MRI radiomic features of peritumoral edema may predict the recurrence sites of glioblastoma multiforme

• Published in: Frontiers in oncology 2023-01, Vol.12, p.1042498-1042498
• Main Authors: Long, Hao, Zhang, Ping, Bi, Yuewei, Yang, Chen, Wu, Manfeng, He, Dian, Huang, Shaozhuo, Yang, Kaijun, Qi, Songtao, Wang, Jun
• Format: Article
• Language: English
• Subjects: glioblastoma; heterogeneity; Oncology; peritumoral edema; radiomics; recurrence
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2022.1042498

As one of the most aggressive malignant tumor in the central nervous system, the main cause of poor outcome of glioblastoma (GBM) is recurrence, a non-invasive method which can predict the area of recurrence pre-operation is necessary.To investigate whether there is radiological heterogeneity within peritumoral edema and identify the reproducible radiomic features predictive of the sites of recurrence of glioblastoma(GBM), which may be of value to optimize patients' management. The clinical information and MR images (contrast-enhanced T1 weighted and FLAIR sequences) of 22 patients who have been histologically proven glioblastoma, were retrospectively evaluated. Kaplan-Meier methods was used for survival analysis. Oedematous regions were manually segmented by an expert into recurrence region, non-recurrence region. A set of 94 radiomic features were obtained from each region using the function of analyzing MR image of 3D slicer. Paired t test was performed to identify the features existing significant difference. Subsequently, the data of two patients from TCGA database was used to evaluate whether these features have clinical value. Ten features with significant differences between the recurrence and non-recurrence subregions were identified and verified on two individual patients from the TCGA database with pathologically confirmed diagnosis of GBM. Our results suggested that heterogeneity does exist in peritumoral edema, indicating that the radiomic features of peritumoral edema from routine MR images can be utilized to predict the sites of GBM recurrence. Our findings may further guide the surgical treatment strategy for GBM.