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Abstract #2323

Diagnosis of Non-Mass-Like Enhancement Lesions on DCE-MRI by Using Quantitative Radiomics and Radiologists’ BI-RADS Reading

Meihao Wang1, Yang Zhang2, Jiejie Zhou1, Haiwei Miu1, Nina Xu1, Xiaxia He1, Shuxin Ye1, Huiru Liu1, Ouchen Wang1, Jiance Li1, Yezhi Lin3, and Min-Ying Su2
1First Affiliate Hospital of Wenzhou Medical University, Wenzhou, China, 2University of California, Irvine, Irvine, CA, United States, 3Wenzhou Medical University, Wenzhou, China

A total of 105 lesions, 70 malignant and 35 benign, presenting as non-mass-like enhancements were analyzed. Two radiologists gave the BI-RADS reading for the morphological distribution and the internal enhancement pattern. For each case, the 3D tumor mask was generated using FCM clustering algorithm with connective labeling and hole filling. Three DCE parameters maps were generated from the images, and PyRadiomics was applied to extract a total of 321 features for each case. The diagnostic model was built using SVM with 10-fold cross-validation. The accuracy of the radiomics model was 82%, higher compared to 72% built with the BI-RADS reading.

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