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

Synopsis

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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