Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment
Ping Xu, Min Yang, Yong Liu, Yanping Li, Hong Zhang, Guangrui Shao
Abstract
BACKGROUND: Edition of the Breast Imaging Reporting and Data System (BI-RADS). Contrast-enhanced ultrasound (CEUS) can help to differentiate and classify breast lesions but there are few studies on NMLs alone. AIM: To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography (US), color Doppler flow imaging (CDFI) and CEUS, and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs. METHODS: A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019. All lesions were examined by US, CDFI and CEUS, and their features from those examinations were analyzed. With pathology as the gold standard, binary logic regression was used to analyze the independent risk factors for malignant breast NMLs, and a regression equation was established to calculate the efficiency of combined diagnosis. Based on the regression equation, the combined diagnostic efficiency of US combined with CEUS (US + CEUS) was determined. The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS, and the diagnostic efficiency of CEUS combined with BI-RADS (CEUS + BI-RADS) was calculated based on the results. ROC curves were drawn to compare the diagnostic values of the three methods, including US, US + CEUS, and CEUS + BI-RADS, for benign and malignant NMLs. RESULTS: tests showed that the area under the ROC curve of US was statistically smaller than that of US + CEUS and CEUS + BI-RADS, and there was no statistical difference between US + CEUS and CEUS + BI-RADS. CONCLUSION: US combined with CEUS can improve diagnostic efficiency for NMLs. The adjustment of the BI-RADS classification according to the features of contrast-enhanced US of NMLs enables the diagnostic results to be simple and intuitive, facilitates the management of NMLs, and effectively reduces the incidence of unnecessary biopsy.