Trial of Deferiprone in Parkinson's Disease.

BACKGROUND: Iron content is increased in the substantia nigra of persons with Parkinson's disease and may contribute to the pathophysiology of the disorder. Early research suggests that the iron chelator deferiprone can reduce nigrostriatal iron content in persons with Parkinson's disease, but its effects on disease progression are unclear. METHODS: We conducted a multicenter, phase 2, randomized, double-blind trial involving participants with newly diagnosed Parkinson's disease who had never received levodopa. Participants were assigned (in a 1:1 ratio) to receive oral deferiprone at a dose of 15 mg per kilogram of body weight twice daily or matched placebo for 36 weeks. Dopaminergic therapy was withheld unless deemed necessary for symptom control. The primary outcome was the change in the total score on the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS; range, 0 to 260, with higher scores indicating more severe impairment) at 36 weeks. Secondary and exploratory clinical outcomes at up to 40 weeks included measures of motor and nonmotor disability. Brain iron content measured with the use of magnetic resonance imaging was also an exploratory outcome. RESULTS: A total of 372 participants were enrolled; 186 were assigned to receive deferiprone and 186 to receive placebo. Progression of symptoms led to the initiation of dopaminergic therapy in 22.0% of the participants in the deferiprone group and 2.7% of those in the placebo group. The mean MDS-UPDRS total score at baseline was 34.3 in the deferiprone group and 33.2 in the placebo group and increased (worsened) by 15.6 points and 6.3 points, respectively (difference, 9.3 points; 95% confidence interval, 6.3 to 12.2; P<0.001). Nigrostriatal iron content decreased more in the deferiprone group than in the placebo group. The main serious adverse events with deferiprone were agranulocytosis in 2 participants and neutropenia in 3 participants. CONCLUSIONS: In participants with early Parkinson's disease who had never received levodopa and in whom treatment with dopaminergic medications was not planned, deferiprone was associated with worse scores in measures of parkinsonism than those with placebo over a period of 36 weeks. (Funded by the European Union Horizon 2020 program; FAIRPARK-II ClinicalTrials.gov number, NCT02655315.).

A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET.

With the arrival of disease-modifying drugs, neurodegenerative diseases will require an accurate diagnosis for optimal treatment. Convolutional neural networks are powerful deep learning techniques that can provide great help to physicians in image analysis. The purpose of this study is to introduce and validate a 3D neural network for classification of Alzheimer's disease (AD), frontotemporal dementia (FTD) or cognitively normal (CN) subjects based on brain glucose metabolism. Retrospective [18F]-FDG-PET scans of 199 CE, 192 FTD and 200 CN subjects were collected from our local database, Alzheimer's disease and frontotemporal lobar degeneration neuroimaging initiatives. Training and test sets were created using randomization on a 90 %-10 % basis, and training of a 3D VGG16-like neural network was performed using data augmentation and cross-validation. Performance was compared to clinical interpretation by three specialists in the independent test set. Regions determining classification were identified in an occlusion experiment and Gradient-weighted Class Activation Mapping. Test set subjects were age- and sex-matched across categories. The model achieved an overall 89.8 % accuracy in predicting the class of test scans. Areas under the ROC curves were 93.3 % for AD, 95.3 % for FTD, and 99.9 % for CN. The physicians' consensus showed a 69.5 % accuracy, and there was substantial agreement between them (kappa = 0.61, 95 % CI: 0.49-0.73). To our knowledge, this is the first study to introduce a deep learning model able to discriminate AD and FTD based on [18F]-FDG PET scans, and to isolate CN subjects with excellent accuracy. These initial results are promising and hint at the potential for generalization to data from other centers.

White Matter Hyperintensity Volume and Poststroke Cognition: An Individual Patient Data Pooled Analysis of 9 Ischemic Stroke Cohort Studies.

BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive dysfunction after ischemic stroke. Yet, uncertainty remains about affected domains, the role of other preexisting brain injury, and infarct types in the relation between WMH burden and poststroke cognition. We aimed to disentangle these factors in a large sample of patients with ischemic stroke from different cohorts. METHODS: We pooled and harmonized individual patient data (n=1568) from 9 cohorts, through the Meta VCI Map consortium (www.metavcimap.org). Included cohorts comprised patients with available magnetic resonance imaging and multidomain cognitive assessment <15 months poststroke. In this individual patient data meta-analysis, linear mixed models were used to determine the association between WMH volume and domain-specific cognitive functioning (Z scores; attention and executive functioning, processing speed, language and verbal memory) for the total sample and stratified by infarct type. Preexisting brain injury was accounted for in the multivariable models and all analyses were corrected for the study site as a random effect. RESULTS: In the total sample (67 years [SD, 11.5], 40% female), we found a dose-dependent inverse relationship between WMH volume and poststroke cognitive functioning across all 4 cognitive domains (coefficients ranging from -0.09 [SE, 0.04, P=0.01] for verbal memory to -0.19 [SE, 0.03, P<0.001] for attention and executive functioning). This relation was independent of acute infarct volume and the presence of lacunes and old infarcts. In stratified analyses, the relation between WMH volume and domain-specific functioning was also largely independent of infarct type. CONCLUSIONS: In patients with ischemic stroke, increasing WMH volume is independently associated with worse cognitive functioning across all major domains, regardless of old ischemic lesions and infarct type.

Quantitative susceptibility mapping demonstrates different patterns of iron overload in subtypes of early-onset Alzheimer's disease.

OBJECTIVES: We aimed to define brain iron distribution patterns in subtypes of early-onset Alzheimer's disease (EOAD) by the use of quantitative susceptibility mapping (QSM). METHODS: EOAD patients prospectively underwent MRI on a 3-T scanner and concomitant clinical and neuropsychological evaluation, between 2016 and 2019. An age-matched control group was constituted of cognitively healthy participants at risk of developing AD. Volumetry of the hippocampus and cerebral cortex was performed on 3DT1 images. EOAD subtypes were defined according to the hippocampal to cortical volume ratio (HV:CTV). Limbic-predominant atrophy (LPMRI) is referred to HV:CTV ratios below the 25th percentile, hippocampal-sparing (HpSpMRI) above the 75th percentile, and typical-AD between the 25th and 75th percentile. Brain iron was estimated using QSM. QSM analyses were made voxel-wise and in 7 regions of interest within deep gray nuclei and limbic structures. Iron distribution in EOAD subtypes and controls was compared using an ANOVA. RESULTS: Sixty-eight EOAD patients and 43 controls were evaluated. QSM values were significantly higher in deep gray nuclei (p < 0.001) and limbic structures (p = 0.04) of EOAD patients compared to controls. Among EOAD subtypes, HpSpMRI had the highest QSM values in deep gray nuclei (p < 0.001) whereas the highest QSM values in limbic structures were observed in LPMRI (p = 0.005). QSM in deep gray nuclei had an AUC = 0.92 in discriminating HpSpMRI and controls. CONCLUSIONS: In early-onset Alzheimer's disease patients, we observed significant variations of iron distribution reflecting the pattern of brain atrophy. Iron overload in deep gray nuclei could help to identify patients with atypical presentation of Alzheimer's disease. KEY POINTS: • In early-onset AD patients, QSM indicated a significant brain iron overload in comparison with age-matched controls. • Iron load in limbic structures was higher in participants with limbic-predominant subtype. • Iron load in deep nuclei was more important in participants with hippocampal-sparing subtype.

Resting-State Functional Connectivity in Frontostriatal and Posterior Cortical Subtypes in Parkinson's Disease-Mild Cognitive Impairment.

BACKGROUND: The "dual syndrome hypothesis" distinguished two subtypes in mild cognitive impairment (MCI) in Parkinson's disease: frontostriatal, characterized by attentional and executive deficits; and posterior cortical, characterized by visuospatial, memory, and language deficits. OBJECTIVE: The aim was to identify resting-state functional modifications associated with these subtypes. METHODS: Ninety-five nondemented patients categorized as having normal cognition (n = 31), frontostriatal (n = 14), posterior cortical (n = 20), or mixed (n = 30) cognitive subtype had a 3 T resting-state functional magnetic resonance imaging scan. Twenty-four age-matched healthy controls (HCs) were also included. A group-level independent component analysis was performed to identify resting-state networks, and the selected components were subdivided into 564 cortical regions in addition to 26 basal ganglia regions. Global intra- and inter-network connectivity along with global and local efficiencies was compared between groups. The network-based statistics approach was used to identify connections significantly different between groups. RESULTS: Patients with posterior cortical deficits had increased intra-network functional connectivity (FC) within the basal ganglia network compared with patients with frontostriatal deficits. Patients with frontostriatal deficits had reduced inter-network FC between several networks, including the visual, default-mode, sensorimotor, salience, dorsal attentional, basal ganglia, and frontoparietal networks, compared with HCs, patients with normal cognition, and patients with a posterior cortical subtype. Similar results were also found between patients with a mixed subtype and HCs. CONCLUSION: MCI subtypes are associated with specific changes in resting-state FC. Longitudinal studies are needed to determine the predictive potential of these markers regarding the risk of developing dementia. © 2021 International Parkinson and Movement Disorder Society.

A multimodal, longitudinal study of cognitive heterogeneity in early-onset Alzheimer's disease.

BACKGROUND AND PURPOSE: Alzheimer's disease (AD) is a heterogeneous pathology. Young patients with AD are particularly likely to have an atypical presentation. The objectives of the present cluster analysis were to determine whether patients with early-onset AD (EOAD) had several distinct cognitive profiles and to compare the resulting clusters with regard to clinical, neuroimaging, and laboratory characteristics. METHODS: We collected cognitive, behavioural, functional, neuroimaging, and laboratory data on 72 patients meeting the criteria for probable mild EOAD. The patients were first classified into clinical phenotype groups by a multidisciplinary board of clinicians. The patients' cognitive and functional decline was monitored for 24 months. A k-means clustering analysis was then used to determine clusters on the basis of the patients' neuropsychological test results. RESULTS: Two distinct clusters were identified: the patients in the first cluster (C1, n = 38) had a predominant memory impairment, whereas patients in the second (C2, n = 34) did not. Dyslipidaemia and the presence of ɛ4 apolipoprotein E allele were more frequent in C1, whereas the cognitive and functional decline was faster in the patients in C2. Moreover, posterior brain abnormalities were more severe in patients in C2 than in patients in C1. CONCLUSIONS: By applying a k-means clustering analysis, we identified two clusters of patients in an EOAD cohort. The clusters differed with regard to certain clinical, imaging, and laboratory characteristics. This clustering procedure might be of value for managing patients with EOAD in general and for identifying those at risk of more rapid decline in particular.

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors.

BACKGROUND: The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults. METHODS: Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session. RESULTS: Significant MRI site and vendor effects (p â€‹< â€‹.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p â€‹< â€‹1.39E-36). In particular, volumes larger than 200 â€‹mm3 (for amygdalar nuclei) and 300 â€‹mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε â€‹< â€‹5% and DICE â€‹> â€‹0.80). CONCLUSION: Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

Three-year changes of cortical 18F-FDG in amnestic vs. non-amnestic sporadic early-onset Alzheimer's disease.

PURPOSE: To examine and compare longitudinal changes of cortical glucose metabolism in amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease and assess potential associations with neuropsychological performance over a 3-year period time. METHODS: Eighty-two participants meeting criteria for early-onset (< 65 years) sporadic form of probable Alzheimer's disease and presenting with a variety of clinical phenotypes (47 amnestic and 35 non-amnestic forms) were included at baseline and followed up for 1.44 ± 1.23 years. All of the participants underwent a work-up at baseline and every year during the follow-up period, which includes clinical examination, neuropsychological testing, genotyping, cerebrospinal fluid biomarker assays, and structural MRI and 18F-FDG PET. Vertex-wise partial volume-corrected glucose metabolic maps across the entire cortical surface were generated and longitudinally assessed together with the neuropsychological scores using linear mixed-effects modeling as a function of amnestic and non-amnestic sporadic forms of early-onset Alzheimer's disease. RESULTS: Similar evolution patterns of glucose metabolic decline between amnestic and non-amnestic forms were observed in widespread neocortical cortices. However, only non-amnestic forms appeared to have a greater reduction of glucose metabolism in lateral orbitofrontal and bilateral medial temporal cortices associated with more severe declines of neuropsychological performance compared with amnestic forms. Furthermore, results suggest that glucose metabolic decline in amnestic forms would progress along an anterior-to-posterior axis, whereas glucose metabolic decline in non-amnestic forms would progress along a posterior-to-anterior axis. CONCLUSIONS: We found differences in spatial distribution and temporal trajectory of glucose metabolic decline between amnestic and non-amnestic early-onset Alzheimer's disease groups, suggesting that one might want to consider treating the two forms of the disease as two separate entities.

Texture features of magnetic resonance images: A marker of slight cognitive deficits in Parkinson's disease.

BACKGROUND: Cognitive impairment is a frequent nonmotor symptom of Parkinson's disease. Depending on severity, patients are considered to have mild cognitive impairment or dementia. However, among the cognitively intact patients, some may have deficits in a less severe range. The early detection of such subtle symptoms may be important for the initiation of care strategies. OBJECTIVE: To identify imaging markers of early cognitive symptoms, potentially before usual signs, such as atrophy, become manifest. METHODS: A total of 102 patients with Parkinson's disease and 17 age-matched cognitively intact healthy controls underwent extensive neuropsychological assessment and T1-weighted magnetic resonance imaging. Parkinson's disease patients were separated into 3 groups according to their cognitive status: intact, with slight slowing, and with mild deficits in executive functions. Texture features as measured by first-order and second-order statistics were computed in the following 6 brain regions: the hippocampus, thalamus, amygdala, putamen, caudate nucleus, and pallidum. They were tested between the groups, and their correlation with cognition was examined. Volumetric measurements were made for comparison. RESULTS: Texture analysis showed significant between-group differences for 2 features-skewness and entropy in the hippocampus, the thalamus, and the amygdala-and the volume analysis revealed no between-group difference. These features were significantly correlated with cognitive performance. CONCLUSION: These results support the assumption that signal alterations associated with Parkinson's disease-related cognitive decline can be captured very early by texture analysis. As these changes appear to reflect clinical phenomena, texture analysis may be a promising marker for helping cognitive phenotyping in Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Hypothalamic Structural and Functional Imbalances in Anorexia Nervosa.

The hypothalamus contains integrative systems that support life, including physiological processes such as food intake, energy expenditure, and reproduction. Here, we show that anorexia nervosa (AN) patients, contrary to normal weight and constitutionally lean individuals, respond with a paradoxical reduction in hypothalamic levels of glutamate/glutamine (Glx) upon feeding. This reversal of the Glx response is associated with decreased wiring in the arcuate nucleus and increased connectivity in the lateral hypothalamic area, which are involved in the regulation on a variety of physiological and behavioral functions including the control of food intake and energy balance. The identification of distinct hypothalamic neurochemical dysfunctions and associated structural variations in AN paves the way for the development of new diagnostic and treatment strategies in conditions associated with abnormal body mass index and a maladaptive response to negative energy balance.

Influence of Motor Deficiency and Spatial Neglect on the Contralesional Posterior Parietal Cortex Functional and Structural Connectivity in Stroke Patients.

The posterior parietal cortex (PPC) is a key structure for visual attention and upper limb function, two features that could be impaired after stroke, and could be implied in their recovery. If it is well established that stroke is responsible for intra- and interhemispheric connectivity troubles, little is known about those existing for the contralesional PPC. In this study, we aimed at mapping the functional (using resting state fMRI) and structural (using diffusion tensor imagery) networks from 3 subparts of the PPC of the contralesional hemisphere (the anterior intraparietal sulcus), the posterior intraparietal sulcus and the superior parieto-occipital cortex to bilateral frontal areas and ipsilesional homologous PPC parts in 11 chronic stroke patients compared to 13 healthy controls. We also aimed at assessing the relationship between connectivity and the severity of visuospatial and motor deficiencies. We showed that interhemispheric functional and structural connectivity between PPCs was altered in stroke patients compared to controls, without any specificity among seeds. Alterations of parieto-frontal intra- and interhemispheric connectivity were less observed. Neglect severity was associated with several alterations in intra- and interhemispheric connectivity, whereas we did not find any behavioral/connectivity correlations for motor deficiency. The results of this exploratory study shed a new light on the influence of the contralesional PPC in post-stroke patients, they have to be confirmed and refined in further larger studies.

A Fully Automatic Method for Optic Radiation Tractography Applicable to Multiple Sclerosis Patients.

The optic radiations (OR) are white matter tracts forming the posterior part of the visual ways. As an important inter-individual variability exists, atlases may be inefficient to locate the OR in a given subject. We designed a fully automatic method to delimitate the OR on a magnetic resonance imaging using tractography. On 15 healthy subjects, we evaluated the validity of our method by comparing the outputs to the Jülich post-mortem histological atlas, and its reproducibility. We also evaluated its feasibility on 98 multiple sclerosis (MS) patients. We correlated different visual outcomes with the inflammatory lesions volume within the OR reconstructed with different methods (our method, atlas, TractSeg). Our method reconstructed the OR bundle in all healthy subjects (< 2 h for most of them), and was reproducible. It demonstrated good classification indexes: sensitivity up to 0.996, specificity up to 0.993, Dice coefficient up to 0.842, and an area under the receiver operating characteristic (ROC) curve of 0.981. Our method reconstructed the OR in 91 of the 98 MS patients (92.9%, < 6 h for most of patients). Compared to an atlas-based approach and the TractSeg method, the inflammatory lesions volume in the OR measured with our method better correlated with the visual cortex volume, visual acuity and mean peripapillar retinal nerve fiber layer thickness. Our method seems to be efficient to reconstruct the OR in healthy subjects, and seems applicable to MS patients. It may be more relevant than an atlas based approach.

Differences in cortical perfusion detected by arterial spin labeling in nonamnestic and amnestic subtypes of early-onset Alzheimer's disease.

OBJECTIVES: Early-onset Alzheimer's disease (EOAD) begins before the age of 65 and is characterized by a faster clinical course and the frequency of nonamnestic symptoms compared to late onset Alzheimer disease (LOAD). However, the pathophysiological process of EOAD remains unclear. We expected that ASL may show widespread cortical hypoperfusion in EOAD compared to LOAD and in nonamnestic EOAD compared to amnestic EOAD. METHODS: In this study, 26 EOAD patients (16 amnestic and 10 nonamnestic patients), 29 LOAD patients and 12 healthy controls underwent pseudo-continuous ASL and 3D FFE T1 sequences. Statistical comparisons between EOAD, LOAD and control groups were made after surface-based analysis of CBF maps in regressing out the cortical thickness. RESULTS: ASL showed a more severe hypoperfusion in nonamnestic EOAD patients compared to amnestic EOAD ones, with mean CBF values (± std) of 26.9 (± 3.8) and 46.6 (± 24.1) mL/100 g/min respectively (P = 0.014), located in the bilateral temporo-parietal neocortex, the precuneus, the posterior cingulate cortices (PCC) and frontal lobes. Comparison between EOAD and LOAD patients showed a trend to hypoperfusion in the left parietal lobe, PCC and precuneus in EOAD (P < 0.001 uncorrected). CONCLUSIONS: Different patterns of hypoperfusion between nonamnestic and amnestic EOAD subtypes were identified, with a more severe and extensive hypoperfusion in nonamnestic patients. A trend towards more severe hypoperfusion was detected in EOAD compared to LOAD. Further studies are needed to validate ASL as a potential tool for the distinction of EOAD subtypes and the prediction of the time course of the disease.

Texture parameters of R2* maps are correlated with iron concentration and red blood cells count in clot analogs: A 7-T micro-MRI study.

BACKGROUND AND PURPOSE: Previous studies have suggested that mechanical revascularization in acute ischemic stroke (AIS) patients could be affected by clot histology. In this 7-T micro-MRI study, we used R2* relaxometry of clot analogs to evaluate the relationship between texture parameters of R2* maps and clot constituents. MATERIALS AND METHODS: Twelve AIS clot analogs were experimentally generated to obtain a wide range of red blood cell concentrations. All clots underwent a MR acquisition using a 7-T micro-MR system. A 3D multi-echo gradient-echo sequence was performed and R2* maps were generated. First order and second order statistics of R2* histograms within the clots were calculated. Iron concentration in clots was measured using absorption spectrometry and red blood cell count (RBC) was obtained by histopathological analysis. RESULTS: RBC count was strongly correlated with iron concentration within clots (r=0.87, P<.001). Higher RBC count and iron concentration were significantly correlated with first order parameters including: (a) global positive shift of the R2* histogram with higher '10th percentile', 'median', 'mean' and '90th percentile'; (b) increase of the global magnitude of voxel values with higher 'total energy' and 'root mean squared'; (c) greater uniformity of the voxel values with higher 'uniformity' and lower 'entropy'. Second order statistical parameters confirmed that higher RBC count and iron concentration correlated with (a) greater concentration of high gray-level values in the image; (b) more "coarse" texture of R2* maps. CONCLUSIONS: Texture analysis of MRI-R2* maps can accurately estimate the red blood cell count and iron content of AIS clot analogs.

Neurodegeneration of the Substantia Nigra after Ipsilateral Infarct: MRI R2* Mapping and Relationship to Clinical Outcome.

Background The substantia nigra (SN) is suspected to be affected after remote infarction, in view of its large array of connections with the supratentorial brain. Whether secondary involvement of SN worsens overall clinical outcome after a supratentorial stroke has not previously been studied. Purpose To assess longitudinal changes in SN R2* by using MRI in the setting of ipsilesional supratentorial infarct and the relationship of SN signal change to clinical outcome. Materials and Methods Participants prospectively included from 2012 to 2015 were evaluated at 24-72 hours (baseline visit) and at 1 year with MRI to quantify R2*. The SN was segmented bilaterally to calculate an R2* asymmetry index (SN-AI); greater SN-AI indicated greater relative R2* in the ipsilateral compared with contralateral SN. The 95th percentile of R2* (hereafter, SN-AI95) was compared according to infarct location with mixed linear regression models. We also conducted voxel-based comparisons of R2* and identified individual infarcted voxels associated with high SN-AI95 through voxel-based lesion-symptom mapping. Multivariable regression models tested the association between SN-AI95 and clinical scores. Results A total of 181 participants were evaluated (127 men, 54 women; mean age ± standard deviation, 64.2 years ± 13.1; 75 striatum infarcts, 106 other locations). Visual inspection, SN-AI95, and average maps consistently showed higher SN R2* at 1 year if ipsilateral striatum was infarcted than if it was not (SN-AI95, 4.25 vs -0.88; P < .001), but this was not observed at baseline. The striatal location of the infarct was associated with higher SN-AI95 at 1 year independently from infarct volume, SN-AI95 at baseline, microbleeds, age, and sex (ß = 4.99; P < .001). Voxel-based lesion-symptom mapping confirmed that striatum but also insula, internal capsule, and external capsule were associated with higher SN-AI95 at 1 year. SN-AI95 was an independent contributor of poor motor outcome (Box and Block Test, ß = -.62 points; P = .01). Conclusion In patients with stroke, greater substantia nigra R2*, likely reflective of greater iron content, can be observed at 1 year ipsilateral from remote infarcts of specific location, which is associated with worse motor function. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Vernooij in this issue.

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory events remains difficult and time-consuming. This article first proposes a machine-learning algorithm to automatically identify resting-state fMRI periods that precede hallucinations versus periods that do not. When applied to whole-brain fMRI data, state-of-the-art classification methods, such as support vector machines (SVM), yield dense solutions that are difficult to interpret. We proposed to extend the existing sparse classification methods by taking the spatial structure of brain images into account with structured sparsity using the total variation penalty. Based on this approach, we obtained reliable classifying performances associated with interpretable predictive patterns, composed of two clearly identifiable clusters in speech-related brain regions. The variation in transition-to-hallucination functional patterns not only from one patient to another but also from one occurrence to the next (e.g., also depending on the sensory modalities involved) appeared to be the major difficulty when developing effective classifiers. Consequently, second, this article aimed to characterize the variability within the prehallucination patterns using an extension of principal component analysis with spatial constraints. The principal components (PCs) and the associated basis patterns shed light on the intrinsic structures of the variability present in the dataset. Such results are promising in the scope of innovative fMRI-guided therapy for drug-resistant hallucinations, such as fMRI-based neurofeedback.

Thalamic alterations remote to infarct appear as focal iron accumulation and impact clinical outcome.

See Duering and Schmidt (doi:10.1093/awx135) for a scientific commentary on this article.Thalamic alterations have been observed in infarcts initially sparing the thalamus but interrupting thalamo-cortical or cortico-thalamic projections. We aimed at extending this knowledge by demonstrating with in vivo imaging sensitive to iron accumulation, one marker of neurodegeneration, that (i) secondary thalamic alterations are focally located in specific thalamic nuclei depending on the initial infarct location; and (ii) such secondary alterations can contribute independently to the long-term outcome. To tackle this issue, 172 patients with an infarct initially sparing the thalamus were prospectively evaluated clinically and with magnetic resonance imaging to quantify iron through R2* map at 24-72 h and at 1-year follow-up. An asymmetry index was used to compare R2* within the thalamus ipsilateral versus contralateral to infarct and we focused on the 95th percentile of R2* as a metric of high iron content. Spatial distribution within the thalamus was analysed on an average R2* map from the entire cohort. The asymmetry index of the 95th percentile within individual nuclei (medio-dorsal, pulvinar, lateral group) were compared according to the initial infarct location in simple and multiple regression analyses and using voxel-based lesion-symptom mapping. Associations between the asymmetry index of the 95th percentile and functional, cognitive and emotional outcome were calculated in multiple regression models. We showed that R2* was not modified at 24-72 h but showed heterogeneous increase at 1 year mainly within the medio-dorsal and pulvinar nuclei. The asymmetry index of the 95th percentile within the medio-dorsal nucleus was significantly associated with infarcts involving anterior areas (frontal P = 0.05, temporal P = 0.02, lenticular P = 0.01) while the asymmetry index of the 95th percentile within the pulvinar nucleus was significantly associated with infarcts involving posterior areas (parietal P = 0.046, temporal P < 0.001) independently of age, gender and infarct volume, which was confirmed by voxel-based lesion-symptom mapping. The asymmetry index of the 95th percentile within the entire thalamus at 1 year was independently associated with poor functional outcome (P = 0.04), poor cognitive outcome (P = 0.03), post-stroke anxiety (P = 0.04) and post-stroke depression (P = 0.02). We have therefore identified that iron accumulates within the thalamus ipsilateral to infarct after a delay with a focal distribution that is strongly linked to the initial infarct location (in relation with the pattern of connectivity between thalamic nuclei and cortical areas or deep nuclei), which independently contributes to functional, cognitive and emotional outcome.

Encoding and immediate retrieval tasks in patients with epilepsy: A functional MRI study of verbal and visual memory.

PURPOSE: Medial lobe temporal structures and more specifically the hippocampus play a decisive role in episodic memory. Most of the memory functional magnetic resonance imaging (fMRI) studies evaluate the encoding phase; the retrieval phase being performed outside the MRI. We aimed to determine the ability to reveal greater hippocampal fMRI activations during retrieval phase. MATERIALS AND METHODS: Thirty-five epileptic patients underwent a two-step memory fMRI. During encoding phase, subjects were requested to identify the feminine or masculine gender of faces and words presented, in order to encourage stimulus encoding. One hour after, during retrieval phase, subjects had to recognize the word and face. We used an event-related design to identify hippocampal activations. RESULTS: There was no significant difference between patients with left temporal lobe epilepsy, patients with right temporal lobe epilepsy and patients with extratemporal lobe epilepsy on verbal and visual learning task. For words, patients demonstrated significantly more bilateral hippocampal activation for retrieval task than encoding task and when the tasks were associated than during encoding alone. Significant difference was seen between face-encoding alone and face retrieval alone. CONCLUSIONS: This study demonstrates the essential contribution of the retrieval task during a fMRI memory task but the number of patients with hippocampal activations was greater when the two tasks were taken into account.

Cognitive phenotypes in parkinson's disease differ in terms of brain-network organization and connectivity.

Cognitive deficits are common in Parkinson's disease and we suspect that dysfunctions of connected brain regions can be the source of these deficits. The aim of the present study was to investigate changes in whole-brain intrinsic functional connectivity according to differences in cognitive profiles in Parkinson's disease. 119 participants were enrolled and divided into four groups according to their cognitive phenotypes (determined by a cluster analysis): (i) 31 cognitively intact patients (G1), (ii) 31 patients with only slight mental slowing (G2), (iii) 43 patients with mild to moderate deficits mainly in executive functions (G3), (iv) 14 patients with severe deficits in all cognitive domains (G4-5). Rs-fMRI whole-brain connectivity was examined by two complementary approaches: graph theory for studying network functional organization and network-based statistics (NBS) for exploring functional connectivity amongst brain regions. After adjustment for age, duration of formal education and center of acquisition, there were significant group differences for all functional organization indexes: functional organization decreased (G1 > G2 > G3 > G4-5) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, P < 0.01) mainly concerned the ventral prefrontal, parietal, temporal and occipital cortices as well as the basal ganglia. In Parkinson's disease, brain network organization is progressively disrupted as cognitive impairment worsens, with an increasing number of altered connections between brain regions. We observed reduced connectivity in highly associative areas, even in patients with only slight mental slowing. The association of slowed mental processing with loss of connectivity between highly associative areas could be an early marker of cognitive impairment in Parkinson's disease and may contribute to the detection of prodromal forms of Parkinson's disease dementia. Hum Brain Mapp 38:1604-1621, 2017. © 2016 Wiley Periodicals, Inc.

Free water elimination improves test-retest reproducibility of diffusion tensor imaging indices in the brain: A longitudinal multisite study of healthy elderly subjects.

Free water elimination (FWE) in brain diffusion MRI has been shown to improve tissue specificity in human white matter characterization both in health and in disease. Relative to the classical diffusion tensor imaging (DTI) model, FWE is also expected to increase sensitivity to microstructural changes in longitudinal studies. However, it is not clear if these two models differ in their test-retest reproducibility. This study compares a bi-tensor model for FWE with DTI by extending a previous longitudinal-reproducibility 3T multisite study (10 sites, 7 different scanner models) of 50 healthy elderly participants (55-80 years old) scanned in two sessions at least 1 week apart. We computed the reproducibility of commonly used DTI metrics (FA: fractional anisotropy, MD: mean diffusivity, RD: radial diffusivity, and AXD: axial diffusivity), derived either using a DTI model or a FWE model. The DTI metrics were evaluated over 48 white-matter regions of the JHU-ICBM-DTI-81 white-matter labels atlas, and reproducibility errors were assessed. We found that relative to the DTI model, FWE significantly reduced reproducibility errors in most areas tested. In particular, for the FA and MD metrics, there was an average reduction of approximately 1% in the reproducibility error. The reproducibility scores did not significantly differ across sites. This study shows that FWE improves sensitivity and is thus promising for clinical applications, with the potential to identify more subtle changes. The increased reproducibility allows for smaller sample size or shorter trials in studies evaluating biomarkers of disease progression or treatment effects. Hum Brain Mapp 38:12-26, 2017. © 2016 Wiley Periodicals, Inc.