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Abstract #3854

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

Jun Lu1, Hailiang Li2, and Zhenghan Yang1
1Beijing Friendship Hospital, Capital Medical University, Beijing, China, 2Henan Cancer Hospital; Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China

Synopsis

Keywords: Tumors (Pre-Treatment), Brain, Neuro

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.

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Keywords