ArticleHuman brain mapping2022
Brain signatures based on structural MRI: Classification for MCI, PMCI, and AD.
Article in Human brain mapping, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Frontiers and hotspots evolution in mild cognitive impairment: a bibliometric analysis of from 2013 to 2023.Frontiers in neuroscience · 2024Pooled it
- Decoupling MCI-specific signatures from shared neurobiological substrates of cognitive aging via deep learning.NPJ digital medicine · 2026Article
- Automatic identification of different stage of Alzheimer's disease using multimodal MRI and artificial intelligence.BMC medical imaging · 2026Article
- Deep learning models identify brain changes during the progression of Alzheimer's disease.NPJ systems biology and applications · 2026Article
- Early screening of mild cognitive impairment based on eye-tracking technology: a cross-sectional study.Aging clinical and experimental research · 2026Article
- Cognitive decline and reduced bone mineral density under the bone-brain axis: mechanistic insights and imaging evaluation strategies.Frontiers in aging neuroscience · 2026Review
- Neuroradiological features across major psychiatric disorders and behavioral variant of Alzheimer's disease: a concise multimodal synthesis.Psychoradiology · 2026Review
- Sex-dependent grey matter atrophy in Alzheimer's disease progression.Brain communications · 2026Article
- Disrupted Energetic and Entropic Landscape in Individuals With Mild Cognitive Impairment: Insights From Network Control Theory.Human brain mapping · 2025Article
- Research progress in predicting the conversion from mild cognitive impairment to Alzheimer's disease via multimodal MRI and artificial intelligence.Frontiers in neurology · 2025Review
- The Association between the rs6656401 Locus of the CR1 Gene and Structural Alterations of Brain Effects in Han Chinese Patients with Alzheimer's Disease.Current Alzheimer research · 2025Article
- Exploring the relationship among Alzheimer's disease, aging and cognitive scores through neuroimaging-based approach.Scientific reports · 2024Article
- Evolutionary neural architecture search for automated MDD diagnosis using multimodal MRI imaging.iScience · 2024Article
- The characteristics of brain atrophy prior to the onset of Alzheimer's disease: a longitudinal study.Frontiers in aging neuroscience · 2024Article
- Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Identifying Alzheimer's disease and mild cognitive impairment with atlas-based multi-modal metrics.Frontiers in aging neuroscience · 2023Article
- Brain signatures based on structural MRI: Classification for MCI, PMCI, and AD.Human brain mapping · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Structural MRI (sMRI) provides valuable information for understanding neurodegenerative illnesses such as Alzheimer's Disease (AD) since it detects the brain's cerebral atrophy. The development of brain networks utilizing single imaging data-sMRI is an understudied area that has the potential to provide a network neuroscientific viewpoint on the brain. In this paper, we proposed a framework for constructing a brain network utilizing sMRI data, followed by the extraction of signature networks and important regions of interest (ROIs). To construct a brain network using sMRI, nodes are defined as regions described by the brain atlas, and edge weights are determined using a distance measure called the Sorensen distance between probability distributions of gray matter tissue probability maps. The brain signatures identified are based on the changes in the networks of disease and control subjects. To validate the proposed methodology, we first identified the brain signatures and critical ROIs associated with mild cognitive impairment (MCI), progressive MCI (PMCI), and Alzheimer's disease (AD) with 60 reference subjects (15 each of control, MCI, PMCI, and AD). Then, 200 examination subjects (50 each of control, MCI, PMCI, and AD) were selected to evaluate the identified signature patterns. Results demonstrate that the proposed framework is capable of extracting brain signatures and has a number of potential applications in the disciplines of brain mapping, brain communication, and brain network-based applications.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.