Dynamic contrast-enhanced breast magnetic resonance imaging for the prediction of early and late recurrences in breast cancer

动态增强乳腺磁共振成像用于预测乳腺癌的早期和晚期复发

阅读:1

Abstract

The aim of the study was to evaluate dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI) features for the prediction of early and late recurrences in patients with breast cancer.Of 1030 breast cancer patients who underwent surgery at our hospital from January 2007 to July 2011, 83 recurrent breast cancer patients were enrolled in this study. We compared MRI features (background parenchymal enhancement [BPE], internal enhancement, adjacent vessel sign, whole-breast vascularity, initial enhancement pattern, kinetic curve types, and quantitative kinetic parameters) and clinico-pathologic variables (age, stage, histologic grade, nuclear grade, existence of lymphovascular invasion and extensive intraductal carcinoma component, and immunohistochemical profiles) between patients with early (≤2.5 years after surgery) and late recurrence (>2.5 years after surgery). Cox proportional hazard regression analysis was performed to evaluate independent risk factors for early and late recurrence.On breast MRI, prominent ipsilateral whole-breast vascularity was independently associated with early recurrence (hazard ratio [HR], 2.86; 95% confidence intervals [CI], 1.39-5.88) and moderate or marked BPE (HR, 2.08; 95% CI, 1.04-4.18) and rim enhancement (HR, 2.14; 95% CI, 1.00-4.59) were independently associated with late recurrence. Clinico-pathologic variables independently associated with early recurrence included negative estrogen receptor (HR, 0.53; 95% CI, 0.29-0.96), whereas T2 stage (HR, 2.08; 95% CI, 1.04-4.16) and nuclear grade III (HR, 2.54; 95% CI, 1.29-4.98) were associated with late recurrence.In DCE-MRI, prominent ipsilateral whole-breast vascularity, moderate or marked BPE, and rim enhancement could be useful for predicting recurrence timing in patients with breast cancer.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。