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MRI semantic features as prognostic indicators and biological mechanism insights in glioblastoma multiforme
Yuxi Gui1, Jie Lou2,3,4, Yusheng Guo2,3,4
1Department of Radiology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, 26 Shengli Avenue, Jiangan, Wuhan, Hubei, 430014, China.
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.
Insights
Magnetic resonance imaging (MRI) semantic features like ependymal extension and contrast-enhancing tumor (CET) crossing the midline are prognostic indicators for glioblastoma multiforme (GBM). These MRI findings correlate with biological pathways, potentially guiding treatment decisions for this aggressive brain tumor.
Area of Science:
- Neuro-oncology
- Radiology
- Genomics
Background:
- Glioblastoma multiforme (GBM) is an aggressive primary brain tumor with a poor prognosis.
- Magnetic resonance imaging (MRI) is crucial for GBM diagnosis and prognosis.
- Identifying reliable prognostic markers is essential for improving patient outcomes.
Purpose of the Study:
- To investigate the association between MRI semantic features and overall survival (OS) in GBM patients.
- To explore the underlying biological mechanisms linking MRI features to survival using transcriptomic analysis.
- To determine the prognostic value of specific MRI semantic features in GBM.
Main Methods:
- Retrospective review of MRI images from 171 GBM patients from TCGA and CPTAC databases.
- Evaluation of twelve MRI semantic features and assessment of their prognostic value using Cox regression and Kaplan-Meier survival analysis.
- Transcriptomic analysis (differential gene expression and GSEA) on 68 tumor samples to link imaging features with biological pathways.
Main Results:
- Age, ependymal extension, and contrast-enhancing tumor (CET) crossing the midline were significantly associated with shorter OS in multivariate analyses.
- Gene set enrichment analysis (GSEA) revealed associations between these MRI features and inflammatory response and tumor invasiveness pathways (e.g., TNF-α signaling, epithelial-to-mesenchymal transition).
- Specific MRI semantic features demonstrated prognostic significance in GBM patients.
Conclusions:
- MRI semantic features, specifically ependymal extension and CET crossing the midline, serve as valuable prognostic indicators for GBM.
- The identified MRI features correlate with key biological pathways involved in GBM progression, offering insights into tumor biology.
- These findings may inform personalized treatment strategies for GBM patients based on distinct semantic MRI characteristics.
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