Abstract
Objective: To correlate high resolution dynamic MR features with prognostic factors in breast cancer. Materials and 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 χ2 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). Conclusion: 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.
| Original language | English |
|---|---|
| Pages (from-to) | 10-18 |
| Number of pages | 9 |
| Journal | Korean Journal of Radiology |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2008 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Breast neoplasms
- Breast, MR
- Prognostic factors
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