The role of MRI in predicting Ki-67 in breast cancer: preliminary results from a prospective study.

TUMORI J(2018)

引用 11|浏览19
暂无评分
摘要
Purpose: In the last decade contrast-enhanced magnetic resonance imaging (MRI) has gained a growing role as a complementary tool for breast cancer diagnosis. Currently the relationship between the kinetic features of a breast lesion and pathologic prognostic factors has become a popular field of research. Our aim is to verify whether breast MRI could be considered a useful tool to predict Ki-67 score, thus resulting as a breast cancer prognosis indicator. Methods: From June to December 2014, we enrolled patients with breast cancer who underwent preoperative dynamic contrast-enhanced MRI at the local health agency. We analyzed the time-signal intensity curves calculating the mean values of the following parameters: the basal enhancement (E-base), the enhancement ratio (ENHratio), the maximum enhancement (E-max), and the steepest slope of the contrast enhancement curve (S-max). Scatterplots and Pearson correlation test were used to investigate the eventual associations among these parameters. Results: A total of 27 patients underwent breast MRI during the study period. The mean +/- SD Ki-67 percentage was 27.03 +/- 16.8; the mean E-max, S-max, E-base, and ENHratio were 433.9 +/- 120.2, 267.3 +/- 96.8, 165.5 +/- 77.1, and 187.1 +/- 94.8, respectively. Scatterplots suggest a positive correlation between Ki-67 and both E-max and S-max. The correlation tests between Ki-67 and E-max, Ki-67 and S-max showed statistical significance. Conclusions: Our preliminary data suggest that enhancement pattern is closely linked to breast cancer proliferation, thus proving the relationship between more proliferating tumors and more rapidly enhanced lesions. This is hypothesis-generating for further studies aimed at promoting breast MRI in the early estimation of cancer prognosis and tumor in vivo response to chemotherapy.
更多
查看译文
关键词
Breast cancer,Magnetic resonance imaging,Prognostic factors
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要