Brain Metabolic Profile in Presymptomatic GRN Carriers Throughout a 5-Year Follow-up.

BACKGROUND AND OBJECTIVES: GRN variants are a frequent cause of familial frontotemporal dementia (FTD). Monitoring disease progression in asymptomatic carriers of genetic variants is a major challenge in delivering preventative therapies before clinical onset. This study aimed to assess the usefulness of fluorodeoxyglucose (FDG)-PET in identifying metabolic changes in presymptomatic GRN carriers (PS-GRN+) and to trace their longitudinal progression. METHODS: Participants were longitudinally evaluated over 5 years in a prospective cohort study focused on GRN disease (Predict-PGRN). They underwent cognitive/behavioral assessment, plasma neurofilament measurement, brain MRI, and FDG-PET. Voxel-wise comparisons of structural and metabolic imaging data between 2 groups were performed for each time point. Longitudinal PET changes were evaluated with voxel-wise comparisons and the metabolic percent annual changes method. The association of regional brain metabolism with plasma neurofilament and cognitive changes was analyzed. RESULTS: Among the 80 individuals enrolled in the study, 58 (27 PS-GRN+ and 31 noncarriers) were included in the analyses. Cross-sectional comparisons between PS-GRN+ and controls found a significant hypometabolism in the left superior temporal sulcus (STS) region (encompassing the middle and superior temporal gyri), approximately 15 years before the expected disease onset, without significant cortical atrophy. The longitudinal metabolic decline over the following 5 years peaked around the right STS in carriers (p < 0.001), without significantly greater volume loss compared with that in controls. Their estimated annualized metabolic decrease (-1.37%) was higher than that in controls (-0.21%, p = 0.004). Lower glucose uptake was associated with higher neurofilament increase (p = 0.003) and lower frontal cognitive scores (p = 0.014) in PS-GRN+. DISCUSSION: This study detected brain metabolic changes in the STS region, preceding structural and cognitive alterations, thus contributing to the characterization of the pathochronology of preclinical GRN disease. Owing to the STS involvement in the perception of facially communicated cues, it is likely that its dysfunction contributes to social cognition deficits characterizing FTD. Overall, our study highlights brain metabolic changes as an early disease-tracking biomarker and proposes annualized percent decrease as a metric to monitor therapeutic response in forthcoming trials.

Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study.

PURPOSE: A reliable tool for outcome prognostication in severe traumatic brain injury (TBI) would improve intensive care unit (ICU) decision-making process by providing objective information to caregivers and family. This study aimed at designing a new classification score based on magnetic resonance (MR) diffusion metrics measured in the deep white matter between day 7 and day 35 after TBI to predict 1-year clinical outcome. METHODS: Two multicenter cohorts (29 centers) were used. MRI-COMA cohort (NCT00577954) was split into MRI-COMA-Train (50 patients enrolled between 2006 and mid-2014) and MRI-COMA-Test (140 patients followed up in clinical routine from 2014) sub-cohorts. These latter patients were pooled with 56 ICU patients (enrolled from 2014 to 2020) from CENTER-TBI cohort (NCT02210221). Patients were dichotomised depending on their 1-year Glasgow outcome scale extended (GOSE) score: GOSE 1-3, unfavorable outcome (UFO); GOSE 4-8, favorable outcome (FO). A support vector classifier incorporating fractional anisotropy and mean diffusivity measured in deep white matter, and age at the time of injury was developed to predict whether the patients would be either UFO or FO. RESULTS: The model achieved an area under the ROC curve of 0.93 on MRI-COMA-Train training dataset, and 49% sensitivity for 96.8% specificity in predicting UFO and 58.5% sensitivity for 97.1% specificity in predicting FO on the pooled MRI-COMA-Test and CENTER-TBI validation datasets. CONCLUSION: The model successfully identified, with a specificity compatible with a personalized decision-making process in ICU, one in two patients who had an unfavorable outcome at 1 year after the injury, and two-thirds of the patients who experienced a favorable outcome.

Global mean diffusivity: A radiomarker discriminating good outcome long term after traumatic brain injury.

BACKGROUND: Traumatic brain injury (TBI) is a chronic pathology responsible for cognitive disorders impacting outcome. Global clinical outcome several years after TBI may be associated with anatomical sequelae. Anatomical lesions are not well described because characterizing diffuse axonal injury and brain atrophy require using specific MRI sequences with quantitative measures. The best radiologic parameter to describe the lesions long term after TBI is not known. OBJECTIVE: We aimed to first, assess the global volumetric and diffusion parameters related to long-term outcome after TBI and second, define the most discriminating parameter. METHODS: In this observational study, we included 96 patients with severe TBI and 22 healthy volunteers. The mean delay after TBI was 63.2 months [range 31-119]. The Glasgow Outcome Scale Extended (GOS-E) was used to assess the global long-term clinical outcome. All patients underwent multimodal MRI with measures of brain volume, ventricle volume, global fractional anisotropy (FA) and global mean diffusivity (MD). RESULTS: All 96 participants had significant impairment in global FA, global MD, brain volume and ventricle volume as compared with the 22 controls (P<0.01). Only global MD significantly differed between the "good recovery" group (GOS-E score 7-8) and the other two groups: GOS-E scores 3-4 and 5-6. Brain volume significantly differed between the GOS-E 7-8 and 3-4 groups. Global MD was the most discriminating radiological parameter for the "good recovery" group versus other patients, long term after TBI. FA appeared less relevant at this time. Global atrophy was higher in patients than controls but lacked reliability to discriminate groups of patients. CONCLUSION: Global mean diffusivity seems a more promising radiomarker than global FA for discriminating good outcome long term after TBI. Further work is needed to understand the evolution of these long-term radiological parameters after TBI.

Long-term cognitive disability after traumatic brain injury: Contribution of the DEX relative questionnaires.

Executive functions are high-level cognitive processes commonly impaired after severe traumatic brain injury (sTBI), which may be associated with persistent anosognosia. The dysexecutive questionnaire (DEX) was designed to assess different domains of executive functioning in daily life. Two versions of the DEX exist (DEX-S completed by the patient, DEX-O completed by a relative) to compare cognitive complaints and patient's awareness. This work was aimed at studying the relevance of DEX-O for assessing daily-life limitations, the persistence of anosognosia and its association with global disability (GOSE) and magnetic resonance imaging (MRI) markers of brain alterations. Sixty-three patients (and relatives) were included within 63.4 months (±20.7) after sTBI. DEX-S and DEX-O scores were significantly positively correlated. We obtained significant correlations between DEX-S and episodic memory and phasic alert but not with executive assessment, GOSE and diffusion MRI markers. DEX-O was significantly correlated with executive function, episodic memory, attention (phasic alert sustained and divided attention), with the GOSE and the volume of the body of the corpus callosum (MRI marker). Anosognosia score (DEX-O minus DEX-S) correlated with mean diffusivity measure. These results highlight the clinical interest of DEX-O in assessing long-term disability.

Deep brain activation patterns involved in virtual gait without and with a doorway: An fMRI study.

The human gait program involves many brain areas such as motor cortices, cerebellum, basal ganglia, brainstem, and spinal cord. The mesencephalic locomotor region (MLR), which contains the pedunculopontine (PPN) and cuneiform (CN) nuclei, is thought to be one of the key supraspinal gait generators. In daily life activities, gait primarily occurs in complex conditions, such as through narrow spaces, or while changing direction or performing motor or cognitive tasks. Here, we aim to explore the activity of these subcortical brain areas while walking through narrow spaces, using functional MRI in healthy volunteers and designing a virtual reality task mimicking walking down a hallway, without and with an open doorway to walk through. As a control, we used a virtual moving walkway in the same environment. Twenty healthy volunteers were scanned. Fifteen subjects were selected for second level analysis based on their ability to activate motor cortices. Using the contrast Gait versus Walkway, we found activated clusters in motor cortices, cerebellum, red nucleus, thalamus, and the left MLR including the CN and PPN. Using the contrast Gait with Doorway versus Walkway with Doorway, we found activated clusters in motor cortices, left putamen, left internal pallidum, left substantia nigra, right subthalamic area, and bilateral MLR involving the CN and PPN. Our results suggest that unobstructed gait involves a motor network including the PPN whereas gait through a narrow space requires the additional participation of basal ganglia and bilateral MLR, which may encode environmental cues to adapt locomotion.

Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study.

OBJECTIVE: C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers. METHODS: Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9+ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9+ and C9- subgroups, and C9+ subjects were further stratified by age. RESULTS: At baseline, significant WM atrophy was detected at each cervical vertebral level in C9+ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9+ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline. INTERPRETATION: Cervical SC imaging detects WM atrophy exclusively in C9+ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.

Brain responses to pictures of children in men with pedophilic disorder: a functional magnetic resonance imaging study.

Structural and functional neuroimaging techniques have recently been used to investigate the mechanisms of sexual attraction to children, a hallmark of pedophilic disorder, and have reported many contradictory or non-replicated findings. Here, our purpose was to identify through functional magnetic resonance imaging the brain responses of 25 male outpatients with pedophilic disorder to visual stimuli depicting children (VSc) and to compare them with 24 male healthy controls matched on sexual orientation (to female or male adults), age, and handedness. No region was differentially activated across the two groups in response to VSc. However, as shown by a random-effects statistical analysis (cluster-level pFWE-corrected < 0.05), in patients with pedophilia, but not in controls, the presentation of VSc induced a bilateral activation in the lateral occipital and temporal cortices, in particular in the right inferior temporal gyrus, as well as an activation in the declive of the cerebellar vermis. In addition, in patients the level of bilateral activation in the above-mentioned regions was positively correlated with ratings of perceived sexual arousal elicited by VSc. These results implicate these regions as possible candidate areas mediating sexual arousal in patients with pedophilic disorder.

Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study.

INTRODUCTION: Extrapyramidal deficits are poorly characterised in amyotrophic lateral sclerosis (ALS) despite their contribution to functional disability, increased fall risk and their quality-of-life implications. Given the concomitant pyramidal and cerebellar degeneration in ALS, the clinical assessment of extrapyramidal features is particularly challenging. OBJECTIVE: The comprehensive characterisation of postural instability in ALS using standardised clinical assessments, gait analyses and computational neuroimaging tools in a prospective study design. METHODS: Parameters of gait initiation in the anticipatory postural adjustment phase (APA) and execution phase (EP) were evaluated in ALS patients with and without postural instability and healthy controls. Clinical and gait analysis parameters were interpreted in the context of brain imaging findings. RESULTS: ALS patients with postural instability exhibit impaired gait initiation with an altered APA phase, poor dynamic postural control and significantly decreased braking index. Consistent with their clinical profile, "unsteady" ALS patients have reduced caudate and brain stem volumes compared to "steady" ALS patients. INTERPRETATION: Our findings highlight that the ALS functional rating scale (ALSFRS-r) does not account for extrapyramidal deficits, which are major contributors to gait impairment in a subset of ALS patients. Basal ganglia degeneration in ALS does not only contribute to cognitive and behavioural deficits, but also adds to the heterogeneity of motor disability.

Taking the brakes off the learning curve.

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc.

CATI: A Large Distributed Infrastructure for the Neuroimaging of Cohorts.

This paper provides an overview of CATI, a platform dedicated to multicenter neuroimaging. Initiated by the French Alzheimer's plan (2008-2012), CATI is a research project called on to provide service to other projects like an industrial partner. Its core mission is to support the neuroimaging of large populations, providing concrete solutions to the increasing complexity involved in such projects by bringing together a service infrastructure, the know-how of its expert academic teams and a large-scale, harmonized network of imaging facilities. CATI aims to make data sharing across studies easier and promotes sharing as much as possible. In the last 4 years, CATI has assisted the clinical community by taking charge of 35 projects so far and has emerged as a recognized actor at the national and international levels.

A New Computational Model for Neuro-Glio-Vascular Coupling: Astrocyte Activation Can Explain Cerebral Blood Flow Nonlinear Response to Interictal Events.

Developing a clear understanding of the relationship between cerebral blood flow (CBF) response and neuronal activity is of significant importance because CBF increase is essential to the health of neurons, for instance through oxygen supply. This relationship can be investigated by analyzing multimodal (fMRI, PET, laser Doppler…) recordings. However, the important number of intermediate (non-observable) variables involved in the underlying neurovascular coupling makes the discovery of mechanisms all the more difficult from the sole multimodal data. We present a new computational model developed at the population scale (voxel) with physiologically relevant but simple equations to facilitate the interpretation of regional multimodal recordings. This model links neuronal activity to regional CBF dynamics through neuro-glio-vascular coupling. This coupling involves a population of glial cells called astrocytes via their role in neurotransmitter (glutamate and GABA) recycling and their impact on neighboring vessels. In epilepsy, neuronal networks generate epileptiform discharges, leading to variations in astrocytic and CBF dynamics. In this study, we took advantage of these large variations in neuronal activity magnitude to test the capacity of our model to reproduce experimental data. We compared simulations from our model with isolated epileptiform events, which were obtained in vivo by simultaneous local field potential and laser Doppler recordings in rats after local bicuculline injection. We showed a predominant neuronal contribution for low level discharges and a significant astrocytic contribution for higher level discharges. Besides, neuronal contribution to CBF was linear while astrocytic contribution was nonlinear. Results thus indicate that the relationship between neuronal activity and CBF magnitudes can be nonlinear for isolated events and that this nonlinearity is due to astrocytic activity, highlighting the importance of astrocytes in the interpretation of regional recordings.

Large-Scale Functional Networks Identified from Resting-State EEG Using Spatial ICA.

Several methods have been applied to EEG or MEG signals to detect functional networks. In recent works using MEG/EEG and fMRI data, temporal ICA analysis has been used to extract spatial maps of resting-state networks with or without an atlas-based parcellation of the cortex. Since the links between the fMRI signal and the electromagnetic signals are not fully established, and to avoid any bias, we examined whether EEG alone was able to derive the spatial distribution and temporal characteristics of functional networks. To do so, we propose a two-step original method: 1) An individual multi-frequency data analysis including EEG-based source localisation and spatial independent component analysis, which allowed us to characterize the resting-state networks. 2) A group-level analysis involving a hierarchical clustering procedure to identify reproducible large-scale networks across the population. Compared with large-scale resting-state networks obtained with fMRI, the proposed EEG-based analysis revealed smaller independent networks thanks to the high temporal resolution of EEG, hence hierarchical organization of networks. The comparison showed a substantial overlap between EEG and fMRI networks in motor, premotor, sensory, frontal, and parietal areas. However, there were mismatches between EEG-based and fMRI-based networks in temporal areas, presumably resulting from a poor sensitivity of fMRI in these regions or artefacts in the EEG signals. The proposed method opens the way for studying the high temporal dynamics of networks at the source level thanks to the high temporal resolution of EEG. It would then become possible to study detailed measures of the dynamics of connectivity.

Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

OBJECTIVE: To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord. MATERIALS AND METHODS: A semi-automated double threshold-based method (DTbM) was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM), threshold-based method (TbM) and manual outlining (ground truth). Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59), a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map. RESULTS: Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC) was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction. CONCLUSION: A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Validation of a semiautomated spinal cord segmentation method.

PURPOSE: To validate semiautomated spinal cord segmentation in healthy subjects and patients with neurodegenerative diseases and trauma. MATERIALS AND METHODS: Forty-nine healthy subjects, as well as 29 patients with amyotrophic lateral sclerosis, 19 with spinal muscular atrophy, and 14 with spinal cord injuries were studied. Cord area was measured from T2 -weighted 3D turbo spin echo images (cord levels from C2 to T9) using the semiautomated segmentation method of Losseff et al (Brain [1996] 119(Pt 3):701-708), compared with manual segmentation. Reproducibility was evaluated using the inter- and intraobserver coefficient of variation (CoV). Accuracy was assessed using the Dice similarity coefficient (DSC). Robustness to initialization was assessed by simulating modifications to the contours drawn manually prior to segmentation. RESULTS: Mean interobserver CoV was 4.00% for manual segmentation (1.90% for Losseff's method) in the cervical region and 5.62% (respectively 2.19%) in the thoracic region. Mean intraobserver CoV was 2.34% for manual segmentation (1.08% for Losseff's method) in the cervical region and 2.35% (respectively 1.34%) in the thoracic region. DSC was high (0.96) in both cervical and thoracic regions. DSC remained higher than 0.8 even when modifying initial contours by 50%. CONCLUSION: The semiautomated segmentation method showed high reproducibility and accuracy in measuring spinal cord area.

Multi-parametric spinal cord MRI as potential progression marker in amyotrophic lateral sclerosis.

OBJECTIVE: To evaluate multimodal MRI of the spinal cord in predicting disease progression and one-year clinical status in amyotrophic lateral sclerosis (ALS) patients. MATERIALS AND METHODS: After a first MRI (MRI1), 29 ALS patients were clinically followed during 12 months; 14/29 patients underwent a second MRI (MRI2) at 11±3 months. Cross-sectional area (CSA) that has been shown to be a marker of lower motor neuron degeneration was measured in cervical and upper thoracic spinal cord from T2-weighted images. Fractional anisotropy (FA), axial/radial/mean diffusivities (λ⊥, λ//, MD) and magnetization transfer ratio (MTR) were measured within the lateral corticospinal tract in the cervical region. Imaging metrics were compared with clinical scales: Revised ALS Functional Rating Scale (ALSFRS-R) and manual muscle testing (MMT) score. RESULTS: At MRI1, CSA correlated significantly (P<0.05) with MMT and arm ALSFRS-R scores. FA correlated significantly with leg ALFSRS-R scores. One year after MRI1, CSA predicted (P<0.01) arm ALSFSR-R subscore and FA predicted (P<0.01) leg ALSFRS-R subscore. From MRI1 to MRI2, significant changes (P<0.01) were detected for CSA and MTR. CSA rate of change (i.e. atrophy) highly correlated (P<0.01) with arm ALSFRS-R and arm MMT subscores rate of change. CONCLUSION: Atrophy and DTI metrics predicted ALS disease progression. Cord atrophy was a better biomarker of disease progression than diffusion and MTR. Our study suggests that multimodal MRI could provide surrogate markers of ALS that may help monitoring the effect of disease-modifying drugs.

Combining spatial independent component analysis with regression to identify the subcortical components of resting-state FMRI functional networks.

Functional brain networks are sets of cortical, subcortical, and cerebellar regions whose neuronal activities are synchronous over multiple time scales. Spatial independent component analysis (sICA) is a widespread approach that is used to identify functional networks in the human brain from functional magnetic resonance imaging (fMRI) resting-state data, and there is now a general agreement regarding the cortical regions involved in each network. It is well known that these cortical regions are preferentially connected with specific subcortical functional territories; however, subcortical components (SC) have not been observed whether in a robust or in a reproducible manner using sICA. This article presents a new method to analyze resting-state fMRI data that enables robust and reproducible association of subcortical regions with well-known patterns of cortical regions. The approach relies on the hypothesis that the time course in subcortical regions is similar to that in cortical regions belonging to the same network. First, sICA followed by hierarchical clustering is performed on cortical time series to extract group functional cortical networks. Second, these networks are complemented with related subcortical areas based on the similarity of their time courses, using an individual general linear model and a random-effect group analysis. Two independent resting-state fMRI datasets were processed, and the SC of both datasets overlapped by 69% to 99% depending on the network, showing the reproducibility and the robustness of our approach. The relationship between SC and functional cortical networks was consistent with functional territories (sensorimotor, associative, and limbic) from an immunohistochemical atlas of the basal ganglia.

Specific and evolving resting-state network alterations in post-concussion syndrome following mild traumatic brain injury.

Post-concussion syndrome has been related to axonal damage in patients with mild traumatic brain injury, but little is known about the consequences of injury on brain networks. In the present study, our aim was to characterize changes in functional brain networks following mild traumatic brain injury in patients with post-concussion syndrome using resting-state functional magnetic resonance imaging data. We investigated 17 injured patients with persistent post-concussion syndrome (under the DSM-IV criteria) at 6 months post-injury compared with 38 mild traumatic brain injury patients with no post-concussion syndrome and 34 healthy controls. All patients underwent magnetic resonance imaging examinations at the subacute (1-3 weeks) and late (6 months) phases after injury. Group-wise differences in functional brain networks were analyzed using graph theory measures. Patterns of long-range functional networks alterations were found in all mild traumatic brain injury patients. Mild traumatic brain injury patients with post-concussion syndrome had greater alterations than patients without post-concussion syndrome. In patients with post-concussion syndrome, changes specifically affected temporal and thalamic regions predominantly at the subacute stage and frontal regions at the late phase. Our results suggest that the post-concussion syndrome is associated with specific abnormalities in functional brain network that may contribute to explain deficits typically observed in PCS patients.

Correction: Specific and Evolving Resting-State Network Alterations in Post-Concussion Syndrome Following Mild Traumatic Brain Injury.

[This corrects the article DOI: 10.1371/journal.pone.0065470.].