Survival risk stratification of 2021 WHO glioblastoma by MRI radiomics and biological exploration.
Authors
Affiliations (9)
Affiliations (9)
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China.
- College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China.
- Department of Oncological and Vascular Intervention, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, China.
- Shanxi Provincial Clinical Research Center for Interventional Medicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, China.
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China.
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China. [email protected].
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China. [email protected].
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China. [email protected].
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China. [email protected].
Abstract
There is variability in overall survival among 2021 World Health Organization isocitrate dehydrogenase wild type glioblastoma (IDH-wt GBM) patients. The aim of the study was to develop a combined model for stratifying survival risk in IDH-wt GBM and explore the biological foundation. A total of 369 IDH-wt GBM patients were retrospectively collected: 273 patients from three local hospitals (training set: n = 192, testing set: n = 81) and 96 patients from the TCIA database (validation set). Radiomics features from tumor and peritumoral edema in preoperative CE-T1WI and T2FLAIR were extracted. Univariate and least absolute shrinkage and selection operator Cox regression analyses selected significant radiomics features to construct radiomics model, while univariable and multivariable analyses identified clinical risk factors for the clinical model. High-risk and low-risk patients from radiomics and clinical model underwent subgroup analysis. The combined model was constructed using the Random Survival Forest model. Additionally, differentially expressed genes between combined high-risk and low-risk groups were identified, with enrichment analyses exploring their biological mechanisms. The radiomics model categorizes patients into high-risk and low-risk groups with superior performance (C-index: 0.762/0.715/0.690 for training/testing/validation sets) compared to the clinical model (C-index: 0.700/0.656/0.643). The combined model demonstrates the highest value in survival risk stratification (C-index: training/testing/validation sets: 0.788/0.725/0.709). The activation of Gamma-aminobutyric acid (GABA) receptor-related pathways is closely associated with malignant progression and prognosis of IDH-wt GBM. The radiomics model might be a new prognostic biomarker for IDH-wt GBM. The combined model shows an approximately 12.57% improvement of stratification ability over the clinical model. Additionally, the significant activation of GABA receptor-related pathways may be a biological feature of combined high-risk IDH-wt GBM.