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Abstract #1449

Diagnostic performance of texture analysis on MRI in differentiated degree of head and neck carcinoma

Yu Chen1, Yuan Li, Yuanli Zhu, Huadan Xue, Zhuhua Zhang, Hailong Zhou, and Zhengyu Jin

1Peking Union Medical College Hospital, Beijing, People's Republic of China

The aim of this study was to determine the diagnostic accuracy of pathological differentiated degree of head and neck squamous cell carcinoma (HNSCC) using MRI texture analysis. The following texture analysis parameters were derived from the T1WI, T2WI , T2fs and Post-Gad T1WI based on different scale: entropy , mean pixel intensity, standard deviation(SD), skewness, and kurtosis. ROC curves and AUC of each parameter was determined, respectively. We conclude that the entropy at fine texture scale on Post-Gad T1WI had the best ability .

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