Skip to main navigation Skip to search Skip to main content

MRI of the breast in patients with DCIS to exclude the presence of invasive disease

  • Eline E. Deurloo
  • , Jincey D. Sriram
  • , Hendrik J. Teertstra
  • , Claudette E. Loo
  • , Jelle Wesseling
  • , Emiel J. Th Rutgers
  • , Kenneth G. A. Gilhuijs

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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. 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. 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%; A(Z) 0.80, P = 0.00006). 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. aEuro cent It is important to determine invasion in breast DCIS. aEuro cent MRI contrast medium uptake kinetics can help exclude the presence of invasion. aEuro cent However, the positive predictive value for the presence of invasion is limited. aEuro cent MRI features were more accurate at predicting invasion than mammographic features alone
Original languageEnglish
Pages (from-to)1504-1511
JournalEuropean radiology
Volume22
Issue number7
DOIs
Publication statusPublished - 2012

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Fingerprint

Dive into the research topics of 'MRI of the breast in patients with DCIS to exclude the presence of invasive disease'. Together they form a unique fingerprint.

Cite this