that combines the following criteria: (i) fully automatic, (ii) works on various MRI contrasts, (iii) robust towards pathology and (iv) freely available and open source. In this study we propose a multi‐atlas based method for the segmentation of the spinal cord white and gray matter that addresses the previous limitations. Moreover, to study the spinal cord morphology, atlas‐based approaches are increasingly used. These approaches rely on the registration of a spinal cord template to an MR image, however the registration usually doesn’t take into account the spinal cord internal structure and thus lacks accuracy. In this study, we propose a new template registration framework that integrates the white and gray matter segmentation to account for the specific gray matter shape of each individual subject. Validation of segmentation was performed in 24 healthy subjects using Symbol‐weighted images, in 8 healthy subjects using diffusion weighted images (exhibiting inverted white‐to‐gray matter contrast compared to T2*‐weighted), and in 5 patients with spinal cord injury. The template registration was validated in 24 subjects using T2*‐weighted data. Results of automatic segmentation on T2*‐weighted images was in close correspondence with the manual segmentation (Dice coefficient in the white/gray matter of 0.91/0.71 respectively). Similarly, good results were obtained in data with inverted contrast (diffusion‐weighted image) and in patients. When compared to the classical template registration framework, the proposed framework that accounts for gray matter shape significantly improved the quality of the registration (comparing Dice coefficient in gray matter: p=9.5×10−6). While further validation is needed to show the benefits of the new registration framework in large cohorts and in a variety of patients, this study provides a fully‐integrated tool for quantitative assessment of white/gray matter morphometry and template‐based analysis. All the proposed methods are implemented in the Spinal Cord Toolbox (SCT), an open‐source software for processing spinal cord multi‐parametric MRI data. Symbol. No caption available. Graphical abstract Figure. No Caption available. HighlightsAutomatic segmentation of the spinal cord white/gray matter in various MRI contrasts.Robust white/gray matter segmentation in patients with spinal cord injury.Vertebral level information as a shape prior for white/gray matter segmentation.Improved template‐based analysis framework that accounts for gray matter shape.

Depletion of brain functional connectivity enhancement leads to disability progression in multiple sclerosis: A longitudinal resting-state fMRI study.

Background: The compensatory effect of brain functional connectivity enhancement in relapsing-remitting multiple sclerosis (RRMS) remains controversial. Objective: To characterize the relationships between brain functional connectivity changes and disability progression in RRMS. Methods: Long-range connectivity, short-range connectivity, and density of connections were assessed using graph theoretical analysis of resting-state functional magnetic resonance imaging (fMRI) data acquired in 38 RRMS patients (disease duration: 120 ± 32 months) and 24 controls. All subjects were explored at baseline and all patients and six controls 2 years later. Results: At baseline, levels of long-range and short-range brain functional connectivity were higher in patients compared to controls. During the follow-up, decrease in connections’ density was inversely correlated with disability progression. Post-hoc analysis evidenced differential evolution of brain functional connectivity metrics in patients according to their level of disability at baseline: while patients with lowest disability at baseline experienced an increase in all connectivity metrics during the follow-up, patients with higher disability at baseline showed a decrease in the connectivity metrics. In these patients, decrease in the connectivity metrics was associated with disability progression. Conclusion: The study provides two main findings: (1) brain functional connectivity enhancement decreases during the disease course after reaching a maximal level, and (2) decrease in brain functional connectivity enhancement participates in disability progression.

Heterogeneity of Muscle Damage Induced by Electrostimulation: A Multimodal MRI Study

PURPOSE Neuromuscular electrostimulation (NMES) leads to a spatially fixed, synchronous, and superficial motor unit recruitment, which could induce muscle damage. Therefore, the extent of muscle damage and its spatial occurrence were expected to be heterogeneous across and along the quadriceps femoris (QF) muscles. The aim of the present study was to characterize muscle spatial heterogeneity in QF damage after a single bout of isometric NMES using multimodal magnetic resonance imaging (MRI). METHODS Twenty-five young healthy males participated in this study. MRI investigations consisted of the assessment of muscle volume, transverse relaxation time (T2), and diffusion tensor imaging (DTI) in muscles positioned near the stimulation electrodes (i.e., vastus lateralis (VL) and vastus medialis (VM)) and muscles located outside the stimulated regions (i.e., vastus intermedius and rectus femoris). These measurements were performed 6 d before, and 2 d and 4 d (D4) after the NMES session. RESULTS For the muscles placed in direct contact with the stimulation electrodes, volume (VL, +8.5%; VM, +3.8%), T2 (VL, +19.5%; VM, +6.7%) and radial diffusivity (λ3) (VL, + 7.3%; VM, +3.7%) significantly increased at D4. Whereas MRI parameter changes were larger for VL as compared with those for other QF muscles at D4, homogeneous alterations were found along all QF muscles. CONCLUSIONS Isometric NMES induced specific and localized alterations in VL and VM, with heterogeneous damage amplitude among them. Potential effects of unaccustomed intermuscle shear stress during electrically evoked isometric contractions could be a key factor in the spatial occurrence and the extent of damage among QF muscles (especially in VL). The kinetics and extent of MRI changes varied between T2 and diffusion tensor imaging metrics, suggesting the involvement of different physiological processes.

Model-driven harmonic parameterization of the cortical surface

In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.