title: Nonmass lesions in magnetic resonance imaging of the breast: additional T2-weighted images improve diagnostic accuracy.
abstract: OBJECTIVE
  In magnetic resonance imaging (MRI) of the breast, contrast enhancements present as mass or nonmass (NM) lesions. This study aimed to test the usefulness of currently accepted T1-weighted Breast Imaging Reporting and Data System predictors and to determine the incremental value of new T2-weighted predictors for differentiation of benign from malignant NM lesions.
  
  
  METHODS
  Consecutive patients undergoing surgery after MRI (1.5-T contrast-enhanced T1- and T2-weighted images) were investigated. Lesions were rated by 2 observers in consensus. Breast Imaging Reporting and Data System criteria for NM included spatial distribution, internal enhancement, and dynamic enhancement pattern. Additional criteria on T2-weighted images were signal intensity, presence of intraductal fluid, or cysts at the enhancements location. Independent differentiation criteria (benign vs malignant) were identified by logistic regression followed by receiver operating characteristics analysis.
  
  
  RESULTS
  Of 316 patients, 65 demonstrated NM. The NM lesions were split almost equally into malignant (34) and benign (31) histology. Breast Imaging Reporting and Data System predictors did not differentiate benign from malignant lesions, whereas signal intensity and the presence of cysts on contrast-enhanced T2-weighted images did, with a sensitivity of 91.2% and a specificity of 64.5%.
  
  
  CONCLUSIONS
  Differentiation of NM can be improved using additional T2-weighted images.
authors.affiliation: Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University Jena, Jena, Germany. pascal.baltzer@med.uni-jena.de
authors.forename: Pascal A T
authors.initials: PA
authors.lastname: Baltzer
authors.forename: Matthias
authors.initials: M
authors.lastname: Dietzel
authors.forename: Werner A
authors.initials: WA
authors.lastname: Kaiser
mesh_terms: D016477:Artifacts; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology / Q000601:surgery; D016009:Chi-Square Distribution; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D012372:ROC Curve; D012680:Sensitivity and Specificity