Multiparametric MRI-based fusion radiomics for preoperatively predicting TERT promoter mutation status and survival in glioblastoma patients

Radiomics uses computer software to mine massive quantitative image features from medical imaging images and then screens the most valuable radiomics features using statistical and/or machine learning methods. Furthermore, it is used to parse clinical information for disease characterisation, tumour grading and staging, efficacy evaluation, and prognosis prediction. In our study, we demonstrated that multiparametric MRI-based fusion radiomics model is an effective preoperative non-invasive method to predict telomerase reverse transcriptase promoter mutations and progression-free survival in glioblastoma patients.