title: Correlation between high resolution dynamic MR features and prognostic factors in breast cancer.
abstract: OBJECTIVE
  To correlate high resolution dynamic MR features with prognostic factors in breast cancer.
  
  
  METHODS
  One hundred and ninety-four women with invasive ductal carcinomas underwent dynamic MR imaging using T1-weighted three-dimensional fast low-angle shot (3D-FLASH) sequence within two weeks prior to surgery. Morphological and kinetic MR features were determined based on the breast imaging and reporting data system (BI-RADS) MR imaging lexicon. Histological specimens were analyzed for tumor size, axillary lymph node status, histological grade, expression of estrogen receptor (ER), expression of progesterone receptor (PR), and expression of p53, c-erbB-2, and Ki-67. Correlations between the MR features and prognostic factors were determined using the Pearson chi(2) test, linear-by-linear association, and logistic regression analysis.
  
  
  RESULTS
  By multivariate analysis, a spiculated margin was a significant, independent predictor of a lower histological grade (p < 0.001), and lower expression of Ki-67 (p = 0.007). Rim enhancement was significant, independent predictor of a higher histological grade (p < 0.001), negative expression of ER (p = 0.001), negative expression of PR (p < 0.001) and a larger tumor size (p = 0.006). A washout curve may predict a higher level of Ki-67 (p = 0.05). Most of the parameters of the initial enhancement phase cannot predict the status of the prognostic factors. Only the enhancement ratio may predict a larger tumor size (p = 0.05).
  
  
  CONCLUSIONS
  Of the BI-RADS-MR features, a spiculated margin may predict favorable prognosis, whereas rim enhancement or washout may predict unfavorable prognosis of breast cancer.
authors.affiliation: Department of Radiology, Seoul National University College of Medicine and Institute of Radiation Medicine, Seoul National University Medical Research Center, Chongno-Gu, Seoul, Korea.
authors.forename: Shin Ho
authors.initials: SH
authors.lastname: Lee
authors.forename: Nariya
authors.initials: N
authors.lastname: Cho
authors.forename: Seung Ja
authors.initials: SJ
authors.lastname: Kim
authors.forename: Joo Hee
authors.initials: JH
authors.lastname: Cha
authors.forename: Kyung Soo
authors.initials: KS
authors.lastname: Cho
authors.forename: Eun Sook
authors.initials: ES
authors.lastname: Ko
authors.forename: Woo Kyung
authors.initials: WK
authors.lastname: Moon
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000473:pathology*; D044584:Carcinoma, Ductal / Q000473:pathology*; D016009:Chi-Square Distribution; D003287:Contrast Media; D005260:Female; D019786:Gadolinium DTPA; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016015:Logistic Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D009361:Neoplasm Invasiveness; D011379:Prognosis; D012189:Retrospective Studies
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA