AIMC Topic: Amyloid beta-Peptides

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Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics Mar 29, 2021
Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying tre...
Humans Machine Learning Alzheimer Disease Positron-Emission Tomography Neuroimaging tau Proteins Biomarkers Longitudinal Studies Magnetic Resonance Imaging Amyloid beta-Peptides
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Improved amyloid burden quantification with nonspecific estimates using deep learning.

European journal of nuclear medicine and molecular imaging Jan 7, 2021
PURPOSE: Standardized uptake value ratio (SUVr) used to quantify amyloid-β burden from amyloid-PET scans can be biased by variations in the tracer's nonspecific (NS) binding caused by the presence of cerebrovascular disease (CeVD). In this work, we p...
Positron-Emission Tomography Amyloid Deep Learning Amyloid beta-Peptides Alzheimer Disease Aniline Compounds Humans Brain
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Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports Nov 2, 2020
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...
Humans Machine Learning ROC Curve Cognition Female Magnetic Resonance Imaging Algorithms Aged Amyloid beta-Peptides Predictive Value of Tests Biomarkers Aged, 80 and over Cerebral Amyloid Angiopathy Brain Male Prognosis
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Classifications of Neurodegenerative Disorders Using a Multiplex Blood Biomarkers-Based Machine Learning Model.

International journal of molecular sciences Sep 21, 2020
Easily accessible biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal dementia (FTD), and related neurodegenerative disorders are urgently needed in an aging society to assist early-stage diagnoses. In this study, we aim...
tau Proteins alpha-Synuclein Amyloid beta-Peptides Peptide Fragments Neurodegenerative Diseases Aged, 80 and over Humans Male Machine Learning Middle Aged Biomarkers Cognitive Dysfunction Female Aged
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The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

Alzheimer's & dementia : the journal of the Alzheimer's Association Sep 13, 2020
INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging d...
Middle Aged Disease Progression Cognitive Dysfunction Image Processing, Computer-Assisted Young Adult Adult Male Aging Atrophy Cerebral Small Vessel Diseases Magnetic Resonance Imaging Amyloid beta-Peptides White Matter Neuropsychological Tests Humans Machine Learning Biomarkers Brain Female Aged Aged, 80 and over
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Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Aging Jul 9, 2020
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathoge...
Humans Brain Female Aged Aged, 80 and over Cluster Analysis Unsupervised Machine Learning Alzheimer Disease Male Bayes Theorem Disease Progression Image Interpretation, Computer-Assisted Amyloid beta-Peptides Longitudinal Studies Atrophy Magnetic Resonance Imaging
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Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.

Human brain mapping May 4, 2020
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to ...
Connectome Basal Ganglia Humans Default Mode Network Machine Learning Amyloid beta-Peptides Databases, Factual Alzheimer Disease Cognitive Dysfunction Datasets as Topic Magnetic Resonance Imaging Cerebral Cortex
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Validation of machine learning models to detect amyloid pathologies across institutions.

Acta neuropathologica communications Apr 28, 2020
Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) are the most commonly used method in Alzheimer's disease (AD) neuropathology practice. Computational approaches based on machine learning ha...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Lewy Body Disease Machine Learning TDP-43 Proteinopathies Amyloid beta-Peptides Neurodegenerative Diseases Alzheimer Disease
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The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases.

European journal of nuclear medicine and molecular imaging Dec 6, 2019
PURPOSE: Although most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer's disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clini...
Amyloid Feasibility Studies Humans Alzheimer Disease Deep Learning Aniline Compounds Amyloid beta-Peptides Positron-Emission Tomography
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Epidemiological pathology of Aβ deposition in the ageing brain in CFAS: addition of multiple Aβ-derived measures does not improve dementia assessment using logistic regression and machine learning approaches.

Acta neuropathologica communications Dec 5, 2019
Aβ-amyloid deposition is a key feature of Alzheimer's disease, but Consortium to Establish a Registry for Alzheimer's Disease (CERAD) assessment, based on neuritic plaque density, shows a limited relationships to dementia. Thal phase is based on a ne...
Cognition Amyloid beta-Peptides Aging Humans Dementia Machine Learning Cohort Studies Brain Logistic Models Female Aged Aged, 80 and over Male
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