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Objective: Along with the known effects of stress on brain structure and inflammatory processes, increasing evidence suggest a role of chronic stress in the pathogenesis of Alzheimer's disease (AD). We investigated the association of accumulated stressful life events (SLEs) with AD pathologies, neuroinflammation, and gray matter (GM) volume among cognitively unimpaired (CU) individuals at heightened risk of AD., Methods: This cross-sectional cohort study included 1,290 CU participants (aged 48-77) from the ALFA cohort with SLE, lumbar puncture (n = 393), and/or structural magnetic resonance imaging (n = 1,234) assessments. Using multiple regression analyses, we examined the associations of total SLEs with cerebrospinal fluid (1) phosphorylated (p)-tau 181 and Aβ 1-42 / 1-40 ratio, (2) interleukin 6 (IL-6), and (3) GM volumes voxel-wise. Further, we performed stratified and interaction analyses with sex, history of psychiatric disease, and evaluated SLEs during specific life periods., Results: Within the whole sample, only childhood and midlife SLEs, but not total SLEs, were associated with AD pathophysiology and neuroinflammation. Among those with a history of psychiatric disease SLEs were associated with higher p-tau 181 and IL-6. Participants with history of psychiatric disease and men, showed lower Aβ 1-42/1-40 with higher SLEs. Participants with history of psychiatric disease and women showed reduced GM volumes in somatic regions and prefrontal and limbic regions, respectively., Interpretation: We did not find evidence supporting the association of total SLEs with AD, neuroinflammation, and atrophy pathways. Instead, the associations appear to be contingent on events occurring during early and midlife, sex and history of psychiatric disease. ANN NEUROL 2024;95:1058-1068., (© 2024 Barcelonabeta Brain Research Center and The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Most people have a soundtrack of life, a set of special musical pieces closely linked to certain biographical experiences. Autobiographical memories (AM) and music listening (ML) involve complex mental processes ruled by differentiate brain networks. The aim of the paper was to determine the way both networks interact in linked occurrences. We performed an fMRI experiment on 31 healthy participants (age: 32.4 ± 7.6, 11 men, 4 left-handers). Participants had to recall AMs prompted by music they reported to be associated with personal biographical events (LMM: linked AM-ML events). In the main control task, participants were prompted to recall emotional AMs while listening known tracks from a pool of popular music (UMM: unlinked AM-ML events). We wanted to investigate to what extent LMM network exceeded the overlap of AM and ML networks by contrasting the activation obtained in LMM versus UMM. The contrast LMM>UMM showed the areas (at P < 0.05 FWE corrected at voxel level and cluster size>20): right frontal inferior operculum, frontal middle gyrus, pars triangularis of inferior frontal gyrus, occipital superior gyrus and bilateral basal ganglia (caudate, putamen and pallidum), occipital (middle and inferior), parietal (inferior and superior), precentral and cerebellum (6, 7 L, 8 and vermis 6 and 7). Complementary results were obtained from additional control tasks. Provided part of tLMM>UMM areas might not be related to ML-AM linkage, we assessed LMM brain network by an independent component analysis (ICA) on contrast images. Results from ICA suggest the existence of a cortico-ponto-cerebellar network including left precuneus, bilateral anterior cingulum, parahippocampal gyri, frontal inferior operculum, ventral anterior part of the insula, frontal medial orbital gyri, caudate nuclei, cerebellum 6 and vermis, which might rule the ML-induced retrieval of AM in closely linked AM-ML events. This topography may suggest that the pathway by which ML is linked to AM is attentional and directly related to perceptual processing, involving salience network, instead of the natural way of remembering typically associated with default mode network., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Atherosclerosis has been linked to cognitive decline in late life; however, the impact of cardiovascular risk factors (CVRFs) and subclinical atherosclerosis on brain metabolism at earlier stages remains unexplored., Objectives: This study sought to determine the association between brain metabolism, subclinical atherosclerosis, and CVRFs in middle-aged asymptomatic individuals., Methods: This study included 547 asymptomatic middle-aged participants (50 ± 4 years, 82% men) from the PESA (Progression of Early Subclinical Atherosclerosis) study with evidence of subclinical atherosclerosis. Participants underwent 18 F-fluorodeoxyglucose (FDG)-positron emission tomography. Global brain FDG uptake and voxel-wise analyses were used to evaluate the associations of cerebral metabolism with CVRFs and atherosclerotic plaque burden in carotids and femorals assessed by 3-dimensional vascular ultrasound., Results: Global FDG uptake showed an inverse correlation with 30-year Framingham Risk Score (FRS) (β = -0.15, p < 0.001). This association was mainly driven by the presence of hypertension (d = 0.36, p < 0.001). Carotid plaque burden was inversely associated with global brain FDG uptake (β = -0.16, p < 0.001), even after adjusting for 30-year FRS. Voxel-wise approaches revealed that the brain areas most strongly affected by hypometabolism in association with 30-year FRS, hypertension, and carotid plaque burden were parietotemporal regions (angular, supramarginal, and inferior/middle temporal gyri) and the cingulate gyrus., Conclusions: In asymptomatic middle-aged individuals, cardiovascular risk is associated with brain hypometabolism, with hypertension being the modifiable CVRF showing the strongest association. Subclinical carotid plaque burden is also linked to reduced brain metabolism independently of CVRFs. Cerebral areas showing hypometabolism include those known to be affected in dementia. These data reinforce the need to control CVRFs early in life in order to potentially reduce the brain's midlife vulnerability to future cognitive dysfunction., Competing Interests: Funding Support and Author Disclosures The PESA study is co-funded equally by CNIC and Banco Santander, Madrid, Spain. The study also receives funding from the Instituto de Salud Carlos III, Madrid, Spain (ISCIII, PI15/02019), the European Regional Development Fund (ERDF–A Way to Build Europe) and the European Social Fund (ESF–Investing in Your Future). Dr. Cortes-Canteli was supported by a Miguel Servet type I research contract (ISCIII, CP16/00174 & MS16/00174) and the Fondo de Investigación Sanitaria (ISCIII, PI17/00590 & PI20/00819). Dr. Toribio-Fernandez was supported by the Iniciativa de Empleo Juvenil of the Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid (PEJD-2018-POST/BMD-9259). Ms. Tristão-Pereira was supported by a “la Caixa” Foundation fellowship (ID 100010434, LCF/BQ/DI19/11730052). Dr. Gispert is supported by the Ministerio de Ciencia e Innovación (MCIN; RYC-2013-13054) and Dr. B. Ibanez by the European Research Council (ERC-2018-CoG 819775-MATRIX). The CNIC is supported by the ISCIII, the MCIN, and the Pro-CNIC Foundation. The BBRC is mainly funded by the “la Caixa” Foundation (ID 100010434) under agreement LCF/PR/GN17/50300004, the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD under grant agreement 115736, and the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement 115952. This Joint Undertaking receives support from the European Union Horizon 2020 Research and Innovation Programme and the EFPIA. Dr. Molinuevo has served as a consultant for, sat on advisory boards of, or delivered lectures in symposia sponsored by Roche Diagnostics, Genentech, Novartis, Lundbeck, Oryzon, Biogen, Lilly, Janssen, Green Valley, MSD, Eisai, Alector, BioCross, GE Healthcare, and ProMIS Neurosciences. Dr. Gispert has given lectures in symposia sponsored by General Electric, Philips, and Biogen. Dr. Sanchez-Gonzalez is a Philips employee. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: There is increasing evidence that AD progression differs by sex., Objective: The aim of this work was to determine sex differences in the association of baseline levels of cerebrospinal fluid (CSF) biomarkers (Aβ42, p-tau, YKL-40, sTREM2) with longitudinal brain changes in cognitively unimpaired (CU) older adults., Methods: This pilot study included 36 CU subjects (age 66.5±5.5, 12 male) scanned twice, two years apart. Using a voxel-wise analysis, we determined the sex differences in the association maps between CSF biomarkers and atrophy rates., Results: We did not find differences related to Aβ42. We found a greater impact of the rest of CSF biomarkers in areas of the Papez circuit in women versus men. Men showed greater involvement in lateral parietal and paracentral areas., Discussion: Results suggest an early differential progression of brain atrophy between sexes. Further research will elucidate whether the mechanisms responsible for sex-specific atrophy patterns are biological and/or environmental.

Background: Magnetic resonance imaging (MRI) has unveiled specific alterations at different stages of Alzheimer's disease (AD) pathophysiologic continuum constituting what has been established as "AD signature". To what extent MRI can detect amyloid-related cerebral changes from structural MRI in cognitively unimpaired individuals is still an area open for exploration., Method: Longitudinal 3D-T1 MRI scans were acquired from a subset of the ADNI cohort comprising 403 subjects: 79 controls (Ctrls), 50 preclinical AD (PreAD), and 274 MCI and dementia due to AD (MCI/AD). Amyloid CSF was used as gold-standard measure with established cutoffs (< 192 pg/mL) to establish diagnostic categories. Cognitively unimpaired individuals were defined as Ctrls if were amyloid negative and PreAD otherwise. The MCI/AD group was amyloid positive. Only subjects with the same diagnostic category at baseline and follow-up visits were considered for the study. Longitudinal morphometric analysis was performed using SPM12 to calculate Jacobian determinant maps. Statistical analysis was carried out on these Jacobian maps to identify structural changes that were significantly different between diagnostic categories. A machine learning classifier was applied on Jacobian determinant maps to predict the presence of abnormal amyloid levels in cognitively unimpaired individuals. The performance of this classifier was evaluated using receiver operating characteristic curve analysis and as a function of the follow-up time between MRI scans. We applied a cost function to assess the benefit of using this classifier in the triaging of individuals in a clinical trial-recruitment setting., Results: The optimal follow-up time for classification of Ctrls vs PreAD was Δt > 2.5 years, and hence, only subjects within this temporal span are used for evaluation (15 Ctrls, 10 PreAD). The longitudinal voxel-based classifier achieved an AUC = 0.87 (95%CI 0.72-0.97). The brain regions that showed the highest discriminative power to detect amyloid abnormalities were the medial, inferior, and lateral temporal lobes; precuneus; caudate heads; basal forebrain; and lateral ventricles., Conclusions: Our work supports that machine learning applied to longitudinal brain volumetric changes can be used to predict, with high precision, the presence of amyloid abnormalities in cognitively unimpaired subjects. Used as a triaging method to identify a fixed number of amyloid-positive individuals, this longitudinal voxel-wise classifier is expected to avoid 55% of unnecessary CSF and/or PET scans and reduce economic cost by 40%.

Background: White matter hyperintensities (WMH) of presumed vascular origin have been associated with an increased risk of Alzheimer's disease (AD). This study aims to describe the patterns of WMH associated with dementia risk estimates and individual risk factors in a cohort of middle-aged/late middle-aged individuals (mean 58 (interquartile range 51-64) years old)., Methods: Magnetic resonance imaging and AD risk factors were collected from 575 cognitively unimpaired participants. WMH load was automatically calculated in each brain lobe and in four equidistant layers from the ventricular surface to the cortical interface. Global volumes and regional patterns of WMH load were analyzed as a function of the Cardiovascular Risk Factors, Aging and Incidence of Dementia (CAIDE) dementia risk score, as well as family history of AD and Apolipoprotein E (APOE) genotype. Additional analyses were performed after correcting for the effect of age and hypertension., Results: The studied cohort showed very low WMH burden (median 1.94 cm 3 ) and 20-year dementia risk estimates (median 1.47 %). Even so, higher CAIDE scores were significantly associated with increased global WMH load. The main drivers of this association were age and hypertension, with hypercholesterolemia and body mass index also displaying a minor, albeit significant, influence. Regionally, CAIDE scores were positively associated with WMH in anterior areas, mostly in the frontal lobe. Age and hypertension showed significant association with WMH in almost all regions analyzed. The APOE-ε2 allele showed a protective effect over global WMH with a pattern that comprised juxtacortical temporo-occipital and fronto-parietal deep white matter regions. Participants with maternal family history of AD had higher WMH load than those without, especially in temporal and occipital lobes., Conclusions: WMH load is associated with AD risk factors even in cognitively unimpaired subjects with very low WMH burden and dementia risk estimates. Our results suggest that tight control of modifiable risk factors in middle-age/late middle-age could have a significant impact on late-life dementia.

Cerebrospinal fluid (CSF) YKL40 and sTREM2 are astroglial and microglial activity biomarkers, respectively. We assessed whether CSF YKL40 and sTREM2 baseline levels are associated with longitudinal brain volume and diffusivity changes in cognitively unimpaired adults. Two brain MRI scans of 36 participants (57 to 78-years old, 12 male) were acquired in a 2-year interval. Aβ 42 , p-tau, YKL40 and sTREM2 concentrations in CSF were determined at baseline. We calculated gray and white matter volume changes per year maps (ΔGM and ΔWM, respectively) by means of longitudinal pairwise registration, and mean diffusivity variation per year (ΔMD) by subtraction. We checked voxel-wise for associations between ΔGM, ΔWM and ΔMD and baseline CSF level of YKL40 and sTREM2 and verified to what extent these associations were modulated by age (YKL40xAGE and sTREM2xAGE interactions). We found a positive association between ΔGM and YKL40 in the left inferior parietal region and no association between sTREM2 and ΔGM. Negative associations were also observed between ΔGM and YKL40xAGE (bilateral frontal areas, left precuneus and left postcentral and supramarginal gyri) and sTREM2xAGE (bilateral temporal and frontal cortex, putamen and left middle cingulate gyrus). We found negative associations between ΔWM and YKL40xAGE (bilateral superior longitudinal fasciculus) and sTREM2xAGE (bilateral superior longitudinal fasciculus, left superior corona radiata, retrolenticular external capsule and forceps minor, among other regions) but none between ΔWM and neither YKL40 nor sTREM2. ΔMD was positively correlated with YKL40 in right orbital region and negatively with sTREM2 in left lingual gyrus and precuneus. In addition, significant associations were found between ΔMD and YKL40xAGE (tail of left hippocampus and surrounding areas and right anterior cingulate gyrus) and sTREM2xAGE (right superior temporal gyrus). Areas showing statistically significant differences were disjoint in analyses involving YKL40 and sTREM2. These results suggest that glial biomarkers exert a relevant and distinct influence in longitudinal brain macro- and microstructural changes in cognitively unimpaired adults, which appears to be modulated by age. In younger subjects increased glial markers (both YKL40 and sTREM2) predict a better outcome, as indicated by a decrease in ΔGM and ΔWM and an increase in ΔMD, whereas in older subjects this association is inverted and higher levels of glial markers are associated with a poorer neuroimaging outcome., (Copyright © 2019. Published by Elsevier Inc.)

Background: Subjective cognitive decline (SCD) consists of self-perceived decline in cognition over time. The occurrence of specific additional features in SCD (so-called SCDplus) confers a higher risk of future cognitive decline. However, it is not known whether SCDplus patients have a distinct cognitive and neuroimaging profile. Therefore, we aimed to study the associations between SCDplus features and cognitive and neuroimaging profiles in a population-based cohort., Methods: A total of 2670 individuals from the ALFA cohort underwent clinical, cognitive, and MRI (n = 532) explorations. Subjects were classified as self-reporting cognitive decline (SCD) or not self-reporting cognitive decline (non-SCD). Within the SCD group, participants were also classified according to the number of SCDplus features they met (SCD+, > 3; SCD-, ≤ 3)., Results: The prevalence of SCD in the cohort was 21.4% (55.8% SCD-, 44.2% SCD+). SCD+ subjects performed worse than non-SCD and SCD- subjects in memory and executive function. Among the SCDplus features, confirmation of decline by an informant was the best predictor of worse cognitive performance and lower gray matter volumes., Conclusions: Our findings show that individuals with SCDplus features have a distinct cognitive and brain volumetric profile similar to that found in Alzheimer's disease and therefore support the use of the SCDplus concept as an enrichment criterion in population-based cohorts.

Background: The ε4 allele of the apolipoprotein E gene (APOE-ε4) is the strongest genetic factor for late-onset Alzheimer's disease. During middle age, cognitively healthy APOE-ε4 carriers already show several brain alterations that resemble those of Alzheimer's disease (AD), but to a subtler degree. These include microstructural white matter (WM) changes that have been proposed as one of the earliest structural events in the AD cascade. However, previous studies have focused mainly on comparison of APOE-ε4 carriers vs noncarriers. Therefore, the extent and magnitude of the brain alterations in healthy ε4 homozygotes, who are the individuals at highest risk, remain to be characterized in detail., Methods: We examined mean, axial, and radial water diffusivity (MD, AxD, and RD, respectively) and fractional anisotropy in the WM as measured by diffusion-weighted imaging in 532 cognitively healthy middle-aged participants from the ALFA study (ALzheimer and FAmilies) cohort, a single-site population-based study enriched for AD risk (68 APOE-ε4 homozygotes, 207 heterozygotes, and 257 noncarriers). We examined the impact of age and APOE genotype on these parameters using tract-based spatial statistics., Results: Healthy APOE-ε4 homozygotes display increased WM diffusivity in regions known to be affected by AD. The effects in AxD were much smaller than in RD, suggesting a disruption of the myelin sheath rather than pure axonal damage., Conclusions: These findings could be interpreted as the result of the reduced capacity of the ε4 isoform of the APOE protein to keep cholesterol homeostasis in the brain. Because cerebral lipid metabolism is strongly related to the pathogenesis of AD, our results shed light on the possible mechanisms through which the APOE-ε4 genotype is associated with an increased risk of AD.

Alzheimer's disease (AD) is characterized by an accumulation of β-amyloid (Aβ 42 ) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that Aβ 42 accumulation is associated with gray matter (GM) changes prior to the development of cognitive impairment, in the so-called preclinical stage of the AD (pre-AD). It also has been proved that the GM atrophy profile is not linear, both in normal ageing but, especially, on AD. However, several other factors may influence this association and may have an impact on the generalization of results from different samples. In this work, we estimate differences in rates of GM volume change in cognitively healthy elders in association with baseline core cerebrospinal fluid (CSF) AD biomarkers, and assess to what these differences are sample dependent. We report the dependence of atrophy rates, measured in a two-year interval, on Aβ 42 , computed both over continuous and categorical values of Aβ 42 , at voxel-level (p < 0.001; k < 100) and corrected for sex, age and education. Analyses were performed jointly and separately, on two samples. The first sample was formed of 31 individuals (22 Ctrl and 9 pre-AD), aged 60-80 and recruited at the Hospital Clinic of Barcelona. The second sample was a replica of the first one with subjects selected from the ADNI dataset. We also investigated the dependence of the GM atrophy rate on the basal levels of continuous p-tau and on the p-tau/Aβ 42 ratio. Correlation analyses on the whole sample showed a dependence of GM atrophy rates on Aβ 42 in medial and orbital frontal, precuneus, cingulate, medial temporal regions and cerebellum. Correlations with p-tau were located in the left hippocampus, parahippocampus and striatal nuclei whereas correlation with p-tau/Aβ 42 was mainly found in ventral and medial temporal areas. Regarding analyses performed separately, we found a substantial discrepancy of results between samples, illustrating the complexities of comparing two independent datasets even when using the same inclusion criteria. Such discrepancies may lead to significant differences in the sample size needed to detect a particular reduction on cerebral atrophy rates in prevention trials. Higher cognitive reserve and more advanced pathological progression in the ADNI sample could partially account for the observed discrepancies. Taken together, our findings in these two samples highlight the importance of comparing and merging independent datasets to draw more robust and generalizable conclusions on the structural changes in the preclinical stages of AD.

Background: Subtle cognitive decline preceding cognitive impairment can be self-perceived, referred to as subjective cognitive decline (SCD), or go unrecognized., Objective: To study the clinical, cognitive, and structural neuroimaging characteristics of psychometrically normal subjects without self-awareness of cognitive decline (unaware decliners, UD) and to compare them with SCD participants and controls., Methods: 2,640 participants from the ALFA cohort, 1,899 controls, 173 UD (decline reported by the informant only), and 568 SCD underwent clinical and cognitive explorations. A subset of 530 underwent structural MRI (379 Controls; 43 UD; 108 SCD). Linear models adjusting for confounders (age, sex, education, and mood state) were used to assess group differences on cognition and voxel-wise grey matter (GM) volumes., Results: 6.6% were UD while 21.5% SCD. No differences in anxiety and depression were observed between controls and UD, while SCD did (p < 0.01). UD showed lower performance in the Memory Binding Test free recall (p < 0.005) than controls, but no differences compared to SCD. Right medial frontal and insular increments of GM volumes were observed in UD with respect to controls. Informant report of decline in UD and SCD was associated with lower left hippocampal GM volume but related to memory performance only in UD (rho = 0.46, p = 0.002)., Conclusions: UD had worse memory performance than controls which correlated with hippocampal GM volume and presented brain volume increments in self-appraisal areas (medial frontal and insula). Individuals unaware of cognitive decline may represent a distinct group at risk for cognitive impairment and support the usefulness of informant-reported cognitive decline.

The identification of healthy individuals harboring amyloid pathology represents one important challenge for secondary prevention clinical trials in Alzheimer's disease (AD). Consequently, noninvasive and cost-efficient techniques to detect preclinical AD constitute an unmet need of critical importance. In this manuscript, we apply machine learning to structural MRI (T1 and DTI) of 96 cognitively normal subjects to identify amyloid-positive ones. Models were trained on public ADNI data and validated on an independent local cohort. Used for subject classification in a simulated clinical trial setting, the proposed method is able to save 60% of unnecessary CSF/PET tests and to reduce 47% of the cost of recruitment. This recruitment strategy capitalizes on available MR scans to reduce the overall amount of invasive PET/CSF tests in prevention trials, demonstrating a potential value as a tool for preclinical AD screening. This protocol could foster the development of secondary prevention strategies for AD.

Alzheimer's disease (AD) is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC) of the subjects with preclinical Alzheimer's disease (PAD), mild cognitive impairment due to AD (MCI) and mild dementia due to Alzheimer's disease (AD), the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC) strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC) in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1 - 42) total tau (t-tau) and phosphorylated tau (p-tau). CSF Aβ1 - 42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1 - 42. APOE4 carriership showed no significant correlations with the connectivity measures.

Analysis of the structural connectomes can lead to powerful insights about the brain's organization and damage. However, the accuracy and reproducibility of constructing the structural connectome done with different acquisition and reconstruction techniques is not well defined. In this work, we evaluated the reproducibility of the structural connectome techniques by performing test-retest (same day) and longitudinal studies (after 1 month) as well as analyzing graph-based measures on the data acquired from 22 healthy volunteers (6 subjects were used for the longitudinal study). We compared connectivity matrices and tract reconstructions obtained with the most typical acquisition schemes used in clinical application: diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI), and diffusion spectrum imaging (DSI). We observed that all techniques showed high reproducibility in the test-retest analysis (correlation >.9). However, HARDI was the only technique with low variability (2%) in the longitudinal assessment (1-month interval). The intraclass coefficient analysis showed the highest reproducibility for the DTI connectome, however, with more sparse connections than HARDI and DSI. Qualitative (neuroanatomical) assessment of selected tracts confirmed the quantitative results showing that HARDI managed to detect most of the analyzed fiber groups and fanning fibers. In conclusion, we found that HARDI acquisition showed the most balanced trade-off between high reproducibility of the connectome, higher rate of path detection and of fanning fibers, and intermediate acquisition times (10-15 minutes), although at the cost of higher appearance of aberrant fibers., (Copyright © 2015 by the American Society of Neuroimaging.)

Objectives: Our aim was to investigate the impact of gray matter (GM) integrity on cognitive performance in multiple sclerosis (MS), and its relationship with white matter (WM) integrity and presence of lesions., Methods: Sixty-seven patients with MS and 26 healthy controls underwent voxel-based analysis of diffusion tensor images (DTI) in GM and tract-based spatial statistics (TBSS) from WM to identify the regional correlations between cognitive functions and integrity. Lesion probability mapping (LPM) was generated for correlation analysis with cognition. Multiple linear regression analyses were used to identify the imaging measures associated with cognitive scores., Results: Compared with controls, patients showed abnormal DTI indices in several GM regions and in most WM tracts. Impairment in DTI indices in specific GM regions was associated with worse performance of distinct cognitive functions. Those regions showed anatomical correspondence with cognitively relevant tracts in TBSS and LPM. The combination of regional GM and WM DTI and lesion volume accounted for 36-51% of the variance of memory and attention scores. Regional GM DTI explained less than 5% of that variance., Conclusion: GM and WM integrity of specific networks influences cognitive performance in MS. However, GM damage assessed by DTI only adds a small increment to the explained variance by WM in predicting cognitive functioning.

Subtraction of Ictal SPECT Co-registered to MRI (SISCOM) is an imaging technique used to localize the epileptogenic focus in patients with intractable partial epilepsy. The aim of this study was to determine the accuracy of registration algorithms involved in SISCOM analysis using FocusDET, a new user-friendly application. To this end, Monte Carlo simulation was employed to generate realistic SPECT studies. Simulated sinograms were reconstructed by using the Filtered BackProjection (FBP) algorithm and an Ordered Subsets Expectation Maximization (OSEM) reconstruction method that included compensation for all degradations. Registration errors in SPECT-SPECT and SPECT-MRI registration were evaluated by comparing the theoretical and actual transforms. Patient studies with well-localized epilepsy were also included in the registration assessment. Global registration errors including SPECT-SPECT and SPECT-MRI registration errors were less than 1.2 mm on average, exceeding the voxel size (3.32 mm) of SPECT studies in no case. Although images reconstructed using OSEM led to lower registration errors than images reconstructed with FBP, differences after using OSEM or FBP in reconstruction were less than 0.2 mm on average. This indicates that correction for degradations does not play a major role in the SISCOM process, thereby facilitating the application of the methodology in centers where OSEM is not implemented with correction of all degradations. These findings together with those obtained by clinicians from patients via MRI, interictal and ictal SPECT and video-EEG, show that FocusDET is a robust application for performing SISCOM analysis in clinical practice.

Brain networks are becoming forefront research in neuroscience. Network-based analysis on the functional and structural connectomes can lead to powerful imaging markers for brain diseases. However, constructing the structural connectome can be based upon different acquisition and reconstruction techniques whose information content and mutual differences has not yet been properly studied in a unified framework. The variations of the structural connectome if not properly understood can lead to dangerous conclusions when performing these type of studies. In this work we present evaluation of the structural connectome by analysing and comparing graph-based measures on real data acquired by the three most important Diffusion Weighted Imaging techniques: DTI, HARDI and DSI. We thus come to several important conclusions demonstrating that even though the different techniques demonstrate differences in the anatomy of the reconstructed fibers the respective connectomes show variations of 20%.

Objective: To investigate whether preterm children with low risk for neurodevelopmental deficits show long-term changes in gray matter (GM) and white matter (WM) volumes compared with term children and to relate these changes to cognitive outcome., Methods: MRI was used to evaluate 20 preterm children who were determined to be at low risk for neurodevelopmental deficits and were born between 30 and 34 weeks' gestational age without major neonatal morbidity or cerebral pathology in the neonatal period and 22 matched, term control subjects. Volumetric images were analyzed by means of voxel-based morphometry to identify regional cerebral alterations. Children also underwent cognitive and behavioral/emotional assessments., Results: Preterm children showed global and regional GM volume reductions in several brain areas, including temporal and parietal lobes and concomitant WM volume reductions in the same areas, although only the left temporal regions achieved statistical significance. Global intellectual performance in the preterm group was significantly decreased compared with control subjects. Neither behavioral nor emotional problems were found in the preterm group. In the whole sample, we found a positive correlation between GM volume bilaterally in the middle temporal and in the postcentral gyri with IQ. Positive correlations were observed between GM and gestational age at birth in parietal and temporal cerebral regions and with WM in parietal regions., Conclusion: Preterm birth has an important impact on the neurodevelopmental and cognitive outcome of children at 9 years of age, being a risk factor for decreased regional cortical GM and WM even in preterm children with low risk for neurodevelopmental deficits.

There is controversy regarding whether Dementia with Lewy Bodies (DLB) and Parkinson's disease with dementia (PDD) may or not be different manifestations of the same disorder. The purpose of the present study was to investigate possible correlations between brain structure and neuropsychological functions in clinically diagnosed patients with DLB and PDD. The study sample consisted of 12 consecutively referred DLB patients, 16 PDD patients, and 16 healthy control subjects recruited from an outpatient setting, who underwent MRI and neuropsychological assessment. Voxel-based morphometry results showed that DLB patients had greater gray matter atrophy in the right superior frontal gyrus, the right premotor area and the right inferior frontal lobe compared to PDD. Furthermore, the anterior cingulate and prefrontal volume correlated with performance on the Continuous Performance Test while the right hippocampus and amygdala volume correlated with Visual Memory Test in the DLB group. In conclusion, DLB patients had more fronto-temporal gray matter atrophy than PDD patients and these reductions correlated with neuropsychological impairment.

The objective was to examine whether cerebral volumes are reduced, and in what regions, in adolescents with anorexia nervosa and to study changes after nutritional recovery. Twelve anorexia nervosa (DSM-IV) patients aged 11-17 consecutively admitted to an Eating Disorders Unit were assessed by means of psychopathological scales, neuropsychological battery and voxel-based morphometric (VBM) magnetic resonance imaging at admission and after 7 months' follow-up. Nine control subjects of similar age, gender and estimated intelligence level were also studied. The two groups showed differences in gray matter (F=22.2; p<0.001) and cerebrospinal fluid (CSF) (F=21.2; p<0.001) but not in white matter volumes. In anorexic patients, gray matter volume correlated negatively with the copy time from the Rey Complex Figure Test. In the regional VBM study several temporal and parietal gray matter regions were reduced. During follow-up there was a greater global increase in gray matter (F=10.7; p=0.004) and decrease in CSF (F=22.1; p=0.001) in anorexic patients. The increase in gray matter correlated with a decrease in cortisol (Spearman correlation=-0.73; p=0.017). At follow-up there were no differences in global gray matter (F=2.1; p=0.165), white matter (F=0.02, p=0.965) or CSF (F=1.8; p=0.113) volumes between both groups. There were still some smaller areas, in the right temporal and both supplementary motor area, showing differences between them in the regional VBM study. In conclusion, in adolescent anorexic patients gray matter is more affected than white matter and mainly involves the posterior regions of the brain. Overall gray matter alterations are reversible after nutritional recovery.

Aim: To test T1 intensity variations induced by levodopa administration in the regional fixation area in the human brain., Method: Using non-invasive magnetic resonance imaging (MRI) technique [T1-weighted sequence MPRAGE; TE/TR/TI = 5/25/800 ms; impulsion angle = 15 degrees; field of view = 256 x 230 x 180 mm3; acquisition matrix = 256 x 192 x 104; reconstruction matrix = 256 x 256 x 128), we tested changes in the T1 MRI signal intensity resulting in changes in the grey matter automatic classification after administration of a single dose of 100 mg of levodopa by a voxel-based morphometry method (VBM) in 12 healthy subjects., Results: The VBM analysis demonstrated an increased number of voxels attributed to grey matter after levodopa administration in an anatomical cluster which included substantia nigra, tegmental ventral area and subthalamic nucleus bilaterally, the principal origin and first relay nuclei of projections in brain dopaminergic systems (t = 8.61; corrected for all grey matter volume P < 0.001)., Conclusion: Our results suggest that levodopa administration could induce an MRI T1 signal intensity variation that is not evident to the naked eye, but is detectable by measuring local signal intensities. Possible clinical applications are discussed.