Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI.

OBJECTIVES: Compelling evidence indicates a significant involvement of cortical lesions in the progressive phase of multiple sclerosis (MS), significantly contributing to late-stage disability. Despite the promise of ultra-high-field magnetic resonance imaging (MRI) in detecting cortical lesions, current evidence falls short in providing insights into the existence of such lesions during the early stages of MS or their underlying cause. This study delineated, at the early stage of MS, (1) the prevalence and spatial distribution of cortical lesions identified by 7 T MRI, (2) their relationship with white matter lesions, and (3) their clinical implications. MATERIALS AND METHODS: Twenty individuals with early-stage relapsing-remitting MS (disease duration <1 year) underwent a 7 T MRI session involving T1-weighted MP2RAGE, T2*-weighted multiGRE, and T2-weighted FLAIR sequences for cortical and white matter segmentation. Disability assessments included the Expanded Disability Status Scale, the Multiple Sclerosis Functional Composite, and an extensive evaluation of cognitive function. RESULTS: Cortical lesions were detected in 15 of 20 patients (75%). MP2RAGE revealed a total of 190 intracortical lesions (median, 4 lesions/case [range, 0-44]) and 216 leukocortical lesions (median, 2 lesions/case [range, 0-75]). Although the number of white matter lesions correlated with the total number of leukocortical lesions (r = 0.91, P < 0.001), no correlation was observed between the number of white matter or leukocortical lesions and the number of intracortical lesions. Furthermore, the number of leukocortical lesions but not intracortical or white-matter lesions was significantly correlated with cognitive impairment (r = 0.63, P = 0.04, corrected for multiple comparisons). CONCLUSIONS: This study highlights the notable prevalence of cortical lesions at the early stage of MS identified by 7 T MRI. There may be a potential divergence in the underlying pathophysiological mechanisms driving distinct lesion types, notably between intracortical lesions and white matter/leukocortical lesions. Moreover, during the early disease phase, leukocortical lesions more effectively accounted for cognitive deficits.

Energetic dysfunction and iron overload in early Parkinson's disease: Two distinct mechanisms?

INTRODUCTION: Identifying biomarkers reflecting cellular dysfunctions in early Parkinson's disease patients (ePD) is needed to develop targeted therapeutic strategies. We aimed to determine if cellular energetic dysfunction related to increased brain sodium concentration would be co-located to microstructural alterations and iron deposition in ePD. METHODS: We prospectively included 12 ePD (mean disease duration 20.0 ± 10.2 months) and 13 healthy controls (HC), scanned with a 7 T 1H and 23Na MRI. Complementary voxel-based and region-based assessments were performed, the latter utilizing a high-resolution multimodal template we created (combining quantitative T1 maps (qT1), transverse relaxation rate (R2*), quantitative magnetic susceptibility mapping (QSM) images) from 200 subjects. This template allowed a precise multiparametric assessment of sodium concentration, QSM, R2*, qT1, mean diffusivity, and fractional anisotropy values. A two-sided p-value<0.05 was considered statistically significant after the Bonferroni correction. RESULTS: Relative to HC, ePD showed significantly higher sodium concentration in left Substantia nigra (SN) pars reticulata (46.13 mM ± 3.52 vs 38.60 mM ± 6.10, p = 0.038), a subpart of the SN pars compacta (SNc) and ventral tegmental area, Putamen, Globus Pallidum external, accumbens nucleus and claustrum. Significantly increased QSM and R2* values, and decreased T1 values, were limited to the Nigrosomes 1 (Nig) and right SNc (all p < 0.05). QSM values in the Nig were significantly correlated to UPDRS-III scores (r = 0.91,p < 0.001). CONCLUSION: In ePD, brain sodium accumulation was broad and dissociated from iron accumulation. As with iron accumulation, a sodium-related pathophysiological approach could lead to identifying potential new therapeutic agents and deserves further investigation.

Multi-scale structural alterations of the thalamus and basal ganglia in focal epilepsy using 7T MRI.

Focal epilepsy is characterized by repeated spontaneous seizures that originate from cortical epileptogenic zone networks (EZN). Analysis of intracerebral recordings showed that subcortical structures, and in particular the thalamus, play an important role in seizure dynamics as well, supporting their structural alterations reported in the neuroimaging literature. Nonetheless, between-patient differences in EZN localization (e.g., temporal vs. non-temporal lobe epilepsy) as well as extension (i.e., number of epileptogenic regions) might impact the magnitude as well as spatial distribution of subcortical structural changes. Here we used 7 Tesla MRI T1 data to provide an unprecedented description of subcortical morphological (volume, tissue deformation, and shape) and longitudinal relaxation (T1 ) changes in focal epilepsy patients and evaluate the impact of the EZN and other patient-specific clinical features. Our results showed variable levels of atrophy across thalamic nuclei that appeared most prominent in the temporal lobe epilepsy group and the side ipsilateral to the EZN, while shortening of T1 was especially observed for the lateral thalamus. Multivariate analyses across thalamic nuclei and basal ganglia showed that volume acted as the dominant discriminator between patients and controls, while (posterolateral) thalamic T1 measures looked promising to further differentiate patients based on EZN localization. In particular, the observed differences in T1 changes between thalamic nuclei indicated differential involvement based on EZN localization. Finally, EZN extension was found to best explain the observed variability between patients. To conclude, this work revealed multi-scale subcortical alterations in focal epilepsy as well as their dependence on several clinical characteristics.

Inhomogeneous Magnetization Transfer (ihMT) imaging in the acute cuprizone mouse model of demyelination/remyelination.

BACKGROUND: To investigate the association of ihMT (inhom signals with the demyelination and remyelination phases of the acute cuprizone mouse model in comparison with histology, and to assess the extent of tissue damage and repair from MRI data. METHODS: Acute demyelination by feeding 0.2% cuprizone for five weeks, followed by a four-week remyelination period was applied on genetically modified plp-GFP mice. Animals were scanned at different time points of the demyelination and remyelination phases of the cuprizone model using a multimodal MRI protocol, including ihMT T1D-filters, MPF (Macromolecular Proton Fraction) and R1 (longitudinal relaxation rate). For histology, plp-GFP (proteolipid protein - Green Fluorescent Protein) microscopy and LFB (Luxol Fast Blue) staining were employed as references for the myelin content. Comparison of MRI with histology was performed in the medial corpus callosum (mCC) and cerebral cortex (CTX) at two brain levels whereas ROI-wise and voxel-based analyses of the MRI metrics allowed investigating in vivo the spatial extent of myelin alterations. RESULTS: IhMT high-pass T1D-filters, targeted toward long T1D components, showed significant temporal variations in the mCC consistent with the effects induced by the cuprizone toxin. In addition, the corresponding signals correlated strongly and significantly with the myelin content assessed by GFP fluorescence and LFB staining over the demyelination and the remyelination phases. The signal of the band-pass T1D-filter, which isolates short T1D components, showed changes over time that were poorly correlated with histology, hence suggesting a sensitivity to pathological processes possibly not related to myelin. Although MPF was also highly correlated to histology, ihMT high-pass T1D-filters showed better capability to characterize the spatial-temporal patterns during the demyelination and remyelination phases of the acute cuprizone model (e.g., rostro-caudal gradient of demyelination in the mCC previously described in the literature). CONCLUSIONS: IhMT sequences selective for long T1D components are specific and sensitive in vivo markers of demyelination and remyelination and have successfully captured the spatially heterogeneous pattern of the demyelination and remyelination mechanisms in the cuprizone model. Interestingly, differences in signal variations between the ihMT high-pass and band-pass T1D-filter, suggest a sensitivity of the ihMT sequences targeted to short T1Ds to alterations other than those of myelin. Future studies will need to further address these differences by examining more closely the origin of the short T1D components and the variation of each T1D component in pathology.

T1D -weighted ihMT imaging - Part II. Investigating the long- and short-T1D components correlation with myelin content. Comparison with R1 and the macromolecular proton fraction.

PURPOSE: To investigate the long- and short-T1D components correlation with myelin content using inhomogeneous magnetization transfer (ihMT) high-pass and band-pass T1D -filters and to compare ihMT, R1 , and the macromolecular proton fraction (MPF) for myelin specific imaging. METHODS: The 3D ihMT rapid gradient echo (ihMTRAGE) sequences with increasing switching times (Δt) were used to derive ihMT high-pass T1D -filters with increasing T1D cutoff values and an ihMT band-pass T1D -filter for components in the 100 µs to 1 ms range. 3D spoiled gradient echo quantitative MT (SPGR-qMT) protocols were used to derive R1 and MPF maps. The specificity of R1 , MPF, and ihMT T1D -filters was evaluated by comparison with two histological reference techniques for myelin imaging. RESULTS: The higher contribution of long-T1D s as compared to the short components as Δt got longer led to an increase in the specificity to myelination. In contrast, focusing on the signal originating from a narrow range of short-T1D s (< 1 ms) as isolated by the band-pass T1D -filter led to lower specificity. In addition, the significantly lower r2 correlation coefficient of the band-pass T1D -filter suggests that the origin of short-T1D components is mostly associated with non-myelin protons. Also, the important contribution of short-T1D s to the estimated MPF, explains its low specificity to myelination as compared to the ihMT high-pass T1D -filters. CONCLUSION: Long-T1D components imaging by means of ihMT high-pass T1D -filters is proposed as an MRI biomarker for myelin content. Future studies should enable the investigation of the sensitivity of ihMT T1D -filters for demyelinating processes.

T1D -weighted ihMT imaging - Part I. Isolation of long- and short-T1D components by T1D -filtering.

PURPOSE: To identify T1D -filtering methods, which can specifically isolate various ranges of T1D components as they may be sensitive to different microstructural properties. METHODS: Modified Bloch-Provotorov equations describing a bi-T1D component biophysical model were used to simulate the inhomogeneous magnetization transfer (ihMT) signal from ihMTRAGE sequences at high RF power and low duty-cycle with different switching time values for the dual saturation experiment: Δt = 0.0, 0.8, 1.6, and 3.2 ms. Simulations were compared with experimental signals on the brain gray and white matter tissues of healthy mice at 7T. RESULTS: The lengthening of Δt created ihMT high-pass T1D -filters, which efficiently eliminated the signal from T1D components shorter than 1 ms, while partially attenuating that of longer components (≥ 1 ms). Subtraction of ihMTR images obtained with Δt = 0.0 ms and Δt = 0.8 ms generated a new ihMT band-pass T1D -filter isolating short-T1D components in the 100-µs to 1-ms range. Simulated ihMTR values in central nervous system tissues were confirmed experimentally. CONCLUSION: Long- and short-T1D components were successfully isolated with high RF power and low duty-cycle ihMT filters in the healthy mouse brain. Future studies should investigate the various T1D -range microstructural correlations in in vivo tissues.

Epileptogenic networks in drug-resistant epilepsy with amygdala enlargement: Assessment with stereo-EEG and 7 T MRI.

OBJECTIVE: Amygdala enlargement is increasingly described in association with temporal lobe epilepsies. Its significance, however, remains uncertain both in terms of etiology and its link with psychiatric disorders and of its involvement in the epileptogenic zone. We assessed the epileptogenic networks underlying drug-resistant epilepsy with amygdala enlargement and investigated correlations between clinical features, epileptogenicity and morphovolumetric amygdala characteristics. METHODS: We identified 12 consecutive patients suffering from drug-resistant epilepsy with visually suspected amygdala enlargement and available stereoelectroencephalographic recording. The epileptogenic zone was defined using the Connectivity Epileptogenicity Index. Morphovolumetric measurements were performed using automatic segmentation and co-registration on the 7TAMIbrain Amygdala atlas. RESULTS: The epileptogenic zone involved the enlarged amygdala in all but three cases and corresponded to distributed, temporal-insular, temporal-insular-prefrontal or prefrontal-temporal networks in ten cases, while only two were temporo-mesial networks. Morphovolumetrically, amygdala enlargement was bilateral in 75% of patients. Most patients presented psychiatric comorbidities (anxiety, depression, posttraumatic stress disorder). The level of depression defined by screening questionnaire was positively correlated with the extent of amygdala enlargement. CONCLUSIONS: Drug-resistant epilepsy with amygdala enlargement is heterogeneous; most cases implied "temporal plus" networks. SIGNIFICANCE: The enlarged amygdala could reflect an interaction of stress-mediated limbic network alterations and mechanisms of epileptogenesis.

Automatic segmentation of deep grey nuclei using a high-resolution 7T magnetic resonance imaging atlas-Quantification of T1 values in healthy volunteers.

We present a new consensus atlas of deep grey nuclei obtained by shape-based averaging of manual segmentation of two experienced neuroradiologists and optimized from 7T MP2RAGE images acquired at (.6 mm)3 in 60 healthy subjects. A group-wise normalization method was used to build a high-contrast and high-resolution T1 -weighted brain template (.5 mm)3 using data from 30 out of the 60 controls. Delineation of 24 deep grey nuclei per hemisphere, including the claustrum and 12 thalamic nuclei, was then performed by two expert neuroradiologists and reviewed by a third neuroradiologist according to tissue contrast and external references based on the Morel atlas. Corresponding deep grey matter structures were also extracted from the Morel and CIT168 atlases. The data-derived, Morel and CIT168 atlases were all applied at the individual level using non-linear registration to fit the subject reference and to extract absolute mean quantitative T1 values derived from the 3D-MP2RAGE volumes, after correction for residual B1+ biases. Three metrics (the Dice and the volumetric similarity coefficients and a novel Hausdorff distance) were used to estimate the inter-rater agreement of manual MRI segmentation and inter-atlas variability, and these metrics were measured to quantify biases due to image registration, and their impact on the measurements of the quantitative T1 values was highlighted. This represents a fully automated segmentation process permitting the extraction of unbiased normative T1 values in a population of young healthy controls as a reference for characterizing subtle structural alterations of deep grey nuclei relevant to a range of neurological diseases.

Semiautomatic quantification of abdominal wall muscles deformations based on dynamic MRI image registration.

Quantitative analysis of abdominal organs motion and deformation is crucial to better understand biomechanical alterations undermining respiratory, digestive or perineal pathophysiology. In particular, biomechanical characterization of the antero-lateral abdominal wall is central in the diagnosis of abdominal muscle deficiency. Here, we present a dedicated semiautomatic dynamic MRI postprocessing method enabling the quantification of spatial and temporal deformations of the antero-lateral abdominal wall muscles. Ten healthy participants were imaged during a controlled breathing session at the L3-L4 disc level using real-time dynamic MRI at 3 T. A coarse feature-tracking step allowed the selection of the inhalation cycle of maximum abdominal excursion. Over this image series, the described method combines (1) a supervised 2D+t segmentation procedure of the abdominal wall muscles, (2) the quantification of muscle deformations based on masks registration, and (3) the mapping of deformations within muscle subzones leveraging a dedicated automatic parcellation. The supervised 2D+t segmentation (1) provided an accurate segmentation of the abdominal wall muscles throughout maximum inhalation with a 0.95 ± 0.03 Dice similarity coefficient (DSC) value and a 2.3 ± 0.7 mm Hausdorff distance value while requiring only manual segmentation of 20% of the data. The robustness of the deformation quantification (2) was indicated by high indices of correspondence between the registered source mask and the target mask (0.98 ± 0.01 DSC value and 2.1 ± 1.5 mm Hausdorff distance value). Parcellation (3) enabled the distinction of muscle substructures that are anatomically relevant but could not be distinguished based on image contrast. The present genuine postprocessing method provides a quantitative analytical frame that could be used in further studies for a better understanding of abdominal wall deformations in physiological and pathological situations.

VEP atlas: An anatomic and functional human brain atlas dedicated to epilepsy patients.

BACKGROUND: Several automated parcellation atlases of the human brain have been developed over the past decades, based on various criteria, and have been applied in basic and clinical research. NEW METHOD: Here we present the Virtual Epileptic Patient (VEP) atlas that offers a new automated brain region parcellation and labeling, which has been developed for the specific use in the domains of epileptology and functional neurosurgery and is able to apply at individual patient's level. RESULTS: It comprises 162 brain regions, including 73 cortical and 8 subcortical regions per hemisphere. We demonstrate the successful application of the VEP atlas in a cohort of 50 retrospective patients. The structural organization is complemented by the functional variation of stereotactic intracerebral EEG (SEEG) signal data features establishing brain region-specific 3d-maps. COMPARISON WITH EXISTING METHODS: The VEP atlas integrates both anatomical and functional definitions in the same atlas, adapted to applications for epilepsy patients and individualizable. CONCLUSION: The covariation of structural and functional organization is the basis for current efforts of patient-specific large-scale brain network modeling exploiting virtual brain technologies for the identification of the epileptogenic regions in an ongoing prospective clinical trial EPINOV.

Modular slowing of resting-state dynamic functional connectivity as a marker of cognitive dysfunction induced by sleep deprivation.

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.

Fat fraction distribution in lower limb muscles of patients with CMT1A: A quantitative MRI study.

OBJECTIVE: To quantitatively describe the MRI fat infiltration pattern of muscle degeneration in Charcot-Marie-Tooth (CMT) type 1A (CMT1A) disease and to look for correlations with clinical variables. METHODS: MRI fat fraction was assessed in lower-limb musculature of patients with CMT1A and healthy controls. More particularly, 14 muscle compartments were selected at leg and thigh levels and for proximal, distal, and medial slices. Muscle fat infiltration profile was determined quantitatively in each muscle compartment and along the entire volume of acquisition to determine a length-dependent gradient of fat infiltration. Clinical impairment was evaluated with muscle strength measurements and CMT Examination Scores (CMTESs). RESULTS: A total of 16 patients with CMT1A were enrolled and compared to 11 healthy controls. Patients with CMT1A showed a larger muscle fat fraction at leg and thigh levels with a proximal-to-distal gradient. At the leg level, the largest fat infiltration was quantified in the anterior and lateral compartments. CMTES was correlated with fat fraction, especially in the anterior compartment of leg muscles. Strength of plantar flexion was also correlated with fat fraction of the posterior compartments of leg muscles. CONCLUSION: On the basis of quantitative MRI measurements combined with a dedicated segmentation method, muscle fat infiltration quantified in patients with CMT1A disclosed a length-dependent peroneal-type pattern of fat infiltration and was correlated to main clinical variables. Quantification of fat fraction at different levels of the leg anterior compartment might be of interest in future clinical trials.

A novel segmentation framework dedicated to the follow-up of fat infiltration in individual muscles of patients with neuromuscular disorders.

PURPOSE: To propose a novel segmentation framework that is dedicated to the follow-up of fat infiltration in individual muscles of patients with neuromuscular disorders. METHODS: We designed a semi-automatic segmentation pipeline of individual leg muscles in MR images based on automatic propagation through nonlinear registrations of initial delineation in a minimal number of MR slices. This approach has been validated for the segmentation of individual muscles from MRI data sets, acquired over a 10-month period, from thighs and legs in 10 patients with muscular dystrophy. The robustness of the framework was evaluated using conventional metrics related to muscle volume and clinical metrics related to fat infiltration. RESULTS: High accuracy of the semi-automatic segmentation (mean Dice similarity coefficient higher than 0.89) was reported. The provided method has excellent reliability regarding the reproducibility of the fat fraction estimation, with an average intraclass correlation coefficient score of 0.99. Furthermore, the present segmentation framework was determined to be more reliable than the intra-expert performance, which had an average intraclass correlation coefficient of 0.93. CONCLUSION: The proposed framework of segmentation can successfully provide an effective and reliable tool for accurate follow-up of any MRI biomarkers in neuromuscular disorders. This method could assist the quantitative assessment of muscular changes occurring in such diseases.

Use of magnetic resonance image registration to estimate displacement in the human earcanal due to the insertion of in-ear devices.

In-ear devices are used in a wide range of applications for which the device's usability and/or efficiency is strongly related to comfort aspects that are influenced by the mechanical interaction between the device and the walls of the earcanal. Although the displacement of the earcanal walls due to the insertion of the device is an important characteristic of this interaction, existing studies on this subject are very limited. This paper proposes a method to estimate this displacement in vivo using a registration technique on magnetic resonance images. The amplitude, the location and the direction of the earcanal wall displacement are computed for four types of earplugs used by one participant. These displacements give indications on how each earplug deforms the earcanal for one specific earcanal geometry and one specific earplug insertion. Although the displacement due to a specific earplug family cannot be generalized using the results of this paper, the latter help to understand where, how much, and how each studied earplug deforms the earcanal of the participant. This method is revealed as a promising tool to investigate further acoustical and physical comfort aspects of in-ear devices.

Structural Connectivity Alterations in Amyotrophic Lateral Sclerosis: A Graph Theory Based Imaging Study.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disorder. Diffusion magnetic resonance imagining (MRI) studies have consistently showed widespread alterations in both motor and non-motor brain regions. However, connectomics and graph theory based approaches have shown inconsistent results. Hub-centered lesion patterns and their impact on local and large-scale brain networks remain to be established. The objective of this work is to characterize topological properties of structural brain connectivity in ALS using an array of local, global and hub-based network metrics. MATERIALS AND METHODS: Magnetic resonance imagining data were acquired from 25 patients with ALS and 26 age-matched healthy controls. Structural network graphs were constructed from diffusion tensor MRI. Network-based statistics (NBS) and graph theory metrics were used to compare structural networks without a priori regions of interest. RESULTS: Patients with ALS exhibited global network alterations with decreased global efficiency (Eglob) (p = 0.03) and a trend of reduced whole brain mean degree (p = 0.05) compared to controls. Six nodes showed significantly decreased mean degree in ALS: left postcentral gyrus, left interparietal and transverse parietal sulcus, left calcarine sulcus, left occipital temporal medial and lingual sulcus, right precentral gyrus and right frontal inferior sulcus (p < 0.01). Hub distribution was comparable between the two groups. There was no selective hub vulnerability or topological reorganization centered on these regions as the hub disruption index (κ) was not significant for the relevant metrics (degree, local efficiency and betweenness centrality). Using NBS, we identified an impaired motor subnetwork of 11 nodes and 10 edges centered on the precentral and the paracentral nodes (p < 0.01). Significant clinical correlations were identified between degree in the frontal area and the disease progression rate of ALS patients (p < 0.01). CONCLUSION: Our study provides evidence that alterations of structural connectivity in ALS are primarily driven by node degree and white matter tract degeneration within an extended network around the precentral and the paracentral areas without hub-centered reorganization.

Spatial difference can occur between activated and damaged muscle areas following electrically-induced isometric contractions.

KEY POINTS: T2 mapping combined to image registration and statistical parametric mapping analysis is a suitable methodology to accurately localize and compare the extent of both activated and damaged muscle areas. Activated muscle areas following electrically-induced isometric contractions are superficial, but damaged regions are muscle specific and can be related to the muscle morphology and/or the relative spatial position within a muscle group leading to potential intramuscular muscle shear strain. Tissues other than active skeletal muscle fibres can be altered during unaccustomed neuromuscular electrical stimulation-induced isometric contractions. ABSTRACT: Skeletal muscle isometric contractions induced by neuromuscular electrical stimulation (NMES) exercise can generate damage within activated muscles. This study aimed at comparing the localization and the extent of NMES-activated muscle areas and induced damage regions using magnetic resonance imaging. Thirteen healthy subjects performed a single bout of NMES-induced isometric contractions known to induce a decrease in maximal voluntary isometric contraction (MVC) and increase in muscle volume and transverse relaxation time (T2 ). All the parameters were measured before, immediately after (POST), 7 days (D7), 14 days (D14) and 21 days (D21) after the NMES session. Spatial normalization of T2 maps were performed to compare the localization of muscle activation areas and damaged muscle regions from statistical mapping analyses. A significant decrease in MVC was found at POST (-26 ± 9%) and in delayed time at D7 (-20 ± 6%) and D14 (-12 ± 5%). Although muscle activation was statistically detected through T2 increase at POST in superficial parts of the two muscles located beneath the stimulation electrodes (i.e. vastus lateralis and vastus medialis), alterations quantified in a delayed time from increased T2 were mainly located in the deep muscle region of the vastus lateralis (+57 ± 24% of mean T2 ) and superficial area of the vastus medialis (+24 ± 16% of mean T2 ) at D7 and were still observed in whole muscle at D21. The discrepancy between activated and damaged areas in the vastus lateralis implies that tissues other than active skeletal muscle fibres were altered during unaccustomed NMES-induced isomeric contractions.

Diffusion Properties and 3D Architecture of Human Lower Leg Muscles Assessed with Ultra-High-Field-Strength Diffusion-Tensor MR Imaging and Tractography: Reproducibility and Sensitivity to Sex Difference and Intramuscular Variability.

Purpose To demonstrate the reproducibility of the diffusion properties and three-dimensional structural organization measurements of the lower leg muscles by using diffusion-tensor imaging (DTI) assessed with ultra-high-field-strength (7.0-T) magnetic resonance (MR) imaging and tractography of skeletal muscle fibers. On the basis of robust statistical mapping analyses, this study also aimed at determining the sensitivity of the measurements to sex difference and intramuscular variability. Materials and Methods All examinations were performed with ethical review board approval; written informed consent was obtained from all volunteers. Reproducibility of diffusion tensor indexes assessment including eigenvalues, mean diffusivity, and fractional anisotropy (FA) as well as muscle volume and architecture (ie, fiber length and pennation angle) were characterized in lower leg muscles (n = 8). Intramuscular variability and sex differences were characterized in young healthy men and women (n = 10 in each group). Student t test, statistical parametric mapping, correlation coefficients (Spearman rho and Pearson product-moment) and coefficient of variation (CV) were used for statistical data analysis. Results High reproducibility of measurements (mean CV ± standard deviation, 4.6% ± 3.8) was determined in diffusion properties and architectural parameters. Significant sex differences were detected in FA (4.2% in women for the entire lower leg; P = .001) and muscle volume (21.7% in men for the entire lower leg; P = .008), whereas architecture parameters were almost identical across sex. Additional differences were found independently of sex in diffusion properties and architecture along several muscles of the lower leg. Conclusion The high-spatial-resolution DTI assessed with 7.0-T MR imaging allows a reproducible assessment of structural organization of superficial and deep muscles, giving indirect information on muscle function. ©RSNA, 2018 Online supplemental material is available for this article.

Whole brain inhomogeneous magnetization transfer (ihMT) imaging: Sensitivity enhancement within a steady-state gradient echo sequence.

PURPOSE: To implement, characterize, and optimize an interleaved inhomogeneous magnetization transfer (ihMT) gradient echo sequence allowing for whole-brain imaging within a clinically compatible scan time. THEORY AND METHODS: A general framework for ihMT modelling was developed based on the Provotorov theory of radiofrequency saturation, which accounts for the dipolar order underpinning the ihMT effect. Experimental studies and numerical simulations were performed to characterize and optimize the ihMT-gradient echo dependency with sequence timings, saturation power, and offset frequency. The protocol was optimized in terms of maximum signal intensity and the reproducibility assessed for a nominal resolution of 1.5 mm isotropic. All experiments were performed on healthy volunteers at 1.5T. RESULTS: An important mechanism driving signal optimization and leading to strong ihMT signal enhancement that relies on the dynamics of radiofrequency energy deposition has been identified. By taking advantage of the delay allowed for readout between ihMT pulse bursts, it was possible to boost the ihMT signal by almost 2-fold compared to previous implementation. Reproducibility of the optimal protocol was very good, with an intra-individual error < 2%. CONCLUSION: The proposed sensitivity-boosted and time-efficient steady-state ihMT-gradient echo sequence, implemented and optimized at 1.5T, allowed robust high-resolution 3D ihMT imaging of the whole brain within a clinically compatible scan time. Magn Reson Med 79:2607-2619, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches.

Manual and automated segmentation of individual muscles in magnetic resonance images have been recognized as challenging given the high variability of shapes between muscles and subjects and the discontinuity or lack of visible boundaries between muscles. In the present study, we proposed an original algorithm allowing a semi-automatic transversal propagation of manually-drawn masks. Our strategy was based on several ascending and descending non-linear registration approaches which is similar to the estimation of a Lagrangian trajectory applied to manual masks. Using several manually-segmented slices, we have evaluated our algorithm on the four muscles of the quadriceps femoris group. We mainly showed that our 3D propagated segmentation was very accurate with an averaged Dice similarity coefficient value higher than 0.91 for the minimal manual input of only two manually-segmented slices.