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Abstract #3628

Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status

Jinlong He1, Jianlin Wu1, Yang Gao2, Qiong Wu2, Jing Shen1, Shaoyu Wang3, Huapeng Zhang3, Jialiang Ren4, and Peng Wang5
1Tianjin Medical University Graduate School, Tianjin, China, 2Department Of Imaging Diagnosis, Affiliated Hospital Of Inner Monglia Medical University, Hohhot, China, 3MR Scientific Marketing, Siemens Healthineers, Shanghai, China, 4GE Healthcare, Shanghai, China, 5Inner Monglia Medical University, Hohhot, China


Objective:To compare the performance of clinical model, radiomics model, and combined model in predicting biomarker status (IDH, MGMT, TERT, 1p/19q) of glioma.Methods: 81 glioma patients confirmed by histology were enrolled in this study. The predictive performance of each model was validated by receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA).Results: The mixed model showed the highest performance in each genic phenotype (IDH AUC = 0.93, MGMT AUC=0.88, TERT AUC=0.76, 1p/19q AUC=0.71).Conclusion: The mixed model is an effective tool to distinguish genic phenotype of brain glioma which have highest diagnostic efficiency than other models.

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