| 南聪慧,张伟,王慧颖,华薇,袁宝霖.动态增强MRI定量评估乳腺良恶性病变的效能[J].中国医学影像技术,2018,34(4):558~562 |
| 动态增强MRI定量评估乳腺良恶性病变的效能 |
| Efficacy of dynamic contrast-enhanced MRI in quantitative assessment of benign and malignant breast lesions |
| 投稿时间：2017-07-26 修订日期：2018-01-23 |
| DOI：10.13929/j.1003-3289.201707125 |
| 中文关键词: 乳腺肿瘤 对比剂 磁共振成像 背景实质 |
| 英文关键词:Breast neoplasms Contrast media Magnetic resonance imaging Background parenchyma |
| 基金项目:辽宁省自然科学基金（2014021015）、国家重点研发计划重大慢性非传染性疾病防控研究重点专项（2016YFC1303005）。 |
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| 中文摘要: |
| 目的 探讨动态增强磁共振成像（DCE-MRI）评价乳腺良恶性病变中病灶及背景实质血流动力学参数的价值。方法 收集41例接受乳腺DCE-MRI检查的患者（共45个病灶），其中良性病变21个（良性组），恶性病变24个（恶性组），测量病灶及背景实质的容量转移常数（Ktrans）、速率常数（Kep）、血浆分数（Vp），对2组各参数进行统计学分析；以病理结果为金标准，评价各参数诊断乳腺恶性病灶的效能。结果 恶性组病灶Ktrans和Kep、背景实质Ktrans和Kep均高于良性组（P均<0.05）。2组病灶Vp和背景实质Vp差异均无统计学意义（P均>0.05）。诊断乳腺恶性病变时，背景实质Ktrans的AUC较其他参数高，敏感度、特异度分别为87.50%、76.19%。所有参数联合的Logistic回归模型AUC值最高，为0.86（P<0.001）。结论 DCE-MRI相关参数中，背景实质Ktrans对乳腺疾病的诊断价值较高。定量分析DCE-MRI数据有助于鉴别乳腺良恶性病变，其背景实质的血流动力学特征有望成为无创诊断乳腺病变的新方法。 |
| 英文摘要: |
| Objective To explore the diagnostic value of dynamic contrast-enhanced MRI (DCE-MRI) in evaluation of hemodynamic parameters of lesions and background parenchyma in benign and malignant breast lesions. Methods Breast DCE-MRI data were collected from 41 patients, including 21 benign lesions (benign group) and 24 malignant lesions (malignant group). Volume transfer constant (Ktrans), rate constant (Kep) and plasma fraction (Vp) of lesions and background parenchyma were measured, and the parameters of both groups were statistically analyzed. Taking pathological diagnosis as the gold standards, the efficacy of parameters in diagnosis of malignant breast lesions was evaluated. Results Ktrans and Kep of lesions and background parenchyma in the malignant group were higher than those in benign group (all P<0.05). There was no significant difference between Vp of lesions and background parenchyma in both groups (both P>0.05). In the diagnosis of malignant lesions, AUC of Ktrans of background parenchyma was the best, the sensitivity and specificity was 87.50% and 76.19%, respectively. All parameters combined Logistic regression model had the highest AUC value (0.86, P<0.001). Conclusion Among DCE-MRI related parameters, Ktrans of background parenchyma has the highest diagnostic value. Quantitative analysis of DCE-MRI data can help to identify benign and malignant breast lesions, and the hemodynamic characteristics of the background parenchyma are expected to be new methods for non-invasive diagnosis of breast lesions. |
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