Department of Radiology, Trakya University School of Medicine, Uzunoglu 2, Apt. No: 60 Daire: 4/13, 22030 Edirne, Turkey.
Eur J Radiol. 2012 May;81(5):863-7. doi: 10.1016/j.ejrad.2011.02.021. Epub 2011 Mar 12.
The aim of the study is to assess the predictive power of DCE-MRI semi-quantitative parameters during treatment of breast cancer, for disease-free (DFS) and overall survival (OS).
Forty-nine women (age range, 28-84 years; mean, 50.6 years) with breast cancer underwent dynamic contrast enhancement MRI at 1.0T imaging, using 2D FLASH sequences. Time intensity curves (TICs) were obtained from the regions showing maximal enhancement in subtraction images. Semi-quantitative parameters (TICs; maximal relative enhancement within the first minute, E (max/1); maximal relative enhancement of the entire study, E(max); steepest slope of the contrast enhancement curve; and time to peak enhancement) derived from the DCE-MRI data. These parameters were then compared with presence of recurrence or metastasis, DFS and OS by using Cox regression (proportional hazards model) analysis, linear discriminant analysis.
The results from of the 49 patients enrolled into the survival analysis demonstrated that traditional prognostic parameters (tumor size and nodal metastasis) and semi-quantitative parameters (E(max/1), and steepest slope) demonstrated significant differences in survival intervals (p<0.05). Further Cox regression (proportional hazards model) survival analysis revealed that semi-quantitative parameters contributed the greatest prediction of both DFS, OS in the resulting models (for E(max/1): p=0.013, hazard ratio 1.022; for stepest slope: p=0.004, hazard ratio 1.584).
This study shows that DCE-MRI has utility predicting survival analysis with breast cancer patients.
本研究旨在评估乳腺癌治疗过程中 DCE-MRI 半定量参数对无病生存(DFS)和总生存(OS)的预测能力。
49 名女性(年龄 28-84 岁,平均 50.6 岁)接受了 1.0T 成像的动态对比增强 MRI,使用 2D FLASH 序列。在减影图像中显示最大增强的区域获得时间强度曲线(TIC)。从 DCE-MRI 数据中获得半定量参数(TIC;第 1 分钟内的最大相对增强,E(max/1);整个研究的最大相对增强,E(max);对比度增强曲线的最陡斜率;以及增强峰值时间)。然后通过 Cox 回归(比例风险模型)分析、线性判别分析,将这些参数与复发或转移、DFS 和 OS 的存在进行比较。
纳入生存分析的 49 名患者的结果表明,传统预后参数(肿瘤大小和淋巴结转移)和半定量参数(E(max/1)和最陡斜率)在生存间隔方面存在显著差异(p<0.05)。进一步的 Cox 回归(比例风险模型)生存分析显示,半定量参数对 DFS 和 OS 的预测贡献最大(对于 E(max/1):p=0.013,风险比 1.022;对于最陡斜率:p=0.004,风险比 1.584)。
本研究表明,DCE-MRI 对乳腺癌患者的生存分析具有预测作用。