Publications by authors named "Stephanie Bombois"

54 Publications

The cerebral network of COVID-19-related encephalopathy: a longitudinal voxel-based 18F-FDG-PET study.

Eur J Nucl Med Mol Imaging 2021 Jan 15. Epub 2021 Jan 15.

Département de Neurologie, Sorbonne Université, AP-HP, Hôpitaux Universitaires Pitié-Salpêtrière Charles Foix, 75013, Paris, France.

Purpose: Little is known about the neuronal substrates of neuropsychiatric symptoms associated with COVID-19 and their evolution during the course of the disease. We aimed at describing the longitudinal brain metabolic pattern in COVID-19-related encephalopathy using 18F-FDG-PET/CT.

Methods: Seven patients with variable clinical presentations of COVID-19-related encephalopathy were explored thrice with brain 18F-FDG-PET/CT, once in the acute phase, 1 month later and 6 months after COVID-19 onset. PET images were analysed with voxel-wise and regions-of-interest approaches in comparison with 32 healthy controls.

Results: Patients' neurological manifestations during acute encephalopathy were heterogeneous. However, all of them presented with predominant cognitive and behavioural frontal disorders. SARS-CoV-2 RT-PCR in the CSF was negative for all patients. MRI revealed no specific abnormalities for most of the subjects. All patients had a consistent pattern of hypometabolism in a widespread cerebral network including the frontal cortex, anterior cingulate, insula and caudate nucleus. Six months after COVID-19 onset, the majority of patients clinically had improved but cognitive and emotional disorders of varying severity remained with attention/executive disabilities and anxio-depressive symptoms, and lasting prefrontal, insular and subcortical 18F-FDG-PET/CT abnormalities.

Conclusion: The implication of this widespread network could be the neural substrate of clinical features observed in patients with COVID-19, such as frontal lobe syndrome, emotional disturbances and deregulation of respiratory failure perception. This study suggests that this network remains mildly to severely impaired 6 months after disease onset.
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http://dx.doi.org/10.1007/s00259-020-05178-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7810428PMC
January 2021

Characteristics and progression of patients with frontotemporal dementia in a regional memory clinic network.

Alzheimers Res Ther 2021 01 8;13(1):19. Epub 2021 Jan 8.

Univ. Lille, Inserm, CHU Lille, Lille Neuroscience & Cognition, CNRMAJ, LiCEND, DistAlz, F-59000, Lille, France.

Background: Due to heterogeneous clinical presentation, difficult differential diagnosis with Alzheimer's disease (AD) and psychiatric disorders, and evolving clinical criteria, the epidemiology and natural history of frontotemporal lobar degeneration (FTD) remain elusive. In order to better characterize FTD patients, we relied on the database of a regional memory clinic network with standardized diagnostic procedures and chose AD patients as a comparator.

Methods: Patients that were first referred to our network between January 2010 and December 2016 and whose last clinical diagnosis was degenerative or vascular dementia were included. Comparisons were conducted between FTD and AD as well as between the different FTD syndromes, divided into language variants (lvFTD), behavioral variant (bvFTD), and FTD with primarily motor symptoms (mFTD). Cognitive progression was estimated with the yearly decline in Mini Mental State Examination (MMSE).

Results: Among the patients that were referred to our network in the 6-year time span, 690 were ultimately diagnosed with FTD and 18,831 with AD. Patients with FTD syndromes represented 2.6% of all-cause dementias. The age-standardized incidence was 2.90 per 100,000 person-year and incidence peaked between 75 and 79 years. Compared to AD, patients with FTD syndromes had a longer referral delay and delay to diagnosis. Patients with FTD syndromes had a higher MMSE score than AD at first referral while their progression was similar. mFTD patients had the shortest survival while survival in bvFTD, lvFTD, and AD did not significantly differ. FTD patients, especially those with the behavioral variant, received more antidepressants, anxiolytics, and antipsychotics than AD patients.

Conclusions: FTD syndromes differ with AD in characteristics at baseline, progression rate, and treatment. Despite a broad use of the new diagnostic criteria in an organized memory clinic network, FTD syndromes are longer to diagnose and account for a low proportion of dementia cases, suggesting persistent underdiagnosis. Congruent with recent publications, the late peak of incidence warns against considering FTD as being exclusively a young-onset dementia.
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http://dx.doi.org/10.1186/s13195-020-00753-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796569PMC
January 2021

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study.

Magn Reson Imaging 2021 02 19;76:108-115. Epub 2020 Nov 19.

Laboratory of Alzheimer's Neuroimaging and Alzheimer's Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was -0.22[IQR = 0.50] for LGA-SPM8, -0.12[0.57] for LGA-SPM12, -0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies.
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http://dx.doi.org/10.1016/j.mri.2020.11.008DOI Listing
February 2021

The Clinical Value of the Faux Pas Test for Diagnosing Behavioral-Variant Frontotemporal Dementia.

J Geriatr Psychiatry Neurol 2020 Oct 8:891988720964253. Epub 2020 Oct 8.

Equipe NACA, Laboratoire PSITEC, EA 4072, UFR de Psychologie, Univ-Lille, Pont de Bois, Villeneuve d'Ascq, France.

Objective: We studied the clinical value of the faux pas test to diagnose behavioral-variant frontotemporal dementia.

Methods: The faux pas test was administered to patients referred to a memory clinic in a context of behavioral disturbances. The diagnosis of behavioral-variant frontotemporal dementia (n = 14) or not (n = 25) was confirmed after a 3 years follow-up.

Results: The faux pas test displayed a high sensitivity for behavioral-variant frontotemporal dementia (.83) however its specificity was only moderate (.64).

Conclusions: Our results confirm that the FPT capture's specific cognitive impairments in patients with behavioral-variant frontotemporal dementia. However, some patients with psychiatric disease or other neurological diseases may also show impaired scores.
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http://dx.doi.org/10.1177/0891988720964253DOI Listing
October 2020

Diagnosis of severe cognitive disorder: the family history as a key issue.

Neurol Sci 2020 Jul 21;41(7):1945-1947. Epub 2020 Jan 21.

Department of Neurology, Univ.Lille, INSERM U1171 Degenerative and Vascular Cognitive Disorders, F-59000, Lille, France.

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http://dx.doi.org/10.1007/s10072-019-04226-2DOI Listing
July 2020

Profile of and risk factors for poststroke cognitive impairment in diverse ethnoregional groups.

Neurology 2019 12 11;93(24):e2257-e2271. Epub 2019 Nov 11.

From the Centre for Healthy Brain Ageing (J.W.L., J.D.C., R.J.C., H.B., D.M.L., N.A.K., P.S.S.), University of New South Wales, Sydney, Australia; Department of Neurology and Laboratory of Functional Neurosciences (O.G., M.B., M.R.), University Hospital of Amiens, France; Clinical Neurosciences (H.J., S.M., T.E.), Neurology, University of Helsinki and Helsinki University Hospital, Finland; Department of Internal Medicine (S.M.), Gerontology and Geriatrics Section, and Department of Cardiology (J.W.J.), Leiden University Medical Center, the Netherlands; Department of Neurology (S.M., B.S.), Feinberg School of Medicine, Northwestern University, Chicago, IL; Department of Neurology (H.-J.B.), Seoul National University School of Medicine, Seoul National University Bundang Hospital, Seongnam; Department of Neurology (J.-S.L., B.-C.L.), Hallym University Sacred Heart Hospital, Anyang, Republic of Korea; Department of Psychiatry and Neuropsychology (S.K., E.D.), School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University; Department of Neurology (J.S.), Cardiovascular Research Institute Maastricht, Maastricht University Medical Center, the Netherlands; Memory Aging and Cognition Centre (C.C., X.X., E.J.C.), Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore; Centre for Population Health Sciences (X.X.), Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; Neuroscience and Ageing Research Unit (R.O.A., A.O.), Institute for Advanced Medical Research and Training, and Department of Medicine (R.O.A.), College of Medicine, University of Ibadan, Nigeria; Institute of Neuroscience (R.N.K.), Newcastle University, Newcastle Upon Tyne, UK; Peninsula Clinical School (V.K.S., C.M.), Central Clinical School, Monash University; Department of Aged Care (C.M.), Alfred Health, Melbourne, Australia; National Neuroscience Institute (N.K., R.J.C.); Duke-NUS Medical School (N.K.), Singapore; Dementia Collaborative Research Centre (H.B., P.S.S.), University of New South Wales, Sydney, Australia; and University of Lille (R.B., S.B., H.H.), Inserm, CHU Lille, U1171-Degenerative & Vascular Cognitive Disorders, France.

Objective: To address the variability in prevalence estimates and inconsistencies in potential risk factors for poststroke cognitive impairment (PSCI) using a standardized approach and individual participant data (IPD) from international cohorts in the Stroke and Cognition Consortium (STROKOG) consortium.

Methods: We harmonized data from 13 studies based in 8 countries. Neuropsychological test scores 2 to 6 months after stroke or TIA and appropriate normative data were used to calculate standardized cognitive domain scores. Domain-specific impairment was based on percentile cutoffs from normative groups, and associations between domain scores and risk factors were examined with 1-stage IPD meta-analysis.

Results: In a combined sample of 3,146 participants admitted to hospital for stroke (97%) or TIA (3%), 44% were impaired in global cognition and 30% to 35% were impaired in individual domains 2 to 6 months after the index event. Diabetes mellitus and a history of stroke were strongly associated with poorer cognitive function after covariate adjustments; hypertension, smoking, and atrial fibrillation had weaker domain-specific associations. While there were no significant differences in domain impairment among ethnoracial groups, some interethnic differences were found in the effects of risk factors on cognition.

Conclusions: This study confirms the high prevalence of PSCI in diverse populations, highlights common risk factors, in particular diabetes mellitus, and points to ethnoracial differences that warrant attention in the development of prevention strategies.
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http://dx.doi.org/10.1212/WNL.0000000000008612DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6937495PMC
December 2019

Texture Features of Magnetic Resonance Images: an Early Marker of Post-stroke Cognitive Impairment.

Transl Stroke Res 2020 08 1;11(4):643-652. Epub 2019 Nov 1.

Laboratoire de Pharmacologie, Faculté de Médecine, University of Lille, INSERM, CHU Lille, U1171, Degenerative & Vascular Cognitive Disorders, 1, Place de Verdun, 59000, Lille, France.

Stroke is frequently associated with delayed, long-term cognitive impairment (CI) and dementia. Recent research has focused on identifying early predictive markers of CI occurrence. We carried out a texture analysis of magnetic resonance (MR) images to identify predictive markers of CI occurrence based on a combination of preclinical and clinical data. Seventy-two-hour post-stroke T1W MR images of 160 consecutive patients were examined, including 75 patients with confirmed CI at the 6-month post-stroke neuropsychological examination. Texture features were measured in the hippocampus and entorhinal cortex and compared between patients with CI and those without. A correlation study determined their association with MoCA and MMSE clinical scores. Significant features were then combined with the classical prognostic factors, age and gender, to build a machine learning algorithm as a predictive model for CI occurrence. A middle cerebral artery transient occlusion model was used. Texture features were compared in the hippocampus of sham and lesioned rats and were correlated with histologically assessed neural loss. In clinical studies, two texture features, kurtosis and inverse difference moment, differed significantly between patients with and without CI and were significantly correlated with MoCA and MMSE scores. The prediction model had an accuracy of 88 ± 3%. The preclinical model revealed a significant correlation between texture features and neural density in the hippocampus contralateral to the ischemic area. These preliminary results suggest that texture features of MR images are representative of neural alteration and could be a part of a screening strategy for the early prediction of post-stroke CI.
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http://dx.doi.org/10.1007/s12975-019-00746-3DOI Listing
August 2020

Corrigendum: Somatostatin and Neuropeptide Y in Cerebrospinal Fluid: Correlations With Amyloid Peptides Aß, and Tau Proteins in Elderly Patients With Mild Cognitive Impairment.

Front Aging Neurosci 2019 19;11:11. Epub 2019 Feb 19.

Université Sorbonne Paris Cité, UMR-S894, INSERM Université Paris Descartes, Centre de Psychiatrie et Neuroscience, Paris, France.

[This corrects the article DOI: 10.3389/fnagi.2018.00297.].
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http://dx.doi.org/10.3389/fnagi.2019.00011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390179PMC
February 2019

Biological and imaging predictors of cognitive impairment after stroke: a systematic review.

J Neurol 2019 Nov 22;266(11):2593-2604. Epub 2018 Oct 22.

Degenerative and Vascular Cognitive Disorders, CHU Lille, Department of Neurology, Roger Salengro Hospital, University Lille, Inserm U1171, 59000, Lille, France.

Background: Cognitive impairment is frequent after stroke, and several studies have suggested that biological and imaging characteristics present before stroke are associated with the development of post-stroke cognitive impairment.

Objective: The aim of our study was to systematically review biological and imaging predictors of cognitive impairment after stroke.

Method: Studies were identified from bibliographic databases and reference lists, and were included if conducted in patients with acute stroke, with at least 30 patients, and a follow-up of at least 3 months. We included articles on potential biomarkers of cognitive impairment that pre-existed to stroke.

Results: We identified 22,169 articles, including 20,349 with abstract. After analysis, 66 studies conducted in 42 cohorts met selection criteria. They included 30-9522 patients [median 170; interquartile range (IQR) 104-251] with a median follow-up of 12 months (IQR 3-36). All studies met quality criteria for description of the study population and standardization of biomarkers. Twenty-nine studies met all quality criteria. There was no convincing evidence that any biological marker may predict cognitive impairment. The most consistent predictors of cognitive impairment after stroke were global atrophy and medial temporal lobe atrophy.

Conclusion: Pre-existing cerebral atrophy is the most consistent predictor of cognitive impairment that can be identified in patients with an acute stroke.
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http://dx.doi.org/10.1007/s00415-018-9089-zDOI Listing
November 2019

Early MoCA predicts long-term cognitive and functional outcome and mortality after stroke.

Neurology 2018 11 17;91(20):e1838-e1850. Epub 2018 Oct 17.

From the Institute for Stroke and Dementia Research (V.Z., M.K.G., C.M., A.K., F.A.W., M.D.), University Hospital, Ludwig-Maximilians-University, Munich, Germany; University of Lille (T.D., A.-M.M., H.H., S.B., R.B.), Inserm, CHU Lille, "Degenerative and Vascular Cognitive Disorders", Lille, France; German Centre for Neurodegenerative Diseases (M.D.); and Munich Cluster for Systems Neurology (M.D.), Germany.

Objective: To examine whether the Montreal Cognitive Assessment (MoCA) administered within 7 days after stroke predicts long-term cognitive impairment, functional impairment, and mortality.

Methods: MoCA was administered to 274 patients from 2 prospective hospital-based cohort studies in Germany (n = 125) and France (n = 149). Cognitive and functional outcomes were assessed at 6, 12, and 36 months after stroke by comprehensive neuropsychological testing, the Clinical Dementia Rating (CDR) scale, the modified Rankin Scale (mRS), and Instrumental Activities of Daily Living (IADL) and analyzed with generalized estimating equations. All-cause mortality was investigated by Cox proportional hazard models. Analyses were adjusted for demographic variables, education, vascular risk factors, premorbid cognitive status, and NIH Stroke Scale scores. The additive predictive value of MoCA was examined with receiver operating characteristic curves.

Results: In pooled analyses, a baseline MoCA score <26 was associated with cognitive impairment, defined by neuropsychological testing (odds ratio [OR] 5.30, 95% confidence interval [CI] 2.75-10.22) and by CDR score ≥0.5 (OR 2.53, 95% CI 1.53-4.18); functional impairment, defined by mRS score >2 (OR 5.03, 95% CI 2.20-11.51) and by IADL score <8 (OR 2.48, 95% CI 1.40-4.38); and mortality (hazard ratio 7.24, 95% CI 1.99-26.35) across the 3-year follow-up. Patients with MoCA score <26 performed worse across all prespecified cognitive domains (executive function/attention, memory, language, visuospatial ability). MoCA increased the area under the curve for predicting cognitive impairment (neuropsychological testing 0.81 vs 0.72, = 0.01) and functional impairment (mRS score >2, 0.88 vs 0.84, = 0.047).

Conclusion: Early cognitive testing by MoCA predicts long-term cognitive outcome, functional outcome, and mortality after stroke. Our results support routine use of the MoCA in stroke patients.
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http://dx.doi.org/10.1212/WNL.0000000000006506DOI Listing
November 2018

Somatostatin and Neuropeptide Y in Cerebrospinal Fluid: Correlations With Amyloid Peptides Aβ and Tau Proteins in Elderly Patients With Mild Cognitive Impairment.

Front Aging Neurosci 2018 1;10:297. Epub 2018 Oct 1.

Université Sorbonne Paris Cité, UMR-S894, INSERM Université Paris Descartes, Centre de Psychiatrie et Neuroscience, Paris, France.

A combination of low cerebrospinal fluid (CSF) Amyloid β (Aβ) and high Total-Tau (T-Tau) and Phosphorylated-Tau (P-Tau) occurs at a prodromal stage of Alzheimer's disease (AD) and recent findings suggest that network abnormalities and interneurons dysfunction contribute to cognitive deficits. Somatostatin (SOM) and Neuropeptide Y (NPY) are two neuropeptides which are expressed in GABAergic interneurons with different fates in AD the former only being markedly affected. The aim of this study was to analyze CSF SOM, NPY and CSF Aβ; T-Tau, P-Tau relationships in 43 elderly mild cognitively impairment (MCI) participants from the Biomarker of AmyLoïd pepTide and AlZheimer's disease Risk (BALTAZAR) cohort. In these samples, CSF SOM and CSF Aβ on the one hand, and CSF NPY and CSF T-Tau and P-Tau on the other hand are positively correlated. CSF SOM and NPY concentrations should be further investigated to determine if they can stand for early AD biomarkers. Clinical Trial Registration: www.ClinicalTrials.gov, identifier #NCT01315639.
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http://dx.doi.org/10.3389/fnagi.2018.00297DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174237PMC
October 2018

The relationship between CSF biomarkers and cerebral metabolism in early-onset Alzheimer's disease.

Eur J Nucl Med Mol Imaging 2019 02 28;46(2):324-333. Epub 2018 Aug 28.

Nuclear Medicine Department, CHU Lille, F-59000, Lille, France.

Purpose: One can reasonably suppose that cerebrospinal spinal fluid (CSF) biomarkers can identify distinct subgroups of Alzheimer's disease (AD) patients. In order to better understand differences in CSF biomarker patterns, we used FDG PET to assess cerebral metabolism in CSF-based subgroups of AD patients.

Methods: Eighty-five patients fulfilling the criteria for probable early-onset AD (EOAD) underwent lumbar puncture, brain F-FDG PET and MRI. A cluster analysis was performed, with the CSF biomarkers for AD as variables. Vertex-wise, partial-volume-corrected metabolic maps were computed for the patients and compared between the clusters of patients. Linear correlations between each CSF biomarker and the metabolic maps were assessed.

Results: Three clusters emerged. The "Aβ42" cluster contained 32 patients with low levels of Aβ42, while tau and p-tau remained within the normal range. The "Aβ42 + tau" cluster contained 41 patients with low levels of Aβ42 and high levels of tau and p-tau. Lastly, the "tau" cluster contained 12 patients with very high levels of tau and p-tau and low-normal levels of Aβ42. There were no inter-cluster differences in age, sex ratio, educational level, APOE genotype, disease duration or disease severity. The "Aβ42 + tau" and "tau" clusters displayed more marked frontal hypometabolism than the "Aβ42" cluster did, and frontal metabolism was significantly negatively correlated with the CSF tau level. The "Aβ42" and "Aβ42 + tau" clusters displayed more marked hypometabolism in the left occipitotemporal region than the "tau" cluster did, and metabolism in this region was significantly and positively correlated with the CSF Aβ42 level.

Conclusion: The CSF biomarkers can be used to identify metabolically distinct subgroups of patients with EOAD. Future research should seek to establish whether these biochemical differences have clinical consequences.
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http://dx.doi.org/10.1007/s00259-018-4113-1DOI Listing
February 2019

Identification of a specific functional network altered in poststroke cognitive impairment.

Neurology 2018 05 20;90(21):e1879-e1888. Epub 2018 Apr 20.

From Université Lille, INSERM, CHU Lille, U1171-Degenerative and Vascular Cognitive Disorders, Lille, France.

Objective: To study the association between poststroke cognitive impairment and defining a specific resting functional marker.

Methods: The resting-state functional connectivity 6 months after an ischemic stroke in 56 patients was investigated. Twenty-nine of the patients who had an impairment of one or several cognitive domains were compared to 27 without any cognitive deficit. We studied the whole-brain connectivity using 2 complementary approaches: graph theory to study the functional network organization and network-based statistics to explore connectivity between brain regions. We assessed the potential cortical atrophy using voxel-based morphometry analysis.

Results: The overall topological organization of the functional network was not altered in cognitively impaired stroke patients, who had the same mean node degree, average clustering coefficient, and global efficiency as cognitively healthy stroke patients. Network-based statistics analysis showed that poststroke cognitive impairment was associated with dysfunction of a whole-brain network composed of 167 regions and 178 connections, and functional disconnections between superior, middle, and inferior frontal gyri and the superior and inferior temporal gyri. These regions had connections that were specifically and positively correlated with cognitive domain scores. No intergroup differences in overall gray matter thickness and ischemic infarct topography were observed. To assess the effect of prestroke white matter hyperintensities on connectivity, we included the initial Fazekas scale in the regression model for a second network-based analysis. The resulting network was associated with the same key alterations but had fewer connections.

Conclusions: The observed functional network alterations suggest that the appearance of a cognitive impairment following stroke may be associated with a particular functional alteration, shared specifically between cognitive domains.
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http://dx.doi.org/10.1212/WNL.0000000000005553DOI Listing
May 2018

Plasma amyloid levels within the Alzheimer's process and correlations with central biomarkers.

Alzheimers Dement 2018 07 17;14(7):858-868. Epub 2018 Feb 17.

Memory Resource and Research Centre of Montpellier, Department of Neurology, CHU Gui de Chauliac, Université de Montpellier, Montpellier, France.

Introduction: Diagnostic relevance of plasma amyloid β (Aβ) for Alzheimer's disease (AD) process yields conflicting results. The objective of the study was to assess plasma levels of Aβ and Aβ in amnestic mild cognitive impairment (MCI), nonamnestic MCI, and AD patients and to investigate relationships between peripheral and central biomarkers.

Methods: One thousand forty participants (417 amnestic MCI, 122 nonamnestic MCI, and 501 AD) from the Biomarker of AmyLoïd pepTide and AlZheimer's diseAse Risk multicenter prospective study with cognition, plasma, cerebrospinal fluid (CSF), and magnetic resonance imaging assessments were included.

Results: Plasma Aβ and Aβ were lower in AD (36.9 [11.7] and 263 [80] pg/mL) than in amnestic MCI (38.2 [11.9] and 269 [68] pg/mL) than in nonamnestic MCI (39.7 [10.5] and 272 [52] pg/mL), respectively (P = .01 for overall difference between groups for Aβ and P = .04 for Aβ). Globally, plasma Aβ correlated with age, Mini-Mental State Examination, and APOE ε4 allele. Plasma Aβ correlated with all CSF biomarkers in MCI but only with CSF Aβ in AD.

Discussion: Plasma Aβ was associated with cognitive status and CSF biomarkers, suggesting the interest of plasma amyloid biomarkers for diagnosis purpose.
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http://dx.doi.org/10.1016/j.jalz.2018.01.004DOI Listing
July 2018

Cerebrospinal fluid Alzheimer biomarkers can be useful for discriminating dementia with Lewy bodies from Alzheimer's disease at the prodromal stage.

J Neurol Neurosurg Psychiatry 2018 05 10;89(5):467-475. Epub 2018 Jan 10.

Neuropsychology Unit, Neurology Service, and CNRS, ICube Laboratory UMR 7357 and FMTS, Team IMIS/Neurocrypto, University Hospital of Strasbourg, CMRR (Memory Resources and Research Centre), Geriatrics Day Hospital, Geriatrics Service, Strasbourg, France.

Background: Differential diagnosis between dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) is not straightforward, especially in the early stages of disease. We compared AD biomarkers (phospho-Tau, total-Tau, Aβ42 and Aβ40) in cerebrospinal fluid (CSF) of patients with DLB and AD, focusing especially on the prodromal stage.

Methods: A total of 1221 CSF were collected in different memory centres (ePLM network) in France and analysed retrospectively. Samples were obtained from patients with prodromal DLB (pro-DLB; n=57), DLB dementia (DLB-d; n=154), prodromal AD (pro-AD; n=132) and AD dementia (n=783), and control subjects (CS; n=95). These centres use the same diagnostic procedure and criteria to evaluate the patients.

Results: In patients with pro-DLB, CSF Aβ42 levels appeared much less disrupted than in patients at the demented stage (DLB-d) (P<0.05 CS>pro-DLB; P<0.001 CS>DLB-d). On average, Aβ40 levels in patients with DLB (pro-DLB and DLB-d) were much below those in patients with pro-AD (P<0.001 DLB groups
Conclusions: Reduced levels of CSF Aβ42 were found in patients with DLB but rather at a later stage, reaching those of patients with AD, in whom Aβ42 levels were decreased even at the prodromal stage. At the prodromal stage of DLB, the majority of patients presented a normal CSF profile. CSF t-Tau and phospho-Tau were the best biomarkers to discriminate between AD and DLB, whatever the stage of disease.
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http://dx.doi.org/10.1136/jnnp-2017-316385DOI Listing
May 2018

Relevance of Follow-Up in Patients with Core Clinical Criteria for Alzheimer Disease and Normal CSF Biomarkers.

Curr Alzheimer Res 2018 ;15(7):691-700

University Lille, Inserm U1171, Centre Memoire de Ressources et de Recherche & CNR-MAJ, CHU Lille, F-59000 Lille, France.

Background: Few patients with a normal cerebrospinal fluid (CSF) biomarker profile fulfill the clinical criteria for Alzheimer disease (AD).

Objective: The aim of this study was to test the hypothesis of misdiagnoses for these patients.

Method: Patients from the e-PLM centers fulfilling the core clinical criteria for probable AD dementia or mild cognitive impairment due to AD (AD-MCI), with normal CSF Aβ1-42, T-tau and P-tau biomarkers and clinical follow-up, were included. Clinical and imaging data were reviewed by an independent board, from baseline (visit with clinical evaluation and CSF analysis) to the end of the follow-up, for a final diagnosis.

Results: In the e-PLM cohort of 1098 AD patients with CSF analysis, 37 (3.3%) patients (20 with AD dementia core clinical criteria and 17 with AD-MCI core clinical criteria) had normal CSF biomarker profile and a clinical follow-up. All patients presented with episodic memory impairment and 27 (73%) had medial temporal lobe atrophy on MRI-scan. After a median follow-up of 36 months (range 7-74), the final diagnosis was AD MCI or dementia for 9 (24%) patients, and unlikely due to AD for 28 (76%) patients. A misdiagnosis was corrected in 18 (49%) patients (mood disorders, non-AD degenerative dementia, vascular cognitive impairment, alcohol cognitive disorders, temporal epilepsy and hippocampal sclerosis), and 10 (27%) patients had cognitive disorders of undetermined etiology.

Conclusion: AD diagnosis (MCI or dementia) with normal CSF biomarkers is a rare condition. A clinical follow- up is particularly recommended to consider an alternative diagnosis.
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http://dx.doi.org/10.2174/1567205015666180110113238DOI Listing
May 2019

STROKOG (stroke and cognition consortium): An international consortium to examine the epidemiology, diagnosis, and treatment of neurocognitive disorders in relation to cerebrovascular disease.

Alzheimers Dement (Amst) 2017 18;7:11-23. Epub 2016 Nov 18.

Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, Sydney, Australia.

Introduction: The Stroke and Cognition consortium (STROKOG) aims to facilitate a better understanding of the determinants of vascular contributions to cognitive disorders and help improve the diagnosis and treatment of vascular cognitive disorders (VCD).

Methods: Longitudinal studies with ≥75 participants who had suffered or were at risk of stroke or TIA and which evaluated cognitive function were invited to join STROKOG. The consortium will facilitate projects investigating rates and patterns of cognitive decline, risk factors for VCD, and biomarkers of vascular dementia.

Results: Currently, STROKOG includes 25 (21 published) studies, with 12,092 participants from five continents. The duration of follow-up ranges from 3 months to 21 years.

Discussion: Although data harmonization will be a key challenge, STROKOG is in a unique position to reuse and combine international cohort data and fully explore patient level characteristics and outcomes. STROKOG could potentially transform our understanding of VCD and have a worldwide impact on promoting better vascular cognitive outcomes.
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http://dx.doi.org/10.1016/j.dadm.2016.10.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5257024PMC
November 2016

Cognitive status after intracerebral haemorrhage - Authors' reply.

Lancet Neurol 2016 11 11;15(12):1206-1207. Epub 2016 Oct 11.

Université Lille, Inserm U1171, Degenerative and Vascular Cognitive Disorders, CHU Lille, Department of Neurology, Lille, France. Electronic address:

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http://dx.doi.org/10.1016/S1474-4422(16)30239-3DOI Listing
November 2016

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

Hum Brain Mapp 2017 01 13;38(1):12-26. Epub 2016 Aug 13.

Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy.

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.
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http://dx.doi.org/10.1002/hbm.23350DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493991PMC
January 2017

Influence of Medication on Fatigue Six Months after Stroke.

Stroke Res Treat 2016 19;2016:2410921. Epub 2016 Jun 19.

Degenerative & Vascular Cognitive Disorders, Univ. Lille, INSERM U1171, 59000 Lille, France; Department of Neurology, Lille University Hospital, 59000 Lille, France.

Poststroke fatigue (PSF) is frequent and affects patients' quality of life. Medication use was hypothesized as being responsible for PSF. Our objective was to evaluate potential relationships between 6-month PSF and medication use at discharge and 6 months after an ischemic stroke. This study is part of STROKDEM, an ongoing longitudinal cohort study, whose main aim is to determine predictors of poststroke dementia. Patients were included within 72 hours after an ischemic stroke and followed up with standardized evaluations. Medication use 7 days and 6 months after stroke was rated, and polypharmacy was defined as the number of categories of treatments received by a patient. PSF was evaluated using the Chalder Fatigue Scale. Medical history, vascular risk factors, depression, anxiety, and sleep disturbances were evaluated. One hundred and fifty-three patients were included: 52.9% presented PSF. PSF at 6 months was not predicted by medication use at discharge nor associated with medication use at month 6. We found severity of PSF to be increased in patients with polypharmacy. Our results suggest that PSF is not a side effect of drugs use, which more reflects presence of disturbances frequently observed after stroke such as depression, anxiety, or sleep disturbances. Clinical study is registered on clinicaltrials.gov (NCT01330160).
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http://dx.doi.org/10.1155/2016/2410921DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930814PMC
July 2016

Dementia risk after spontaneous intracerebral haemorrhage: a prospective cohort study.

Lancet Neurol 2016 07 28;15(8):820-829. Epub 2016 Apr 28.

Université Lille, Inserm U1171, Degenerative and Vascular Cognitive Disorders, CHU Lille, Department of Neurology, Lille, France. Electronic address:

Background: Dementia occurs in at least 10% of patients within 1 year after stroke. However, the risk of dementia after spontaneous intracerebral haemorrhage that accounts for about 15% of all strokes has not been investigated in prospective studies. We aimed to determine the incidence of dementia and risk factors after an intracerebral haemorrhage.

Methods: We did a prospective observational cohort study in patients with spontaneous intracerebral haemorrhage from the Prognosis of Intracerebral Haemorrhage (PITCH) cohort who were admitted to Lille University Hospital, Lille, France. We included patients aged 18 years and older with parenchymal haemorrhage on the first CT scan. Exclusion criteria were pure intraventricular haemorrhage; intracerebral haemorrhage resulting from intracranial vascular malformation, intracranial venous thrombosis, head trauma, or tumour; haemorrhagic transformation within an infarct; and referral from other hospitals. Median follow-up was 6 years. We studied risk factors (clinical and neuroradiological [MRI] biomarkers) of new-onset dementia as per a prespecified subgroup analysis, according to intracerebral haemorrhage location. Dementia diagnosis was based on the National Institute on Aging-Alzheimer's Association criteria for all-cause dementia. We did multivariable analyses using competing risk analyses, with death during follow-up as a competing event.

Findings: From the 560 patients with spontaneous intracerebral haemorrhage enrolled in the PITCH cohort between Nov 3, 2004 and March 29, 2009, we included 218 patients (median age 67·5 years) without pre-existing dementia who were alive at 6 months follow-up. 63 patients developed new-onset dementia leading to an incidence rate of 14·2% (95% CI 10·0-19·3) at 1 year after intracerebral haemorrhage, and incidence reached 28·3% (22·4-34·5) at 4 years. The incidence of new-onset dementia was more than two times higher in patients with lobar intracerebral haemorrhage (incidence at 1 year 23·4%, 14·6-33·3) than for patients with non-lobar intracerebral haemorrhage (incidence at 1 year 9·2%, 5·1-14·7). Disseminated superficial siderosis (subhazard ratio [SHR] 7·45, 95% CI 4·27-12·99), cortical atrophy score (SHR per 1-point increase 2·61, 1·70-4·01), a higher number of cerebral microbleeds (SHR for >5 cerebral microbleeds 2·33, 1·38-3·94), and older age (SHR per 10-year increase 1·34, 1·00-1·79) were risk factors of new-onset dementia.

Interpretation: There is a substantial risk of incident dementia in dementia-free survivors of spontaneous intracerebral haemorrhage; our results suggest that underlying cerebral amyloid angiopathy is a contributing factor to the occurrence of new-onset dementia. Future clinical trials including patients with intracerebral haemorrhage should assess cognitive endpoints.

Funding: French Ministry of Education, Research, and Technology, Adrinord, Inserm U1171.
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http://dx.doi.org/10.1016/S1474-4422(16)00130-7DOI Listing
July 2016

Test-retest reliability of the default mode network in a multi-centric fMRI study of healthy elderly: Effects of data-driven physiological noise correction techniques.

Hum Brain Mapp 2016 06 17;37(6):2114-32. Epub 2016 Mar 17.

Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy.

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016. © 2016 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/hbm.23157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6867386PMC
June 2016

Differential Diagnosis of Dementia with High Levels of Cerebrospinal Fluid Tau Protein.

J Alzheimers Dis 2016 ;51(3):905-13

Department of Neurology, Rouen University Hospital, Rouen, France.

Background: Total Tau concentration in cerebrospinal fluid (CSF) is widely used as a biomarker in the diagnosis of neurodegenerative process primarily in Alzheimer's disease (AD). A particularly high Tau level may indicate AD but may also be associated with Creutzfeldt-Jakob disease (CJD). In such situations little is known about the distribution of differential diagnoses.

Objective: Our study aimed to describe the different diagnoses encountered in clinical practice for patients with dementia and CSF Tau levels over 1000 pg/ml. We studied the p-Tau/Tau ratio to specify its ability to distinguish AD from CJD.

Methods: Patients (n = 202) with CSF Tau levels over 1000 pg/ml were recruited in three memory clinics in France. All diagnoses were made using the same diagnostic procedure and criteria.

Results: Patients were diagnosed with AD (n = 148, 73.2%), mixed dementia (n = 38, 18.8%), CJD, vascular dementia (n = 4, 2.0% for each), Lewy body dementia, and frontotemporal dementia (n = 3, 1.5% for each). Dispersion of CSF Tau levels clearly showed an overlap between all diagnoses. Using the p-Tau/Tau ratio suggestive of CJD (<0.075), all CJD patients were correctly categorized and only two AD patients were miscategorized. This ratio was highly associated with CJD compared to AD (p < 0.0001).

Conclusion: Our study showed that in clinical practice, extremely high CSF Tau levels are mainly related to diagnosis of AD. CJD patients represent a minority. Our results support a sequential interpretation algorithm for CSF biomarkers in dementia. High CSF Tau levels should alert clinicians to check the p-Tau/Tau ratio to consider a probable diagnosis of CJD.
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http://dx.doi.org/10.3233/JAD-151111DOI Listing
December 2016

Multiple Simultaneous Spontaneous Intracerebral Hemorrhages: A Rare Entity.

Cerebrovasc Dis 2016 16;41(1-2):74-9. Epub 2015 Dec 16.

Department of Neurology, University of Lille, UDSL, CHU Lille, INSERM U 1171, Lille, France.

Background: In hospital databases, multiple simultaneous spontaneous intracerebral hemorrhages (ICH-m) account for 0.7-5.6% of all ICHs. Their long-term outcome has never been systematically and prospectively investigated. We aimed at identifying the long-term outcome of patients with ICH-m.

Methods: We prospectively recruited consecutive adults with ICH-m and followed them up for at least 4.5 years. We classified patients into the following 3 groups: (i) definite or probable cerebral amyloid angiopathy (CAA), (ii) deep perforating vasculopathy (DPV) and (iii) unknown causes.

Results: Of 562 consecutive patients with ICH, 32 had ICH-m (5.7%): 8 (25%) with probable CAA, 5 (16%) with DPV and 19 (59%) with ICH-m of undetermined cause. At the last visit (cumulative follow-up of 39.5 person-year), 27 patients (84%) had died, and 3 of the 5 survivors were independent. Late-onset seizures, recurrent ICH-m (symptomatic or not) and new brain microbleeds were mainly found in patients with probable CAA.

Conclusions: ICH-m is a rare but extremely severe expression of ICH. Survivors with CAA are more likely to develop late seizures and new hemorrhagic lesions. Because of low survival rates, large multicenter cohort studies are needed for a better understanding of this rare condition.
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http://dx.doi.org/10.1159/000442475DOI Listing
November 2016

Aβ1-40 and Aβ1-42 Plasmatic Levels In Stroke: Influence of Pre-Existing Cognitive Status and Stroke Characteristics.

Curr Alzheimer Res 2017 ;14(6):686-694

Department of Neurology, Stroke Unit, Roger Salengro Hospital, Rue Emile Laine, F-59037 Lille, France.

Many stroke patients have pre-existing cognitive impairment. Plasma amyloid β peptides (Aβ) - possible biomarkers of Alzheimer's pathology - induce vascular dysfunction. Our objective was to evaluate factors influencing plasma Aβ1-40 and Aβ1-42 peptides in a cohort of stroke patients. In the Biostroke study (ClinicalTrials.gov Identifier: NCT00763217), we collected vascular risk factors, neuroimaging features and biological tests including Aβ1-40 and Aβ1-42. We used the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) to systematically assess the pre-existing cognitive status. Of 403 patients (371 ischemia), 25 met criteria for pre-existing dementia, 142 for pre-existing cognitive decline-no-dementia, and 236 had no PCoI. Aβ1-42 was independently associated with PCoI (odds ratio 0.973; 95% confidence interval: 0.950-0.996; p=0.024). Factors associated with plasma Aβ1- 40 were age, smoking and diabetes mellitus. After exclusion of hemorrhagic strokes, the results remained unchanged, but blood samples taken less than 12 hours after onset were associated with lower plasma Aβ1-40. Our results support a dissociated response of the 2 plasma Aβ peptides in stroke patients, plasma Aβ1-40 being involved in vascular aspects whereas Aβ1-42 might be involved in neurodegenerative processes.
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http://dx.doi.org/10.2174/1567205012666151027141730DOI Listing
April 2018

Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study.

Neuroimage 2016 Jan 9;124(Pt A):442-454. Epub 2015 Jul 9.

LENITEM Laboratory of Epidemiology, Neuroimaging, & Telemedicine, IRCCS San Giovanni di Dio-FBF, Brescia, Italy; Memory Clinic and LANVIE, Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland.

To date, limited data are available regarding the inter-site consistency of test-retest reproducibility of functional connectivity measurements, in particular with regard to integrity of the Default Mode Network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3.0T using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test-retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test-retest reproducibility in the consortium was high (ICC=0.81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test-retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (≈4% test-retest error, ICC=0.85), the medial frontal cortex the least reliable (≈12%, ICC=0.82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response.
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http://dx.doi.org/10.1016/j.neuroimage.2015.07.010DOI Listing
January 2016

Factors Associated with Poststroke Fatigue: A Systematic Review.

Stroke Res Treat 2015 25;2015:347920. Epub 2015 May 25.

Department of Neurology, Stroke Center, University of Lille, INSERM U1171, 59045 Lille, France.

Background. Poststroke fatigue (PSF) is a frequent, disabling symptom that lacks a consensual definition and a standardized evaluation method. The (multiple) causes of PSF have not been formally characterized. Objective. To identify factors associated with PSF. Method. A systematic review of articles referenced in MEDLINE. Only original studies having measured PSF and potentially associated factors were included. Data was extracted from articles using predefined data fields. Results. Although PSF tends to be more frequent in female patients and older patients, sociodemographic factors do not appear to have a major impact. There are strong associations between PSF and emotional disturbances (such as depression and anxiety). PSF may also be linked to attentional disturbances (mainly slowing in processing speed). The literature data have failed to demonstrate a clear impact of the type and severity of stroke. It has been suggested that PSF results from alterations in the frontothalamostriatal system and/or inflammatory processes. Pain, sleep disorders, and prestroke fatigue also appeared to be associated with PSF. Implications. A better understanding of PSF may improve stroke patient care and facilitate the development of effective treatments.
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http://dx.doi.org/10.1155/2015/347920DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4458555PMC
June 2015

Longitudinal reproducibility of automatically segmented hippocampal subfields: A multisite European 3T study on healthy elderly.

Hum Brain Mapp 2015 Sep 3;36(9):3516-27. Epub 2015 Jun 3.

Center for Mind/Brain Sciences (CIMEC), University of Trento, Rovereto, Italy.

Recently, there has been an increased interest in the use of automatically segmented subfields of the human hippocampal formation derived from magnetic resonance imaging (MRI). However, little is known about the test-retest reproducibility of such measures, particularly in the context of multisite studies. Here, we report the reproducibility of automated Freesurfer hippocampal subfields segmentations in 65 healthy elderly enrolled in a consortium of 13 3T MRI sites (five subjects per site). Participants were scanned in two sessions (test and retest) at least one week apart. Each session included two anatomical 3D T1 MRI acquisitions harmonized in the consortium. We evaluated the test-retest reproducibility of subfields segmentation (i) to assess the effects of averaging two within-session T1 images and (ii) to compare subfields with whole hippocampus volume and spatial reliability. We found that within-session averaging of two T1 images significantly improved the reproducibility of all hippocampal subfields but not that of the whole hippocampus. Volumetric and spatial reproducibility across MRI sites were very good for the whole hippocampus, CA2-3, CA4-dentate gyrus (DG), subiculum (reproducibility error∼2% and DICE > 0.90), good for CA1 and presubiculum (reproducibility error ∼ 5% and DICE ∼ 0.90), and poorer for fimbria and hippocampal fissure (reproducibility error ∼ 15% and DICE < 0.80). Spearman's correlations confirmed that test-retest reproducibility improved with volume size. Despite considerable differences of MRI scanner configurations, we found consistent hippocampal subfields volumes estimation. CA2-3, CA4-DG, and sub-CA1 (subiculum, presubiculum, and CA1 pooled together) gave test-retest reproducibility similar to the whole hippocampus. Our findings suggest that the larger hippocampal subfields volume may be reliable longitudinal markers in multisite studies.
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http://dx.doi.org/10.1002/hbm.22859DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6869769PMC
September 2015

Cerebrospinal fluid amyloid-β 42/40 ratio in clinical setting of memory centers: a multicentric study.

Alzheimers Res Ther 2015 1;7(1):30. Epub 2015 Jun 1.

Biochimie-Protéomique Clinique - IRB - CCBHM, INSERM U1040, Université de Montpellier, Montpellier, France.

Introduction: The cerebrospinal fluid (CSF) biomarkers amyloid-β (Aβ), tau and phosphorylated tau (p-tau181) are now used for the diagnosis of Alzheimer's disease (AD). Aβ40 is the most abundant Aβ peptide isoform in the CSF, and the Aβ 42/40 ratio has been proposed to better reflect brain amyloid production. However, its additional value in the clinical setting remains uncertain.

Methods: A total of 367 subjects with cognitive disorders who underwent a lumbar puncture were prospectively included at three French memory centers (Paris-North, Lille and Montpellier; the PLM Study). The frequency of positive, negative and indeterminate CSF profiles were assessed by various methods, and their adequacies with the diagnosis of clinicians were tested using net reclassification improvement (NRI) analyses.

Results: On the basis of local optimum cutoffs for Aβ42 and p-tau181, 22% of the explored patients had indeterminate CSF profiles. The systematic use of Aβ 42/40 ratio instead of Aβ42 levels alone decreased the number of indeterminate profiles (17%; P = 0.03), but it failed to improve the classification of subjects (NRI = -2.1%; P = 0.64). In contrast, the use of Aβ 42/40 ratio instead of Aβ42 levels alone in patients with a discrepancy between p-tau181 and Aβ42 led to a reduction by half of the number of indeterminate profiles (10%; P < 0.001) and was further in agreement with clinician diagnosis (NRI = 10.5%; P = 0.003).

Conclusions: In patients with a discrepancy between CSF p-tau181 and CSF Aβ42, the assessment of Aβ 42/40 ratio led to a reliable biological conclusion in over 50% of cases that agreed with a clinician's diagnosis.
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http://dx.doi.org/10.1186/s13195-015-0114-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450486PMC
June 2015

A diagnostic scale for Alzheimer's disease based on cerebrospinal fluid biomarker profiles.

Alzheimers Res Ther 2014 26;6(3):38. Epub 2014 Jun 26.

CHU de Montpellier and Université Montpellier I, IRMB, CCBHM, Laboratoire de Biochimie Protéomique Clinique, 80 Avenue Augustin Fliche, 34295 Montpellier, France ; Centre Mémoire Ressources Recherche Languedoc-Roussillon, CHU de Montpellier, Hôpital Gui de Chauliac, Montpellier, and Université Montpellier I, Montpellier, France.

Introduction: The relevance of the cerebrospinal fluid (CSF) biomarkers for the diagnosis of Alzheimer's disease (AD) and related disorders is clearly established. However, the question remains on how to use these data, which are often heterogeneous (not all biomarkers being pathologic). The objective of this study is to propose to physicians in memory clinics a biologic scale of probabilities that the patient with cognitive impairments has an Alzheimer's disease (AD) pathologic process.

Methods: For that purpose, we took advantage of the multicenter data of our Paris-North, Lille, and Montpellier (PLM) study, which has emerged through the initial sharing of information from these memory centers. Different models combining the CSF levels of amyloid-β 42, tau, and p-tau(181) were tested to generate categories of patients with very low (<10%), low (<25%), high (>75%), and very high predictive values (>90%) for positive AD. In total, 1,273 patients (646 AD and 627 non-AD) from six independent memory-clinic cohorts were included.

Results: A prediction model based on logistic regressions achieved a very good stratification of the population but had the disadvantages of needing mathematical optimization and being difficult to use in daily clinical practice. Remarkably, a simple and intuitive model based on the number (from zero to three) of three pathologic CSF biomarkers resulted in a very efficient predictive scale for AD in patients seen in memory clinics. The scale's overall predictive value for AD for the different categories were as follows: class 0, 9.6% (95% confidence interval (CI), 6.0% to 13.2%); class 1, 24.7% (95% CI, 18.0% to 31.3%); class 2, 77.2% (95% CI, 67.8% to 86.5%); and class 3, 94.2% (95% CI, 90.7% to 97.7%). In addition, with this scale, significantly more patients were correctly classified than with the logistic regression. Its superiority in model performance was validated by the computation of the net reclassification index (NRI). The model was also validated in an independent multicenter dataset of 408 patients (213 AD and 195 non-AD).

Conclusions: In conclusion, we defined a new scale that could be used to facilitate the interpretation and routine use of multivariate CSF data, as well as helping the stratification of patients in clinical research trials.
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http://dx.doi.org/10.1186/alzrt267DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4255520PMC
December 2014