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Background and ObjectivesD-2-hydroxyglutarate (2HG) characterizesIDH-mutant gliomas and can be detected and quantified with edited MRS (MEGA-PRESS). In this study, we investigated the clinical, radiologic, and molecular parameters affecting 2HG levels.MethodsMEGA-PRESS data were acquired in 71 patients with glioma (24 untreated, 47 treated) on a 3 T system. Eighteen patients were followed during cytotoxic (n = 12) or targeted (n = 6) therapy. 2HG was measured in tumor samples using gas chromatography coupled to mass spectrometry (GCMS).ResultsMEGA-PRESS detected 2HG with a sensitivity of 95% in untreated patients and 62% in treated patients. Sensitivity depended on tumor volume (>27 cm3;p= 0.02), voxel coverage (>75%;p= 0.002), and expansive presentation (defined by equal size of T1and FLAIR abnormalities,p= 0.04). 2HG levels were positively correlated withIDH-mutant allelic fraction (p= 0.03) and total choline levels (p< 0.001) and were higher inIDH2-mutant compared withIDH1R132H-mutant and non–R132HIDH1-mutant patients (p= 0.002). In patients receiving IDH inhibitors, 2HG levels decreased within a few days, demonstrating the on-target effect of the drug, but 2HG level decrease did not predict tumor response. Patients receiving cytotoxic treatments showed a slower decrease in 2HG levels, consistent with tumor response and occurring before any tumor volume change on conventional MRI. At progression, 1p/19q codeleted gliomas, but not the non-codeleted, showed detectable in vivo 2HG levels, pointing out to different modes of progression characterizing these 2 entities.DiscussionMEGA-PRESS edited MRS allows in vivo monitoring of 2-hydroxyglutarate, confirming efficacy ofIDHinhibition and suggests different patterns of tumor progression in astrocytomas compared with oligodendrogliomas.

Advances in deep learning can be applied to acute stroke imaging to build powerful and explainable prediction models that could supersede traditionally used biomarkers. We aimed to evaluate the performance and interpretability of a deep learning model based on convolutional neural networks (CNN) in predicting long-term functional outcome with diffusion-weighted imaging (DWI) acquired at day 1 post-stroke. Ischemic stroke patients (n = 322) were included from the ASTER and INSULINFARCT trials as well as the Pitié-Salpêtrière registry. We trained a CNN to predict long-term functional outcome assessed at 3 months with the modified Rankin Scale (dichotomized as good [mRS ≤ 2] vs. poor [mRS ≥ 3]) and compared its performance to two logistic regression models using lesion volume and ASPECTS. The CNN contained an attention mechanism, which allowed to visualize the areas of the brain that drove prediction. The deep learning model yielded a significantly higher area under the curve (0.83 95%CI [0.78–0.87]) than lesion volume (0.78 [0.73–0.83]) and ASPECTS (0.77 [0.71–0.83]) (p

Cerebellum is a key structure for functional motor recovery after stroke. Enhancing the cerebello-motor pathway by paired associative stimulation (PAS) might improve upper limb function. Here, we conducted a randomized, double-blind, sham-controlled pilot trial investigating the efficacy of a 5-day treatment of cerebello-motor PAS coupled with physiotherapy for promoting upper limb motor function compared to sham stimulation. The secondary objectives were to determine in the active treated group (i) whether improvement of upper limb motor function was associated with changes in corticospinal excitability or changes in functional activity in the primary motor cortex and (ii) whether improvements were correlated to the structural integrity of the input and output pathways. To that purpose, hand dexterity and maximal grip strength were assessed along with TMS recordings and multimodal magnetic resonance imaging, before the first treatment, immediately after the last one and a month later. Twenty-seven patients were analyzed. Cerebello-motor PAS was effective compared to sham in improving hand dexterity (p: 0.04) but not grip strength. This improvement was associated with increased activation in the ipsilesional primary motor cortex (p: 0.04). Moreover, the inter-individual variability in clinical improvement was partly explained by the structural integrity of the afferent (p: 0.06) and efferent pathways (p: 0.02) engaged in this paired associative stimulation (i.e., cortico-spinal and dentato-thalamo-cortical tracts). In conclusion, cerebello-motor-paired associative stimulation combined with physiotherapy might be a promising approach to enhance upper limb motor function after stroke. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT 02284087. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13311-022-01205-y.

Background and ObjectivesThe main culprit gene for paroxysmal kinesigenic dyskinesia, characterized by brief and recurrent attacks of involuntary movements, is PRRT2. The location of the primary dysfunction associated with paroxysmal dyskinesia remains a matter of debate and may vary depending on the etiology. While striatal dysfunction has often been implicated in these patients, evidence from preclinical models indicates that the cerebellum could also play a role. We aimed to investigate the role of the cerebellum in the pathogenesis of PRRT2-related dyskinesia in humans.MethodsWe enrolled 22 consecutive right-handed patients with paroxysmal kinesigenic dyskinesia with a pathogenic variant of PRRT2 and their matched controls. Participants underwent a multimodal neuroimaging protocol. We recorded anatomic and diffusion-weighted MRI, as well as resting-state fMRI, during which we tested the aftereffects of sham and repetitive transcranial magnetic stimulation applied to the cerebellum on endogenous brain activity. We quantified the structural integrity of gray matter using voxel-based morphometry, the structural integrity of white matter using fixel-based analysis, and the strength and direction of functional cerebellar connections using spectral dynamic causal modeling.ResultsPatients with PRRT2 had decreased gray matter volume in the cerebellar lobule VI and in the medial prefrontal cortex, microstructural alterations of white matter in the cerebellum and along the tracts connecting the cerebellum to the striatum and the cortical motor areas, and dysfunction of cerebellar motor pathways to the striatum and the cortical motor areas, as well as abnormal communication between the associative cerebellum (Crus I) and the medial prefrontal cortex. Cerebellar stimulation modulated communication within the motor and associative cerebellar networks and tended to restore this communication to the level observed in healthy controls.DiscussionPatients with PRRT2-related dyskinesia have converging structural alterations of the motor cerebellum and related pathways with a dysfunction of cerebellar output toward the cerebello-thalamo-striato-cortical network. We hypothesize that abnormal cerebellar output is the primary dysfunction in patients with a PRRT2 pathogenic variant, resulting in striatal dysregulation and paroxysmal dyskinesia. More broadly, striatal dysfunction in paroxysmal dyskinesia might be secondary to aberrant cerebellar output transmitted by thalamic relays in certain disorders.Trial Registration Information:ClinicalTrials.gov identifier: NCT03481491.

ObjectivesThe classic Braak neuropathologic staging model in Parkinson disease (PD) suggests that brain lesions progress from the medulla oblongata to the cortex. An alternative model in which neurodegeneration first occurs in the cortex has also been proposed. These 2 models may correspond to different patient phenotypes. To test these 2 models and to investigate whether they were influenced by the presence of REM sleep behavior disorder (RBD), we used multimodal MRI and partial least squares path modeling (PLS-PM) assuming that patients with RBD followed distinct neurodegeneration pattern.MethodsFifty-four patients with PD (34 with RBD) and 25 healthy volunteers were scanned with T1-weighted, diffusion tensor, and neuromelanin-sensitive imaging. Volume, signal, and mean, axial, and radial diffusivities were calculated in brainstem, basal forebrain, and cortical regions. PLS-PM, estimating a network of causal relationships between blocks of variables, was used to build and test an analytical model based on Braak staging. The overall quality of the model was assessed with goodness of fit coefficient (Gof).ResultsPLS-PM was run on patients with PD with RBD and without RBD separately. In PD with RBD, a brainstem-to-cortex model had significant Gof (0.71,p= 0.01), whereas a cortex-to-brainstem model did not. In contrast, in patients with PD without RBD, the brainstem-to-cortex model was not significant (Gof = 0.64,p= 0.27), and the cortex-to-brainstem model was highly significant (Gof = 0.72,p= 0.008).ConclusionsWith the PLS-PM imaging–based model, the neurodegeneration pattern of patients with PD with RBD was consistent with the Braak brainstem-to-cortex model, whereas that of patients without RBD followed the cortex-to-brainstem model.

This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson’s disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson’s disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson’s disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson’s disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra’s morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson’s disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.

International audience; Purpose: Performing simultaneous quantitative MRI at ultra-high field is challenging, as B0 and B1 + heterogeneities as well as Specific Absorption Rate increase. Too large deviations of flip angle from the target can induce biases and impair signal-to-noise ratio in the quantification process. In this work, we use calibration-free parallel transmission, a dedicated pulse sequence parameter optimization and signal fitting to recover 3D proton density, flip angle, T1 and T2 maps over the whole brain, in a clinically suitable time. Methods: Eleven optimized contrasts were acquired with an unbalanced Steady-State Free Precession sequence by varying flip angle amplitude and radiofrequency phase cycling increment, at a 1.0x1.0x3.0mm 3 resolution. Acquisition time was of 16min36sec for the whole brain. Parallel transmission and Universal Pulses were used to mitigate B1 + heterogeneity to improve the results' reliability over six healthy volunteers (3 females/males, age 22.6±2.7 years-old). Quantification of the physical parameters was performed by fitting acquired contrasts to the simulated ones using the Bloch-Torrey equations with a realistic diffusion coefficient. Results: Whole-brain 3D maps of effective flip angle, PD and relaxation times were estimated. Parallel transmission improved the robustness of the results at 7T. Results were in accordance with literature and with measurements from standard methods. Conclusion: These preliminary results show robust PD, FA, T1 and T2 map retrieval. Other parameters, such as Apparent Diffusion Coefficient, could be assessed. With further optimization in the acquisition, scan time could be reduced and spatial resolution increased to bring this multi-parametric quantification method to clinical research routine at 7-tesla.

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time-consuming, error-prone, and unsuitable for combining datasets from many sources. Here we showcasefMRIPrep(http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure (BIDS) to standardize both the input datasets —MRI data as stored by the scanner— and the outputs —data ready for modeling and analysis—,fMRIPrepis capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity offMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

D-2-hydroxyglutarate (2HG) characterizesMEGA-PRESS data were acquired in 71 patients with glioma (24 untreated, 47 treated) on a 3 T system. Eighteen patients were followed during cytotoxic (n = 12) or targeted (n = 6) therapy. 2HG was measured in tumor samples using gas chromatography coupled to mass spectrometry (GCMS).MEGA-PRESS detected 2HG with a sensitivity of 95% in untreated patients and 62% in treated patients. Sensitivity depended on tumor volume (27 cmMEGA-PRESS edited MRS allows in vivo monitoring of 2-hydroxyglutarate, confirming efficacy of

Funder: Fondation pour la Recherche M��dicale (Foundation for Medical Research in France); doi: https://doi.org/10.13039/501100002915, Reward sensitivity has been suggested as one of the central pathophysiological mechanisms in Tourette disorder. However, the subjective valuation of a reward by introduction of delay has received little attention in Tourette disorder, even though it has been suggested as a trans-diagnostic feature of numerous neuropsychiatric disorders. We aimed to assess delay discounting in Tourette disorder and to identify its brain functional correlates. We evaluated delayed discounting and its brain functional correlates in a large group of 54 Tourette disorder patients and 31 healthy controls using a data-driven approach. We identified a subgroup of 29 patients with steeper reward discounting, characterised by a higher burden of impulse-control disorders and a higher level of general impulsivity compared to patients with normal behavioural performance or to controls. Reward discounting was underpinned by resting-state activity of a network comprising the orbito-frontal, cingulate, pre-supplementary motor area, temporal and insular cortices, as well as ventral striatum and hippocampus. Within this network, (i) lower connectivity of pre-supplementary motor area with ventral striatum predicted a higher impulsivity and a steeper reward discounting and (ii) a greater connectivity of pre-supplementary motor area with anterior insular cortex predicted steeper reward discounting and more severe tics. Overall, our results highlight the heterogeneity of the delayed reward processing in Tourette disorder, with steeper reward discounting being a marker of burden in impulsivity and impulse control disorders, and the pre-supplementary motor area being a hub region for the delay discounting, impulsivity and tic severity.

Background Progressive supranuclear palsy (PSP) is a neurodegenerative clinically heterogeneous disorder, formal diagnosis being based on postmortem histological brain examination. Objective We aimed to perform a precise in vivo staging of neurodegeneration in PSP using quantitative multimodal MRI. The ability of MRI biomarkers to differentiate PSP from PD was also evaluated. Methods Eleven PSP patients were compared to 26 age-matched healthy controls and 51 PD patients. Images were acquired at 3 Tesla (three-dimensional T1 -weighted, diffusion tensor, and neuromelanin-sensitive images) and 7 Tesla (three-dimensional-T2 * images). Regions of interest included the cortical areas, hippocampus, amygdala, basal ganglia, basal forebrain, brainstem nuclei, dentate nucleus, and cerebellum. Volumes, mean diffusivity, and fractional anisotropy were measured. In each region, a threshold value for group categorization was calculated, and four grades of change (0-3) were determined. Results PSP patients showed extensive volume decreases and diffusion changes in the midbrain, SN, STN, globus pallidus, basal forebrain, locus coeruleus, pedunculopontine nucleus, and dentate nucleus, in close agreement with the degrees of impairment in histological analyses. The predictive factors for the separation of PSP and healthy controls were, in descending order, the neuromelanin-based SN volume; midbrain fractional anisotropy; volumes of the midbrain, globus pallidus, and putamen; and fractional anisotropy in the locus coeruleus. The best predictors for separating PSP from PD were the neuromelanin-based volume in the SN, fractional anisotropy in the pons, volumes of the midbrain and globus pallidus, and fractional anisotropy in the basal forebrain. Conclusions These results suggest that it is possible to evaluate brain neurodegeneration in PSP noninvasively, even in small brainstem nuclei, in close agreement with previously published histological data. © 2019 International Parkinson and Movement Disorder Society.

BACKGROUND: Abnormal sensory processing, including temporal discrimination threshold, has been described in various dystonic syndromes. OBJECTIVE: To investigate visual sensory processing in DYT-SGCE and identify its structural correlates. METHODS: DYT-SGCE patients without DBS (DYT-SGCE-non-DBS) and with DBS (DYT-SGCE-DBS) were compared to healthy volunteers in three tasks: a temporal discrimination threshold, a movement orientation discrimination, and movement speed discrimination. Response times attributed to accumulation of sensory visual information were computationally modelized, with mu parameter indicating sensory mean growth rate. We also identified the structural correlates of behavioral performance for temporal discrimination threshold. RESULTS: Twenty-four DYT-SGCE-non-DBS, 13 DYT-SGCE-DBS, and 25 healthy volunteers were included in the study. In DYT-SGCE-DBS, the discrimination threshold was higher in the temporal discrimination threshold (P = 0.024), with no difference among the groups in other tasks. The sensory mean growth rate (mu) was lower in DYT-SGCE in all three tasks (P < 0.01), reflecting a slower rate of sensory accumulation for the visual information in these patients independent of DBS. Structural imaging analysis showed a thicker left primary visual cortex (P = 0.001) in DYT-SGCE-non-DBS compared to healthy volunteers, which also correlated with lower mu in temporal discrimination threshold (P = 0.029). In DYT-SGCE-non-DBS, myoclonus severity also correlated with a lower mu in the temporal discrimination threshold task (P = 0.048) and with thicker V1 on the left (P = 0.022). CONCLUSION: In DYT-SGCE, we showed an alteration of the visual sensory processing in the temporal discrimination threshold that correlated with myoclonus severity and structural changes in the primary visual cortex. (c) 2019 International Parkinson and Movement Disorder Society.

Background and Purpose— Early severity of stroke symptoms—especially in mild-to-severe stroke patients—are imperfect predictors of long-term motor and aphasia outcome. Motor function and language processing heavily rely on the preservation of important white matter fasciculi in the brain. Axial diffusivity (AD) from the diffusion tensor imaging model has repeatedly shown to accurately reflect acute axonal damage and is thus optimal to probe the integrity of important white matter bundles and their relationship with long-term outcome. Our aim was to investigate the independent prognostic value of the AD of white matter tracts in the motor and language network evaluated at 24 hours poststroke for motor and aphasia outcome at 3 months poststroke. Methods— Seventeen (motor cohort) and 28 (aphasia cohort) thrombolyzed patients with initial mild-to-severe stroke underwent a diffusion tensor imaging sequence at 24 hours poststroke. Motor and language outcome were evaluated at 3 months poststroke with a composite motor score and the aphasia handicap scale. We first used stepwise regression to determine which classic (age, initial motor or aphasia severity, and lesion volume) and imaging (ratio of affected/unaffected AD of motor and language fasciculi) factors were related to outcome. Second, to determine the specificity of our a priori choices of fasciculi, we performed voxel-based analyses to determine if the same, additional, or altogether new regions were associated with long-term outcome. Results— The ratio of AD in the corticospinal tract was the sole predictor of long-term motor outcome, and the ratio of AD in the arcuate fasciculus—along with age and initial aphasia severity—was an independent predictor of 3-month aphasia outcome. White matter regions overlapping with these fasciculi naturally emerged in the corresponding voxel-based analyses. Conclusions— AD of the corticospinal tract and arcuate fasciculus are effective biomarkers of long-term motor and aphasia outcome, respectively.

Background Medial prefrontal cortex (MPFC) activity during self-referential processing has been associated with rumination and found aberrant in depression. We investigated whether this aberrant activity reflects a trait marker that persists in remitted patients. Methods Twenty-five patients fully remitted from major depression for at least 6 months, and 29 matched healthy controls were scanned with fMRI while presented with personality trait words in two conditions: Self condition asked whether the trait described themselves; General condition asked whether the trait was generally desirable. Contrasts-of-interest were examined in a factorial model and rumination correlates were examined in 2-sample t-tests with Ruminative Response Style score as covariate. All findings were reported at a conservative p Results Self-referential processing increased anterior cortical midline activity to a similar extent in both groups. Dorsal anterior cingulate cortex (MNI(x,y,z) = -12,20,26) and dorsal MPFC (MNI(x,y,z) = -6,46,40) activity during self-referential processing was positively associated with rumination in healthy control subjects and negatively associated with rumination in remitted patients. Limitations A longitudinal design tracking the relationship between rumination and MPFC activity would have aided the interpretation of our findings as to whether high ruminators are exhibiting an adaptive process to maintain remission or whether it represents a maladaptive process considering that high ruminators have an increased vulnerability for relapse. Conclusions The association between increased anterior cortical midline activity during self-referential processing and rumination differentiated healthy controls from formerly depressed patients. Self-referential neural processing during remission from depression may depend on the cognitive tendencies to ruminate.

Background Codeletion of chromosome arms 1p and 19q (1p/19q codeletion) highly benefits diagnosis and prognosis in gliomas. In this study, we investigated the effect of 1p/19q codeletion on cancer cell metabolism and evaluated possible metabolic targets for tailored therapies. Methods We combined in vivo 1H (proton) magnetic resonance spectroscopy (MRS) measurements in human gliomas with the analysis of a series of standard amino acids by liquid chromatography-mass spectroscopy (LC-MS) in human glioma biopsies. Sixty-five subjects with low-grade glioma were included in the study: 31 underwent the MRI/MRS examination, 47 brain tumor tissue samples were analyzed with LC-MS, and 33 samples were analyzed for gene expression with quantitative PCR. Additionally, we performed metabolic tracer experiments in cell models with 1p deletion. Results We report the first in vivo detection of cystathionine by MRS in 1p/19q codeleted gliomas. Selective accumulation of cystathionine was observed in codeleted gliomas in vivo, in brain tissue samples, as well as in cells harboring heterozygous deletions for serine- and cystathionine-pathway genes located on 1p: phosphoglycerate dehydrogenase (PHGDH) and cystathionine gamma-lyase (CTH). Quantitative PCR analyses showed 40-50% lower expression of both PHGDH and CTH in 1p/19q codeleted gliomas compared with their non-codeleted counterparts. Conclusions Our results provide strong evidence of a selective vulnerability of codeleted gliomas to serine and glutathione depletion and point to cystathionine as a possible noninvasive marker of treatment response.

The main culprit gene for paroxysmal kinesigenic dyskinesia, characterized by brief and recurrent attacks of involuntary movements, isWe enrolled 22 consecutive right-handed patients with paroxysmal kinesigenic dyskinesia with a pathogenic variant ofPatients withPatients withClinicalTrials.gov identifier: NCT03481491.

International audience; Current quantification methods of 123I-FP-CIT SPECT rely on anatomical parcellation of the striatum. We propose here to implement a new method based on MRI segmentation and functional atlas of the basal ganglia (MR-ATLAS) that could provide a reliable quantification within the sensorimotor, associative, and limbic territories of the striatum. Patients with Parkinson’s disease (PD), idiopathic rapid eye movement sleep behavioral disorder (iRBD), and healthy controls underwent 123I-FP-CIT SPECT, MRI, motor, and cognitive assessments. SPECT data were corrected for partial volume effects and registered to a functional atlas of the striatum to allow quantification in every functional region of the striatum (nucleus accumbens, limbic, associative, and sensorimotor parts of the striatum). The MR-ATLAS quantification method is proved to be reliable in every territory of the striatum. In addition, good correlations were found between cognitive dysexecutive tests and the binding within the functional (limbic) territories of the striatum using the MR-ATLAS method, slightly better than correlations found using the anatomical quantification method. This new MR-ATLAS method provides a robust and useful tool for studying the dopaminergic system in PD, particularly with respect to cognitive functions. It may also be relevant to further unravel the relationship between dopaminergic denervation and cognitive or behavioral symptoms.

In Parkinson’s disease, there is a progressive reduction in striatal dopaminergic function, and loss of neuromelanin-containing dopaminergic neurons and increased iron deposition in the substantia nigra. We tested the hypothesis of a relationship between impairment of the dopaminergic system and changes in the iron metabolism. Based on imaging data of patients with prodromal and early clinical Parkinson’s disease, we assessed the spatiotemporal ordering of such changes and relationships in the sensorimotor, associative and limbic territories of the nigrostriatal system. Patients with Parkinson’s disease (disease duration < 4 years) or idiopathic REM sleep behaviour disorder (a prodromal form of Parkinson’s disease) and healthy controls underwent longitudinal examination (baseline and 2-year follow-up). Neuromelanin and iron sensitive MRI and dopamine transporter single-photon emission tomography were performed to assess nigrostriatal levels of neuromelanin, iron, and dopamine. For all three functional territories of the nigrostriatal system, in the clinically most and least affected hemispheres separately, the following was performed: cross-sectional and longitudinal intergroup difference analysis of striatal dopamine and iron, and nigral neuromelanin and iron; in Parkinson’s disease patients, exponential fitting analysis to assess the duration of the prodromal phase and the temporal ordering of changes in dopamine, neuromelanin or iron relative to controls; and voxel-wise correlation analysis to investigate concomitant spatial changes in dopamine-iron, dopamine-neuromelanin and neuromelanin-iron in the substantia nigra pars compacta. The temporal ordering of dopaminergic changes followed the known spatial pattern of progression involving first the sensorimotor, then the associative and limbic striatal and nigral regions. Striatal dopaminergic denervation occurred first followed by abnormal iron metabolism and finally neuromelanin changes in the substantia nigra pars compacta, which followed the same spatial and temporal gradient observed in the striatum but shifted in time. In conclusion, dopaminergic striatal dysfunction and cell loss in the substantia nigra pars compacta are interrelated with increased nigral iron content., Using multi-modal imaging (MRI and SPECT) in patients with prodromal and early clinical Parkinson’s disease, Biondetti et al. reveal dopaminergic changes, abnormal iron metabolism and neuromelanin changes first in the sensorimotor, then the associative and finally the limbic regions of the nigrostriatal system.

International audience; BackgroundDevelopment of reliable and accurate imaging biomarkers of dopaminergic cell neurodegeneration is necessary to facilitate therapeutic drug trials in Parkinson's disease (PD). Neuromelanin‐sensitive MRI techniques have been effective in detecting neurodegeneration in the substantia nigra pars compacta (SNpc). The objective of the current study was to investigate longitudinal neuromelanin signal changes in the SNpc in PD patients.MethodsIn this prospective, longitudinal, observational case–control study, we included 140 PD patients and 64 healthy volunteers divided into 2 cohorts. Cohort I included 99 early PD patients (disease duration, 1.5 ± 1.0 years) and 41 healthy volunteers analyzed at baseline (V1), where 79 PD patients and 32 healthy volunteers were rescanned after 2.0 ± 0.2 years of follow‐up (V2). Cohort II included 41 progressing PD patients (disease duration, 9.3 ± 3.7 years) and 23 healthy volunteers at V1, where 30 PD patients were rescanned after 2.4 ± 0.5 years of follow‐up. Subjects were scanned at 3 T MRI using 3‐dimensional T1‐weighted and neuromelanin‐sensitive imaging. Regions of interest were delineated manually to calculate SN volumes, volumes corrected by total intracranial volume, signal‐to‐noise ratio, and contrast‐to‐noise ratio.ResultsResults showed (1) significant reduction in volume and volume corrected by total intracranial volume between visits, greater in progressing PD than nonsignificant changes in healthy volunteers; (2) no significant effects of visit for signal intensity (signal‐to‐noise ratio); (3) significant interaction in volume between group and visit; (4) greater volume corrected by total intracranial volume at baseline in female patients and greater decrease in volume and increase in the contrast‐to‐noise ratio in progressing female PD patients compared with male patients; and (5) correlations between neuromelanin SN changes and disease severity and duration.ConclusionsWe observed a progressive and measurable decrease in neuromelanin‐based SN signal and volume in PD, which might allow a direct noninvasive assessment of progression of SN loss and could represent a target biomarker for disease‐modifying treatments. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Myoclonus-dystonia (MD) is a syndrome characterized by myoclonus of subcortical origin and dystonia, frequently associated with psychiatric comorbidities. The motor and psychiatric phenotypes of this syndrome likely result from cortico-striato-thamalo-cerebellar-cortical pathway dysfunction. We hypothesized that reactive and proactive inhibitory control may be altered in these patients. Using the Stop Signal Task, we assessed reactive and proactive inhibitory control in MD patients with (n = 12) and without (n = 21) deep brain stimulation of the globus pallidus interna and compared their performance to matched healthy controls (n = 24). Reactive inhibition was considered as the ability to stop an already initiated action and measured using the stop signal reaction time. Proactive inhibition was assessed through the influence of several consecutive GO or STOP trials on decreased response time or inhibitory process facilitation. The proactive inhibition was solely impaired in unoperated MD patients. Patients with deep brain stimulation showed impairment in reactive inhibition, independent of presence of obsessive–compulsive disorders. This impairment in reactive inhibitory control correlated with intrinsic severity of myoclonus (i.e. pre-operative score). The results point to a dissociation in reactive and proactive inhibitory control in MD patients with and without deep brain stimulation of the globus pallidus interna.

Background Machine learning algorithms using magnetic resonance imaging (MRI) data can accurately discriminate parkinsonian syndromes. Validation in patients recruited in routine clinical practice is missing. Objective The aim of this study was to assess the accuracy of a machine learning algorithm trained on a research cohort and tested on an independent clinical replication cohort for the categorization of parkinsonian syndromes. Methods Three hundred twenty-two subjects, including 94 healthy control subjects, 119 patients with Parkinson's disease (PD), 51 patients with progressive supranuclear palsy (PSP) with Richardson's syndrome, 35 with multiple system atrophy (MSA) of the parkinsonian variant (MSA-P), and 23 with MSA of the cerebellar variant (MSA-C), were recruited. They were divided into a training cohort (n = 179) scanned in a research environment and a replication cohort (n = 143) examined in clinical practice on different MRI systems. Volumes and diffusion tensor imaging (DTI) metrics in 13 brain regions were used as input for a supervised machine learning algorithm. To harmonize data across scanners and reduce scanner-dependent effects, we tested two types of normalizations using patient data or healthy control data. Results In the replication cohort, high accuracies were achieved using volumetry in the classification of PD-PSP, PD-MSA-C, PSP-MSA-C, and PD-atypical parkinsonism (balanced accuracies: 0.840-0.983, area under the receiver operating characteristic curves: 0.907-0.995). Performances were lower for the classification of PD-MSA-P, MSA-C-MSA-P (balanced accuracies: 0.765-0.784, area under the receiver operating characteristic curve: 0.839-0.871) and PD-PSP-MSA (balanced accuracies: 0.773). Performance using DTI was improved when normalizing by controls, but remained lower than that using volumetry alone or combined with DTI. Conclusions A machine learning approach based on volumetry enabled accurate classification of subjects with early-stage parkinsonism, examined on different MRI systems, as part of their clinical assessment. © 2020 International Parkinson and Movement Disorder Society.

Tourette disorder (TD), which is characterized by motor and vocal tics, is not in general considered as a product of impulsivity, despite a frequent association with attention deficit hyperactivity disorder and impulse control disorders. It is unclear which type of impulsivity, if any, is intrinsically related to TD and specifically to the severity of tics. The waiting type of motor impulsivity, defined as the difficulty to withhold a specific action, shares some common features with tics. In a large group of adult TD patients compared to healthy controls, we assessed waiting motor impulsivity using a behavioral task, as well as structural and functional underpinnings of waiting impulsivity and tics using multi-modal neuroimaging protocol. We found that unmedicated TD patients showed increased waiting impulsivity compared to controls, which was independent of comorbid conditions, but correlated with the severity of tics. Tic severity did not account directly for waiting impulsivity, but this effect was mediated by connectivity between the right orbito-frontal cortex with caudate nucleus bilaterally. Waiting impulsivity in unmedicated patients with TD also correlated with a higher gray matter signal in deep limbic structures, as well as connectivity with cortical and with cerebellar regions on a functional level. Neither behavioral performance nor structural or functional correlates were related to a psychometric measure of impulsivity or impulsive behaviors in general. Overall, the results suggest that waiting impulsivity in TD was related to tic severity, to functional connectivity of orbito-frontal cortex with caudate nucleus and to structural changes within limbic areas.

The execution of coordinated hand movements requires complex interactions between premotor and primary motor areas in the two hemispheres. The supplementary motor area (SMA) is involved in movement preparation and bimanual coordination. How the SMA controls bimanual coordination remains unclear, although there is evidence suggesting that the SMA could modulate interhemispheric interactions. With a delayed‐response task, we investigated interhemispheric interactions underlying normal movement preparation and the role of the SMA in these interactions during the delay period of unimanual or bimanual hand movements. We used functional MRI and transcranial magnetic stimulation in 22 healthy volunteers (HVs), and then in two models of SMA dysfunction: (a) in the same group of HVs after transient disruption of the right SMA proper by continuous transcranial magnetic theta‐burst stimulation; (b) in a group of 22 patients with congenital mirror movements (CMM), whose inability to produce asymmetric hand movements is associated with SMA dysfunction. In HVs, interhemispheric connectivity during the delay period was modulated according to whether or not hand coordination was required for the forthcoming movement. In HVs following SMA disruption and in CMM patients, interhemispheric connectivity was modified during the delay period and the interhemispheric inhibition was decreased. Using two models of SMA dysfunction, we showed that the SMA modulates interhemispheric interactions during movement preparation. This unveils a new role for the SMA and highlights its importance in coordinated movement preparation.

Performing simultaneous quantitative MRI at ultrahigh field is challenging, as BEleven optimized contrasts were acquired with an unbalanced SSFP sequence by varying flip-angle amplitude and RF phase-cycling increment, at a 1.0 × 1.0 × 3.0 mmWhole-brain 3D maps of effective flip angle, proton density, and relaxation times were estimated. Parallel transmission improved the robustness of the results at 7 T. Results were in accordance with literature and with measurements from standard methods.These preliminary results show robust proton density, flip angle, T

BackgroundSeveral studies have shown that machine learning algorithms using MRI data can accurately discriminate parkinsonian syndromes. Validation under clinical conditions is missing.ObjectivesTo evaluate the accuracy for the categorization of parkinsonian syndromes of a machine learning algorithm trained with a research cohort and tested on an independent clinical replication cohort.Methods361 subjects, including 94 healthy controls, 139 patients with PD, 60 with PSP with Richardson’s syndrome, 41 with MSA of the parkinsonian variant (MSA-P) and 27 with MSA of the cerebellar variant (MSA-P), were recruited. They were divided into a training cohort (n=179) scanned in a research environment, and a replication cohort (n=182), scanned in clinical conditions on different MRI systems. Volumes and DTI metrics in 13 brain regions were used as input for a supervised machine learning algorithm.ResultHigh accuracy was achieved using volumetry in the classification of PD versus PSP, PD versus MSA-P, PD versus MSA-C, PD versus atypical parkinsonian syndromes and PSP versus MSA-C in both cohorts, although slightly lower in the replication cohort (balanced accuracy: 0.800 to 0.915 in the training cohort; 0.741 to 0.928 in the replication cohort). Performance was lower in the classification of PSP versus MSA-P and MSA-P versus MSA-C. When adding DTI metrics, the performance tended to increase in the training cohort, but not in the replication cohort.ConclusionsA machine learning approach based on volumetric and DTI data can accurately classify subjects with early-stage parkinsonism, scanned on different MRI systems, in the setting of their clinical workup.

Background Cognitive deficits in Parkinson's disease (PD) may result from damage in the cortex as well as in the dopaminergic, noradrenergic, and cholinergic inputs to the cortex. Cholinergic inputs to the cortex mainly originate from the basal forebrain and are clustered in several regions, called Ch1 to Ch4, that project to the hippocampus (Ch1‐2), the olfactory bulb (Ch3), and the cortex and amygdala (Ch4). Objective We investigated changes in basal forebrain and their role in cognitive deficits in PD. Methods We studied 52 nondemented patients with PD (Hoehn & Yahr 1‐2) and 25 age‐matched healthy controls using diffusion and resting state functional MRI. Results PD patients had a loss of structural integrity within the Ch1‐2 and Ch3‐4 nuclei of the basal forebrain as well as in the fornix. Tractography showed that the probability of anatomical connection was decreased in PD between Ch3‐4 and the associative prefrontal cortex, occipital cortex, and peri‐insular regions. There was a reduction in functional connectivity between Ch1‐2 and the bilateral hippocampi and parahippocampal gyri, the left middle and superior temporal gyri, and the left fusiform gyrus and between Ch3‐4 and the right inferior frontal gyrus and the right and left thalamus. In Ch1‐2, loss of structural integrity and connectivity correlated with scores at the memory tests, whereas changes in Ch3‐4 correlated with scores of global cognition and executive functions. Conclusion This study highlights the association between deficits of different cholinergic nuclei of the basal forebrain and the extent of cognitive impairments in nondemented PD patients. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

A common means of studying motor recovery in stroke patients is to extract Diffusion Tensor Imaging (DTI) parameters from the corticospinal tract (CST) and correlate them with clinical outcome scores. To that purpose, conducting group-level analyses through spatial normalization has become a popular approach. However, the reliability of such analyses depends on the accuracy of the particular registration strategy employed. To date, most studies have employed scalar-based registration using either high-resolution T1 images or Fractional Anisotropy (FA) maps to warp diffusion data to a common space. However, more powerful registration algorithms exist for aligning major white matter structures, such as Fiber Orientation Distribution (FOD)-based registration. Regardless of the strategy chosen, automatic normalization algorithms are prone to distortions caused by stroke lesions. While lesion masking is a common means to lessen such distortions, the extent of its effect on tract-related DTI parameters and their correlation with motor outcome has yet to be determined. Here, we aimed to address these concerns by first investigating the effect of common T1 and FA-based registration as well as novel FOD-based registration algorithms with and without lesion masking on lesion load and DTI parameter extraction of the CST in datasets typically acquired for subacute-chronic and acute stroke patients. Second, we studied how differences in these procedures influenced correlation strength between CST damage (through DTI parameters) and motor outcome. Our results showed that, for high-quality subacute-chronic stroke data, FOD-based registration captured significantly higher lesion loads and significantly larger FA asymmetries in the CST. This was also associated with significantly stronger correlations in motor outcome with respect to T1 or FA-based registration methods. For acute data acquired in a clinical setting, there were few observed differences, suggesting that commonly employed FA-based registration is appropriate for group-level analyses.

Background Hepatic encephalopathy (HE) may occur after transjugular intrahepatic portosystemic shunt (TIPSS) placement. Multimodal magnetic resonance imaging (MRI), combining anatomical sequences, diffusion tensor imaging (DTI) and 1 H magnetic resonance spectroscopy, is modified in cirrhotic patients. Aims To describe multimodal MRI images before TIPSS, to assess if TIPSS induces changes in multimodal MRI, and to find predictors of HE after TIPSS in patients with cirrhosis. Methods Consecutive cirrhotic patients with an indication for TIPSS were prospectively screened. Diagnosis of minimal HE was performed using psychometric HE test score. Multimodal MRI was performed before and 3 months after TIPSS placement. Results Twenty-five consecutive patients were analysed (median age = 59, male gender 76%, median Child-Pugh score = 8 [5-8], MELD score = 12 [9-17], indication for TIPSS placement: ascites/secondary prophylaxis of variceal bleeding/other 20/3/2), no HE/minimal HE/overt HE: 21/4/0. 8/25 patients developed HE after TIPSS. Before TIPSS placement, metabolite concentrations were different in patients with or without minimal HE (lower myo-inositol, mI, higher glutamate/glutamine), but there were no differences in DTI data. TIPSS placement induced changes in metabolite concentrations even in asymptomatic patients, but not in DTI metrics. Baseline fractional anisotropy was significantly lower in patients who developed HE after TIPSS in five regions of interest. Conclusions TIPSS placement induced significant changes in cerebral metabolites, even in asymptomatic patients. Patients who developed HE after TIPSS displayed lower fractional anisotropy before TIPSS. Brain MRI with DTI acquisition may help selecting patients at risk of HE.

Background and Purpose— Many studies have attempted to bring to light the neural correlates of poststroke motor impairment, but few have used multimodal approach to explain it. The aim of this study was to elucidate neural structural and functional correlates of upper limb motor impairment by combining electrophysiological, anatomic, and functional neuroimaging data. Methods— Forty ischemic stroke patients (median [min–max] age: 63 [33–82] years, time poststroke: 3.5 [1.1–58] months) with unilateral upper limb weakness were included. The upper limb motor impairment was defined by a motor composite score. Simple linear analysis followed by multiple linear regression analysis were performed to identify which variables (corticospinal excitability, laterality indices within the primary motor cortex or corticospinal [CST], and corpus callosum tracts integrity) were the best explaining factors of upper limb motor impairment. Results— There was a significant correlation between the resting motor threshold ratio and CST damage ( r = −0.50 [95% CI, −0.70 to −0.22]; P r = −0.73 [95% CI, −0.85 to −0.54]; P P Conclusions— The implementation of quantitative neurophysiological measurements such as the resting motor threshold as a surrogate marker of impairment could be considered in neurorehabilitation trials.

Background The objective of this study was to investigate pedunculopontine nucleus network dysfunctions that mediate impaired postural control and sleep disorder in Parkinson's disease. Methods We examined (1) Parkinson's disease patients with impaired postural control and rapid eye movement sleep behavior disorder (further abbreviated as sleep disorder), (2) Parkinson's disease patients with sleep disorder only, (3) Parkinson's disease patients with neither impaired postural control nor sleep disorder, and (4) healthy volunteers. We assessed postural control with clinical scores and biomechanical recordings during gait initiation. Participants had video polysomnography, daytime sleepiness self-evaluation, and resting-state functional MRIs. Results Patients with impaired postural control and sleep disorder had longer duration of anticipatory postural adjustments during gait initiation and decreased functional connectivity between the pedunculopontine nucleus and the supplementary motor area in the locomotor network that correlated negatively with the duration of anticipatory postural adjustments. Both groups of patients with sleep disorder had decreased functional connectivity between the pedunculopontine nucleus and the anterior cingulate cortex in the arousal network that correlated with daytime sleepiness. The degree of dysfunction in the arousal network was related to the degree of connectivity in the locomotor network in all patients with sleep disorder, but not in patients without sleep disorder or healthy volunteers. Conclusions These results shed light on the functional neuroanatomy of pedunculopontine nucleus networks supporting the clinical manifestation and the interdependence between sleep and postural control impairments in Parkinson's disease. © 2016 International Parkinson and Movement Disorder Society

Objectifs Le diagnostic differentiel des syndromes parkinsoniens d’origine neurodegenerative est difficile, notamment en phase precoce. L’IRM structurelle constitue une aide diagnostique precieuse puisqu’elle fournit des biomarqueurs capables de discriminer les differentes entites. Alors que l’imagerie est consideree normale dans la maladie de Parkinson (MPI), la paralysie supranucleaire progressive (PSP) est caracterisee par une atteinte preferentielle du mesencephale, alors que l’atteinte du putamen, du pont et du cervelet domine l’atrophie multisystematisee (AMS). Notre objectif etait d’evaluer la capacite d’un algorithme a classer correctement les sujets atteints de syndrome parkinsonien sur la base de donnees de volumetrie et de diffusion. Materiels et methodes Cette etude prospective reposait une cohorte d’apprentissage incluant 181 sujets scannes en milieu de recherche sur deux appareils IRM (sujets sains : n = 72, MPI : n = 62, PSP : n = 22, AMS : n = 25) et sur une cohorte test incluant 169 sujets recrutes dans un service de neuroradiologie et images en conditions cliniques sur quatre appareils IRM (sujets sains : n = 20, MPI : n = 72, PSP : n = 36, AMS : n = 41). Le protocole incluait une sequence anatomique en ponderation T1 haute resolution et un tenseur de diffusion. Des volumes et des metriques de diffusion (fraction d’anisotropie, diffusivite moyenne, diffusivite radiale et diffusivite axiale) ont ete extraits de facon automatisee pour differentes regions d’interet corticales et sous-corticales. Un algorithme de type support vector machine lineaire a ete entraine sur la base des differents biomarqueurs extraits sur la cohorte d’apprentissage, puis teste sur la cohorte d’apprentissage et sur la cohorte test. Differentes tâches de classification ont ete testees : sujets sains versus sujets parkinsoniens, MPI versus PSP, MPI versus AMS et PSP versus AMS. Resultats Lorsqu’on compare les donnees de volumetrie et de diffusion entre groupes de sujets, il n’y avait aucune difference significative entre sujets sains et patients atteints de MPI. La PSP et l’AMS se distinguaient de la MPI et des sujets sains par une atteinte du mesencephale dans la PSP, du pont dans l’AMS, et des ganglions de la base (putamen dans les deux maladies, thalamus et pallidum plutot dans la PSP). La PSP et l’AMS differaient entre elles par l’atteinte du tronc cerebral en termes de ratio mesencephale sur pont et de diffusivite dans le pont, et par l’atteinte du thalamus. Les performances de l’algorithme teste avec les donnees volumetriques etaient, selon les tâches de classification, bonnes a excellentes dans la cohorte d’apprentissage (precision equilibree ≥ 0,78), moyennes a excellentes dans la cohorte test (precision equilibree ≥ 0,70). L’ajout des donnees de diffusion a la volumetrie etait globalement associe a une amelioration des performances dans la cohorte d’apprentissage (precision equilibree ≥ 0,82) et a une baisse dans la cohorte test (precision equilibree ≥ 0,60). Cette baisse de performance dans la cohorte test pouvait etre imputee a l’heterogeneite des donnees de diffusion due a un effet machine. Conclusion L’utilisation d’un algorithme de type support vector machine entraine sur des donnees de volumetrie et de diffusion permet de separer les syndromes parkinsoniens avec de bonnes performances, meme en utilisant des donnees heterogenes obtenues sur differents appareils IRM. Ces resultats pourraient etre translates dans un environnement clinique.