Radiomics nomogram based on multiparametric MRI features for preoperative prediction of MGMT promoter methylation status in glioblastomas

Motivation: Noninvasive measurement of the MGMT methylation status has great clinical significance for making a tailored treatment plan and prognosis assessment. Goal(s): This study aimed to establish and validate a radiomics nomogram with robust radiomics features from ADC and ISO-CE-T1-weighted images. Approach: The radiomics features were selected using LASSO regression. A radiomics nomogram combined radiomics signature and clinical factors were established with multivariate logistic regression analysis. Results: The radiomics nomogram is a promising method. The Hosmer-Lemeshow test concluded that the radiomics nomogram showed goodness of fit. The decision curve showed that the addition of clinical characteristics to the nomogram showed incremental predictive value. Impact: The multiparametric MRI-based radiomics nomogram was a promising method to preoperatively predict the MGMT mpromoter ethylation status noninvasively. Besides, the nomogram transformed the prediction signature into a visual and readable graph, making it easier to understand.