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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