Volume 14 Supplement 1
Positive predictive value of MRI vacuum biopsies in the diagnosis of nonmass-like lesions of the breast
© Teh et al.; licensee BioMed Central Ltd. 2012
Published: 9 November 2012
To evaluate the positive predictive value of MRI scoring for malignant mass-like (ML) and nonmass-like (NML) lesions based on the BI-RADS descriptors. To identify MRI characteristics of nonmass lesions which predict malignancy for invasive and non-invasive cancers.
Retrospective analysis of 486 MRI-guided vacuum biopsies performed at Northwick Park Hospital between April 2006 and November 2011. Each lesion was categorised according to BI-RADS lexicon (ML vs. NML lesions) and time-enhancement curves, and given an overall score of MRI 1 to 5 according to overall level of suspicion for malignant disease where MRI 4 and 5 are considered suspicious or diagnostic for malignancy. Biopsy and surgical histology results obtained.
A total of 291 ML and 152 NML lesions, of which there were 150 cancers diagnosed. Positive predictive value of MRI characteristic for malignant mass lesions is 70%. Positive predictive value of MRI characteristic for nonmass lesions is 57%. Segmental enhancement is the most common MRI morphology found in 45% DCIS. No specific features predict for invasive disease in NML lesions. Time-enhancement curves were mainly type 2 (44.6%) and type 3 (52.7%) in malignant ML lesions and unhelpful in predicting malignancy in NML lesions (72% type 2 and 59% type 3 were benign).
No specific BI-RADS feature predicts for invasive disease in NML lesions. Segmental enhancement is the most common MRI appearance for DCIS. Time-enhancement curves are unhelpful in predicting malignancy in NML lesions.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.