Abstract #4051

DCE-MRI texture analysis in differentiating adenocarcinoma and squamous cell cancer of cervix

Xie Yuanliang¹, Wang Xiang², Du Dan², Jiang Yanping², and Sun Jianqing³

¹Radiology, Cental Hospital of Wuhan,Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, ²Radiology, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, ³Philips Healthcare, Shanghai, China

Synopsis

Adenocarcinoma comprises 25% of cervical cancers and has a bad prognosis and poor outcome of radiotherapy and chemical treatment in the advanced stage. Here, we report a radiomics method with multi-class texture features from semi-quantitative DCE-MRI maps to distinguish adenocarcinoma from squamous cell cancer. Multivariate models were trained on the training cohort and their performance was evaluated on the 5-fold cross-validation cohort using the area under ROC curve (AUC), accuracy, specificity and sensitivity. Our results showed the mean sensitivity, specificity, PPV, NPV and AUC were 0.96, 0.889, 0.967, 0.889 and 0.967 respectively in diagnosing adenocarcinoma of cervix.

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