ArticleNeurosurgical review2026
MRI semantic features as prognostic indicators and biological mechanism insights in glioblastoma multiforme.
Article in Neurosurgical review, 2026. 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Evolving Landscape of Glioblastoma Research: Integrating Therapeutic Advances and Diagnostic Frontiers.Brain sciences · 2026Review
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Authors and funding
9 authors.
Funding
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Abstract
Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor with a poor prognosis. Magnetic resonance imaging (MRI) is widely used for the clinical diagnosis and prognostic evaluation of GBM. This study aimed to investigate the relationship between MRI semantic features and overall survival, and to explore the underlying biological mechanisms by transcriptomic analysis. In this study, we reviewed the MRI images of 171 patients with GBM from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases and evaluated twelve MRI semantic features. Cox regression model and Kaplan-Meier survival curve were used to assess the prognostic value of the imaging features. Additionally, we investigated the relationship between imaging features and gene expression using differential gene expression and enrichment analysis in the cohort of 68 tumor samples with RNA-seq data. 171patients with GBM were included in the imaging-prognostic cohort (median age was 60.0 years and 59.6% were male). In the multivariate analyses, age (HR: 1.04, 95% CI: 1.03-1.06, P < 0.001), ependymal extension (HR:1.88, 95% CI:1.32-2.69, P < 0.001), contrast-enhancing tumor (CET) crossing midline (HR:2.38, 95% CI:1.16-4.91, P = 0.018) were significantly associated with shorter overall survival (OS). Gene set enrichment analysis (GSEA) showed that these features were significantly associated with pathways involved in inflammatory responses and tumor invasiveness, such as TNF-α signaling via NF-κB and epithelial-to-mesenchymal transition. Our study demonstrated that MRI semantic features, including ependymal extension and CET crossing the midline, can serve as prognostic indicators for patients with GBM. Additionally, several selected MRI features were found to be associated with specific biological pathways, potentially informing treatment decisions based on these distinctive semantic characteristics of GBM.
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