Underestimation of Breast Cancer Based on Ultrasound Breast Imaging-Reporting and Data System (BI-RADS) Assessment of Ductal Carcinoma In Situ: A Retrospective Study of 296 Lesions

Abstract

Background: Ultrasound Breast Imaging-Reporting and Data System (BI-RADS) classification may underestimate ductal carcinoma in situ (DCIS). Currently, there is a lack of research on ultrasound BI-RADS underestimating DCIS. Objectives: To improve the diagnosis of DCIS, this study aimed to investigate factors associated with the underestimation of DCIS, based on ultrasound BI-RADS assessments. Methods: In this cross-sectional study, consecutive patients with breast ultrasound BI-RADS classification and biopsy results were retrospectively examined. DCIS was found in the pathology reports of all patients. DCIS cases classified as BI-RADS 4A or lower were considered as underestimations of DCIS, while DCIS cases classified as BI-RADS 4B or higher were considered as non-underestimation of DCIS. The demographics, clinical manifestations, features of breast images, BI-RADS classification, and pathological results of the two groups were compared to explore possible associated factors. A stepwise logistic regression analysis was also carried out based on the significance of factors associated with the underestimation of DCIS according to the BI-RADS assessment. Results: Between January 2015 and May 2017, a total of 296 breast DCIS lesions were diagnosed in 294 female patients. Overall, 65 lesions (22.0%) were underestimated DCIS, and 231 lesions (78.0%) were non-underestimated DCIS; no significant differences were found between their clinical presentations. The univariate analysis showed that the age of the patients, presence of microinvasions, maximum lesion diameter, shape, margin, orientation, echo pattern, posterior acoustic features, ultrasound pattern, and vascularity of lesions were possibly associated factors, which could lead to the underestimation of DCIS. The logistic regression analysis showed that age above 50 years, maximum lesion diameter < 10 mm, lack of microinvasion, and circumscribed margins were associated with the underestimation of DCIS. Conclusion: In this study, 22% of DCIS lesions was underestimated by the BI-RADS assessment. The patient’s age, maximum lesion diameter, microinvasion, and lesion margin were associated with the underestimation of DCIS.