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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., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Amyloid and tau pathological accumulation should be considered for Alzheimer's disease (AD) definition and before subjects' enrollment in disease-modifying trials. Although age, APOEε4, and sex influence cerebrospinal fluid (CSF) biomarker levels, none of these variables are considered by current normality/abnormality cutoffs. Using baseline CSF data from 2 independent cohorts (PharmaCOG/European Alzheimer's Disease Neuroimaging Initiative and Alzheimer's Disease Neuroimaging Initiative), we investigated the effect of age, APOEε4 status, and sex on CSF Aβ42/P-tau distribution and cutoff extraction by applying mixture models with covariates. The Aβ42/P-tau distribution revealed the presence of 3 subgroups (AD-like, intermediate, control-like) and 2 cutoffs. The identification of the intermediate subgroup and of the higher cutoff was APOEε4 dependent in both cohorts. APOE-specific classification (higher cutoff for APOEε4+, lower cutoff for APOEε4-) showed higher diagnostic accuracy in identifying MCI due to AD compared to single Aβ42 and Aβ42/P-tau cutoffs. APOEε4 influences amyloid and tau CSF markers and AD progression in MCI patients supporting i) the use of APOE-specific cutoffs to identify MCI due to AD and ii) the utility of considering APOE genotype for early AD diagnosis., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: amyloid-PET reading has been classically implemented as a binary assessment, although the clinical experience has shown that the number of borderline cases is non negligible not only in epidemiological studies of asymptomatic subjects but also in naturalistic groups of symptomatic patients attending memory clinics. In this work we develop a model to compare and integrate visual reading with two independent semi-quantification methods in order to obtain a tracer-independent multi-parametric evaluation., Methods: We retrospectively enrolled three cohorts of cognitively impaired patients submitted to 18 F-florbetaben (53 subjects), 18 F-flutemetamol (62 subjects), 18 F-florbetapir (60 subjects) PET/CT respectively, in 6 European centres belonging to the EADC. The 175 scans were visually classified as positive/negative following approved criteria and further classified with a 5-step grading as negative, mild negative, borderline, mild positive, positive by 5 independent readers, blind to clinical data. Scan quality was also visually assessed and recorded. Semi-quantification was based on two quantifiers: the standardized uptake value (SUVr) and the ELBA method. We used a sigmoid model to relate the grading with the quantifiers. We measured the readers accord and inconsistencies in the visual assessment as well as the relationship between discrepancies on the grading and semi-quantifications., Conclusion: It is possible to construct a map between different tracers and different quantification methods without resorting to ad-hoc acquired cases. We used a 5-level visual scale which, together with a mathematical model, delivered cut-offs and transition regions on tracers that are (largely) independent from the population. All fluorinated tracers appeared to have the same contrast and discrimination ability with respect to the negative-to-positive grading. We validated the integration of both visual reading and different quantifiers in a more robust framework thus bridging the gap between a binary and a user-independent continuous scale., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Valosin-containing protein (VCP) mutations are rare causes of autosomal dominant frontotemporal dementias associated with Paget's disease of bone, inclusion body myopathy, and amyotrophic lateral sclerosis. We analyzed the VCP gene in a cohort of 199 patients with frontotemporal dementia and identified 7 heterozygous mutations in unrelated families, including 3 novel mutations segregating with dementia. This expands the VCP mutation spectrum and suggests that although VCP mutations are rare (3.5% in this study), the gene should be analyzed even in absence of the full syndromic complex. Reporting genetic variants with convincing arguments for pathogenicity is important considering the large amount of data generated by next-generation sequencing and the growing difficulties to interpret rare genetic variants identified in isolated cases., (Copyright © 2018 Elsevier Inc. All rights reserved.)

We investigated whether dementia risk factors were associated with prodromal Alzheimer's disease (AD) according to the International Working Group-2 and National Institute of Aging-Alzheimer's Association criteria, and with cognitive decline. A total of 1394 subjects with mild cognitive impairment from 14 different studies were classified according to these research criteria, based on cognitive performance and biomarkers. We compared the frequency of 10 risk factors between the subgroups, and used Cox-regression to examine the effect of risk factors on cognitive decline. Depression, obesity, and hypercholesterolemia occurred more often in individuals with low-AD-likelihood, compared with those with a high-AD-likelihood. Only alcohol use increased the risk of cognitive decline, regardless of AD pathology. These results suggest that traditional risk factors for AD are not associated with prodromal AD or with progression to dementia, among subjects with mild cognitive impairment. Future studies should validate these findings and determine whether risk factors might be of influence at an earlier stage (i.e., preclinical) of AD., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Neuroimaging biomarkers differ between patients with early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). Whether these changes reflect cognitive heterogeneity or differences in disease severity is still unknown. This study aimed at investigating changes in neuroimaging biomarkers, according to the age of onset of the disease, in mild amnestic Alzheimer's disease patients with positive amyloid biomarkers in cerebrospinal fluid. Both patient groups were impaired on tasks assessing verbal and visual recognition memory. EOAD patients showed greater executive and linguistic deficits, while LOAD patients showed greater semantic memory impairment. In EOAD and LOAD, hypometabolism involved the bilateral temporoparietal junction and the posterior cingulate cortex. In EOAD, atrophy was widespread, including frontotemporoparietal areas, whereas it was limited to temporal regions in LOAD. Atrophic volumes were greater in EOAD than in LOAD. Hypometabolic volumes were similar in the 2 groups. Greater extent of atrophy in EOAD, despite similar extent of hypometabolism, could reflect different underlying pathophysiological processes, different glucose-based compensatory mechanisms or distinct level of premorbid atrophic lesions., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Few studies have examined the relationship between CSF and structural biomarkers, and cognitive function in MCI. We examined the relationship between cognitive function, hippocampal volume and cerebrospinal fluid (CSF) Aβ 42 and tau in 145 patients with MCI. Patients were assessed on cognitive tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB), the Geriatric Depression Scale and the Functional Activities Questionnaire. Hippocampal volume was measured using magnetic resonance imaging (MRI), and CSF markers of Aβ 42 , tau and p-tau 181 were also measured. Worse performance on a wide range of memory and sustained attention tasks were associated with reduced hippocampal volume, higher CSF tau and p-tau 181 and increased tau/Aβ 42 ratio. Memory tasks were also associated with lower ability to conduct functional activities of daily living, providing a link between AD biomarkers, memory performance and functional outcome. These results suggest that biomarkers of Aβ and tau are strongly related to cognitive performance as assessed by the CANTAB, and have implications for the early detection and characterization of incipient AD., (Copyright © 2017 Elsevier Inc. All rights reserved.)

An emerging issue in neuroimaging is to assess the diagnostic reliability of PET and its application in clinical practice. We aimed at assessing the accuracy of brain FDG-PET in discriminating patients with MCI due to Alzheimer's disease and healthy controls. Sixty-two patients with amnestic MCI and 109 healthy subjects recruited in five centers of the European AD Consortium were enrolled. Group analysis was performed by SPM8 to confirm metabolic differences. Discriminant analyses were then carried out using the mean FDG uptake values normalized to the cerebellum computed in 45 anatomical volumes of interest (VOIs) in each hemisphere (90 VOIs) as defined in the Automated Anatomical Labeling (AAL) Atlas and on 12 meta-VOIs, bilaterally, obtained merging VOIs with similar anatomo-functional characteristics. Further, asymmetry indexes were calculated for both datasets. Accuracy of discrimination by a Support Vector Machine and the AAL VOIs was tested against a validated method (PALZ). At the voxel level SMP8 showed a relative hypometabolism in the bilateral precuneus, and posterior cingulate, temporo-parietal and frontal cortices. Discriminant analysis classified subjects with an accuracy ranging between .91 and .83 as a function of data organization. The best values were obtained from a subset of 6 meta-VOIs plus 6 asymmetry values reaching an area under the ROC curve of .947, significantly larger than the one obtained by the PALZ score. High accuracy in discriminating MCI converters from healthy controls was reached by a non-linear classifier based on SVM applied on predefined anatomo-functional regions and inter-hemispheric asymmetries. Data pre-processing was automated and simplified by an in-house created Matlab-based script encouraging its routine clinical use. Further validation toward nonconverter MCI patients with adequately long follow-up is needed.

We explored resting-state metabolic connectivity in prodromal Alzheimer's disease (pAD) patients and in healthy controls (CTR), through a voxel-wise interregional correlation analysis of 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) by means of statistical parametric mapping. Baseline 18F-fluorodeoxyglucose-positron emission tomography of 36 patients with amnestic mild cognitive impairment who converted to Alzheimer's disease (AD) dementia after an average time of 2 years (pAD) and of 105 CTR were processed. The area of hypometabolism in pAD showed less metabolic connectivity in patients than in CTR (autocorrelation and correlation with large temporal and frontal areas, respectively). pAD patients showed limited correlation even in selected nonhypometabolic areas, including the hippocampi and the dorsolateral prefrontal cortex (DLFC). On the contrary, in CTR group correlation was highlighted between hippocampi and precuneus/posterior cingulate and frontal cortex, and between dorsolateral prefrontal cortex and caudate nuclei and parietal cortex. The reduced metabolic connections both in hypometabolic and nonhypometabolic areas in pAD patients suggest that metabolic disconnection (reflecting early diaschisis) may antedate remote hypometabolism (early sign of synaptic degeneration)., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The objective of this study is to identify the cerebral regions that are assessed by the Frontal Assessment Battery (FAB). Using SPM voxel-based analysis, we looked for correlations between FAB performance and brain SPECT perfusion in 47 patients with the frontal variant of frontotemporal dementia (fv-FTD) recruited by the French FTD research network, a multicentre initiative of French University hospitals with expertise in the field of dementia. A significant correlation was found between FAB performance and perfusion in the medial and dorsolateral frontal cortex bilaterally, independently of age, gender and MMSE. No correlations were observed with orbital frontal or parietal perfusion, in spite of the presence of hypoperfusion in these areas, or with perfusion of any other cortical or subcortical region. These findings confirm that the FAB is an adequate tool for assessing functions related to the dorsolateral and medial frontal cortex, and is thus useful for the evaluation of diseases associated with frontal dysfunction.