Xu Tingting, Zhang Lin, Xu Hong, Kang Sifeng, Xu Yali, Luo Xiaoyu, Hua Ting, Tang Guangyu
Department of Radiology, Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China.
Oncotarget. 2017 Nov 1;8(69):114360-114370. doi: 10.18632/oncotarget.22267. eCollection 2017 Dec 26.
This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis.
Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.
Low-risk tumors showed significantly lower and s ( = 2.065, = 0.043 and = 3.548, = 0.001, respectively) and higher ADC value ( = 4.713, = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression ( = 0.000), lower MMP-9 expression ( = 0.001), and lower microvessel density (MVD) values ( = 0.008) compared with non-low-risk breast cancers. and values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers.
The prediction parameter using , , and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.
本研究旨在评估低风险和非低风险乳腺癌在动态对比增强磁共振成像(DCE-MRI)特征方面的质量差异,并探讨其可能的病理基础。
本研究获得了机构审查委员会的批准并取得了知情同意。对104例经病理证实的乳腺癌患者(104个病灶)的磁共振图像进行前瞻性分析。所有纳入患者均为中国女性。比较了两种亚型乳腺癌之间的DCE-MRI形态学表现、表观扩散系数(ADC)值、定量DCE-MRI参数和病理生物标志物。将定量DCE-MRI参数和ADC值添加到多变量模型中的形态学特征中,以评估预测低风险乳腺癌的诊断性能。这些值进一步进行了受试者操作特征(ROC)曲线分析。
与非低风险乳腺癌相比,低风险肿瘤的 和s显著更低(分别为 =2.065, =0.043和 =3.548, =0.001),ADC值更高( =4.713, =0.000)。我们的结果显示,两种乳腺癌亚型在临床数据和传统影像学表现方面无显著差异。将定量DCE-MRI参数和ADC值添加到传统MRI中可提高MRI的诊断性能:ROC曲线下面积从0.63提高到0.91。与非低风险乳腺癌相比,低风险乳腺癌的基质金属蛋白酶(MMP)-2表达显著更低( =0.000),MMP-9表达更低( =0.001),微血管密度(MVD)值更低( =0.008)。 和 值与病理生物标志物呈正相关。ADC值与病理生物标志物呈显著负相关。
利用DCE-MRI和扩散加权成像获得的 、 和ADC预测参数有助于识别低风险乳腺癌。包括MVD、血管内皮生长因子、MMP-2和MMP-9在内的生物学因素降低可能解释其可能的病理基础。