Abstract

Motivation: WHO Grade, IDH mutation and MGMT promoter methylation are important for precise diagnosis and treatment plans for diffuse glioma patients. Goal(s): This study aimed to investigate the predictive value of radiomics features extracted from Structural MRI, ADC and SWI. Approach: Radiomic features were extracted from T1WI, T2WI, T1CE, FLAIR, ADC and SWI. Analysis of variance F-test were used for feature selection. 11 classifiers were utilized for model establishment. Results: For WHO Grade task, the highest AUC was 0.990; for IDH mutation task, the highest AUC was 0.947. All the constructed models failed to predict MGMT promoter methylation status efficiently. Impact: This work will help neuro-oncologists better understand the radiological manifestation of gliomas.