| Autor: |
Fangzhan Guan, Zilong Wang, Yuning Qiu, Yu Guo, Dongling Pei, Minkai Wang, Aoqi Xing, Zhongyi Liu, Bin Yu, Jingliang Cheng, Xianzhi Liu, Yuchen Ji, Dongming Yan, Jing Yan, Zhenyu Zhang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Journal of Translational Medicine, Vol 21, Iss 1, Pp 1-14 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1479-5876 |
| DOI: |
10.1186/s12967-023-04551-3 |
| Popis: |
Abstract Background To develop and validate a conventional MRI-based radiomic model for predicting prognosis in patients with IDH wild-type glioblastoma (GBM) and reveal the biological underpinning of the radiomic phenotypes. Methods A total of 801 adult patients (training set, N = 471; internal validation set, N = 239; external validation set, N = 91) diagnosed with IDH wild-type GBM were included. A 20-feature radiomic risk score (Radscore) was built for overall survival (OS) prediction by univariate prognostic analysis and least absolute shrinkage and selection operator (LASSO) Cox regression in the training set. GSEA and WGCNA were applied to identify the intersectional pathways underlying the prognostic radiomic features in a radiogenomic analysis set with paired MRI and RNA-seq data (N = 132). The biological meaning of the conventional MRI sequences was revealed using a Mantel test. Results Radscore was demonstrated to be an independent prognostic factor (P |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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