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https://www.readbyqxmd.com/read/27931796/the-alzheimer-s-disease-neuroimaging-initiative-3-continued-innovation-for-clinical-trial-improvement
#1
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
#2
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
#3
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
#4
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)...
November 24, 2016: Medical Image Analysis
https://www.readbyqxmd.com/read/27911322/shape-attributes-of-brain-structures-as-biomarkers-for-alzheimer-s-disease
#5
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
#6
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
#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/27898305/view-aligned-hypergraph-learning-for-alzheimer-s-disease-diagnosis-with-incomplete-multi-modality-data
#8
Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen
Effectively utilizing incomplete multi-modality data for the diagnosis of Alzheimer's disease (AD) and its prodrome (i.e., mild cognitive impairment, MCI) remains an active area of research. Several multi-view learning methods have been recently developed for AD/MCI diagnosis by using incomplete multi-modality 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 sub-optimal learning performance...
November 16, 2016: Medical Image Analysis
https://www.readbyqxmd.com/read/27896962/adaptive-testing-of-snp-brain-functional-connectivity-association-via-a-modular-network-analysis
#9
Chen Gao, Junghi Kim, Wei Pan
Due to its high dimensionality and high noise levels, analysis of a large brain functional network may not be powerful and easy to interpret; instead, decomposition of a large network into smaller subcomponents called modules may be more promising as suggested by some empirical evidence. For example, alteration of brain modularity is observed in patients suffering from various types of brain malfunctions. Although several methods exist for estimating brain functional networks, such as the sample correlation matrix or graphical lasso for a sparse precision matrix, it is still difficult to extract modules from such network estimates...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27886012/histogram-based-feature-extraction-from-individual-gray-matter-similarity-matrix-for-alzheimer-s-disease-classification
#10
Iman Beheshti, Norihide Maikusa, Hiroshi Matsuda, Hasan Demirel, Gholamreza Anbarjafari
Automatic computer-aided diagnosis (CAD) systems have been widely used in classification of patients who suffer from Alzheimer's disease (AD). This paper presents an automatic CAD system based on histogram feature extraction from single-subject gray matter similarity-matrix for classifying the AD patients from healthy controls (HC) using structural magnetic resonance imaging (MRI) data. The proposed CAD system is composed of five stages. In the first stage, segmentation is employed to perform pre-processing on the MRI images, and segment into gray matter, white matter, and cerebrospinal fluid using the voxel-based morphometric toolbox procedure...
November 19, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27872486/alpha-2-macroglobulin-in-alzheimer-s-disease-a-marker-of-neuronal-injury-through-the-rcan1-pathway
#11
V R Varma, S Varma, Y An, T J Hohman, S Seddighi, R Casanova, A Beri, E B Dammer, N T Seyfried, O Pletnikova, A Moghekar, M R Wilson, J J Lah, R J O'Brien, A I Levey, J C Troncoso, M S Albert, M Thambisetty
Preclinical changes that precede the onset of symptoms and eventual diagnosis of Alzheimer's disease (AD) are a target for potential preventive interventions. A large body of evidence suggests that inflammation is closely associated with AD pathogenesis and may be a promising target pathway for such interventions. However, little is known about the association between systemic inflammation and preclinical AD pathophysiology. We first examined whether the acute-phase protein, alpha-2 macroglobulin (A2M), a major component of the innate immune system, was associated with cerebrospinal fluid (CSF) markers of neuronal injury in preclinical AD and risk of incident AD in the predictors of cognitive decline among normal individuals (BIOCARD) cohort...
November 22, 2016: Molecular Psychiatry
https://www.readbyqxmd.com/read/27864083/robust-skull-stripping-using-multiple-mr-image-contrasts-insensitive-to-pathology
#12
Snehashis Roy, John A Butman, Dzung L Pham
Automatic skull-stripping or brain extraction of magnetic resonance (MR) images is often a fundamental step in many neuroimage processing pipelines. The accuracy of subsequent image processing relies on the accuracy of the skull-stripping. Although many automated stripping methods have been proposed in the past, it is still an active area of research particularly in the context of brain pathology. Most stripping methods are validated on T1-w MR images of normal brains, especially because high resolution T1-w sequences are widely acquired and ground truth manual brain mask segmentations are publicly available for normal brains...
November 15, 2016: NeuroImage
https://www.readbyqxmd.com/read/27836336/medial-temporal-lobe-subregional-morphometry-using-high-resolution-mri-in-alzheimer-s-disease
#13
David A Wolk, Sandhitsu R Das, Susanne G Mueller, Michael W Weiner, Paul A Yushkevich
Autopsy studies of Alzheimer's disease (AD) have found that neurofibrillary tangle (NFT) pathology of the medial temporal lobe (MTL) demonstrates selective topography with relatively stereotyped subregional involvement at early disease stages, prompting interest in more granular measurement of these structures with in vivo magnetic resonance imaging. We applied a novel, automated method for measurement of hippocampal subfields and extrahippocampal MTL cortical regions. The cohort included cognitively normal (CN) adults (n = 86), early mild cognitive impairment (n = 43), late MCI (n = 22), and mild AD (n = 40) patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI)...
September 30, 2016: Neurobiology of Aging
https://www.readbyqxmd.com/read/27834776/genetic-risk-as-a-marker-of-amyloid-%C3%AE-and-tau-burden-in-cerebrospinal-fluid
#14
Nicola Voyle, Hamel Patel, Amos Folarin, Stephen Newhouse, Caroline Johnston, Pieter Jelle Visser, Richard J B Dobson, Steven J Kiddle
BACKGROUND: The search for a biomarker of Alzheimer's disease (AD) pathology (amyloid-β (Aβ) and tau) is ongoing, with the best markers currently being measurements of Aβ and tau in cerebrospinal fluid (CSF) and via positron emission tomography (PET) scanning. These methods are relatively invasive, costly, and often have high screening failure rates. Consequently, research is aiming to elucidate blood biomarkers of Aβ and tau. OBJECTIVE: This study aims to investigate a case/control polygenic risk score (PGRS) as a marker of tau and investigate blood markers of a combined Aβ and tau outcome for the first time...
November 6, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27830173/alzheimer-s-disease-severity-objectively-determined-and-measured
#15
Alden L Gross, Dan M Mungas, Jeannie-Marie S Leoutsakos, Marilyn S Albert, Richard N Jones
INTRODUCTION: With expansion of clinical trials to individuals across the spectrum of Alzheimer disease (AD) from preclinical to symptomatic phases, it is increasingly important to quantify AD severity using methods that capture underlying pathophysiology. METHODS: We derived an AD severity measure based on biomarkers from brain imaging, neuropathology, and cognitive testing using latent variable modeling. We used data from ADNI-1 (N = 822) and applied findings to BIOCARD study (N = 349)...
2016: Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
https://www.readbyqxmd.com/read/27815632/genomics-and-csf-analyses-implicate-thyroid-hormone-in-hippocampal-sclerosis-of-aging
#16
Peter T Nelson, Yuriko Katsumata, Kwangsik Nho, Sergey C Artiushin, Gregory A Jicha, Wang-Xia Wang, Erin L Abner, Andrew J Saykin, Walter A Kukull, David W Fardo
We report evidence of a novel pathogenetic mechanism in which thyroid hormone dysregulation contributes to dementia in elderly persons. Two single nucleotide polymorphisms (SNPs) on chromosome 12p12 were the initial foci of our study: rs704180 and rs73069071. These SNPs were identified by separate research groups as risk alleles for non-Alzheimer's neurodegeneration. We found that the rs73069071 risk genotype was associated with hippocampal sclerosis (HS) pathology among people with the rs704180 risk genotype (National Alzheimer's Coordinating Center/Alzheimer's Disease Genetic Consortium data; n = 2113, including 241 autopsy-confirmed HS cases)...
December 2016: Acta Neuropathologica
https://www.readbyqxmd.com/read/27803665/identify-the-atrophy-of-alzheimer-s-disease-mild-cognitive-impairment-and-normal-aging-using-morphometric-mri-analysis
#17
Xiangyu Ma, Zhaoxia Li, Bin Jing, Han Liu, Dan Li, Haiyun Li
Quantitatively assessing the medial temporal lobe (MTL) structures atrophy is vital for early diagnosis of Alzheimer's disease (AD) and accurately tracking of the disease progression. Morphometry characteristics such as gray matter volume (GMV) and cortical thickness have been proved to be valuable measurements of brain atrophy. In this study, we proposed a morphometric MRI analysis based method to explore the cross-sectional differences and longitudinal changes of GMV and cortical thickness in patients with AD, MCI (mild cognitive impairment) and the normal elderly...
2016: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/27802220/brain-regions-involved-in-arousal-and-reward-processing-are-associated-with-apathy-in-alzheimer-s-disease-and-frontotemporal-dementia
#18
Edward D Huey, Seonjoo Lee, Gayathri Cheran, Jordan Grafman, Davangere P Devanand
BACKGROUND: Apathy is a common and problematic symptom of several neurodegenerative illnesses, but its neuroanatomical bases are not understood. OBJECTIVE: To determine the regions associated with apathy in subjects with mild Alzheimer's disease (AD) using a method that accounts for the significant co-linearity of regional atrophy and neuropsychiatric symptoms. METHODS: We identified 57 subjects with mild AD (CDR = 1) and neuropsychiatric symptoms in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database...
November 19, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27776438/independent-component-analysis-support-vector-machine-based-computer-aided-diagnosis-system-for-alzheimer-s-with-visual-support
#19
Laila Khedher, Ignacio A Illán, Juan M Górriz, Javier Ramírez, Abdelbasset Brahim, Anke Meyer-Baese
Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning methods is proposed to be applied on segmented brain magnetic resonance imaging (MRI) from Alzheimer's disease neuroimaging initiative (ADNI) participants for automatic classification. The proposed CAD system possesses two relevant characteristics: optimal performance and visual support for decision making...
July 22, 2016: International Journal of Neural Systems
https://www.readbyqxmd.com/read/27767986/serum-shbg-levels-are-not-associated-with-longitudinal-cognitive-decline-in-mild-cognitive-impairment
#20
Katherine Amy Lin, Colin Rundel, P Murali Doraiswamy
BACKGROUND: Prior studies have noted gender differences in cognition, imaging, and pathological markers in mild cognitive impairment (MCI) subjects. Sex hormone-binding globulin (SHBG), a major controlling factor in the proportion of bioavailable versus bound testosterone and estrogen, has been proposed to contribute to links between hormones and dementia, but has not yet been investigated fully in a prospective biomarker trial. OBJECTIVE: This study examined whether, among subjects with MCI, SHBG levels predict future rate of cognitive decline...
October 20, 2016: Journal of Alzheimer's Disease: JAD
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