ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2016
Predicting progression from mild cognitive impairment to Alzheimer's disease using longitudinal callosal atrophy.
Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Diagnosis of Alzheimer's disease using transfer learning with multi-modal 3D Inception-v4.Quantitative imaging in medicine and surgery · 2025Article
- Article
- Early MCI-to-AD Conversion Prediction Using Future Value Forecasting of Multimodal Features.Computational intelligence and neuroscience · 2021Article
- Predicting Alzheimer's Disease Conversion From Mild Cognitive Impairment Using an Extreme Learning Machine-Based Grading Method With Multimodal Data.Frontiers in aging neuroscience · 2020Article
- Genetic Association Between Alzheimer's Disease Risk Variant of theFrontiers in neuroscience · 2020Article
- Permutation based testing on covariance separability.Computational statistics · 2019Article
- Discrimination and conversion prediction of mild cognitive impairment using convolutional neural networks.Quantitative imaging in medicine and surgery · 2018Article
- Early identification of MCI converting to AD: a FDG PET study.European journal of nuclear medicine and molecular imaging · 2017Article
- MRI-Based Classification Models in Prediction of Mild Cognitive Impairment and Dementia in Late-Life Depression.Frontiers in aging neuroscience · 2017Article
- Reliability of measuring regional callosal atrophy in neurodegenerative diseases.NeuroImage. Clinical · 2016Article
- Alzheimer's disease severity, objectively determined and measured.Alzheimer's & dementia (Amsterdam, Netherlands) · 2016Article
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5 authors.
Funding
Abstract
introductionWe investigate whether longitudinal callosal atrophy could predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD).
methodsLongitudinal (baseline + 1-year follow-up) MRI scans of 132 MCI subjects from the Alzheimer's Disease Neuroimaging Initiative were used. A total of 54 subjects did not convert to AD over an average (±SD) follow-up of 5.46 (±1.63) years, whereas 78 converted to AD with an average conversion time of 2.56 (±1.65) years. Annual change in the corpus callosum thickness profile was calculated from the baseline and 1-year follow-up MRI. A logistic regression model with fused lasso regularization for prediction was applied to the annual changes.
resultsWe found a sex difference. The accuracy of prediction was 84% in females and 61% in males. The discriminating regions of corpus callosum differed between sexes. In females, the genu, rostrum, and posterior body had predictive power, whereas the genu and splenium were relevant in males. DISCUSSION: Annual callosal atrophy predicts MCI-to-AD conversion in females more accurately than in males.
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