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Abstract #1721

Radiomics features of magnetic resonance images as novel predictive factors of bone invasion in meningiomas

Jing Zhang1, Jianqing Sun2, Guojing Zhang1, Yuntai Cao1, and Junlin Zhou1
1Radiology, Lanzhou University Second Hospital, Lanzhou, China, 2Philips Healthcare, Shanghai, Shanghai, China

Objectives Radiomics method was used to predict bone invasion. Methods 1227 quantitative imaging features were extracted. Recursive Feature Elimination (RFE) was performed to select the most informative features. Ridge Classifier was chosen to predict model. Results The AUCof the radiomics model derived from CET1WI and T2WI sequence were0.72,0.72and 0.72,0.64 in the training and test datasets , respectively, and combined CET1WI and T2WI sequences were 0.73and 0.72 when predict bone invasion. Conclusions The radiomics model developed in this study may aid neurosurgeons in the pre-operative prediction of bone invasion by meningiomas ,which can contribute to make clinical strategies and predict prognosis.

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