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Abstract #4123

Identifying metastatic axillary lymph node of breast cancer by quantitative parameters with histogram and texture features on pharmacokinetic modeling dynamic contrast-enhanced MRI: A Pilot Radiomics Study

Hong-Bing Luo1, Yuan-Yuan Liu1, Shao-Yu Wang2, Jing Ren1, and Peng Zhou1

1Department of Radiology, Sichuan Cancer Hospital & Institute, Chengdu, China, 2MR Scientific Marketing, Siemens Healthineers, Shanghai, China

This study aimed to investigate the discriminative performance of pharmacokinetic quantitative parameters with histogram and texture features on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting axillary lymph nodes metastasis in breast cancer. Results showed that 6 pharmacokinetic quantitative and their histogram parameters,53 texture features of DCE-MRI were statistically difference between the positive and negative group. In cross-validation, the accuracy of the classifier obtained 90% for identifying the metastatic axillary lymph node. The radiomic features based on quantitatively pharmacokinetic DCE-MRI demonstrated promising application in discriminating between metastatic positive and negative axillary nodes of breast cancer.

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