A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas

Objective The aim of this study was to develop a radiomics signature for prediction of progression-free survival (PFS) in lower-grade gliomas and to investigate the genetic background behind the radiomics signature. Methods In this retrospective study, training (n = 216) and validation (n = 84) cohorts were collected from the Chinese Glioma Genome Atlas and the Cancer Genome Atlas, respectively. For each patient, a total of 431 radiomics features were extracted from preoperative T2-weighted magnetic resonance images. A radiomics signature was generated in the training cohort, and its prognostic value was evaluated in both the training and validation cohorts. The genetic characteristics of the group with high-risk scores were identified by radiogenomic analysis, and a nomogram was established for prediction of PFS. Results There was a significant association between the radiomics signature (including 9 screened radiomics features) and PFS, which was independent of other clinicopathologic factors in both the training (P
Highlights • We developed a non-invasive model for the prediction of PFS in patients with lower-grade gliomas. • We further revealed the biological processes underlying the radiomic signature by using comprehensive radiogenomic analysis. • PFS of lower-grade gliomas could be predicted effectively based on the radiomics model.