Sun Yat-sen University Cancer Center, Guandong, 510060, PR China; Shenzhen Peking University-The Hong Kong University of Science and Technology (PKU-HKUST) Medical Center, Peking University Shenzhen Hospital, 518035, Shenzhen, PR China.
Sun Yat-sen University Cancer Center, Guandong, 510060, PR China; The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guandong, 510120, PR China; Guangdong Province Hospital of Chinese Medical, Guangzhou, Guandong, 510120, PR China.
Comput Biol Med. 2023 Jun;159:106878. doi: 10.1016/j.compbiomed.2023.106878. Epub 2023 Apr 11.
Glioblastoma (GBM) is a remarkable heterogeneous tumor with few non-invasive, repeatable, and cost-effective prognostic biomarkers reported. In this study, we aim to explore the association between radiomic features and prognosis and genomic alterations in GBM.
A total of 180 GBM patients (training cohort: n = 119; validation cohort 1: n = 37; validation cohort 2: n = 24) were enrolled and underwent preoperative MRI scans. From the multiparametric (T1, T1-Gd, T2, and T2-FLAIR) MR images, the radscore was developed to predict overall survival (OS) in a multistep postprocessing workflow and validated in two external validation cohorts. The prognostic accuracy of the radscore was assessed with concordance index (C-index) and Brier scores. Furthermore, we used hierarchical clustering and enrichment analysis to explore the association between image features and genomic alterations.
The MRI-based radscore was significantly correlated with OS in the training cohort (C-index: 0.70), validation cohort 1 (C-index: 0.66), and validation cohort 2 (C-index: 0.74). Multivariate analysis revealed that the radscore was an independent prognostic factor. Cluster analysis and enrichment analysis revealed that two distinct phenotypic clusters involved in distinct biological processes and pathways, including the VEGFA-VEGFR2 signaling pathway (q-value = 0.033), JAK-STAT signaling pathway (q-value = 0.049), and regulation of MAPK cascade (q-value = 0.0015/0.025).
Radiomic features and radiomics-derived radscores provided important phenotypic and prognostic information with great potential for risk stratification in GBM.
胶质母细胞瘤（GBM）是一种具有显著异质性的肿瘤，目前报道的无创、可重复、具有成本效益的预后生物标志物很少。在本研究中，我们旨在探索 GBM 中影像组学特征与预后和基因组改变之间的关系。
共纳入 180 名 GBM 患者（训练队列：n=119；验证队列 1：n=37；验证队列 2：n=24），并进行术前 MRI 扫描。从多参数（T1、T1-Gd、T2 和 T2-FLAIR）MR 图像中，采用多步后处理工作流程开发 radscore 以预测总生存期（OS），并在两个外部验证队列中进行验证。通过一致性指数（C-index）和 Brier 评分评估 radscore 的预后准确性。此外，我们使用层次聚类和富集分析来探索图像特征与基因组改变之间的关系。
基于 MRI 的 radscore 与训练队列（C-index：0.70）、验证队列 1（C-index：0.66）和验证队列 2（C-index：0.74）的 OS 显著相关。多变量分析显示 radscore 是独立的预后因素。聚类分析和富集分析显示，两个不同的表型聚类涉及不同的生物学过程和途径，包括 VEGFA-VEGFR2 信号通路（q 值=0.033）、JAK-STAT 信号通路（q 值=0.049）和 MAPK 级联调节（q 值=0.0015/0.025）。
放射组学特征和放射组学衍生的 radscore 提供了重要的表型和预后信息，具有很大的风险分层潜力在 GBM 中。
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