乳腺MRI检查对乳腺非肿块样强化病变的鉴别诊断价值

Clinical Application of MRI in Differential Diagnosis of Benign and Malignant Breast Lesions with Non-Mass Enhancement

目的 探讨乳腺MRI检查对非肿块样强化(NME)病变的良恶性鉴别诊断价值。方法 回顾性分析本院乳腺MRI图像上显示为NME且经穿刺或手术获得病理结果的107例女性患者(良性病变39例,恶性病变68例)影像及临床资料。分析比较良、恶性病变组NME的分布类型、强化方式、表观扩散系数(ADC)值及时间-信号强度曲线(TIC)是否存在差异,并对有意义的影响因素进行多因素二元Logistic回归分析筛选出预测恶性疾病的危险因素。结果 多因素二元Logistic回归分析结果显示段样分布、簇环样强化、Ⅲ型TIC曲线及ADC值是预测NME为恶性病变的危险因素(OR=3.889,95%CI:0.629~24.049;OR=15.367,95%CI:2.602~90.769;OR=7.262,95%CI:1.315~40.099;OR=0.997,95%CI:0.995~0.998;P均<0.05)。结论 MRI强化特征及ADC值可有效提高乳腺NME病灶的良恶性鉴别诊断效能。

Objective To explore the value of MRI in the differential diagnosis of benign and malignant non mass like enhancement(NME) lesions. Methods A retrospective analysis was conducted on the imaging and clinical data of 107 female patients(39 cases of benign lesions and 68 cases of malignant lesions) who showed NME on breast MRI images of our hospital and obtained pathological results through puncture or surgery. The distribution types, enhancement methods, ADC values, and time signal intensity curves(TIC) of NME were analyzed and compared between the benign and malignant groups. Multivariate binary Logistic regression analysis was conducted on meaningful influencing factors to screen out risk factors for predicting malignant diseases. Results The results of multivariate binary Logistic regression analysis showed that segment distribution, cluster ring enhancement, type Ⅲ TIC curve, and ADC values were identified as significant factors for predicting malignant breast NME lesions(OR=3.889,95%CI:0.629-24.049;OR=15.367,95%CI:2.602-90.769;OR=7.262,95%CI:1.315-40.099;OR=0.997,95%CI:0.995-0.998,respectively;P<0.05). Conclusion MRI enhanced features and ADC values can effectively improve the differential diagnosis of benign and malignant breast NME lesions.