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Xiao Luo, Kaicheng Li, Y L Jia, Qingze Zeng, Yeerfan Jiaerken, Tiantian Qiu, Peiyu Huang, Xiaojun Xu, Zhujing Shen, Xiaojun Guan, Jiong Zhou, Chao Wang, J J Xu, Minming Zhang
The APOE ε4 allele is associated with impaired intrinsic functional connectivity in neural networks, especially in the default mode network (DMN). However, effective connectivity (EC) reflects the direct causal effects of one brain region to another, which has rarely been investigated. Recently, Granger causality analysis (GCA) proved suitable for the study of directionality in neuronal interactions. Using GCA, we examined the differences in the EC between the anterior medial prefrontal cortex/posterior cingulate cortex (aMPFC/PCC) and the whole brain in 17 ε4 carrying and 32 non-carrying cognitively intact elderly individuals...
March 17, 2018: Brain Imaging and Behavior
Mahsa Dadar, Vladimir S Fonov, D Louis Collins
INTRODUCTION: Linear registration to a standard space is one of the major steps in processing and analyzing magnetic resonance images (MRIs) of the brain. Here we present an overview of linear stereotaxic MRI registration and compare the performance of 5 publicly available and extensively used linear registration techniques in medical image analysis. METHODS: A set of 9693 T1-weighted MR images were obtained for testing from 4 datasets: ADNI, PREVENT-AD, PPMI, and HCP, two of which have multi-center and multi-scanner data and three of which have longitudinal data...
March 13, 2018: NeuroImage
Yeerfan Jiaerken, Xiao Luo, Xinfeng Yu, Peiyu Huang, Xiaojun Xu, Minming Zhang
Our purpose is to evaluate the microstructural and metabolism property in the white matter that later become white matter hyperintensity (WMH), and of WMH that later disappeared. Forty subjects with two-year follow-up were included. Each subject had 3DT1, T2FLAIR, DTI and FDG-PET scans. White matter was classified into: constant WMH, growing WMH, shrinking WMH and normal appearing white matter (NAWM). The average DTI (FA and MD) and FDG-PET (standardized FDG-PET rSUV) of each of the above-mentioned region were extracted and compared...
January 1, 2018: Journal of Cerebral Blood Flow and Metabolism
Deepthi P Varikuti, Sarah Genon, Aristeidis Sotiras, Holger Schwender, Felix Hoffstaedter, Kaustubh R Patil, Christiane Jockwitz, Svenja Caspers, Susanne Moebus, Katrin Amunts, Christos Davatzikos, Simon B Eickhoff
The relationship between grey matter volume (GMV) patterns and age can be captured by multivariate pattern analysis, allowing prediction of individuals' age based on structural imaging. Raw data, voxel-wise GMV and non-sparse factorization (with Principal Component Analysis, PCA) show good performance but do not promote relatively localized brain components for post-hoc examinations. Here we evaluated a non-negative matrix factorization (NNMF) approach to provide a reduced, but also interpretable representation of GMV data in age prediction frameworks in healthy and clinical populations...
March 5, 2018: NeuroImage
Vanessa Scarapicchia, Erin L Mazerolle, John D Fisk, Lesley J Ritchie, Jodie R Gawryluk
Background: Alzheimer's disease (AD) is a neurodegenerative disorder that may benefit from early diagnosis and intervention. Therefore, there is a need to identify early biomarkers of AD using non-invasive techniques such as functional magnetic resonance imaging (fMRI). Recently, novel approaches to the analysis of resting-state fMRI data have been developed that focus on the moment-to-moment variability in the blood oxygen level dependent (BOLD) signal. The objective of the current study was to investigate BOLD variability as a novel early biomarker of AD and its associated psychophysiological correlates...
2018: Frontiers in Aging Neuroscience
Yan Wang, Guangkai Ma, Xi Wu, Jiliu Zhou
Automatic and accurate segmentation of hippocampal structures in medical images is of great importance in neuroscience studies. In multi-atlas based segmentation methods, to alleviate the misalignment when registering atlases to the target image, patch-based methods have been widely studied to improve the performance of label fusion. However, weights assigned to the fused labels are usually computed based on predefined features (e.g. image intensities), thus being not necessarily optimal. Due to the lack of discriminating features, the original feature space defined by image intensities may limit the description accuracy...
March 7, 2018: Neuroinformatics
Marco Lorenzi, Andre Altmann, Boris Gutman, Selina Wray, Charles Arber, Derrek P Hibar, Neda Jahanshad, Jonathan M Schott, Daniel C Alexander, Paul M Thompson, Sebastien Ourselin
The joint modeling of brain imaging information and genetic data is a promising research avenue to highlight the functional role of genes in determining the pathophysiological mechanisms of Alzheimer's disease (AD). However, since genome-wide association (GWA) studies are essentially limited to the exploration of statistical correlations between genetic variants and phenotype, the validation and interpretation of the findings are usually nontrivial and prone to false positives. To address this issue, in this work, we investigate the functional genetic mechanisms underlying brain atrophy in AD by studying the involvement of candidate variants in known genetic regulatory functions...
March 6, 2018: Proceedings of the National Academy of Sciences of the United States of America
Cynthia Picard, Cédric Julien, Josée Frappier, Justin Miron, Louise Théroux, Doris Dea, John C S Breitner, Judes Poirier
Genome-wide association studies have identified several cholesterol metabolism-related genes as top risk factors for late-onset Alzheimer's disease (LOAD). We hypothesized that specific genetic variants could act as disease-modifying factors by altering the expression of those genes. Targeted association studies were conducted with available genomic, transcriptomic, proteomic, and histopathological data from 3 independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Quebec Founder Population (QFP), and the United Kingdom Brain Expression Consortium (UKBEC)...
February 9, 2018: Neurobiology of Aging
Ivayla Apostolova, Catharina Lange, Per Suppa, Lothar Spies, Susanne Klutmann, Gerhard Adam, Michel J Grothe, Ralph Buchert
PURPOSE: Increased blood glucose level (BGL) has been reported to cause alterations of FDG uptake in the brain that mimic Alzheimer's disease (AD), even within the "acceptable" range ≤ 160 mg/dl. The aim of this study was (i) to confirm this in a large sample of well-characterized normal control (NC) subjects, and (ii) to analyze its impact on the prediction of AD dementia (ADD) in mild cognitive impairment (MCI). METHODS: The study included NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that were cognitively stable for ≥36 months after PET (n = 87, 74...
March 3, 2018: European Journal of Nuclear Medicine and Molecular Imaging
Oskar Hansson, John Seibyl, Erik Stomrud, Henrik Zetterberg, John Q Trojanowski, Tobias Bittner, Valeria Lifke, Veronika Corradini, Udo Eichenlaub, Richard Batrla, Katharina Buck, Katharina Zink, Christina Rabe, Kaj Blennow, Leslie M Shaw
INTRODUCTION: We studied whether fully automated Elecsys cerebrospinal fluid (CSF) immunoassay results were concordant with PET and predicted clinical progression, even with cutoffs established in an independent cohort. METHODS: Cutoffs for Elecsys amyloid-β1-42 (Aβ), total tau/Aβ(1-42), and phosphorylated tau/Aβ(1-42) were defined against [18 F]flutemetamol PET in Swedish BioFINDER (n = 277) and validated against [18 F]florbetapir PET in Alzheimer's Disease Neuroimaging Initiative (n = 646)...
February 27, 2018: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
José V Pardo, Joel T Lee
Alzheimer's disease (AD) progresses insidiously over decades. Therefore, study of preclinical AD is critical to identify early pathophysiological changes as potential targets for prevention or treatment. The brain processes at the preclinical stage remain minimally understood. Aside from age, the E4 allele of APOE flags a group at particularly high risk of late-onset AD (LOAD). Studies of these individuals could provide insights about the ontogenesis of AD offering clues for novel treatment strategies. To this end, cognitively normal, APOE*E4 homozygotes from the Alzheimer's Diseases Neuroimaging Research Initiative database (ADNI-LONI) provided fluorodeoxyglucose and amyloid (florbetapir) PET scans ( n = 8 and 7, respectively; mean age 76 years)...
January 2018: ENeuro
L E M Wisse, S R Das, C Davatzikos, B C Dickerson, S X Xie, P A Yushkevich, D A Wolk
Introduction: Suspected non-Alzheimer's pathophysiology (SNAP) is a biomarker driven designation that represents a heterogeneous group in terms of etiology and prognosis. SNAP has only been identified by cross-sectional neurodegeneration measures, whereas longitudinal measures might better reflect "active" neurodegeneration and might be more tightly linked to prognosis. We compare neurodegeneration defined by cross-sectional 'hippocampal volume' only (SNAP/L-) versus both cross-sectional and longitudinal 'hippocampal atrophy rate' (SNAP/L+) and investigate how these definitions impact prevalence and the clinical and biomarker profile of SNAP in Mild Cognitive Impairment (MCI)...
2018: NeuroImage: Clinical
Jorge L Del-Aguila, Maria Victoria Fernández, Suzanne Schindler, Laura Ibanez, Yuetiva Deming, Shengmei Ma, Ben Saef, Kathleen Black, John Budde, Joanne Norton, Rachel Chasse, Oscar Harari, Alison Goate, Chengjie Xiong, John C Morris, Carlos Cruchaga
Many genetic studies for Alzheimer's disease (AD) have been focused on the identification of common genetic variants associated with AD risk and not on other aspects of the disease, such as age at onset or rate of dementia progression. There are multiple approaches to untangling the genetic architecture of these phenotypes. We hypothesized that the genetic architecture of rate of progression is different than the risk for developing AD dementia. To test this hypothesis, we used longitudinal clinical data from ADNI and the Knight-ADRC at Washington University, and we calculated PRS (polygenic risk score) based on the IGAP study to compare the genetic architecture of AD risk and dementia progression...
2018: Journal of Alzheimer's Disease: JAD
Vanderson Dill, Pedro Costa Klein, Alexandre Rosa Franco, Márcio Sarroglia Pinho
Current state-of-the-art methods for whole and subfield hippocampus segmentation use pre-segmented templates, also known as atlases, in the pre-processing stages. Typically, the input image is registered to the template, which provides prior information for the segmentation process. Using a single standard atlas increases the difficulty in dealing with individuals who have a brain anatomy that is morphologically different from the atlas, especially in older brains. To increase the segmentation precision in these cases, without any manual intervention, multiple atlases can be used...
February 9, 2018: Computers in Biology and Medicine
Baskar Duraisamy, Jayanthi Venkatraman Shanmugam, Jayanthi Annamalai
An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this neuro degenerative disease generates major life-threatening issues, especially memory loss among patients in society. Moreover, categorizing NC (Normal Control), MCI (Mild Cognitive Impairment) and AD early in course allows the patients to experience benefits from new treatments. Therefore, it is important to construct a reliable classification technique to discriminate the patients with or without AD from the bio medical imaging modality...
February 19, 2018: Brain Imaging and Behavior
Fayçal Ben Bouallègue, Denis Mariano-Goulart, Pierre Payoux
Joint analysis of amyloid and metabolic PET patterns across healthy, mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects was performed using baseline 18F-florbetapir and 18F-FDG PET of 684 subjects from the ADNI (251 normal, 204 stable MCI, 85 AD converters, and 144 AD). Correlation between regional amyloid and metabolic uptake was measured and predictive value of PET profile regarding AD conversion in cognitively impaired subjects was assessed using survival analysis and support vector machine classification (SVM)...
2018: Journal of Alzheimer's Disease: JAD
Fayçal Ben Bouallègue, Fabien Vauchot, Denis Mariano-Goulart, Pierre Payoux
We evaluated the performance of amyloid PET textural and shape features in discriminating normal and Alzheimer's disease (AD) subjects, and in predicting conversion to AD in subjects with mild cognitive impairment (MCI) or significant memory concern (SMC). Subjects from the Alzheimer's Disease Neuroimaging Initiative with available baseline 18F-florbetapir and T1-MRI scans were included. The cross-sectional cohort consisted of 181 controls and 148 AD subjects. The longitudinal cohort consisted of 431 SMC/MCI subjects, 85 of whom converted to AD during follow-up...
February 9, 2018: Brain Imaging and Behavior
Antonio Martinez-Torteya, Hugo Gomez-Rueda, Victor Trevino, Joshua Farber, Jose Tamez-Pena, For The Alzheimer's Disease Neuroimaging Initiative
BACKGROUND: Diagnosing Alzheimer's disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who convert from mild cognitive impairment (MCI) to AD would have clinical implications. OBJECTIVES: This study's goals were to identify features from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion...
February 1, 2018: Current Alzheimer Research
Kim-Han Thung, Pew-Thian Yap, Ehsan Adeli, Seong-Whan Lee, Dinggang Shen
In this paper, we aim to predict conversion and time-to-conversion of mild cognitive impairment (MCI) patients using multi-modal neuroimaging data and clinical data, via cross-sectional and longitudinal studies. However, such data are often heterogeneous, high-dimensional, noisy, and incomplete. We thus propose a framework that includes sparse feature selection, low-rank affinity pursuit denoising (LRAD), and low-rank matrix completion (LRMC) in this study. Specifically, we first use sparse linear regressions to remove unrelated features...
January 31, 2018: Medical Image Analysis
Douglas W Scharre, Emily Weichart, Dylan Nielson, Jun Zhang, Punit Agrawal, Per B Sederberg, Michael V Knopp, Ali R Rezai
The study objective was to evaluate the safety and efficacy of deep brain stimulation (DBS) at the ventral capsule/ventral striatum (VC/VS) region to specifically modulate frontal lobe behavioral and cognitive networks as a novel treatment approach for Alzheimer's disease (AD) patients. This is a non-randomized phase I prospective open label interventional trial of three subjects with matched comparison groups. AD participants given DBS for at least 18 months at the VC/VS target were compared on the Clinical Dementia Rating-Sum of Boxes (CDR-SB), our primary outcome clinical measure, to matched groups without DBS from the AD Neuroimaging Initiative (ADNI) cohort...
January 30, 2018: Journal of Alzheimer's Disease: JAD
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