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Abstract #4749

Multi-parametric MRI-based Radiomics integrated with Clinical Features for Predicting the Ki-67 Labeling Index in Nasopharyngeal Carcinoma

Zhuo Wang1, Zhiqiang Chen2, Xiaohua Chen1, Shaoru Zhang1, Shili Liu1, Ruodi Zhang1, Yunshu Zhou1, Yuhui Xiong3, and AiJun  Wang4
1Department of Clinical Medicine of Ningxia Medical University, Yinchuan, China, 2the First Hospital Affiliated to Hainan Medical College, Haikou, China, 3GE Healthcare, Beijing, China, 4General Hospital of Ningxia Medical University, Yinchuan, China

Synopsis

Keywords: Cancer, Head & Neck/ENT, multi-parametric MRI-based radiomicsTo investigate the value of a nomogram based on multi-parametric MRI-based radiomics combined with clinical imaging features in predicting the Ki-67 LI in nasopharyngeal carcinoma. Least absolute shrinkage and selection operator (LASSO) regression was performed to select radiomics features. A nomogram was established using multivariable logistic regression. The receiver operating characteristic (ROC) curves, calibration, and decision curves were performed to evaluate the predictive performance of the different models. The nomograms constructed by integrating radiomics score (Rad-Score) with clinical imaging factors outperformed the clinical or the radiomics models alone.

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