ArticleJournal of imaging informatics in medicine2025
Differences in Topography of Individual Amyloid Brain Networks by Amyloid PET Images in Healthy Control, Mild Cognitive Impairment, and Alzheimer's Disease.
Article in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Electroacupuncture Improves the Learning and Memory by Modulating Hippocampal Glucose Metabolism through IGF1/IGF1R Signaling in Alzheimer's Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
Amyloid plaques, implicated in Alzheimer's disease, exhibit a spatial propagation pattern through interconnected brain regions, suggesting network-driven dissemination. This study utilizes PET imaging to investigate these brain connections and introduces an innovative method for analyzing the amyloid network. A modified version of a previously established method is applied to explore distinctive patterns of connectivity alterations across cognitive performance domains. PET images illustrate differences in amyloid accumulation, complemented by quantitative network indices. The normal control group shows minimal amyloid accumulation and preserved network connectivity. The MCI group displays intermediate amyloid deposits and partial similarity to normal controls and AD patients, reflecting the evolving nature of cognitive decline. Alzheimer's disease patients exhibit high amyloid levels and pronounced disruptions in network connectivity, which are reflected in low levels of global efficiency (Eg) and local efficiency (Eloc). It is mostly in the temporal lobe where connectivity alterations are found, particularly in regions related to memory and cognition. Network connectivity alterations, combined with amyloid PET imaging, show potential as discriminative markers for different cognitive states. Dataset-specific variations must be considered when interpreting connectivity patterns. The variability in MCI and AD overlap emphasizes the heterogeneity in cognitive decline progression, suggesting personalized approaches for neurodegenerative disorders. This study contributes to understanding the evolving network characteristics associated with normal cognition, MCI, and AD, offering valuable insights for developing diagnostic and prognostic markers.
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