ArticleFrontiers in oncology2023
Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 5 citations in OpenAlex.
- Genetic associations link lung cancer liability to brain imaging phenotypes and nominate an FN1-associated tumor-oligodendrocyte program in small-cell lung cancer.Frontiers in oncology · 2026Article
- 18F-FDG PET/CT metabolic network connectivity in clinical staging of diffuse large B-cell lymphoma.Frontiers in oncology · 2026Article
- Association of regional specificity of blood-brain barrier permeability with pathological subtypes in cerebral white matter of patients with non-brain metastatic lung cancer.Frontiers in oncology · 2026Article
- Directional interactions from non-small cell lung cancer to brain glucose metabolism revealed by total-body PET imaging.European journal of nuclear medicine and molecular imaging · 2025Article
- FDG-PET-based brain network analysis: a brief review of metabolic connectivity.EJNMMI reports · 2025Review
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung cancer has one of the highest mortality rates of all cancers, and non-small cell lung cancer (NSCLC) accounts for the vast majority (about 85%) of lung cancers. Psychological and cognitive abnormalities are common in cancer patients, and cancer information can affect brain function and structure through various pathways. To observe abnormal brain function in NSCLC patients, the main purpose of this study was to construct an individualized metabolic brain network of patients with advanced NSCLC using the Kullback-Leibler divergence-based similarity (KLS) method. Methods: This study included 78 patients with pathologically proven advanced NSCLC and 60 healthy individuals, brain Results: Significant differences in the degree and betweenness distributions of brain network nodes between the NSCLC and control groups ( Conclusions: An individualized brain metabolic network of patients with NSCLC was constructed using the KLS method, thereby providing more clinical information to guide further clinical treatment.
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