School of life science, Northwestern Polytechnical University, Xi'an, 710072, China; Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi'an, 710038, China.
Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi'an, 710038, China.
Eur J Radiol. 2022 Sep;154:110423. doi: 10.1016/j.ejrad.2022.110423. Epub 2022 Jun 23.
The composition and extent of edema (ED) region can reflect the aggressive degree of glioblastoma (GBM). Investigating its heterogeneity pattern and identifying the high-risk habitat may provide important prognostic information.
We prospectively collected 122 GBM patients from the Cancer Imaging Archive (TCIA) and 65 GBM patients from the local institution for the training cohort and external test cohort respectively. The signal intensities of ED region from T1-weighted contrast-enhanced images (T1CE) and T2-weighted fluid-attenuated inversion recovery images (FLAIR) were pooled together from each patient as a global matrix. Then, K-means clustering was applied, which could segment ED regions into several habitats (i.e., subregions). A group of radiomics features were extracted and radiomics signatures (RadScores) were derived. The high-risk habitat was identified and evaluated in light of the prognostic at the intra-regional, inter-regional, and model levels. Molecular analysis was also conducted to investigate the potential of the high-risk habitat in complementing biological information.
After three levels comparison, the high-risk habitat was determined. When combing with the RadScores of enhanced tumor (ET), the concordance index (C-index) was leveraged from 0.658 to 0.677. When combining with clinical factors and RadScores of ET, the C-index increased to 0.770. For molecular analysis, we observed a more significant difference among groups in survival prediction after uniting MGMT methylation status and the high-risk habitat signature.
This study demonstrates that investigating the spatial heterogeneity of ED and identifying the high-risk habitat within it may provide more references for GBM treatment and prognosis studies.
脑水肿（ED）区域的组成和范围可以反映胶质母细胞瘤（GBM）的侵袭程度。研究其异质性模式并确定高危生境可能提供重要的预后信息。
我们前瞻性地从癌症成像档案（TCIA）中收集了 122 名 GBM 患者，并从当地机构收集了 65 名 GBM 患者作为训练队列和外部测试队列。每位患者的 T1 加权对比增强图像（T1CE）和 T2 加权液体衰减反转恢复图像（FLAIR）中的 ED 区域的信号强度被合并为一个全局矩阵。然后，应用 K-means 聚类，将 ED 区域分割成几个生境（即亚区）。提取一组放射组学特征，并得出放射组学特征（RadScores）。根据区域内、区域间和模型水平的预后，确定并评估高危生境。还进行了分子分析，以研究高危生境在补充生物学信息方面的潜力。
经过三级比较，确定了高危生境。当将增强肿瘤（ET）的 RadScores 结合起来时，一致性指数（C-index）从 0.658 提高到 0.677。当将临床因素和 ET 的 RadScores 结合起来时，C-index 增加到 0.770。对于分子分析，在将 MGMT 甲基化状态和高危生境特征结合起来后，我们观察到在生存预测方面，各组之间的差异更为显著。
本研究表明，研究 ED 的空间异质性并确定其中的高危生境可能为 GBM 治疗和预后研究提供更多参考。
