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MRI of the breast in patients with DCIS to exclude the presence of invasive disease
Authors:Eline E. Deurloo  Jincey D. Sriram  Hendrik J. Teertstra  Claudette E. Loo  Jelle Wesseling  Emiel J. Th. Rutgers  Kenneth G. A. Gilhuijs
Affiliation:Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands. e.e.deurloo@amc.uva.nl
Abstract:

Objectives

Core biopsy underestimates invasion in more than 20% of patients with preoperatively diagnosed ductal carcinoma in situ (DCIS) without evidence of invasion (pure DCIS). The aim of the current study was to evaluate the efficacy of preoperative magnetic resonance imaging (MRI) to discriminate between patients with DCIS who are at high risk of invasive breast cancer and patients at low risk.

Methods

One hundred and twenty-five patients, preoperatively diagnosed with pure DCIS (128 lesions; 3 bilateral) by core-needle biopsy, were prospectively included. Clinical, mammographic, histological (core biopsy) and MRI features were assessed. All patients underwent breast surgery. Analyses were performed to identify features associated with presence of invasion.

Results

Eighteen lesions (14.1%) showed invasion on final histology. Seventy-three lesions (57%) showed suspicious enhancement on MRI with a type 1 (n?=?12, 16.4%), type 2 (n?=?19, 26.0%) or type 3 curve, respectively (n?=?42, 57.5%). At multivariate analysis, the most predictive features for excluding presence of invasive disease were absence of enhancement or a type 1 curve on MRI (negative predictive value 98.5%; AZ 0.80, P?=?0.00006).

Conclusion

Contrast medium uptake kinetics at MRI provide high negative predictive value to exclude presence of invasion and may be useful in primary surgical planning in patients with a preoperative diagnosis of pure DCIS.

Key Points

? It is important to determine invasion in breast DCIS. ? MRI contrast medium uptake kinetics can help exclude the presence of invasion. ? However, the positive predictive value for the presence of invasion is limited. ? MRI features were more accurate at predicting invasion than mammographic features alone.
Keywords:
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