Background Accurate classification of gliomas is crucial for prescribing therapy and
assessing the prognosis of patients. Purpose To develop a radiomics nomogram using …

Purpose To evaluate the efficacy of three‐dimensional (3D) segmentation‐based radiomics
analysis of multiparametric MRI combined with proton magnetic resonance spectroscopy …

Background Glioblastomas (GBMs) represent both the most common and the most highly
malignant primary brain tumors. The subjective visual imaging features from MRI make it …

Rationale and Objectives Glioblastoma multiforme (GBM) is the most common and deadly
type of primary malignant tumor of the central nervous system. Accurate risk stratification is …

Background To investigate the feasibility of integrating global radiomics and local deep
features based on multi-modal magnetic resonance imaging (MRI) for developing a …

Objective To assess whether radiomics features derived from multiparametric MRI can
predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II …

Objectives To construct a radiomics nomogram for the individualized estimation of the
survival stratification in glioblastoma (GBM) patients using the multiregional information …

Background Genotype status of glioma have important significance to clinical treatment and
prognosis. At present, there are few studies on the prediction of multiple genotype status in …

Purpose To evaluate whether radiomic feature–based magnetic resonance (MR) imaging
signatures allow prediction of survival and stratification of patients with newly diagnosed …

Background Accurate glioma grading plays an important role in the clinical management of
patients and is also the basis of molecular stratification nowadays. Purpose/Hypothesis To …