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Abstract #3080

Radiomics Approach for Prediction of Tumor Recurrence and Progression of Skull Base Meningioma

Ching-Chung Ko1, Yang Zhang2, Jeon Hor Chen2,3, Peter Chang2, Daniel Chow2, Tiffany Kwong2, and Min-Ying Lydia Su2

1Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan, 2Department of Radiological Sciences, University of California, Irvine, CA, United States, 3Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung, Taiwan

A subset of low grade skull base meningiomas (SBM) shows early progression/recurrence (P/R). In clinical practice, one of the main challenges in the treatment of SBM is to determine factors that correlate with P/R. This study investigated the role of radiomics for the prediction of P/R. Sixty patients diagnosed with benign SBM were studied. Totally 99 descriptors were extracted from the various MR sequences. The prediction accuracy of P/R was 90% and the AUC of the prediction model was 0.94. Our study also noted that subsequent P/R of SBM after surgery was not associated with the completeness of tumor resection.

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