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https://www.readbyqxmd.com/read/28106548/does-the-female-advantage-in-verbal-memory-contribute-to-underestimating-alzheimer-s-disease-pathology-in-women-versus-men
#1
Erin E Sundermann, Anat Biegon, Leah H Rubin, Richard B Lipton, Susan Landau, Pauline M Maki
There is a growing recognition of sex differences in Alzheimer's disease (AD). Females show an advantage over males on tests of verbal memory, which are used to diagnose AD and its precursor, amnestic mild cognitive impairment (aMCI). Women retain this advantage in aMCI despite reduced hippocampal volume and temporal lobe glucose metabolism. Here we examined whether this female advantage endures despite evidence of AD-specific pathology, cortical amyloid-β (Aβ) deposition measured with [18F]AV45 (florbetapir) positron emission tomography...
January 18, 2017: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/28106546/a-common-variant-of-il-6r-is-associated-with-elevated-il-6-pathway-activity-in-alzheimer-s-disease-brains
#2
Patrick C G Haddick, Jessica L Larson, Nisha Rathore, Tushar R Bhangale, Qui T Phung, Karpagam Srinivasan, David V Hansen, Jennie R Lill, Margaret A Pericak-Vance, Jonathan Haines, Lindsay A Farrer, John S Kauwe, Gerard D Schellenberg, Carlos Cruchaga, Alison M Goate, Timothy W Behrens, Ryan J Watts, Robert R Graham, Joshua S Kaminker, Marcel van der Brug
The common p.D358A variant (rs2228145) in IL-6R is associated with risk for multiple diseases and with increased levels of soluble IL-6R in the periphery and central nervous system (CNS). Here, we show that the p.D358A allele leads to increased proteolysis of membrane bound IL-6R and demonstrate that IL-6R peptides with A358 are more susceptible to cleavage by ADAM10 and ADAM17. IL-6 responsive genes were identified in primary astrocytes and microglia and an IL-6 gene signature was increased in the CNS of late onset Alzheimer's disease subjects in an IL6R allele dependent manner...
January 18, 2017: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/28100725/genome-wide-association-study-identifies-mapt-locus-influencing-human-plasma-tau-levels
#3
Jason Chen, Jin-Tai Yu, Kevin Wojta, Hui-Fu Wang, Henrik Zetterberg, Kaj Blennow, Jennifer S Yokoyama, Michael W Weiner, Joel H Kramer, Howard Rosen, Bruce L Miller, Giovanni Coppola, Adam L Boxer
OBJECTIVE: To identify genetic loci associated with plasma tau concentrations in healthy elders and individuals with Alzheimer disease. METHODS: Four hundred sixty-three non-Hispanic white individuals exceeding quality control criteria were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI-1) cohort. Association of plasma tau with genetic polymorphisms was performed with a linear regression model. Significant associations were validated in an independent replication cohort consisting of 431 healthy elders or individuals with mild cognitive impairment recruited from the University of California, San Francisco Memory and Aging Center...
January 18, 2017: Neurology
https://www.readbyqxmd.com/read/28066842/diagnosis-of-alzheimer-s-disease-using-view-aligned-hypergraph-learning-with-incomplete-multi-modality-data
#4
Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view corresponding to a specific modality or a combination of several modalities. However, existing methods usually ignore the underlying coherence among views, which may lead to suboptimal learning performance. In this paper, we propose a view-aligned hypergraph learning (VAHL) method to explicitly model the coherence among the views...
October 2016: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
https://www.readbyqxmd.com/read/28063108/validation-of-18-f-fdg-pet-single-subject-optimized-spm-procedure-with-different-pet-scanners
#5
Luca Presotto, Tommaso Ballarini, Silvia Paola Caminiti, Valentino Bettinardi, Luigi Gianolli, Daniela Perani
(18)F-fluoro-deoxy-glucose Positron Emission Tomography (FDG-PET) allows early identification of neurodegeneration in dementia. The use of an optimized method based on the SPM software package highly improves diagnostic accuracy. However, the impact of different scanners for data acquisition on the SPM results and the effects of different pools of healthy subjects on the statistical comparison have not been investigated yet. Images from 144 AD patients acquired using six different PET scanners were analysed with an optimized single-subject SPM procedure to identify the typical AD hypometabolism pattern at single subject level...
January 6, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28057473/analysis-of-longitudinal-diffusion-weighted-images-in-healthy-and-pathological-aging-an-adni-study
#6
Frithjof Kruggel, Fumitaro Masaki, Ana Solodkin
BACKGROUND & NEW METHOD: The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer's Disease Neuroimaging initiative (ADNI). RESULTS AND COMPARISON WITH EXISTING METHODS: While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level...
January 2, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28054724/learning-based-3t-brain-mri-segmentation-with-guidance-from-7t-mri-labeling
#7
Minghui Deng, Renping Yu, Li Wang, Feng Shi, Pew-Thian Yap, Dinggang Shen
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largely on the availability of good training ground truth. However, the commonly used 3T MR images are of insufficient image quality and often exhibit poor intensity contrast between WM, GM, and CSF. Therefore, they are not ideal for providing good ground truth label data for training learning-based methods...
December 2016: Medical Physics
https://www.readbyqxmd.com/read/28048035/mo-fg-campus-iep3-02-gradient-nonlinearity-calibration-and-correction-for-full-volume-imaging-of-a-compact-asymmetric-mri-gradient-system
#8
S Tao, J Trzasko, Y Shu, P Weavers, J Gunter, J Huston, S Lee, E Tan, M Bernstein
PURPOSE: Due to engineering limitations, the spatial encoding gradient fields generated by an MRI scanner are inherently nonlinear and images must undergo geometric correction prior to display. The gradient nonlinearity (GNL) of a conventional symmetric whole-body gradient is typically characterized using a spherical harmonic polynomial (SHP) expansion of magnetic gradient fields with up to fifth-order terms. Only odd-order terms are required due to design symmetry (i.e., 3rd/5th-order)...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28033119/gradient-nonlinearity-calibration-and-correction-for-a-compact-asymmetric-magnetic-resonance-imaging-gradient-system
#9
S Tao, J D Trzasko, J L Gunter, P T Weavers, Y Shu, J Huston, S K Lee, E T Tan, M A Bernstein
Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resonance imaging cannot be perfectly linear and always contain higher-order, nonlinear components. If ignored during image reconstruction, gradient nonlinearity (GNL) manifests as image geometric distortion. Given an estimate of the GNL field, this distortion can be corrected to a degree proportional to the accuracy of the field estimate. The GNL of a gradient system is typically characterized using a spherical harmonic polynomial model with model coefficients obtained from electromagnetic simulation...
December 29, 2016: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28017480/cognitive-reserve-moderates-the-association-between-functional-network-anti-correlations-and-memory-in-mci
#10
Nicolai Franzmeier, Katharina Buerger, Stefan Teipel, Yaakov Stern, Martin Dichgans, Michael Ewers
Cognitive reserve (CR) shows protective effects on cognitive function in older adults. Here, we focused on the effects of CR at the functional network level. We assessed in patients with amnestic mild cognitive impairment (aMCI) whether higher CR moderates the association between low internetwork cross-talk on memory performance. In 2 independent aMCI samples (n = 76 and 93) and healthy controls (HC, n = 36), CR was assessed via years of education and intelligence (IQ). We focused on the anti-correlation between the dorsal attention network (DAN) and an anterior and posterior default mode network (DMN), assessed via sliding time window analysis of resting-state functional magnetic resonance imaging (fMRI)...
February 2017: Neurobiology of Aging
https://www.readbyqxmd.com/read/28003242/heterogeneity-of-neuroanatomical-patterns-in-prodromal-alzheimer-s-disease-links-to-cognition-progression-and-biomarkers
#11
Aoyan Dong, Jon B Toledo, Nicolas Honnorat, Jimit Doshi, Erdem Varol, Aristeidis Sotiras, David Wolk, John Q Trojanowski, Christos Davatzikos
Individuals with mild cognitive impairment and Alzheimer's disease clinical diagnoses can display significant phenotypic heterogeneity. This variability likely reflects underlying genetic, environmental and neuropathological differences. Characterizing this heterogeneity is important for precision diagnostics, personalized predictions, and recruitment of relatively homogeneous sets of patients into clinical trials. In this study, we apply state-of-the-art semi-supervised machine learning methods to the Alzheimer's disease Neuroimaging cohort (ADNI) to elucidate the heterogeneity of neuroanatomical differences between subjects with mild cognitive impairment (n = 530) and Alzheimer's disease (n = 314) and cognitively normal individuals (n = 399), thereby adding to an increasing literature aiming to establish neuroanatomical and neuropathological (e...
December 20, 2016: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/27966045/inter-rater-variability-of-visual-interpretation-and-comparison-with-quantitative-evaluation-of-11-c-pib-pet-amyloid-images-of-the-japanese-alzheimer-s-disease-neuroimaging-initiative-j-adni-multicenter-study
#12
Tomohiko Yamane, Kenji Ishii, Muneyuki Sakata, Yasuhiko Ikari, Tomoyuki Nishio, Kazunari Ishii, Takashi Kato, Kengo Ito, Michio Senda
PURPOSE: The aim of this study was to assess the inter-rater variability of the visual interpretation of (11)C-PiB PET images regarding the positivity/negativity of amyloid deposition that were obtained in a multicenter clinical research project, Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI). The results of visual interpretation were also compared with a semi-automatic quantitative analysis using mean cortical standardized uptake value ratio to the cerebellar cortex (mcSUVR)...
December 13, 2016: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/27942077/robust-multi-atlas-label-propagation-by-deep-sparse-representation
#13
Chen Zu, Zhengxia Wang, Daoqiang Zhang, Peipeng Liang, Yonghong Shi, Dinggang Shen, Guorong Wu
Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns...
March 2017: Pattern Recognition
https://www.readbyqxmd.com/read/27931796/the-alzheimer-s-disease-neuroimaging-initiative-3-continued-innovation-for-clinical-trial-improvement
#14
REVIEW
Michael W Weiner, Dallas P Veitch, Paul S Aisen, Laurel A Beckett, Nigel J Cairns, Robert C Green, Danielle Harvey, Clifford R Jack, William Jagust, John C Morris, Ronald C Petersen, Jennifer Salazar, Andrew J Saykin, Leslie M Shaw, Arthur W Toga, John Q Trojanowski
INTRODUCTION: The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study. METHODS: ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis...
December 5, 2016: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
https://www.readbyqxmd.com/read/27931251/conflicting-cerebrospinal-fluid-biomarkers-and-progression-to-dementia-due-to-alzheimer-s-disease
#15
Panagiotis Alexopoulos, Lukas Werle, Jennifer Roesler, Nathalie Thierjung, Lena Sophie Gleixner, Igor Yakushev, Nikolaos Laskaris, Stefan Wagenpfeil, Philippos Gourzis, Alexander Kurz, Robert Perneczky
BACKGROUND: According to new diagnostic guidelines for Alzheimer's disease (AD), biomarkers enable estimation of the individual likelihood of underlying AD pathophysiology and the associated risk of progression to AD dementia for patients with mild cognitive impairment (MCI). Nonetheless, how conflicting biomarker constellations affect the progression risk is still elusive. The present study explored the impact of different cerebrospinal fluid (CSF) biomarker constellations on the progression risk of MCI patients...
December 9, 2016: Alzheimer's Research & Therapy
https://www.readbyqxmd.com/read/27928657/multi-domain-transfer-learning-for-early-diagnosis-of-alzheimer-s-disease
#16
Bo Cheng, Mingxia Liu, Dinggang Shen, Zuoyong Li, Daoqiang Zhang
Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD...
December 7, 2016: Neuroinformatics
https://www.readbyqxmd.com/read/27914302/progressive-multi-atlas-label-fusion-by-dictionary-evolution
#17
Yantao Song, Guorong Wu, Khosro Bahrami, Quansen Sun, Dinggang Shen
Accurate segmentation of anatomical structures in medical images is important in recent imaging based studies. In the past years, multi-atlas patch-based label fusion methods have achieved a great success in medical image segmentation. In these methods, the appearance of each input image patch is first represented by an atlas patch dictionary (in the image domain), and then the latent label of the input image patch is predicted by applying the estimated representation coefficients to the corresponding anatomical labels of the atlas patches in the atlas label dictionary (in the label domain)...
February 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/27911322/shape-attributes-of-brain-structures-as-biomarkers-for-alzheimer-s-disease
#18
Tanya Glozman, Justin Solomon, Franco Pestilli, Leonidas Guibas
We describe a fully automatic framework for classification of two types of dementia based on the differences in the shape of brain structures. We consider Alzheimer's disease (AD), mild cognitive impairment of individuals who converted to AD within 18 months (MCIc), and normal controls (NC). Our approach uses statistical learning and a feature space consisting of projection-based shape descriptors, allowing for canonical representation of brain regions. Our framework automatically identifies the structures most affected by the disease...
November 26, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27911297/sample-size-estimation-for-alzheimer-s-disease-trials-from-japanese-adni-serial-magnetic-resonance-imaging
#19
Motonobu Fujishima, Atsushi Kawaguchi, Norihide Maikusa, Ryozo Kuwano, Takeshi Iwatsubo, Hiroshi Matsuda
BACKGROUND: Little is known about the sample sizes required for clinical trials of Alzheimer's disease (AD)-modifying treatments using atrophy measures from serial brain magnetic resonance imaging (MRI) in the Japanese population. OBJECTIVE: The primary objective of the present study was to estimate how large a sample size would be needed for future clinical trials for AD-modifying treatments in Japan using atrophy measures of the brain as a surrogate biomarker...
November 28, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27908163/learning-based-3t-brain-mri-segmentation-with-guidance-from-7t-mri-labeling
#20
Minghui Deng, Renping Yu, Li Wang, Feng Shi, Pew-Thian Yap, Dinggang Shen
PURPOSE: Segmentation of brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is crucial for brain structural measurement and disease diagnosis. Learning-based segmentation methods depend largely on the availability of good training ground truth. However, the commonly used 3T MR images are of insufficient image quality and often exhibit poor intensity contrast between WM, GM, and CSF. Therefore, they are not ideal for providing good ground truth label data for training learning-based methods...
December 2016: Medical Physics
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