Department of Radiological Sciences, Nagasaki University Graduate School of Biomedical Sciences, Sakamoto, Nagasaki, Japan.
Magn Reson Med Sci. 2010;9(4):217-25. doi: 10.2463/mrms.9.217.
We assessed the usefulness and limitations of utilizing apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) for the differential diagnosis of benign and malignant non-mass-like breast lesions. We retrospectively reviewed 27 such lesions (16 malignant, 11 benign) detected on magnetic resonance (MR) imaging and analyzed the enhancing patterns of dynamic contrast-enhanced DCE-MRI (distribution and internal enhancement), kinetic curve patterns, and ADC values. All images were obtained with a 1.5-tesla MR unit, with patients supine. On DCE-MRI, malignant lesions tended to show either segmental or branching-ductal distribution, and when lesions with these patterns were considered malignant, sensitivity was 68.8%; specificity, 63.6%; positive predictive value (PPV), 73.3%; negative predictive value (NPV), 58.3%; and accuracy, 66.7%. Kinetic curve analysis did not reliably differentiate benign and malignant non-mass-like lesions. There was no significant difference between the mean ADC value of the malignant lesions, 0.968 × 10(-3) mm(2)/s at b=1000 s/mm(2), and that of benign lesions, 1.207 × 10(-3) mm(2)/s (P=0.109). Receiver operating characteristic (ROC) analysis revealed the most effective threshold of ADC value for differentiating tumors as 1.1 × 10(-3) mm(2)/s; values lower than this were observed more often in malignant than benign lesions (P=0.054). Us of this threshold yielded sensitivity of 68.8%; specificity, 72.7%; PPV, 78.6%; NPV, 61.5%; and accuracy, 70.4%. Combining the ADC value criteria with the analysis of DCE-MRI pattern increased sensitivity to 93.8%, negative predictive value (NPV) to 85.7%, and accuracy to 77.8% but decreased specificity to 54.5%. Use of ADC values does not adequately improve DCE-MRI performance for differential diagnosis of non-mass-like breast lesions, but adding the ADC value criteria to the DCE-MRI pattern analysis improves sensitivity, NPV, and accuracy.
我们评估了利用磁共振扩散加权成像（DWI）中的表观扩散系数（ADC）值对非肿块样乳腺良恶性病变进行鉴别诊断的有用性和局限性。我们回顾性分析了 27 例经磁共振成像（MRI）检测到的非肿块样病变（16 例恶性，11 例良性），分析了动态对比增强磁共振成像（DCE-MRI）的强化模式（分布和内部强化）、动力学曲线模式和 ADC 值。所有图像均在 1.5T 磁共振仪上获得，患者仰卧位。在 DCE-MRI 上，恶性病变倾向于表现为节段性或分支状导管分布，当考虑这些模式的病变为恶性时，其敏感性为 68.8%；特异性为 63.6%；阳性预测值（PPV）为 73.3%；阴性预测值（NPV）为 58.3%；准确性为 66.7%。动力学曲线分析不能可靠地区分良性和恶性非肿块样病变。恶性病变的平均 ADC 值（b=1000 s/mm(2) 时为 0.968×10(-3)mm(2)/s）与良性病变的平均 ADC 值（1.207×10(-3)mm(2)/s）之间无显著差异（P=0.109）。受试者工作特征（ROC）分析显示，区分肿瘤的最有效 ADC 值阈值为 1.1×10(-3)mm(2)/s；恶性病变中低于此阈值的病变更为常见（P=0.054）。使用此阈值时，敏感性为 68.8%；特异性为 72.7%；PPV 为 78.6%；NPV 为 61.5%；准确性为 70.4%。将 ADC 值标准与 DCE-MRI 模式分析相结合，可将敏感性提高至 93.8%，将阴性预测值（NPV）提高至 85.7%，将准确性提高至 77.8%，但特异性降低至 54.5%。ADC 值的使用并不能充分提高 DCE-MRI 对非肿块样乳腺病变的鉴别诊断性能，但将 ADC 值标准添加到 DCE-MRI 模式分析中可以提高敏感性、NPV 和准确性。
