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J Korean Soc Magn Reson Med. 2013 Jun;17(2):73-82. English. Original Article. https://doi.org/10.13104/jksmrm.2013.17.2.73
Ko MS , Kim SH , Kang BJ , Choi BG , Song BJ , Cha ES , Kiraly AP , Kim IS .
Department of Radiology, Seoul St. Mary's Hospital, Seoul, Korea. rad-ksh@catholic.ac.kr
Health Screening and Promotion Center, Asan Medical Center, Seoul, Korea.
Department of General Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Department of Radiology, School of Medicine, Ewha Womans University, Seoul, Korea.
Siemens Corporation, Corporate Research, Seoul, Korea.
Siemens Ltd., Seoul, Korea.
Abstract

PURPOSE: To determine the quantitative parameters of breast MRI that predict tumor invasion in biopsy-proven DCIS. MATERIALS AND METHODS: From January 2009 to March 2010, 42 MRI examinations of 41 patients with biopsy-proven DCIS were included. The quantitative parameters, which include the initial percentage enhancement (E1), peak percentage enhancement (E(peak)), time to peak enhancement (TTP), signal enhancement ratio (SER), arterial enhancement fraction (AEF), apparent diffusion coefficient (ADC) value, long diameter and the volume of the lesion, were calculated as parameters that might predict invasion. Univariate and multivariate analyses were used to identify the parameters associated with invasion. RESULTS: Out of 42 lesions, 23 lesions were confirmed to be invasive ductal carcinoma (IDC) and 19 lesions were confirmed to be pure DCIS. Tumor size (p = 0.003; 6.5 +/- 3.2 cm vs. 3.6 +/- 2.6 cm, respectively) and SER (p = 0.036; 1.1 +/- 0.3 vs. 0.9 +/- 0.3, respectively) showed statistically significant high in IDC. In contrast, E1, Epeak, TTP, ADC, AEF and volume of the lesion were not statistically significant. Tumor size and SER had statistically significant associations with invasion, with an odds ratio of 1.04 and 22.93, respectively. CONCLUSION: Of quantitative parameters analyzed, SER and the long diameter of the lesion could be specific parameter for predicting invasion in the biopsy-proven DCIS.

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