Department of Radiology, Qilu Hospital of Shandong University, Jinan, Shandong, China (mainland).
Department of Radiology, Laigang Hospital Affiliated to Taishan Medical University, Laiwu, Shandong, China (mainland).
Med Sci Monit. 2018 Apr 12;24:2180-2188. doi: 10.12659/msm.907000.
BACKGROUND This study aims to subdivide BI-RADS-MRI (Breast Imaging Reporting and Data System Magnetic Resonance Imaging) Category 4 lesions and to evaluate the role of Fischer's scoring system, apparent diffusion coefficient (ADC), and Fischer's + ADC in differential diagnosis of breast lesions. MATERIAL AND METHODS This study retrospectively analyzed the data of 143 patients (150 breast lesions), who were diagnosed by biopsy, and received dynamic contrast enhancement and diffusion-weighted imaging. The diagnostic efficacies of ADC, Fischer's scoring system, and the Fischer's + ADC were analyzed by the receiver operating characteristics curve. The area under the curve (AUC) was calculated. Fischer's scoring system and the Fischer's + ADC were used to subdivide BI-RADS Category 4 breast lesions. RESULTS ADC value was negatively correlated with the tumor grade. The AUC of Fischer's + ADC (0.949) was significantly higher than that of ADC (0.855) and Fischer's (0.912) (P=0.0008 and 0.001, respectively). Scored by Fischer's scoring system, Category 4 and 5 indicated a likely malignant threshold with sensitivity and specificity of 98.70% and 65.75%, respectively. Scored by the Fischer's + ADC method, Category 4B and 4C indicated a likely malignant threshold with sensitivity of 97.40% and specificity of 82.19%. Kappa values were 0.63 (ADC), 0.65 (Fischer's), and 0.80 (Fischer's + ADC), respectively. The positive predictive value of BI-RADS 4A, 4B, and 4C were 7.69%, 52.38% and 89.29%, respectively. CONCLUSIONS Fischer's scoring system combined with ADC could reasonably subdivide Category 4 breast lesions with high specificity and sensitivity.
本研究旨在细分 BI-RADS-MRI（乳腺影像报告和数据系统磁共振成像）类别 4 病变，并评估 Fischer 评分系统、表观扩散系数（ADC）和 Fischer+ADC 在鉴别诊断乳腺病变中的作用。
本研究回顾性分析了 143 例（150 个乳腺病变）经活检诊断、行动态对比增强及扩散加权成像患者的资料。通过受试者工作特征曲线分析 ADC、Fischer 评分系统及 Fischer+ADC 的诊断效能，计算曲线下面积（AUC）。应用 Fischer 评分系统及 Fischer+ADC 对 BI-RADS 类别 4 乳腺病变进行细分。
ADC 值与肿瘤分级呈负相关。Fischer+ADC 的 AUC（0.949）显著高于 ADC（0.855）和 Fischer（0.912）（P=0.0008 和 0.001）。按照 Fischer 评分系统进行评分，4 类和 5 类为提示恶性的可能阈值，其敏感度和特异度分别为 98.70%和 65.75%。应用 Fischer+ADC 方法评分，4B 类和 4C 类为提示恶性的可能阈值，敏感度为 97.40%，特异度为 82.19%。Kappa 值分别为 0.63（ADC）、0.65（Fischer）和 0.80（Fischer+ADC）。BI-RADS 4A、4B 和 4C 的阳性预测值分别为 7.69%、52.38%和 89.29%。
Fischer 评分系统结合 ADC 可合理细分 BI-RADS 类别 4 乳腺病变，具有较高的敏感度和特异度。
