早期乳腺癌无创腋窝淋巴结分期的临床初步观察

目的：探讨超声检查评估乳腺癌腋窝淋巴结转移状态的临床应用价值。方法入组军事医学科学院附属医院2013年12月至2015年9月期间连续收治的282例新发 Tis-T2期乳腺癌患者，指定2名高年资超声医师行腋窝超声检查，根据淋巴结声像学参数，将患者分为转移组、未转移组或可疑组。腋窝淋巴结分期以病理学结果作为金标准，分析超声检查评估乳腺癌腋窝淋巴结转移的准确性，比较各组腋窝淋巴结转移负荷；单因素及多因素Logistic 回归分析各个声像学参数对判断腋窝淋巴结转移状态的预测价值。结果超声判断腋窝淋巴结转移组＋未转移组的灵敏度、特异度、阳性及阴性预测值、准确度分别为85．6％、87．1％、86．4％、86．3％和86．3％，Kappa 值为0．727（P ＜0．001）。在病理证实腋窝淋巴结转移患者中，超声判断未转移组的平均淋巴结转移负荷明显低于超声转移组（1．2／6．9枚，P ＜0．001），超声判断为未转移而病理结果证实为转移的患者共16例，其中14例患者腋窝淋巴结转移负荷仅为1枚，其余2例患者分别为2枚和3枚。单因素 Logistic 回归分析显示，最大皮质厚度预测腋窝淋巴结转移诊断效能最佳（ROC 曲线下面积为0．872）；多因素 Logistic 回归分析显示，最大皮质厚度、髓质与皮质厚度比值与腋窝淋巴结转移相关（P ＜0．05）。多因素 Logistic 回归模型 ROC 曲线下面积为0．879，灵敏度及特异度分别为77．0％和85．1％。结论超声检查评估腋窝淋巴结转移具有较高的准确性；超声判断假阴性的患者腋窝淋巴结转移负荷较低。最大皮质厚度是判断腋窝淋巴结转移最主要的声像学参数。在早期乳腺癌患者中，超声检查无创评估可能是潜在的替代前哨淋巴结活检行腋窝淋巴结分期的手段。

Noninvasive axillary lymph node staging for early-stage breast cancer by ultrasound examination:a preliminary clinical study

Objective To investigate the clinical value of axillary ultrasound (AUS)in the identification of axillary nodal metastasis (ALNM).Methods Two hundred and eighty-two consecutive patients with stage Tis-T2 breast cancer were prospectively enrolled between December 2013 and September 2015.All the patients underwent AUS performed by two specified senior ultrasound doctors.Sonographic features of their axillary lymph nodes (longitudinal and transverse diameters,cortical and hilar thickness,blood flow form)were collected.These patients were divided into metastatic, suspicious and non-metastatic groups based on the ultrasound features by ultrasound doctors.The diagnostic accuracy of AUS was compared with results of pathology.Univariate and multivariate Logistic regression analyses were used to evaluate the relationship between sonographic features and ALNM.The area under the ROC curve was used to assess the accuracy of the multivariate Logistic regression model.Results The sensitivity,specificity,positive and negative predictive value and accuracy of AUS were respectively 85.6%,87.1%,86.4%,86.3%,and 86.3% in the metastatic and non-metastatic groups.The Kappa value was 0.727(P <0.001).The ALNM burden in the non-metastatic group was significantly lower than in the metastatic group (1.2 vs 6.9,P <0.001).The false-negative results were found only in 16 cases,fourteen of whom had only 1,and two had 2 and 3 ALNM,respectively.Univariate Logistic regression analysis showed that maximum cortical thickness was the most significant predictive factor of ALNM(the area under the ROC curve was 0.872).Multivariate Logistic regression analysis suggested that cortical thickness and the ratio of hilar thickness to cortical thickness were predictive factors of ALNM(P <0.05).The area under the ROC curve of the multivariate Logistic regression model was 0.879 and its sensitivity and specificity were 77.0% and 85.1%,respectively.Conclusion AUS is a valuable tool for detecting ALNM.Patients with false-negative results of AUS have a lower axillary metastatic burden.Maximum cortical thickness is the most significant predictive factor of ALNM.AUS may be a potential alternative method for sentinel lymph node biopsy as axillary lymph node staging in early-stage breast cancer patients.