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目的建立以乳腺癌腋窝淋巴结超声诊断特征为变量的Logistic回归模型,评价常规超声及实时弹性成像技术对乳腺癌腋窝淋巴结有无转移鉴别诊断的价值。方法对病理证实的112例乳腺癌患者的113个腋窝淋巴结的常规超声及弹性成像各因素进行综合分析,建立二分类Logistic回归模型,通过绘制ROC曲线评价模型的诊断效能。结果在纳入的113个淋巴结中,术后病理证实28个无转移,85个有转移。经过前进法Logistic回归分析,筛选出弹性应变率比值(SR)、弹性评分及形态等3个指标对乳腺癌腋窝淋巴结转移诊断有统计学意义的特征变量。Logistic回归模型对乳腺癌腋窝淋巴结转移预报的正确率为93.8%,ROC曲线下面积为0.962。结论二分类Logistic回归模型对腋窝淋巴结性质有较好的诊断效能,弹性成像提高了常规超声诊断腋窝淋巴结的准确度。
Objective To establish a Logistic regression model based on the diagnostic characteristics of axillary lymph node in breast cancer as a variable to evaluate the value of conventional ultrasound and real-time elastography in the differential diagnosis of axillary lymph node metastasis in breast cancer. Methods A total of 113 axillary lymph nodes in 112 breast cancer patients confirmed by pathology were analyzed by conventional ultrasound and elastography. Logistic regression model was established. ROC curve was used to evaluate the diagnostic efficacy of the model. Results Of the 113 lymph nodes involved, postoperative pathology confirmed 28 without metastasis and 85 with metastasis. Logistic regression analysis was conducted to find out the characteristic variables for the diagnosis of axillary lymph node metastasis in breast cancer with three indexes of elastic strain ratio (SR), elasticity score and morphology. Logistic regression model for breast cancer axillary lymph node metastasis accuracy was 93.8%, the area under the ROC curve was 0.962. Conclusion The binary Logistic regression model has good diagnostic efficacy for axillary lymph nodes. Elastic imaging improves the accuracy of routine ultrasound in the diagnosis of axillary lymph nodes.