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The Utility of the Fifth Edition of the BI-RADS Ultrasound Lexicon in Category 4 Breast Lesions: A Prospective Multicenter Study in China

  • Yang Gu
  • , Jia Wei Tian
  • , Hai Tao Ran
  • , Wei Dong Ren
  • , Cai Chang
  • , Jian Jun Yuan
  • , Chun Song Kang
  • , You Bin Deng
  • , Hui Wang
  • , Bao Ming Luo
  • , Sheng Lan Guo
  • , Qi Zhou
  • , En Sheng Xue
  • , Wei Wei Zhan
  • , Qing Zhou
  • , Jie Li
  • , Ping Zhou
  • , Chun Quan Zhang
  • , Man Chen
  • , Ying Gu
  • Jin Feng Xu, Wu Chen, Yu Hong Zhang, Hong Qiao Wang, Jian Chu Li, Hong Yan Wang, Yu Xin Jiang
  • Chinese Academy of Medical Sciences
  • The Second Affiliated Hospital of Harbin Medical University
  • The Second Affiliated Hospital of Chongqing Medical University
  • China Medical University
  • Fudan University
  • Henan Provincial People's Hospital
  • Shanxi Medical University
  • Huazhong University of Science and Technology
  • Jilin University
  • Sun Yat-Sen University
  • The First Affiliated Hospital of Guangxi Medical University
  • Fujian Medical University
  • Shanghai Jiao Tong University
  • Renmin Hospital of Wuhan University
  • Qilu Hospital of Shandong University
  • Central South University
  • Nanchang University
  • Guizhou Medical University
  • Shenzhen People's Hospital
  • Dalian Medical University
  • Qingdao University

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Rationale and Objectives: The objective of this study was to evaluate the utility of the fifth edition of the Breast Imaging-Reporting and Data System (BI-RADS) in clinical breast radiology by using prospective multicenter real-time analyses of ultrasound (US) images. Materials and Methods: We prospectively studied 2049 female patients (age range, 19-86 years; mean age 46.88 years) with BI-RADS category 4 breast masses in 32 tertiary hospitals. All the patients underwent B-mode, color Doppler US, and US elastography examination. US features of the mass and associated features were described and categorized according to the fifth edition of the BI-RADS US lexicon. The pathological results were used as the reference standard. The positive predictive values (PPVs) of subcategories 4a-4c were calculated. Results: A total of 2094 masses were obtained, including 1124 benign masses (54.9%) and 925 malignant masses (45.1%). For BI-RADS US features of mass shape, orientation, margin, posterior features, calcifications, architectural distortion, edema, skin changes, vascularity, and elasticity assessment were significantly different for benign and malignant masses (p< 0.05). Typical signs of malignancy were irregular shape (PPV, 57.2%), spiculated margin (PPV, 83.7%), nonparallel orientation (PPV, 63.9%), and combined pattern of posterior features (PPV, 60.6%). For the changed or newly added US features, the PPVs for intraductal calcifications were 80%, 56.4% for internal vascularity, and 80% for a hard pattern on elastography. The associated features such as architectural distortion (PPV, 89.3%), edema (PPV, 69.2%), and skin changes (PPV, 76.2%) displayed high predictive value for malignancy. The rate of malignant was 7.4% (72/975) in category 4a, 61.4% (283/461) in category 4b, and 93.0% (570/613) in category 4c. The PPV for category 4b was higher than the likelihood ranges specified in BI-RADS and the PPVs for categories 4a and 4c were within the acceptable performance ranges specified in the fifth edition of BI-RADS in our study. Conclusion: Not only the US features of the breast mass, but also associated features, including vascularity and elasticity assessment, have become an indispensable part of the fifth edition of BI-RADS US lexicon to distinguish benign and malignant breast lesions. The subdivision of category 4 lesions into categories 4a, 4b, and 4c for US findings is helpful for further assessment of the likelihood of malignancy of breast lesions.

Original languageEnglish
Pages (from-to)S26-S34
JournalAcademic Radiology
Volume29
DOIs
StatePublished - Jan 2022

Keywords

  • Breast
  • Breast Imaging-Reporting and Data System (BI-RADS)
  • Breast neoplasms
  • Ultrasonography

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