Leriglitazone halts disease progression in adult patients with early cerebral adrenoleukodystrophy.

Cerebral adrenoleukodystrophy (CALD) is an X-linked rapidly progressive demyelinating disease leading to death usually within a few years. The standard of care is hematopoietic stem cell transplantation (HSCT), but many men are not eligible due to age, absence of a matched donor, or lesions of the corticospinal tracts (CST). Based on the ADVANCE study showing that leriglitazone decreases the occurrence of CALD, we treated 13 adult CALD patients (19-67 years of age) either not eligible to HSCT (n= 8) or awaiting HSCT (n= 5). Patients were monitored every 3 months with standardized neurological scores, plasma biomarkers and brain MRI comprising lesion volumetrics and diffusion tensor imaging. The disease stabilized clinically and radiologically in 10 patients with up to 2 years of follow-up. Five patients presented with gadolinium enhancing CST lesions that all turned gadolinium negative and, remarkably, regressed in four patients. Plasma neurofilament light chain levels stabilized in all 10 patients and correlated with lesion load. The two patients who continued to deteriorate were over 60 years of age with prominent cognitive impairment. One patient rapidly died from Covid19. These results suggest that leriglitazone can arrest disease progression in adults with early-stage CALD and may be an alternative treatment to HSCT.

Description and Outcome of Severe Hypoglycemic Encephalopathy in the Intensive Care Unit.

BACKGROUND: Disorders of consciousness due to severe hypoglycemia are rare but challenging to treat. The aim of this retrospective cohort study was to describe our multimodal neurological assessment of patients with hypoglycemic encephalopathy hospitalized in the intensive care unit and their neurological outcomes. METHODS: Consecutive patients with disorders of consciousness related to hypoglycemia admitted for neuroprognostication from 2010 to 2020 were included. Multimodal neurological assessment included electroencephalography, somatosensory and cognitive event-related potentials, and morphological and quantitative magnetic resonance imaging (MRI) with quantification of fractional anisotropy. Neurological outcomes at 28 days, 3 months, 6 months, 1 year, and 2 years after hypoglycemia were retrieved. RESULTS: Twenty patients were included. After 2 years, 75% of patients had died, 5% remained in a permanent vegetative state, 10% were in a minimally conscious state, and 10% were conscious but with severe disabilities (Glasgow Outcome Scale-Extended scores 3 and 4). All patients showed pathologic electroencephalography findings with heterogenous patterns. Morphological brain MRI revealed abnormalities in 95% of patients, with various localizations including cortical atrophy in 65% of patients. When performed, quantitative MRI showed decreased fractional anisotropy affecting widespread white matter tracts in all patients. CONCLUSIONS: The overall prognosis of patients with severe hypoglycemic encephalopathy was poor, with only a small fraction of patients who slowly improved after intensive care unit discharge. Of note, patients who did not improve during the first 6 months did not recover consciousness. This study suggests that a multimodal approach capitalizing on advanced brain imaging and bedside electrophysiology techniques could improve diagnostic and prognostic performance in severe hypoglycemic encephalopathy.

Synergistic Role of Quantitative Diffusion Magnetic Resonance Imaging and Structural Magnetic Resonance Imaging in Predicting Outcomes After Traumatic Brain Injury.

OBJECTIVE: This study aimed to assess if quantitative diffusion magnetic resonance imaging analysis would improve prognostication of individual patients with severe traumatic brain injury. METHODS: We analyzed images of 30 healthy controls to extract normal fractional anisotropy ranges along 18 white-matter tracts. Then, we analyzed images of 33 patients, compared their fractional anisotropy values with normal ranges extracted from controls, and computed severity of injury to white-matter tracts. We also asked 2 neuroradiologists to rate severity of injury to different brain regions on fluid-attenuated inversion recovery and susceptibility-weighted imaging. Finally, we built 3 models: (1) fed with neuroradiologists' ratings, (2) fed with white-matter injury measures, and (3) fed with both input types. RESULTS: The 3 models respectively predicted survival at 1 year with accuracies of 70%, 73%, and 88%. The accuracy with both input types was significantly better (P < 0.05). CONCLUSIONS: Quantifying severity of injury to white-matter tracts complements qualitative imaging findings and improves outcome prediction in severe traumatic brain injury.

Habituation of auditory startle reflex is a new sign of minimally conscious state.

Neurological examination of non-communicating patients relies on a few decisive items that enable the crucial distinction between vegetative state (VS)-also coined unresponsive wakefulness syndrome (UWS)-and minimally conscious state. Over the past 10 years, this distinction has proven its diagnostic value as well as its important prognostic value on consciousness recovery. However, clinicians are currently limited by three factors: (i) the current behavioural repertoire of minimally conscious state items is limited and restricted to a few cognitive domains in the goldstandard revised version of the Coma Recovery Scale; (ii) a proportion of ∼15-20% clinically VS/UWS patients are actually in a richer state than VS/UWS as evidenced by functional brain imaging; and (iii) the neurophysiological and cognitive interpretation of each minimally conscious state item is still unclear and debated. In the current study we demonstrate that habituation of the auditory startle reflex (hASR) tested at bedside constitutes a novel, simple and powerful behavioural sign that can accurately distinguish minimally conscious state from VS/UWS. In addition to enlarging the minimally conscious state items repertoire, and therefore decreasing the low sensitivity of current behavioural measures, we also provide an original and rigorous description of the neurophysiological basis of hASR through a combination of functional (high density EEG and 18F-fluorodeoxyglucose PET imaging) and structural (diffusion tensor imaging MRI) measures. We show that preservation of hASR is associated with the functional and structural integrity of a brain-scale fronto-parietal network, including prefrontal regions related to control of action and inhibition, and meso-parietal areas associated with minimally conscious and conscious states. Lastly, we show that hASR predicts 6-month improvement of consciousness. Taken together, our results show that hASR is a cortically-mediated behaviour, and suggest that it could be a new clinical item to clearly and accurately identify non-communicating patients who are in the minimally conscious state.

A strategy for multimodal data integration: application to biomarkers identification in spinocerebellar ataxia.

The growing number of modalities (e.g. multi-omics, imaging and clinical data) characterizing a given disease provides physicians and statisticians with complementary facets reflecting the disease process but emphasizes the need for novel statistical methods of data analysis able to unify these views. Such data sets are indeed intrinsically structured in blocks, where each block represents a set of variables observed on a group of individuals. Therefore, classical statistical tools cannot be applied without altering their organization, with the risk of information loss. Regularized generalized canonical correlation analysis (RGCCA) and its sparse generalized canonical correlation analysis (SGCCA) counterpart are component-based methods for exploratory analyses of data sets structured in blocks of variables. Rather than operating sequentially on parts of the measurements, the RGCCA/SGCCA-based integrative analysis method aims at summarizing the relevant information between and within the blocks. It processes a priori information defining which blocks are supposed to be linked to one another, thus reflecting hypotheses about the biology underlying the data blocks. It also requires the setting of extra parameters that need to be carefully adjusted.Here, we provide practical guidelines for the use of RGCCA/SGCCA. We also illustrate the flexibility and usefulness of RGCCA/SGCCA on a unique cohort of patients with four genetic subtypes of spinocerebellar ataxia, in which we obtained multiple data sets from brain volumetry and magnetic resonance spectroscopy, and metabolomic and lipidomic analyses. As a first step toward the extraction of multimodal biomarkers, and through the reduction to a few meaningful components and the visualization of relevant variables, we identified possible markers of disease progression.

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.

Early Functional Connectome Integrity and 1-Year Recovery in Comatose Survivors of Cardiac Arrest.

Purpose To assess whether early brain functional connectivity is associated with functional recovery 1 year after cardiac arrest (CA). Materials and Methods Enrolled in this prospective multicenter cohort were 46 patients who were comatose after CA. Principal outcome was cerebral performance category at 12 months, with favorable outcome (FO) defined as cerebral performance category 1 or 2. All participants underwent multiparametric structural and functional magnetic resonance (MR) imaging less than 4 weeks after CA. Within- and between-network connectivity was measured in dorsal attention network (DAN), default-mode network (DMN), salience network (SN), and executive control network (ECN) by using seed-based analysis of resting-state functional MR imaging data. Structural changes identified with fluid-attenuated inversion recovery and diffusion-weighted imaging sequences were analyzed by using validated morphologic scales. The association between connectivity measures, structural changes, and the principal outcome was explored with multivariable modeling. Results Patients underwent MR imaging a mean 12.6 days ± 5.6 (standard deviation) after CA. At 12 months, 11 patients had an FO. Patients with FO had higher within-DMN connectivity and greater anticorrelation between SN and DMN and between SN and ECN compared with patients with unfavorable outcome, an effect that was maintained after multivariable adjustment. Anticorrelation of SN-DMN predicted outcomes with higher accuracy than fluid-attenuated inversion recovery or diffusion-weighted imaging scores (area under the receiver operating characteristic curves, respectively, 0.88, 0.74, and 0.71). Conclusion MR imaging-based measures of cerebral functional network connectivity obtained in the acute phase of CA were independently associated with FO at 1 year, warranting validation as early markers of long-term recovery potential in patients with anoxic-ischemic encephalopathy. © RSNA, 2017.

Treatment with chenodeoxycholic acid in cerebrotendinous xanthomatosis: clinical, neurophysiological, and quantitative brain structural outcomes.

BACKGROUND: Cerebrotendinous xanthomatosis (CTX) is a rare neurodegenerative disease related to sterols metabolism. It affects both central and peripheral nervous systems but treatment with chenodeoxycholic acid (CDCA) has been reported to stabilize clinical scores and improve nerve conduction parameters. Few quantitative brain structural studies have been conducted to assess the effect of CDCA in CTX. METHODS AND RESULTS: We collected retrospectively clinical, neurophysiological, and quantitative brain structural data in a cohort of 14 patients with CTX treated by CDCA over a mean period of 5 years. Plasma cholestanol levels normalized under treatment with CDCA within a few months. We observed a significant clinical improvement in patients up to 25 years old, whose treatment was initiated less than 15 years after the onset of neurological symptoms. Conversely, patients whose treatment was initiated more than 25 years after neurological disease onset continued their clinical deterioration. Eleven patients presented with a length-dependent peripheral neuropathy, whose electrophysiological parameters improved significantly under CDCA. Volumetric analyses in a subset of patients showed no overt volume loss under CDCA. Moreover, diffusion weighted imaging showed improved fiber integrity of the ponto-cerebellar and the internal capsule with CDCA. CDCA was well tolerated in all patients with CTX. CONCLUSION: CDCA may reverse the pathophysiological process in patients with CTX, especially if treatment is initiated early in the disease process. Besides tendon xanthoma, this study stresses the need to consider plasma cholestanol measurement in any patient with infantile chronic diarrhea and/or jaundice, juvenile cataract, learning disability and/or autism spectrum disorder, pyramidal signs, cerebellar syndrome or peripheral neuropathy.

Default mode and task-positive networks connectivity during the N-Back task in remitted depressed patients with or without emotional residual symptoms.

Clinical remission of depression may be associated with emotional residual symptoms. We studied the association of emotional blunting, rumination with neural networks dynamics in remitted depressed patients and cognitive performance during an N-Back task. Twenty-six outpatients in remission of depression (Hamilton Depressive rating scale score <7) performed an N-Back task during fMRI assessment. All patients had been treated by paroxetine for a minimum of 4 months. Two subgroups of patients [Nonemotionally blunted (NEB) = 14 and emotionally blunted (EB) = 12] were determined. To identify functional network maps across participants, the Network Detection using Independent Component Analysis approach was employed. Within and between Task Positive Network (TPN) and Default Mode Network (DMN) connectivity were assessed and related to variability of performance on the N-Back task and rumination. EB and NEB patients were not different for the level of accurate responses at the N-Back. However over the entire working memory task, the negative correlation between DMN and TPN was significantly lower in the EB than NEB group and was differently related to cognitive performance and rumination. The stronger the negative correlation between DMN and TPN was, the less variable the reaction time during 3-Back task in NEB patients. Moreover the greater the negative correlation between DMN and TPN was, the lower the rumination score in EB patients. Emotional blunting may be associated with compromised monitoring of rumination and cognitive functioning in remitted depressed patients through altered cooperation between DMN and TPN. The study suggests clinical remission in depression is associated with biological heterogeneity. Hum Brain Mapp 38:3491-3501, 2017. © 2017 Wiley Periodicals, Inc.

Brain Gray Matter MRI Morphometry for Neuroprognostication After Cardiac Arrest.

OBJECTIVES: We hypothesize that the combined use of MRI cortical thickness measurement and subcortical gray matter volumetry could provide an early and accurate in vivo assessment of the structural impact of cardiac arrest and therefore could be used for long-term neuroprognostication in this setting. DESIGN: Prospective cohort study. SETTING: Five Intensive Critical Care Units affiliated to the University in Toulouse (France), Paris (France), Clermont-Ferrand (France), Liège (Belgium), and Monza (Italy). PATIENTS: High-resolution anatomical T1-weighted images were acquired in 126 anoxic coma patients ("learning" sample) 16 ± 8 days after cardiac arrest and 70 matched controls. An additional sample of 18 anoxic coma patients, recruited in Toulouse, was used to test predictive model generalization ("test" sample). All patients were followed up 1 year after cardiac arrest. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Cortical thickness was computed on the whole cortical ribbon, and deep gray matter volumetry was performed after automatic segmentation. Brain morphometric data were employed to create multivariate predictive models using learning machine techniques. Patients displayed significantly extensive cortical and subcortical brain volumes atrophy compared with controls. The accuracy of a predictive classifier, encompassing cortical and subcortical components, has a significant discriminative power (learning area under the curve = 0.87; test area under the curve = 0.96). The anatomical regions which volume changes were significantly related to patient's outcome were frontal cortex, posterior cingulate cortex, thalamus, putamen, pallidum, caudate, hippocampus, and brain stem. CONCLUSIONS: These findings are consistent with the hypothesis of pathologic disruption of a striatopallidal-thalamo-cortical mesocircuit induced by cardiac arrest and pave the way for the use of combined brain quantitative morphometry in this setting.

Longitudinal changes in functional connectivity of cortico-basal ganglia networks in manifests and premanifest huntington's disease.

Huntington's disease (HD) is a genetic neurological disorder resulting in cognitive and motor impairments. We evaluated the longitudinal changes of functional connectivity in sensorimotor, associative and limbic cortico-basal ganglia networks. We acquired structural MRI and resting-state fMRI in three visits one year apart, in 18 adult HD patients, 24 asymptomatic mutation carriers (preHD) and 18 gender- and age-matched healthy volunteers from the TRACK-HD study. We inferred topological changes in functional connectivity between 182 regions within cortico-basal ganglia networks using graph theory measures. We found significant differences for global graph theory measures in HD but not in preHD. The average shortest path length (L) decreased, which indicated a change toward the random network topology. HD patients also demonstrated increases in degree k, reduced betweeness centrality bc and reduced clustering C. Changes predominated in the sensorimotor network for bc and C and were observed in all circuits for k. Hubs were reduced in preHD and no longer detectable in HD in the sensorimotor and associative networks. Changes in graph theory metrics (L, k, C and bc) correlated with four clinical and cognitive measures (symbol digit modalities test, Stroop, Burden and UHDRS). There were no changes in graph theory metrics across sessions, which suggests that these measures are not reliable biomarkers of longitudinal changes in HD. preHD is characterized by progressive decreasing hub organization, and these changes aggravate in HD patients with changes in local metrics. HD is characterized by progressive changes in global network interconnectivity, whose network topology becomes more random over time. Hum Brain Mapp 37:4112-4128, 2016. © 2016 Wiley Periodicals, Inc.

Hierarchical clustering of brain activity during human nonrapid eye movement sleep.

Consciousness is reduced during nonrapid eye movement (NREM) sleep due to changes in brain function that are still poorly understood. Here, we tested the hypothesis that impaired consciousness during NREM sleep is associated with an increased modularity of brain activity. Cerebral connectivity was quantified in resting-state functional magnetic resonance imaging times series acquired in 13 healthy volunteers during wakefulness and NREM sleep. The analysis revealed a modification of the hierarchical organization of large-scale networks into smaller independent modules during NREM sleep, independently from EEG markers of the slow oscillation. Such modifications in brain connectivity, possibly driven by sleep ultraslow oscillations, could hinder the brain's ability to integrate information and account for decreased consciousness during NREM sleep.

Neuroanatomical basis of paroxysmal sympathetic hyperactivity: a diffusion tensor imaging analysis.

PRIMARY OBJECTIVE: Paroxysmal sympathetic hyperactivity (PSH) is observed in a sub-set of patients with moderate-to-severe traumatic brain injury (TBI). The neuroanatomical basis of PSH is poorly understood. It is hypothesized that PSH is linked to changes in connectivity within the central autonomic network. RESEARCH DESIGN: Retrospective analysis in a sub-set of patients from a multi-centre, prospective cohort study Methods and procedures: Adult patients who were <3 weeks after severe TBI were enrolled and screened for PSH using a standard definition. Patients underwent multimodal MRI, which included quantitative diffusion tensor imaging. MAIN OUTCOMES AND RESULTS: Principal component analysis (PCA) was used to resolve the set of tracts into components. Ability to predict PSH was evaluated via area under the receiver operating characteristic (AUROC) and tree-based classification analyses. Among 102 enrolled patients, 16 met criteria for PSH. The first principle component was significantly associated (p = 0.024, AUROC = 0.867) with PSH status even after controlling for age and admission GCS. In a classification tree analysis, age, GCS and decreased FA in the splenium of the corpus callosum and in the right posterior limb of the internal capsule discriminated PSH vs no PSH with an AUROC of 0.933. CONCLUSIONS: Disconnection involving the posterior corpus callosum and of the posterior limb of the internal capsule may play a role in the pathogenesis or expression of PSH.

Characteristics of the default mode functional connectivity in normal ageing and Alzheimer's disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements.

Cognitive decline in normal ageing and Alzheimer's disease (AD) emerges from functional disruption in the coordination of large-scale brain systems sustaining cognition. Integrity of these systems can be examined by correlation methods based on analysis of resting state functional magnetic resonance imaging (fMRI). Here we investigate functional connectivity within the default mode network (DMN) in normal ageing and AD using resting state fMRI. Images from young and elderly controls, and patients with AD were processed using spatial independent component analysis to identify the DMN. Functional connectivity was quantified using integration and indices derived from graph theory. Four DMN sub-systems were identified: Frontal (medial and superior), parietal (precuneus-posterior cingulate, lateral parietal), temporal (medial temporal), and hippocampal (bilateral). There was a decrease in antero-posterior interactions (lower global efficiency), but increased interactions within the frontal and parietal sub-systems (higher local clustering) in elderly compared to young controls. This decreased antero-posterior integration was more pronounced in AD patients compared to elderly controls, particularly in the precuneus-posterior cingulate region. Conjoint knowledge of integration measures and graph indices in the same data helps in the interpretation of functional connectivity results, as comprehension of one measure improves with understanding of the other. The approach allows for complete characterisation of connectivity changes and could be applied to other resting state networks and different pathologies.

Brain networks disconnection in early multiple sclerosis cognitive deficits: an anatomofunctional study.

Severe cognitive impairment involving multiple cognitive domains can occur early during the course of multiple sclerosis (MS). We investigated resting state functional connectivity changes in large-scale brain networks and related structural damage underlying cognitive dysfunction in patients with early MS. Patients with relapsing MS (3-5 years disease duration) were prospectively assigned to two groups based on a standardized neuropsychological evaluation: (1) cognitively impaired group (CI group, n = 15), with abnormal performances in at least 3 tests; (2) cognitively preserved group (CP group, n = 20) with normal performances in all tests. Patients and age-matched healthy controls underwent a multimodal 3T magnetic resonance imaging (MRI) including anatomical T1 and T2 images, diffusion imaging and resting state functional MRI. Structural MRI analysis revealed that CI patients had a higher white matter lesion load compared to CP and a more severe atrophy in gray matter regions highly connected to networks involved in cognition. Functional connectivity measured by integration was increased in CP patients versus controls in attentional networks (ATT), while integration was decreased in CI patients compared to CP both in the default mode network (DMN) and ATT. An anatomofunctional study within the DMN revealed that functional connectivity was mostly altered between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in CI patients compared to CP and controls. In a multilinear regression model, functional correlation between MPFC and PCC was best predicted by PCC atrophy. Disconnection in the DMN and ATT networks may deprive the brain of compensatory mechanisms required to face widespread structural damage.

White matter changes in comatose survivors of anoxic ischemic encephalopathy and traumatic brain injury: comparative diffusion-tensor imaging study.

PURPOSE: To analyze white matter pathologic abnormalities by using diffusion-tensor (DT) imaging in a multicenter prospective cohort of comatose patients following cardiac arrest or traumatic brain injury (TBI). MATERIALS AND METHODS: Institutional review board approval and informed consent from proxies and control subjects were obtained. DT imaging was performed 5-57 days after insult in 49 cardiac arrest and 40 TBI patients. To control for DT imaging-processing variability, patients' values were normalized to those of 111 control subjects. Automated segmentation software calculated normalized axial diffusivity (λ1) and radial diffusivity (λ⊥) in 19 predefined white matter regions of interest (ROIs). DT imaging variables were compared by using general linear modeling, and side-to-side Pearson correlation coefficients were calculated. P values were corrected for multiple testing (Bonferroni). RESULTS: In central white matter, λ1 differed from that in control subjects in six of seven TBI ROIs and five of seven cardiac arrest ROIs (all P < .01). The λ⊥ differed from that in control subjects in all ROIs in both patient groups (P < .01). In hemispheres, λ1 was decreased compared with that in control subjects in three of 12 TBI ROIs (P < .05) and nine of 12 cardiac arrest ROIs (P < .01). The λ⊥ was increased in all TBI ROIs (P < .01) and in seven of 12 cardiac arrest ROIs (P < .05). Cerebral hemisphere λ1 was lower in cardiac arrest than in TBI in six of 12 ROIs (P < .01), while λ⊥ was higher in TBI than in cardiac arrest in eight of 12 ROIs (P < .01). Diffusivity values were symmetrically distributed in cardiac arrest (P < .001 for side-to-side correlation) but not in TBI patients. CONCLUSION: DT imaging findings are consistent with the known predominance of cerebral hemisphere axonal injury in cardiac arrest and chiefly central myelin injury in TBI. This consistency supports the validity of DT imaging for differentiating axon and myelin damage in vivo in humans.

Functional and structural brain connectivity in disorders of consciousness.

Brain connectivity, allowing information to be shared between distinct cortical areas and thus to be processed in an integrated way, has long been considered critical for consciousness. However, the relationship between functional intercortical interactions and the structural connections thought to underlie them is poorly understood. In the present work, we explore both functional (with an EEG-based metric: the median weighted symbolic mutual information in the theta band) and structural (with a brain MRI-based metric: fractional anisotropy) connectivities in a cohort of 78 patients with disorders of consciousness. Both metrics could distinguish patients in a vegetative state from patients in minimally conscious state. Crucially, we discovered a significant positive correlation between functional and structural connectivities. Furthermore, we showed that this structure-function relationship is more specifically observed when considering structural connectivity within the intra- and inter-hemispheric long-distance cortico-cortical bundles involved in the Global Neuronal Workspace (GNW) theory of consciousness, thus supporting predictions of this model. Altogether, these results support the interest of multimodal assessments of brain connectivity in refining the diagnostic evaluation of patients with disorders of consciousness.

MRI volumetry and diffusion tensor imaging for diagnosis and follow-up of late post-traumatic injuries.

BACKGROUND: Traumatic Brain Injury (TBI) is a major cause of acquired disability and can cause devastating and progressive post-traumatic encephalopathy. TBI is a dynamic condition that continues to evolve over time. A better understanding of the pathophysiology of these late lesions is important for the development of new therapeutic strategies. OBJECTIVES: The primary objective was to compare the ability of fluid-attenuated reversion recovery (FLAIR) and diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) markers to identify participants with a Glasgow outcome scale extended (GOS-E) score of 7-8, up to 10 years after their original TBI. The secondary objective was to study the brain regionalization of DTI markers. Finally, we analyzed the evolution of late-developing brain lesions using repeated MRI images, also taken up to 10 years after the TBI. METHODS: In this retrospective study, participants were included from a cohort of people hospitalized following a severe TBI. Following their discharge, they were followed-up and clinically assessed, including a DTI-MRI scan, between 2012 and 2016. We performed a cross-sectional analysis on 97 participants at a median (IQR) of 5 years (3-6) post-TBI, and a further post-TBI longitudinal analysis over 10 years on a subpopulation (n = 17) of the cohort. RESULTS: Although the area under the curve (AUC) of FLAIR, fractional anisotropy (FA), and mean diffusivity (MD) were not significantly different, only the AUC of FA was statistically greater than 0.5. In addition, only the FA was correlated with clinical outcomes as assessed by GOS-E score (P<10-4). On the cross-sectional analysis, DTI markers allowed study post-TBI white matter lesions by region. In the longitudinal subpopulation analysis, the observed number of brain lesions increased for the first 5 years post-TBI, before stabilizing over the next 5 years. CONCLUSIONS: This study has shown for the first time that post-TBI lesions can present in a two-phase evolution. These results must be confirmed in larger studies. French Data Protection Agency (Commission nationale de l'informatique et des libertés; CNIL) study registration no: 1934708v0.

Parkinson's disease patients show reduced cortical-subcortical sensorimotor connectivity.

Reduced dopamine input to cortical and subcortical brain structures, particularly those in the sensorimotor network, is a hallmark of Parkinson's disease (PD). The extent to which dopamine dysfunction affects connectivity within this and other brain networks remains to be investigated. The purpose of this study was to measure anatomical and functional connectivity in groups of PD patients and controls to determine whether connectivity deficits within the cortico-basal ganglia thalamocortical system could be attributed to PD, particularly in sensorimotor connections. A neuroimaging paradigm involving diffusion-weighted magnetic resonance imaging (MRI) and resting-state functional MRI was implemented in a large cohort of PD patients and control subjects. Probabilistic tractography and functional correlation analyses were performed to map connections between brain structures and to derive indices of connectivity that were then used to compare groups. Anatomical connectivity deficits were demonstrated in PD patients, specifically for sensorimotor connections. Functional deficits were also found in some of the same connections. In addition, functional connectivity was found to increase in associative and limbic connections in PD patients compared with controls. This study lends support to findings regarding the dysfunction of the sensorimotor circuit in PD. As deficits in anatomical and functional connectivity within this circuit were in some cases concordant in PD patients, a possible link between brain structure and function is suggested. Increases in functional connectivity in other cortico-basal ganglia thalamocortical circuits may be indicative of compensatory effects in response to system deficits elsewhere.

Resting state FDG-PET functional connectivity as an early biomarker of Alzheimer's disease using conjoint univariate and independent component analyses.

Imaging cerebral glucose metabolism with positron emission tomography (PET) in Alzheimer's disease (AD) has allowed for improved characterisation of this pathology. Such patterns are typically analysed using either univariate or multivariate statistical techniques. In this work we combined voxel-based group analysis and independent component analysis to extract differential characteristic patterns from PET data of glucose metabolism in a large cohort of normal elderly controls and patients with AD. The patterns were used in conjunction with a support vector machine to discriminate between subjects with mild cognitive impairment (MCI) at risk or not of converting to AD. The method was applied to baseline fluoro-deoxyglucose (FDG)-PET images of subjects from the ADNI database. Our approach achieved improved early detection and differentiation of typical versus pathological metabolic patterns in the MCI population, reaching 80% accuracy (85% sensitivity and 75% specificity) when using selected regions. The method has the potential to assist in the advance diagnosis of Alzheimer's disease, and to identify early in the development of the disease those individuals at high risk of rapid cognitive decline who could be candidates for new therapeutic approaches.