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Abstract #0010

MR radiomics analysis in predicting the pathological classification and TNM staging of thymic epithelial tumors

Gang Xiao1, Wei-Cheng Rong1, Zhong-Qiang Shi2, Xiao-Cheng Wei3, Wen Wang1, Yu-Chuan Hu1, and Guang-Bin Cui1

1Tangdu Hospital, Xi’an, China, 2GE Healthcare, Shanghai, China, 3GE Healthcare, Beijing, China

To explore the performance of MR radiomics in predicting the pathological classification and staging of thymic epithelial tumors (TETs), we built two radiomics models based on support vector machine. Besides, we developed a radiomics nomogram for predicting risk stratification of advanced TETs. The models achieved an area under the curve of 77.1% or 90.8% in the test cohort in distinguishing low-, high-risk thymomas and thymic carcinomas or early and advanced TETs. The radiomics model, symptom, and pericardial effusion constituted a radiomics nomogram, with a C-index of 0.957 in the test cohort. Thus, MR radiomics can be useful for assessing TETs.

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