Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI

Jpn J Radiol. 2021 Jan;39(1):56-65. doi: 10.1007/s11604-020-01029-w. Epub 2020 Sep 1.

Abstract

Purpose: Category 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital.

Materials and methods: This retrospective study included 346 breast MRIs with 434 category 2-5 lesions. All enhancing lesions were classified as category 2 (0% probability of malignancy), 3 (> 0%, ≤ 2%), 4 (> 2%, < 95%) and 5 (≥ 95%); category 4 lesions were further subcategorized into 4A (> 2%, ≤ 10%), 4B (> 10%, ≤ 50%) and 4C (> 50%, < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated.

Results: We included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions.

Conclusion: Category 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant.

Keywords: Breast neoplasms; Diagnosis; Magnetic resonance imaging.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast / diagnostic imaging
  • Breast Neoplasms / classification
  • Breast Neoplasms / diagnostic imaging*
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Middle Aged
  • Predictive Value of Tests
  • Radiology Information Systems / statistics & numerical data*
  • Reproducibility of Results
  • Retrospective Studies
  • Young Adult