• Lina Zhao, Jie Gong, Yibin Xi, Man Xu, Chen Li, Xiaowei Kang, Yutian Yin, Wei Qin, Hong Yin, and Mei Shi.
• Department of Radiation Oncology, Xijing Hospital, Air Force Medical University, Xi'an, China.
• Eur Radiol. 2020 Jan 1; 30 (1): 537-546.

ObjectivesTo establish and validate a radiomics nomogram for prediction of induction chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients.MethodsOne hundred twenty-three NPC patients (100 in training and 23 in validation cohort) with multi-MR images were enrolled. A radiomics nomogram was established by integrating the clinical data and radiomics signature generated by support vector machine.ResultsThe radiomics signature consisting of 19 selected features from the joint T1-weighted (T1-WI), T2-weighted (T2-WI), and contrast-enhanced T1-weighted MRI images (T1-C) showed good prognostic performance in terms of evaluating IC response in two cohorts. The radiomics nomogram established by integrating the radiomics signature with clinical data outperformed clinical nomogram alone (C-index in validation cohort, 0.863 vs 0.549; p < 0.01). Decision curve analysis demonstrated the clinical utility of the radiomics nomogram. Survival analysis showed that IC responders had significant better PFS (progression-free survival) than non-responders (3-year PFS 84.81% vs 39.75%, p < 0.001). Low-risk groups defined by radiomics signature had significant better PFS than high-risk groups (3-year PFS 76.24% vs 48.04%, p < 0.05).ConclusionsMultiparametric MRI-based radiomics could be helpful for personalized risk stratification and treatment in NPC patients receiving IC.Key Points• MRI Radiomics can predict IC response and survival in non-endemic NPC. • Radiomics signature in combination with clinical data showed excellent predictive performance. • Radiomics signature could separate patients into two groups with different prognosis.

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