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Diagnostic accuracy of 1.5 Tesla breast magnetic resonance imaging in the pre-operative assessment of axillary lymph nodes
C. de Felice1, V. Cipolla1, A. Stagnitti1, L. M. Porfiri1, D. Guerrieri1, A. Musella2, D. Santucci1, M. L. Meggiorini2,*
1 Department of Radiological Sciences, University of Rome “Sapienza”, Rome
2 Department of Gynaecological Sciences, University of Rome “Sapienza”, Rome (Italy)
Eur. J. Gynaecol. Oncol. 2015, 36(4), 447–451; https://doi.org/10.12892/ejgo2663.2015
Published: 10 August 2015
The purpose of this study was to test the accuracy of 1.5 Tesla magnetic resonance imaging (1.5T MRI) in the preoperative evaluation of axillary lymph nodes in patients with invasive breast cancer. The authors retrospectively analyzed 26 patients with invasive breast cancer who had undergone sentinel lymph node biopsy (SLNB) and/or axillary lymph node dissection (ALND). All patients had been submitted to preoperative contrast enhanced breast 1.5T MRI. On the basis of lymph nodes morphological and dynamic characteristics, lymph nodes were classified as “negative” (short axis < 5 mm), “borderline” (short axis > 5 mm, absence of a hilum) or “positive” (short axis > 5 mm, absence of a hilum and also other suspicious features). The authors compared 1.5T MRI results with the outcome of histological analysis performed according to the TNM criteria; sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) of 1.5T MRI were evaluated. Considering only the lymph nodes “positive”, 1.5 T MRI showed: SE 37.8%, SP 99.3%, FP 0.7%, PPV 92.5%, and NPV 88.1%. However, considering also “borderline”, 1.5T MRI achieved: SE 75.7%, SP 99.3%, FP 0.7%, PPV 96.1%, and NPV was 95%. Contrast enhanced breast 1.5T MRI is not yet a valid alternative to histological analysis but it is a valid tool for a preoperative study of the topography of axillary lymph nodes and has the potential to become a routine method for evaluating the metastatic lymph nodes before submission to ALND.
Axillary lymph nodes
Magnetic resonance imaging