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https://www.readbyqxmd.com/read/28333946/structural-and-functional-connectional-fingerprints-in-mild-cognitive-impairment-and-alzheimer-s-disease-patients
#1
Seong-Jin Son, Jonghoon Kim, Hyunjin Park
Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI)...
2017: PloS One
https://www.readbyqxmd.com/read/28326436/reference-region-selection-and-the-association-between-the-rate-of-amyloid-accumulation-over-time-and-the-baseline-amyloid-burden
#2
Janusch Blautzik, Matthias Brendel, Julia Sauerbeck, Sebastian Kotz, Franziska Scheiwein, Peter Bartenstein, John Seibyl, Axel Rominger
Relative quantitative analysis of amyloid plaque burden in Alzheimer's disease (AD) patients can be reported as standardized uptake value ratio (SUVR) from positron emission tomography (PET). Here, the SUVR is the ratio of the mean amyloid radioligand retention in a composite (COMP) neocortical volume of interest (VOI) to that in a reference VOI, such as the cerebellum, brainstem (BST)/pons, or white matter (WM). Some longitudinal PET investigations show that the rate of amyloid accumulation to follow-up has an inverted U relationship with baseline amyloid SUVR relative to cerebellar or brainstem/pons reference VOIs...
March 22, 2017: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/28323831/genetic-assessment-of-age-associated-alzheimer-disease-risk-development-and-validation-of-a-polygenic-hazard-score
#3
Rahul S Desikan, Chun Chieh Fan, Yunpeng Wang, Andrew J Schork, Howard J Cabral, L Adrienne Cupples, Wesley K Thompson, Lilah Besser, Walter A Kukull, Dominic Holland, Chi-Hua Chen, James B Brewer, David S Karow, Karolina Kauppi, Aree Witoelar, Celeste M Karch, Luke W Bonham, Jennifer S Yokoyama, Howard J Rosen, Bruce L Miller, William P Dillon, David M Wilson, Christopher P Hess, Margaret Pericak-Vance, Jonathan L Haines, Lindsay A Farrer, Richard Mayeux, John Hardy, Alison M Goate, Bradley T Hyman, Gerard D Schellenberg, Linda K McEvoy, Ole A Andreassen, Anders M Dale
BACKGROUND: Identifying individuals at risk for developing Alzheimer disease (AD) is of utmost importance. Although genetic studies have identified AD-associated SNPs in APOE and other genes, genetic information has not been integrated into an epidemiological framework for risk prediction. METHODS AND FINDINGS: Using genotype data from 17,008 AD cases and 37,154 controls from the International Genomics of Alzheimer's Project (IGAP Stage 1), we identified AD-associated SNPs (at p < 10-5)...
March 2017: PLoS Medicine
https://www.readbyqxmd.com/read/28323341/groupwise-envelope-models-for-imaging-genetic-analysis
#4
Yeonhee Park, Zhihua Su, Hongtu Zhu
Motivated by searching for associations between genetic variants and brain imaging phenotypes, the aim of this article is to develop a groupwise envelope model for multivariate linear regression in order to establish the association between both multivariate responses and covariates. The groupwise envelope model allows for both distinct regression coefficients and distinct error structures for different groups. Statistically, the proposed envelope model can dramatically improve efficiency of tests and of estimation...
March 21, 2017: Biometrics
https://www.readbyqxmd.com/read/28321950/the-cerebellum-shrinks-faster-than-normal-ageing-in-alzheimer-s-disease-but-not-in-mild-cognitive-impairment
#5
Hossein Tabatabaei-Jafari, Erin Walsh, Marnie E Shaw, Nicolas Cherbuin
BACKGROUND: While acceleration in age-related cerebral atrophy has been well documented in Alzheimer's disease, the cerebellar contributions to this effect have not been thoroughly investigated. OBJECTIVE: This study investigated cerebellar volume and atrophy rate using magnetic resonance imaging in individuals with normal cognition (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD). METHODS: Two hundred twenty-nine CN, 398 MCI and 191 AD participants of stage I ADNI database with screening scans were evaluated for cerebellar volume...
March 21, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28320654/structured-and-sparse-canonical-correlation-analysis-as-a-brain-wide-multi-modal-data-fusion-approach
#6
Ali-Reza Mohammadi-Nejad, Gholam-Ali Hossein-Zadeh, Hamid Soltanian-Zadeh
Multi-modal data fusion has recently emerged as a comprehensive neuroimaging analysis approach, which usually uses canonical correlation analysis (CCA). However, the current CCA-based fusion approaches face problems like high-dimensionality, multi-collinearity, unimodal feature selection, asymmetry, and loss of spatial information in reshaping the imaging data into vectors. This paper proposes a structured and sparse CCA (ssCCA) technique as a novel CCA method to overcome the above problems. To investigate the performance of the proposed algorithm, we have compared three data fusion techniques: standard CCA; regularized CCA; and ssCCA and evaluated their ability to detect multi-modal data associations...
March 14, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28316569/longitudinal-analysis-for-disease-progression-via-simultaneous-multi-relational-temporal-fused-learning
#7
Baiying Lei, Feng Jiang, Siping Chen, Dong Ni, Tianfu Wang
It is highly desirable to predict the progression of Alzheimer's disease (AD) of patients [e.g., to predict conversion of mild cognitive impairment (MCI) to AD], especially longitudinal prediction of AD is important for its early diagnosis. Currently, most existing methods predict different clinical scores using different models, or separately predict multiple scores at different future time points. Such approaches prevent coordinated learning of multiple predictions that can be used to jointly predict clinical scores at multiple future time points...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28316055/a-comparison-of-accelerated-and-non-accelerated-mri-scans-for-brain-volume-and-boundary-shift-integral-measures-of-volume-change-evidence-from-the-adni-dataset
#8
Emily N Manning, Kelvin K Leung, Jennifer M Nicholas, Ian B Malone, M Jorge Cardoso, Jonathan M Schott, Nick C Fox, Josephine Barnes
The aim of this study was to assess whether the use of accelerated MRI scans in place of non-accelerated scans influenced brain volume and atrophy rate measures in controls and subjects with mild cognitive impairment and Alzheimer's disease. We used data from 861 subjects at baseline, 573 subjects at 6 months and 384 subjects at 12 months from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We calculated whole-brain, ventricular and hippocampal atrophy rates using the k-means boundary shift integral (BSI)...
March 18, 2017: Neuroinformatics
https://www.readbyqxmd.com/read/28295799/your-algorithm-might-think-the-hippocampus-grows-in-alzheimer-s-disease-caveats-of-longitudinal-automated-hippocampal-volumetry
#9
Tejas Sankar, Min Tae M Park, Tasha Jawa, Raihaan Patel, Nikhil Bhagwat, Aristotle N Voineskos, Andres M Lozano, M Mallar Chakravarty
Hippocampal atrophy rate-measured using automated techniques applied to structural MRI scans-is considered a sensitive marker of disease progression in Alzheimer's disease, frequently used as an outcome measure in clinical trials. Using publicly accessible data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we examined 1-year hippocampal atrophy rates generated by each of five automated or semiautomated hippocampal segmentation algorithms in patients with Alzheimer's disease, subjects with mild cognitive impairment, or elderly controls...
March 15, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28291242/mining-outcome-relevant-brain-imaging-genetic-associations-via-three-way-sparse-canonical-correlation-analysis-in-alzheimer-s-disease
#10
Xiaoke Hao, Chanxiu Li, Lei Du, Xiaohui Yao, Jingwen Yan, Shannon L Risacher, Andrew J Saykin, Li Shen, Daoqiang Zhang
Neuroimaging genetics is an emerging field that aims to identify the associations between genetic variants (e.g., single nucleotide polymorphisms (SNPs)) and quantitative traits (QTs) such as brain imaging phenotypes. In recent studies, in order to detect complex multi-SNP-multi-QT associations, bi-multivariate techniques such as various structured sparse canonical correlation analysis (SCCA) algorithms have been proposed and used in imaging genetics studies. However, associations between genetic markers and imaging QTs identified by existing bi-multivariate methods may not be all disease specific...
March 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28286328/two-distinct-classes-of-degenerative-change-are-independently-linked-to-clinical-progression-in-mild-cognitive-impairment
#11
Jean-Philippe Coutu, Emily R Lindemer, Ender Konukoglu, David H Salat
We previously demonstrated 2 statistically distinct factors of degeneration in Alzheimer's disease: one strongly related to white matter damage and age interpreted as "age- and vascular-related", and the other related to cortical atrophy thought to represent "neurodegenerative changes associated with Alzheimer's disease". Those factors are now replicated in a distinct cross-sectional data set of 364 participants from the Alzheimer's Disease Neuroimaging Initiative and their interpretation is improved using correlations with CSF biomarkers...
February 16, 2017: Neurobiology of Aging
https://www.readbyqxmd.com/read/28276464/robust-identification-of-alzheimer-s-disease-subtypes-based-on-cortical-atrophy-patterns
#12
Jong-Yun Park, Han Kyu Na, Sungsoo Kim, Hyunwook Kim, Hee Jin Kim, Sang Won Seo, Duk L Na, Cheol E Han, Joon-Kyung Seong
Accumulating evidence suggests that Alzheimer's disease (AD) is heterogenous and can be classified into several subtypes. Here, we propose a robust subtyping method for AD based on cortical atrophy patterns and graph theory. We calculated similarities between subjects in their atrophy patterns throughout the whole brain, and clustered subjects with similar atrophy patterns using the Louvain method for modular organization extraction. We applied our method to AD patients recruited at Samsung Medical Center and externally validated our method by using the AD Neuroimaging Initiative (ADNI) dataset...
March 9, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28269787/cognitive-composites-domain-scores-related-to-neuroimaging-biomarkers-within-probable-amnestic-mild-cognitive-impairment-storage-subtype
#13
Ana Espinosa, Montserrat Alegret, Pedro Pesini, Sergi Valero, Asunción Lafuente, Mar Buendía, Itziar San José, Marta Ibarria, Miguel A Tejero, Joan Giménez, Susana Ruiz, Isabel Hernández, Francesc Pujadas, Pablo Martínez-Lage, Josep Munuera, Javier Arbizu, Lluis Tárraga, Suzanne B Hendrix, Agustín Ruiz, James T Becker, Susan M Landau, Oscar Sotolongo-Grau, Manuel Sarasa, Mercè Boada
The probable-amnestic (Pr-a) mild cognitive impairment (MCI)-storage subtype is a phenotype with 8.5 times more risk of conversion to dementia, mainly Alzheimer's disease (AD), than the possible non-amnestic (Pss-na) MCI. The aim of this study was to find the optimized cognitive composites (CCs) domain scores most related to neuroimaging biomarkers within Pr-aMCI-storage subtype patients. The Fundació ACE (ACE) study with 20 Pr-aMCI-storage subtype subjects (MCI) were analyzed. All subjects underwent a neuropsychological assessment, a structural MRI, FDG-PET, and PIB-PET...
2017: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/28268812/identification-of-blood-biomarkers-for-use-in-point-of-care-diagnosis-tool-for-alzheimer-s-disease
#14
E Jammeh, P Zhao, C Carroll, S Pearson, E Ifeachor
Early diagnosis of Alzheimer's Disease (AD) is widely regarded as necessary to allow treatment to be started before irreversible damage to the brain occur and for patients to benefit from new therapies as they become available. Low-cost point-of-care (PoC) diagnostic tools that can be used to routinely diagnose AD in its early stage would facilitate this, but such tools require reliable and accurate biomarkers. However, traditional biomarkers for AD use invasive cerebrospinal fluid (CSF) analysis and/or expensive neuroimaging techniques together with neuropsychological assessments...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28266059/fractional-anisotropy-derived-from-the-diffusion-tensor-distribution-function-boosts-power-to-detect-alzheimer-s-disease-deficits
#15
Talia M Nir, Neda Jahanshad, Julio E Villalon-Reina, Dmitry Isaev, Artemis Zavaliangos-Petropulu, Liang Zhan, Alex D Leow, Clifford R Jack, Michael W Weiner, Paul M Thompson
PURPOSE: In diffusion MRI (dMRI), fractional anisotropy derived from the single-tensor model (FA(DTI) ) is the most widely used metric to characterize white matter (WM) microarchitecture, despite known limitations in regions with crossing fibers. Due to time constraints when scanning patients in clinical settings, high angular resolution diffusion imaging acquisition protocols, often used to overcome these limitations, are still rare in clinical population studies. However, the tensor distribution function (TDF) may be used to model multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors...
March 7, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28260614/classification-of-alzheimer-s-disease-and-prediction-of-mild-cognitive-impairment-to-alzheimer-s-conversion-from-structural-magnetic-resource-imaging-using-feature-ranking-and-a-genetic-algorithm
#16
Iman Beheshti, Hasan Demirel, Hiroshi Matsuda
We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking and a genetic algorithm to analyze structural magnetic resonance imaging data; using this system, we can predict conversion of mild cognitive impairment (MCI)-to-Alzheimer's disease (AD) at between one and three years before clinical diagnosis. The CAD system was developed in four stages. First, we used a voxel-based morphometry technique to investigate global and local gray matter (GM) atrophy in an AD group compared with healthy controls (HCs)...
February 27, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28255200/optimizing-neuropsychological-assessments-for-cognitive-behavioral-and-functional-impairment-classification-a-machine-learning-study
#17
Petronilla Battista, Christian Salvatore, Isabella Castiglioni
Subjects with Alzheimer's disease (AD) show loss of cognitive functions and change in behavioral and functional state affecting the quality of their daily life and that of their families and caregivers. A neuropsychological assessment plays a crucial role in detecting such changes from normal conditions. However, despite the existence of clinical measures that are used to classify and diagnose AD, a large amount of subjectivity continues to exist. Our aim was to assess the potential of machine learning in quantifying this process and optimizing or even reducing the amount of neuropsychological tests used to classify AD patients, also at an early stage of impairment...
2017: Behavioural Neurology
https://www.readbyqxmd.com/read/28247064/genome-wide-association-study-identifies-four-novel-loci-associated-with-alzheimer-s-endophenotypes-and-disease-modifiers
#18
Yuetiva Deming, Zeran Li, Manav Kapoor, Oscar Harari, Jorge L Del-Aguila, Kathleen Black, David Carrell, Yefei Cai, Maria Victoria Fernandez, John Budde, Shengmei Ma, Benjamin Saef, Bill Howells, Kuan-Lin Huang, Sarah Bertelsen, Anne M Fagan, David M Holtzman, John C Morris, Sungeun Kim, Andrew J Saykin, Philip L De Jager, Marilyn Albert, Abhay Moghekar, Richard O'Brien, Matthias Riemenschneider, Ronald C Petersen, Kaj Blennow, Henrik Zetterberg, Lennart Minthon, Vivianna M Van Deerlin, Virginia Man-Yee Lee, Leslie M Shaw, John Q Trojanowski, Gerard Schellenberg, Jonathan L Haines, Richard Mayeux, Margaret A Pericak-Vance, Lindsay A Farrer, Elaine R Peskind, Ge Li, Antonio F Di Narzo, John S K Kauwe, Alison M Goate, Carlos Cruchaga
More than 20 genetic loci have been associated with risk for Alzheimer's disease (AD), but reported genome-wide significant loci do not account for all the estimated heritability and provide little information about underlying biological mechanisms. Genetic studies using intermediate quantitative traits such as biomarkers, or endophenotypes, benefit from increased statistical power to identify variants that may not pass the stringent multiple test correction in case-control studies. Endophenotypes also contain additional information helpful for identifying variants and genes associated with other aspects of disease, such as rate of progression or onset, and provide context to interpret the results from genome-wide association studies (GWAS)...
February 28, 2017: Acta Neuropathologica
https://www.readbyqxmd.com/read/28238738/reference-standard-space-hippocampus-labels-according-to-the-eadc-adni-harmonized-protocol-utility-in-automated-volumetry
#19
Dominik Wolf, Martina Bocchetta, Gregory M Preboske, Marina Boccardi, Michel J Grothe
BACKGROUND: A harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium-Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. METHODS: Manual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels...
February 23, 2017: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
https://www.readbyqxmd.com/read/28236166/alteration-of-regional-homogeneity-and-white-matter-hyperintensities-in-amnestic-mild-cognitive-impairment-subtypes-are-related-to-cognition-and-csf-biomarkers
#20
Xiao Luo, Yerfan Jiaerken, Peiyu Huang, Xiao Jun Xu, Tiantian Qiu, Yunlu Jia, Zhujing Shen, Xiaojun Guan, Jiong Zhou, Minming Zhang
Amnestic mild cognitive impairment can be further classified as single-domain aMCI (SD-aMCI) with isolated memory deficit, or multi-domain aMCI (MD-aMCI) if memory deficit is combined with impairment in other cognitive domains. Prior studies reported these clinical subtypes presumably differ in etiology. Thus, we aimed to explore the possible mechanisms between different aMCI subtypes by assessing alteration in brain activity and brain vasculature, and their relations with CSF AD biomarkers. 49 healthy controls, 32 SD-aMCI, and 32 MD-aMCI, who had undergone structural scans, resting-state functional MRI (rsfMRI) scans and neuropsychological evaluations, were identified...
February 24, 2017: Brain Imaging and Behavior
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