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Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials
Michael W. Weiner,Dallas P. Veitch,Paul S. Aisen,Laurel A. Beckett,Nigel J. Cairns,Robert C. Green,Danielle J Harvey,Clifford R. Jack,William J. Jagust,John C. Morris,Ronald C. Petersen,Andrew J. Saykin,Leslie M. Shaw,Arthur W. Toga,John Q. Trojanowski,Alzheimer’s Disease Neuroimaging Initiative +15 more
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TLDR
The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers.About:
The article was published on 2017-04-01 and is currently open access. It has received 169 citations till now. The article focuses on the topics: Alzheimer's Disease Neuroimaging Initiative & Biomarker (medicine).read more
Citations
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Journal ArticleDOI
Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks
Silvia Basaia,Federica Agosta,Luca Wagner,Elisa Canu,Giuseppe Magnani,Roberto Santangelo,Massimo Filippi +6 more
TL;DR: A deep learning algorithm is built and validated predicting the individual diagnosis of Alzheimer's disease and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan, demonstrating that it is exploitable by not-trained operators and likely to be generalizable to unseen patient data.
Journal ArticleDOI
Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative
Dallas P. Veitch,Michael W. Weiner,Paul S. Aisen,Laurel A. Beckett,Nigel J. Cairns,Robert C. Green,Danielle J Harvey,Clifford R. Jack,William J. Jagust,John C. Morris,Ronald C. Petersen,Andrew J. Saykin,Leslie M. Shaw,Arthur W. Toga,John Q. Trojanowski +14 more
TL;DR: Select topics that provide insights into AD progression are discussed and how this knowledge may improve clinical trials are outlined.
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Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images
TL;DR: This paper proposes a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network and delivers 82.4% accuracy and 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD.
Journal ArticleDOI
Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: Relationship to neuroimaging and CSF biomarkers.
Kwangsik Nho,Alexandra Kueider-Paisley,Siamak MahmoudianDehkordi,Matthias Arnold,Shannon L. Risacher,Gregory Louie,Colette Blach,Rebecca Baillie,Xianlin Han,Gabi Kastenmüller,Wei Jia,Guoxiang Xie,Shahzad Ahmad,Thomas Hankemeier,Cornelia M. van Duijn,John Q. Trojanowski,Leslie M. Shaw,Michael W. Weiner,P. Murali Doraiswamy,Andrew J. Saykin,Rima Kaddurah-Daouk +20 more
TL;DR: In this paper, the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF), atrophy (magnetic resonance imaging), and brain glucose metabolism (FDG PET).
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Early increase of CSF sTREM2 in Alzheimer’s disease is associated with tau related-neurodegeneration but not with amyloid-β pathology
Marc Suárez-Calvet,Marc Suárez-Calvet,Estrella Morenas-Rodríguez,Estrella Morenas-Rodríguez,Gernot Kleinberger,Kai Schlepckow,Miguel Ángel Araque Caballero,Nicolai Franzmeier,Anja Capell,Katrin Fellerer,Brigitte Nuscher,Erden Eren,Erden Eren,Johannes Levin,Johannes Levin,Yuetiva Deming,Laura Piccio,Celeste M. Karch,Carlos Cruchaga,Leslie M. Shaw,John Q. Trojanowski,Michael W. Weiner,Michael Ewers,Christian Haass,Christian Haass +24 more
TL;DR: CSF sTREM2 increased in early symptomatic stages of late-onset AD but, unexpectedly, was observed decreased at the earliest asymptomatic phase when only abnormal Aβ pathology but no tau pathology or neurodegeneration, is present.
References
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Large-scale genomics unveil polygenic architecture of human cortical surface area
Chi-Hua Chen,Qian Peng,Qian Peng,Andrew J. Schork,Min-Tzu Lo,Chun Chieh Fan,Yunpeng Wang,Yunpeng Wang,Rahul S. Desikan,Francesco Bettella,Donald J. Hagler,Lars T. Westlye,Lars T. Westlye,William S. Kremen,Terry L. Jernigan,Stephanie Le Hellard,Stephanie Le Hellard,Vidar M. Steen,Vidar M. Steen,Thomas Espeseth,Thomas Espeseth,Matthew J. Huentelman,Asta Håberg,Ingrid Agartz,Srdjan Djurovic,Srdjan Djurovic,Ole A. Andreassen,Nicholas J. Schork,Anders M. Dale +28 more
TL;DR: It is shown that a substantial proportion of variation in cortical surface area is explained by additive effects of SNPs dispersed throughout the genome, with a larger heritable effect for visual and auditory sensory and insular cortices.
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Trajectories of Neuropsychiatric Symptoms and Cognitive Decline in Mild Cognitive Impairment
TL;DR: The course of neuropsychiatric symptoms (NPS) in adults with mild cognitive impairment (MCI) is characterized and baseline individual-level predictors and associated cognitive and functional outcomes are examined to find patients with worsening NPS may be at greater risk of developing AD and severe cognitive andfunctional impairment.
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Integrative analysis of multi-dimensional imaging genomics data for Alzheimer's disease prediction
TL;DR: The experimental results suggest that for AD prediction, in general, PET is the best modality and even though the discriminant power of genetic SNP features is weak, adding this modality to other modalities does help improve the classification accuracy.
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Multi-resolutional shape features via non-Euclidean wavelets: applications to statistical analysis of cortical thickness.
Won Hwa Kim,Vikas Singh,Moo K. Chung,Chris Hinrichs,Deepti Pachauri,Ozioma C. Okonkwo,Sterling C. Johnson +6 more
TL;DR: This paper contrasts traditional univariate methods with the multi-resolution approach which show increased sensitivity and improved statistical power to detect a group-level effects, and provides an open source implementation.
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Measuring brain atrophy with a generalized formulation of the boundary shift integral
Ferran Prados,Ferran Prados,Manuel Jorge Cardoso,Kelvin K. Leung,David M. Cash,David M. Cash,Marc Modat,Marc Modat,Nick C. Fox,Claudia A. M. Wheeler-Kingshott,Sebastien Ourselin,Sebastien Ourselin +11 more
TL;DR: This work presents a generalized and extended formulation of the boundary shift integral (gBSI) using probabilistic segmentations to estimate anatomic changes between 2 time points, providing increased sensitivity to disease changes through the use of the Probabilistic exclusive OR region.
Related Papers (5)
2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception
Michael W. Weiner,Dallas P. Veitch,Paul S. Aisen,Laurel A. Beckett,Nigel J. Cairns,Jesse M. Cedarbaum,Robert C. Green,Danielle J Harvey,Clifford R. Jack,William J. Jagust,Johan Luthman,John C. Morris,Ronald C. Petersen,Andrew J. Saykin,Leslie M. Shaw,Li Shen,Adam J. Schwarz,Arthur W. Toga,John Q. Trojanowski,Alzheimer’s Disease Neuroimaging Initiative +19 more
Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease.
Dallas P. Veitch,Michael W. Weiner,Paul S. Aisen,Laurel A. Beckett,Charles DeCarli,Robert C. Green,Danielle J Harvey,Clifford R. Jack,William J. Jagust,Susan M. Landau,John C. Morris,Ozioma C. Okonkwo,Richard J. Perrin,Ronald C. Petersen,Monica Rivera-Mindt,Andrew J. Saykin,Leslie M. Shaw,Arthur W. Toga,Duygu Tosun,John Q. Trojanowski,Alzheimer’s Disease Neuroimaging Initiative +20 more