Breast MRI: Are T2 IR sequences useful in the evaluation of breast lesions?
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).
Ballesio
Laura
L
Department of Radiological Sciences, Umberto I Hospital, "Sapienza" University of Rome, Viale Del Policlinico 155, 00161 Rome, Italy.
Savelli
Sara
S
Angeletti
Marco
M
Porfiri
Lucio Maria
LM
D'Ambrosio
Ilaria
I
Maggi
Claudia
C
Castro
Elisabetta Di
ED
Bennati
Paolo
P
Fanelli
Gloria Pasqua
GP
Vestri
Anna Rita
AR
Manganaro
Lucia
L
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