ArticleJournal of neuroimaging : official journal of the American Society of Neuroimaging
Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment.
Article in Journal of neuroimaging : official journal of the American Society of Neuroimaging. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Brain structure and allelic associations in Alzheimer's disease.CNS neuroscience & therapeutics · 2023Article
- Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering.Neuroinformatics · 2019Article
- 3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification.Scientific reports · 2018Article
- Changes in the Hippocampal Volume and Shape in Early-Onset Mild Cognitive Impairment.Psychiatry investigation · 2018Article
- Controlled feature selection and compressive big data analytics: Applications to biomedical and health studies.PloS one · 2018Article
- Functional Connectivity of the Hippocampus in Early- and vs. Late-Onset Alzheimer's Disease.Journal of clinical neurology (Seoul, Korea) · 2017Article
- Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2017Review
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Authors and funding
9 authors.
Funding
Abstract
background and purposeThis study investigates 36 subjects aged 55-65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to expand our knowledge of early-onset (EO) Alzheimer's Disease (EO-AD) using neuroimaging biomarkers.
methodsNine of the subjects had EO-AD, and 27 had EO mild cognitive impairment (EO-MCI). The structural ADNI data were parcellated using BrainParser, and the 15 most discriminating neuroimaging markers between the two cohorts were extracted using the Global Shape Analysis (GSA) Pipeline workflow. Then the Local Shape Analysis (LSA) Pipeline workflow was used to conduct local (per-vertex) post-hoc statistical analyses of the shape differences based on the participants' diagnoses (EO-MCI+EO-AD). Tensor-based Morphometry (TBM) and multivariate regression models were used to identify the significance of the structural brain differences based on the participants' diagnoses.
resultsThe significant between-group regional differences using GSA were found in 15 neuroimaging markers. The results of the LSA analysis workflow were based on the subject diagnosis, age, years of education, apolipoprotein E (ε4), Mini-Mental State Examination, visiting times, and logical memory as regressors. All the variables had significant effects on the regional shape measures. Some of these effects survived the false discovery rate (FDR) correction. Similarly, the TBM analysis showed significant effects on the Jacobian displacement vector fields, but these effects were reduced after FDR correction.
conclusionsThese results may explain some of the differences between EO-AD and EO-MCI, and some of the characteristics of the EO cognitive impairment subjects.
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