Value of the BI-RADS classification in MR-Mammography for diagnosis of benign and malignant breast tumors

Eur Radiol. 2011 Dec;21(12):2475-83. doi: 10.1007/s00330-011-2210-7. Epub 2011 Jul 31.

Abstract

Aim: To assess whether the BI-RADS classification in MR-Mammography (MRM) can distinguish between benign and malignant lesions.

Material and method: 207 MRM investigations were categorised according to BI-RADS. The results were compared to histology. All MRM studies were interpreted by two examiners. Statistical significance for the accuracy of MRM was calculated.

Results: A significant correlation between specific histology and MRM-tumour-morphology could not be reported. Mass (68%) was significant for malignancy. Significance raised with irregular shape (88%), spiculated margin (97%), rim enhancement (98%), fast initial increase (90%), post initial plateau (65%), and intermediate T2 result (82%). Highly significant for benignity was an oval mass (79%), slow initial increase (94%) and a hyperintense T2 result (77%), also an inconspicuous MRM result (77%) was often seen in benign histology. Symmetry (90%) and further post initial increase (90%) were significant, whereas a regional distribution (74%) was lowly significant for benignity.

Conclusion: On basis of the BI-RADS classification an objective comparability and statement of diagnosis could be made highly significant. Due to the fact of false-negative and false-positive MRM-results, histology is necessary.

MeSH terms

  • Algorithms
  • Breast
  • Breast Diseases / classification*
  • Breast Diseases / diagnosis*
  • Breast Diseases / diagnostic imaging
  • Breast Diseases / pathology
  • Breast Neoplasms / classification
  • Breast Neoplasms / diagnosis
  • Diagnosis, Differential
  • Female
  • Humans
  • Magnetic Resonance Imaging* / methods
  • Mammography*
  • Middle Aged
  • Neoplasm Recurrence, Local / diagnosis*
  • Neoplasm Recurrence, Local / diagnostic imaging
  • Neoplasm Recurrence, Local / pathology
  • Observer Variation
  • Reproducibility of Results
  • Sensitivity and Specificity