title: Breast MRI: Are T2 IR sequences useful in the evaluation of breast lesions?
abstract: OBJECTIVE
  To evaluate the potential role of signal intensities calculated in T2 images as an adjunctive parameter in the analysis of mass-like enhancements classified as BIRADS (Breast Imaging Reporting and Data System) assessment categories 2, 3, 4 or 5 with the standard T1 criteria.
  
  
  METHODS
  After a retrospective review of 338-breast Magnetic Resonance Imaging (MRI) performed for the evaluation of a suspicious lesion we selected a group of 65 mass-like enhancements ranging from 5 to 20mm, classified as BIRADS assessment categories 2, 3, 4 or 5, histologically proved. In all cases we calculated the ratio between the signal intensity (SI) of the nodule and the pectoralis major muscle (LMSIR, lesion to muscle signal intensity ratio) with a multiROIs (region of interest) analysis on T2 images. A ROC analysis was performed to test the ability of the two diagnostic parameters separately considered (BIRADS and LMSIR) and combined in a new mono-dimensional variable obtained by a computerized discriminant function.
  
  
  RESULTS
  Histological examination assessed 34 malignant lesions (52.3%) and 31 benign lesions (47.7%). The evaluation of ROC curves gave the following results: BIRADS area under the curve (AUC) 0.913, S.E. 0.0368, LMSIR AUC 0.854, S.E. 0.0487, combined BIRADS-LMSIR AUC 0.965, S.E. 0.0191 with a definitive increase in the AUC between the overall ROC area and those of the two diagnostic modalities separately considered.
  
  
  CONCLUSIONS
  T2-weighted SI assessment with LMSIR measurement improves the diagnostic information content of standard breast MRI and can be considered a promising potential tool in the differential diagnosis of mass-like enhancements judged as borderline lesions (BIRADS 3 and 4).
authors.affiliation: Department of Radiological Sciences, Umberto I Hospital, "Sapienza" University of Rome, Viale Del Policlinico 155, 00161 Rome, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Ballesio
authors.forename: Sara
authors.initials: S
authors.lastname: Savelli
authors.forename: Marco
authors.initials: M
authors.lastname: Angeletti
authors.forename: Lucio Maria
authors.initials: LM
authors.lastname: Porfiri
authors.forename: Ilaria
authors.initials: I
authors.lastname: D'Ambrosio
authors.forename: Claudia
authors.initials: C
authors.lastname: Maggi
authors.forename: Elisabetta Di
authors.initials: ED
authors.lastname: Castro
authors.forename: Paolo
authors.initials: P
authors.lastname: Bennati
authors.forename: Gloria Pasqua
authors.initials: GP
authors.lastname: Fanelli
authors.forename: Anna Rita
authors.initials: AR
authors.lastname: Vestri
authors.forename: Lucia
authors.initials: L
authors.lastname: Manganaro
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity