乳腺良恶性肿块的鉴别：动态对比增强磁共振成像（DCE-MRI）的半定量分析与表观扩散系数（ADC）图的直方图分析相结合
Differentiation between malignant and benign breast masses: combination of semi-quantitative analysis on DCE-MRI and histogram analysis of ADC maps.
作者信息
Liu H-L, Zong M, Wei H, Lou J-J, Wang S-Q, Zou Q-G, Shi H-B, Jiang Y-N
机构信息
Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210029, China.
Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210029, China.
出版信息
Clin Radiol. 2018 May;73(5):460-466. doi: 10.1016/j.crad.2017.11.026. Epub 2017 Dec 30.
AIM
To investigate the performance of combined semi-quantitative analysis on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) and histogram analysis of diffusion-weighted imaging (DWI) for distinguishing malignant from benign breast masses.
MATERIALS AND METHODS
This study included 178 patients with breast masses (benign:malignant=88:9) who underwent both DCE-MRI and DWI. The semi-quantitative parameters, derived from DCE-MRI, included maximum slope of increase (MSI), signal intensity slope (SI), initial percentage of enhancement (E), percentage of peak enhancement (E), early signal enhancement ratio (ESER), and second enhancement percentage (SEP). Histogram parameters derived from apparent diffusion coefficient (ADC) maps included ADC, ADC, ADC, ADC, ADC, ADC, ADC, ADC, skewness, and kurtosis. All parameters were compared between malignant and benign groups, and their differences were tested using independent-samples t-test or Mann-Whitney test. Receiver operating characteristic (ROC) curves were used to determine the diagnostic value of each significant parameter.
RESULTS
Among semi-quantitative parameters, SI exhibited the best diagnostic performance in predicting malignancy (cut-off value, 0.096; ROC, 0.756; sensitivity, 86.7%; specificity, 61.4%). Among histogram parameters, ADC exhibited the best diagnostic performance in predicting malignancy (cut-off value, 1.051; ROC, 0.885; sensitivity, 86.7%; specificity, 84.1%). The optimal diagnostic performance of combined ADC and SI (area under curve [AUC], 0.888; sensitivity, 82.2%; specificity, 95.5%) was significantly better than SI alone (p<0.001). Moreover, the combination showed higher AUC (0.888 versus 0.885) than ADC alone, but the difference was not statistically significant (p=0.914).
CONCLUSION
SI and ADC are significant predictors for breast malignancy. The combination of DCE-MRI and DWI improves differentiating performance.
目的
探讨动态对比增强（DCE）磁共振成像（MRI）的联合半定量分析及扩散加权成像（DWI）直方图分析在鉴别乳腺良恶性肿块中的性能。
材料与方法
本研究纳入了178例接受DCE-MRI和DWI检查的乳腺肿块患者（良性：恶性 = 88:9）。从DCE-MRI得出的半定量参数包括最大上升斜率（MSI）、信号强度斜率（SI）、初始强化百分比（E）、峰值强化百分比（E）、早期信号强化率（ESER）和二次强化百分比（SEP）。从表观扩散系数（ADC）图得出的直方图参数包括ADC、ADC、ADC、ADC、ADC、ADC、ADC、ADC、偏度和峰度。对所有参数在恶性和良性组之间进行比较，并使用独立样本t检验或曼-惠特尼检验来检验它们的差异。采用受试者工作特征（ROC）曲线来确定每个显著参数的诊断价值。
结果
在半定量参数中，SI在预测恶性方面表现出最佳诊断性能（截断值为0.096；ROC为0.756；敏感性为86.7%；特异性为61.4%）。在直方图参数中，ADC在预测恶性方面表现出最佳诊断性能（截断值为1.051；ROC为0.885；敏感性为86.7%；特异性为84.1%）。联合ADC和SI的最佳诊断性能（曲线下面积[AUC]为0.888；敏感性为82.2%；特异性为95.5%）显著优于单独的SI（p<0.001）。此外，联合检测的AUC（0.888对0.885）高于单独的ADC，但差异无统计学意义（p = 0.914）。
结论
SI和ADC是乳腺恶性肿瘤的重要预测指标。DCE-MRI和DWI的联合应用提高了鉴别性能。
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