Magnetic Resonance Imaging of the Breast Prior to Biopsy
- David A. Bluemke, MD, PhD;
- Constantine A. Gatsonis, PhD;
- Mei Hsiu Chen, MS;
- Gia A. DeAngelis, MD;
- Nanette DeBruhl, MD;
- Steven Harms, MD;
- Sylvia H. Heywang-Köbrunner, MD, PhD;
- Nola Hylton, PhD;
- Christiane K. Kuhl, MD;
- Constance Lehman, MD, PhD;
- Etta D. Pisano, MD;
- Petrina Causer, MD;
- Stuart J. Schnitt, MD;
- Stanley F. Smazal, MD;
- Carol B. Stelling, MD;
- Paul T. Weatherall, MD;
- Mitchell D. Schnall, MD, PhD
- Author Affiliations: Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Md (Dr Bluemke); Center for Statistical Sciences, Brown University, Providence, RI (Dr Gatsonis and Ms Chen); Department of Radiology, University of Virginia Health System, Charlottesville (Dr DeAngelis); Department of Radiological Sciences, School of Medine, University of California, Los Angeles (Dr DeBruhl); Department of Radiology, University of Arkansas for Medical Sciences, Little Rock (Dr Harms); Department of Breast Imaging, Technical University, Munich, Germany (Dr Heywang-Köbrunner); Magnetic Resonance Science Center and Department of Radiology, University of California, San Francisco (Dr Hylton); Department of Radiology, University of Bonn, Bonn, Germany (Dr Kuhl); Cancer Care Alliance and Department of Radiology, University of Washington, Seattle (Dr Lehman); Department of Radiology, University of North Carolina, Chapel Hill (Dr Pisano); Department of Radiology, University of Toronto and Sunnybrook Cancer Care Center, Toronto, Ontario (Dr Causer); Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Mass (Dr Schnitt); Radiology Imaging Associates and Porter Adventist Hospital, Littleton, Colo (Dr Smazal); Division of Diagnostic Imaging, University of Texas M. D. Anderson Cancer Center, Houston (Dr Stelling); Department of Radiology, University of Texas Southwestern Medical Center, Dallas (Dr Weatherall); and the Department of Radiology, University of Pennsylvania, Philadelphia (Dr Schnall).
- Corresponding Author: David A. Bluemke, MD, PhD, Department of Radiology, Johns Hopkins Hospital, 600 N Wolfe St, Baltimore, MD 21287 (dbluemke{at}jhmi.edu).
Abstract
Context Breast magnetic resonance imaging (MRI) has been shown to have high sensitivity for cancer detection and is increasingly used following mammography to evaluate suspicious breast lesions.
Objective To determine the accuracy of breast MRI in conjunction with mammography for the detection of breast cancer in patients with suspicious mammographic or clinical findings.
Design, Setting, and Patients Prospective multicenter investigation of the International Breast MR Consortium conducted at 14 university hospitals in North America and Europe from June 2, 1998, through October 31, 2001, of 821 patients referred for breast biopsy for American College of Radiology category 4 or 5 mammographic assessment or suspicious clinical or ultrasound finding.
Interventions MRI examinations performed prior to breast biopsy; MRI results were interpreted at each site, which were blinded to pathological results.
Main Outcome Measures Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of breast MRI.
Results Among the 821 patients, there were 404 malignant index lesions, of which 63 were ductal carcinoma in situ (DCIS) and 341 were invasive carcinoma. Of the 417 nonmalignant index lesions, 366 were benign, 47 showed atypical histology, and 4 were lobular carcinoma in situ. The AUC pooled over all institutions was 0.88 (95% confidence interval [CI], 0.86-0.91). MRI correctly detected cancer in 356 of 404 cancer cases (DCIS or invasive cancer), resulting in a sensitivity of 88.1% (95% CI, 84.6%-91.1%), and correctly identified as negative for cancer 281 of 417 cases without cancer, resulting in a specificity of 67.7% (95% CI, 62.7%-71.9%). MRI performance was not significantly affected by mammographic breast density, tumor histology, or menopausal status. The positive predictive values for 356 of 492 patients was 72.4% (95% CI, 68.2%-76.3%) and of mammography for 367 of 695 patients was 52.8% (95% CI, 49.0%-56.6%) (P<.005). Dynamic MRI did not improve the AUC compared with 3-dimensional MRI alone, but the specificity of a washout pattern for 123 of 136 patients without cancer was 90.4% (95% CI, 84%-95%).
Conclusions Breast MRI has high sensitivity but only moderate specificity independent of breast density, tumor type, and menopausal status. Although the positive predictive value of MRI is greater than mammography, MRI does not obviate the need for subsequent tissue sampling in this setting.
