Abstract:
:There is no disease-modifying treatment currently available for AD, one of the more impacting neurodegenerative diseases affecting more than 47.5 million people worldwide. The definition of new approaches for the design of proper clinical trials is highly demanded in order to achieve non-confounding results and assess more effective treatment. In this study, a cohort of 200 subjects was obtained from the Alzheimer's Disease Neuroimaging Initiative. Subjects were followed-up for 24 months, and classified as AD (50), progressive-MCI to AD (50), stable-MCI (50), and cognitively normal (50). Structural T1-weighted MRI brain studies and neuropsychological measures of these subjects were used to train and optimize an artificial-intelligence classifier to distinguish mild-AD patients who need treatment (AD + pMCI) from subjects who do not need treatment (sMCI + CN). The classifier was able to distinguish between the two groups 24 months before AD definite diagnosis using a combination of MRI brain studies and specific neuropsychological measures, with 85% accuracy, 83% sensitivity, and 87% specificity. The combined-approach model outperformed the classification using MRI data alone (72% classification accuracy, 69% sensitivity, and 75% specificity). The patterns of morphological abnormalities localized in the temporal pole and medial-temporal cortex might be considered as biomarkers of clinical progression and evolution. These regions can be already observed 24 months before AD definite diagnosis. The best neuropsychological predictors mainly included measures of functional abilities, memory and learning, working memory, language, visuoconstructional reasoning, and complex attention, with a particular focus on some of the sub-scores of the FAQ and AVLT tests.
journal_name
Front Aging Neuroscijournal_title
Frontiers in aging neuroscienceauthors
Salvatore C,Cerasa A,Castiglioni Idoi
10.3389/fnagi.2018.00135subject
Has Abstractpub_date
2018-05-24 00:00:00pages
135issn
1663-4365journal_volume
10pub_type
杂志文章abstract::The McGill-R-Thy1-APP transgenic rat is an animal model of the familial form of Alzheimer's disease (AD). This model mirrors several neuropathological hallmarks of the disease, including the accumulation of beta-amyloid and the formation of amyloid plaques (in homozygous animals only), neuroinflammation and the gradua...
journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2018.00250
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abstract::Background: Although obesity and physical activity influence psychosocial well-being, these effects may vary based on race, gender, and their intersection. Using 6-year follow-up data of a nationally representative sample of adults over age of 50 in the United States, this study aimed to explore race by gender differe...
journal_title:Frontiers in aging neuroscience
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doi:10.3389/fnagi.2016.00312
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journal_title:Frontiers in aging neuroscience
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journal_title:Frontiers in aging neuroscience
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abstract::[This corrects the article on p. 7 in vol. 7, PMID: 25762930.]. ...
journal_title:Frontiers in aging neuroscience
pub_type: 已发布勘误
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journal_title:Frontiers in aging neuroscience
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2017.00389
更新日期:2017-11-30 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2020.00177
更新日期:2020-06-12 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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更新日期:2018-04-23 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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更新日期:2013-07-18 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2015.00228
更新日期:2015-12-10 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2020.586286
更新日期:2020-10-19 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
doi:10.3389/fnagi.2016.00176
更新日期:2016-07-19 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章,评审
doi:10.3389/fnagi.2015.00040
更新日期:2015-03-24 00:00:00
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pub_type: 杂志文章
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章,评审
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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journal_title:Frontiers in aging neuroscience
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journal_title:Frontiers in aging neuroscience
pub_type: 已发布勘误
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更新日期:2020-02-18 00:00:00
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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journal_title:Frontiers in aging neuroscience
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journal_title:Frontiers in aging neuroscience
pub_type: 杂志文章
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