Habib Rahbar1, Sana Parsian2, Diana L Lam2, Brian N Dontchos2, Nicole K Andeen3, Mara H Rendi3, Constance D Lehman2, Savannah C Partridge2. 1. University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA. Electronic address: hrahbar@uw.edu. 2. University of Washington, Seattle Cancer Care Alliance, Department of Radiology, Breast Imaging Section, 825 Eastlake Avenue East, P.O. Box 19023, Seattle, WA 98109-1023, USA. 3. University of Washington Department of Anatomic Pathology, 1959 NE Pacific St., Box 357470, Seattle, WA 98195, USA.
Abstract
OBJECTIVE: The objective was to explore whether 3-T magnetic resonance imaging (MRI) can identify low-risk ductal carcinoma in situ (DCIS). METHODS: Dynamic contrast-enhanced and diffusion-weighted (DWI) MRI features of 36 DCIS lesions [8 low risk, Van Nuys Pathologic Classification (VNPC) 1; 28 high risk, VNPC 2/3] were reviewed. An MRI model that best identified low-risk DCIS was determined using multivariate logistic regression. RESULTS: Low-risk DCIS exhibited different DWI properties [i.e., higher contrast-to-noise ratio (P=.02) and lower normalized apparent diffusion coefficients (P=.04)] than high-risk DCIS. A model combining these DWI features provided best performance (area under receiver operating characteristic curve =0.86). CONCLUSIONS: DWI may help identify DCIS lesions requiring less therapy.
OBJECTIVE: The objective was to explore whether 3-T magnetic resonance imaging (MRI) can identify low-risk ductal carcinoma in situ (DCIS). METHODS: Dynamic contrast-enhanced and diffusion-weighted (DWI) MRI features of 36 DCIS lesions [8 low risk, Van Nuys Pathologic Classification (VNPC) 1; 28 high risk, VNPC 2/3] were reviewed. An MRI model that best identified low-risk DCIS was determined using multivariate logistic regression. RESULTS: Low-risk DCIS exhibited different DWI properties [i.e., higher contrast-to-noise ratio (P=.02) and lower normalized apparent diffusion coefficients (P=.04)] than high-risk DCIS. A model combining these DWI features provided best performance (area under receiver operating characteristic curve =0.86). CONCLUSIONS: DWI may help identify DCIS lesions requiring less therapy.
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