李洁,张晓鹏,曹崑,唐磊,孙应实,单军,欧阳涛.乳腺MR动态增强扫描联合扩散加权成像的临床应用评价[J].中国医学影像技术,2005,21(12):1821~1825
乳腺MR动态增强扫描联合扩散加权成像的临床应用评价
Clinical evaluation of combining dynamic contrast-enhanced MR imaging and diffusion-weighted MR imaging for diagnosis of breast lesion
投稿时间:2005-09-06  修订日期:2005-11-25
DOI:
中文关键词:  乳腺  磁共振成像  动态,对比增强  扩散加权成像
英文关键词:Breast  Magnetic resonance imaging  Dynamic, contrast enhancement  Diffusion-weighted imaging
基金项目:
作者单位E-mail
李洁 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036  
张晓鹏 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036 zxpabc@263.net 
曹崑 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036  
唐磊 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036  
孙应实 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036  
单军 北京大学临床肿瘤学院暨北京肿瘤医院放射科,北京 100036  
欧阳涛 北京大学临床肿瘤学院暨北京肿瘤医院乳腺外科,北京 100036  
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中文摘要:
      目的 探讨动态增强扫描联合扩散加权成像对乳腺病变定性诊断临床应用价值。方法 35例临床或钼靶X线可疑恶性发现的病人,获得病理证实的41个病灶,其中良性病灶13个,恶性病灶28个。同时进行动态增强扫描和扩散加权成像,MR扫描采用3D 快速扰相位梯度回波(FSPGR)和单次激发EPI,b=1000 s/mm2。由两名医生共同在ADW工作站Functool 2软件进行图像分析,观察病变形态和动态增强表现,绘制时间-信号强度曲线,根据病变的形态特征、时间-信号强度曲线采用评分法对病变性质进行判断,分为恶性,可疑恶性及良性三种。参照动态增强病变位置确定扩散图像病变所在,描记扩散图像上病变的感兴趣区,由软件计算获得表观扩散系数(ADC)值。采用ROC曲线法确定ADC值的诊断阈值,并进行性质判断。联合动态增强扫描和ADC值,采用评分法根据积分情况进行综合定性诊断。比较动态增强扫描、DWI ADC值及联合应用对乳腺病变定性诊断效能。结果 动态增强扫描(病灶形态学表现结合时间-信号强度曲线)诊断乳腺病变的敏感性、特异性和准确性分别为96.4%(26/27)、61.5%(8/13)和85.4%(35/41)。ROC曲线分析确定ADC诊断阈值为1.42×10-3 mm2/s,曲线下面积为0.690。ADC值诊断敏感性、特异性和准确性分别为89.3%(25/28)、61.5%(8/13)和80.5%(33/41)。动态增强扫描和DWI-ADC值联合诊断的敏感性、特异性和准确性分别为89.3%(25/28)、76.9%(10/13)和 85.4%(35/41)。有50%(14/28)的恶性病灶动态增强扫描表现不典型,通过ADC值得到进一步确定诊断。结论 动态增强扫描联合扩散加权成像有助于提高乳腺病变定性诊断的特异性,可为动态增强扫描不能确定诊断的病灶提供更有价值的信息。
英文摘要:
      Objective To evaluate the clinical value of combining dynamic contrast-enhanced MRI and diffusion weighted MR imaging (DWI) for the diagnosis of breast lesion. Methods Forty-one lesions from 35 patients were acquired with histopathological demonstration, of which 28 were malignant and 13 were benign. All lesions were examined with dynamic contrast-enhanced MRI and DWI. The sequences used were 3D fast spoiled gradient echo (FSPGR) and single-shot echo planar imaging (SS-EPI), b=1000 s/mm2. The images were reviewed by two radiologists at ADW 4.2 workstation and made consensus on the shape, contour and the type of time-signal intensity curve (TIC). The suspicious malignant aspect of morphology and types of TIC was given a point. The lesions were classified as malignant, suspicious or benign according the score summed up. Apparent diffusion coefficient (ADC) of the lesion was acquired using region of interest (ROI) technique correlated with the location of enhanced lesion by Functool Ⅱ software on the workstation. Threshold of ADC for diagnosis was acquired by ROC analysis, and lesions were classified as benign and malignant. The validities of dynamic contrast-enhanced imaging, ADC, and combination of the two Methods were evaluated. Results The sensitivity, specificity and accuracy of dynamic contrast-enhanced imaging were 96.4% (26/27), 61.5% (8/13) and 85.4% (35/41). Area under the curve for ADC was 0.690 by ROC analysis, and the threshold was 1.42×10-3 mm2/s. The sensitivity, specificity and accuracy of ADC were 89.3% (25/28), 61.5% (8/13) and 80.5% (33/41). The combination of dynamic contrast-enhanced MRI and DWI-ADC of breast lesions had a sensitivity, specificity and accuracy of 89.3% (25/28), 76.9% (10/13) and 85.4% (35/41). In half of malignant lesions which manifest atypically on dynamic contrast-enhanced MRI, definite diagnosis for malignance make instead of suspicious diagnosis due to combination with ADC. In two benign lesions, the suspicious malignant diagnosis was changed to be benign according to combination of dynamic MRI and ADC. Conclusion The combination of dynamic contrast-enhanced MRI and DWI is useful to increase specificity, and provide valuable information for the diagnosis of those lesions suspicious in dynamic contrast-enhanced MRI.
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