Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China.
MR Collaboration NE Asia, Siemens Healthcare, Shanghai, P.R. China.
J Magn Reson Imaging. 2018 Jan;47(1):91-96. doi: 10.1002/jmri.25762. Epub 2017 Jun 3.
To investigate the application of whole-lesion histogram analysis of pharmacokinetic parameters for differentiating malignant from benign breast lesions on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
In all, 92 women with 97 breast lesions (26 benign and 71 malignant lesions) were enrolled in this study. Patients underwent dynamic breast MRI at 3T using a prototypical CAIPIRINHA-Dixon-TWIST-VIBE (CDT-VIBE) sequence and a subsequent surgery or biopsy. Inflow rate of the agent between plasma and interstitium (K ), outflow rate of agent between interstitium and plasma (K ), extravascular space volume per unit volume of tissue (v ) including mean value, 25th/50th/75th/90th percentiles, skewness, and kurtosis were then calculated based on the whole lesion. A single-sample Kolmogorov-Smirnov test, paired t-test, and receiver operating characteristic curve (ROC) analysis were used for statistical analysis.
Malignant breast lesions had significantly higher K , K , and lower v in mean values, 25th/50th/75th/90th percentiles, and significantly higher skewness of v than benign breast lesions (all P < 0.05). There was no significant difference in kurtosis values between malignant and benign breast lesions (all P > 0.05). The 90th percentile of K , the 90th percentile of K , and the 50th percentile of v showed the greatest areas under the ROC curve (AUC) for each pharmacokinetic parameter derived from DCE-MRI. The 90th percentile of K achieved the highest AUC value (0.927) among all histogram-derived values.
The whole-lesion histogram analysis of pharmacokinetic parameters can improve the diagnostic accuracy of breast DCE-MRI with the CDT-VIBE technique. The 90th percentile of K may be the best indicator in differentiation between malignant and benign breast lesions.
4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:91-96.
研究基于药代动力学参数的整体病变直方图分析在鉴别乳腺良恶性病变中的应用。
本研究共纳入 92 例 97 个乳腺病变患者（26 个良性病变，71 个恶性病变）。患者在 3T 磁共振扫描仪上使用原型 CAIPIRINHA-Dixon-TWIST-VIBE（CDT-VIBE）序列进行了动态乳腺 MRI 检查，随后进行了手术或活检。基于整个病变，计算了血浆与间质之间的流入速率（K）、间质与血浆之间的流出速率（K）、血管外间隙体积与组织体积比（v），包括平均值、25%/50%/75%/90%分位数、偏度和峰度。采用单样本 Kolmogorov-Smirnov 检验、配对 t 检验和受试者工作特征曲线（ROC）分析进行统计学分析。
恶性乳腺病变的 K、K 和 v 的平均值、25%/50%/75%/90%分位数明显较高，而 v 的偏度明显较高（均 P＜0.05）。恶性与良性乳腺病变的 v 的峰度值无明显差异（均 P＞0.05）。DCE-MRI 各药代动力学参数中，K 的 90%分位数、K 的 90%分位数和 v 的 50%分位数的 ROC 曲线下面积（AUC）最大。K 的 90%分位数的 AUC 值最高（0.927）。
基于药代动力学参数的整体病变直方图分析可提高 CDT-VIBE 技术乳腺 DCE-MRI 的诊断准确性。K 的 90%分位数可能是鉴别良恶性乳腺病变的最佳指标。
4 技术功效分级：2 J. Magn. Reson. Imaging 2018；47：91-96。
