ArticleFrontiers in aging neuroscience2021
Gray Matter Deterioration Pattern During Alzheimer's Disease Progression: A Regions-of-Interest Based Surface Morphometry Study.
Article in Frontiers in aging neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Alzheimer's Disease Accelerates Cerebral Atrophy by Over a Decade Compared to Healthy Aging.Annals of biomedical engineering · 2026Article
- Exploring Links between Brain Image-Derived Phenotypes and Accelerometer-Measured Physical Activity in the UK Biobank.bioRxiv : the preprint server for biology · 2026Article
- Normalizing flow based neural processes for Alzheimer's disease progression prediction.PloS one · 2026Article
- Hybrid multimodal late fusion frameworks for bvFTD classification in imbalanced dementia datasets.Frontiers in aging neuroscience · 2026Article
- Morphological and metabolic alterations in different stages of Alzheimer's diseases: a study using surface-based morphometry (SBM) and amide proton transfer (APT) imaging.Scientific reports · 2025Article
- Cortical Structure Abnormalities in Patients With Noise-Induced Hearing Loss: A Surface-Based Morphometry Study.Brain and behavior · 2025Article
- Association of retinal layer thickness with brain volume and cortical thickness in older adults.Scientific reports · 2025Article
- Brain structural alterations in young women with premature ovarian insufficiency: Implications for dementia risk.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Cortical morphology changes in default mode network regions as predictors of cognitive decline in relation to amyloid and tau deposits.Brain communications · 2025Article
- The role of brain mechanisms in diabetic peripheral neuropathy: recent advances and comprehensive analysis.Frontiers in cellular neuroscience · 2025Review
- Surface-Based Morphometry Analysis of the Cerebral Cortex in Patients With Probable Idiopathic Rapid Eye Movement Sleep Behavior Disorder.Brain and behavior · 2024Article
- Progranulin and neuropathological features of Alzheimer's disease: longitudinal study.Aging clinical and experimental research · 2024Article
- Histogram-based features track Alzheimer's progression in brain MRI.Scientific reports · 2024Article
- Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals.IEEE access : practical innovations, open solutions · 2024Article
- Predicting mild cognitive impairment progression to Alzheimer's disease based on machine learning analysis of cortical morphological features.Aging clinical and experimental research · 2023Article
- Article
- Revealing the correlations between brain cortical characteristics and susceptibility genes for Alzheimer disease: a cross-sectional study.Quantitative imaging in medicine and surgery · 2023Article
- Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives.Neuroinformatics · 2023Review
- Extra cup of tea intake associated with increased risk of Alzheimer's disease: Genetic insights from Mendelian randomization.Frontiers in nutrition · 2023Article
- Surface-based correlates of cognition along the Alzheimer's continuum in a memory clinic population.Frontiers in neurology · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Accurate detection of the regions of Alzheimer's disease (AD) lesions is critical for early intervention to effectively slow down the progression of the disease. Although gray matter volumetric abnormalities are commonly detected in patients with mild cognition impairment (MCI) and patients with AD, the gray matter surface-based deterioration pattern associated with the progression of the disease from MCI to AD stages is largely unknown. To identify group differences in gray matter surface morphometry, including cortical thickness, the gyrification index (GI), and the sulcus depth, 80 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were split into healthy controls (HCs;
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