| 阮镜良,许晓琳,田晶,杨海云,罗葆明.应用Logistic回归模型筛选剪切波弹性成像评估颈部淋巴结的定量参数[J].中国医学影像技术,2016,32(4):500~503 |
| 应用Logistic回归模型筛选剪切波弹性成像评估颈部淋巴结的定量参数 |
| Screening of shear wave elastography quantitative parameters in assessment of cervical lymph nodes using Logistic regression model |
| 投稿时间：2015-07-15 修订日期：2016-02-17 |
| DOI：10.13929/j.1003-3289.2016.04.005 |
| 中文关键词: 颈部 淋巴结 Logistic回归模型 剪切波 弹性成像技术 定量参数 |
| 英文关键词:Neck Lymph nodes Logistic regression model Shear wave Elasticity imaging techniques Quantitative parameters |
| 基金项目:国家自然科学基金面上项目(30872996). |
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| 中文摘要: |
| 目的 采用Logistic回归模型探讨剪切波弹性成像(SWE)评估颈部淋巴结良恶性的价值和筛选SWE的定量参数.方法 对59例患者共95个疑似恶性颈部淋巴结在颈部淋巴结清扫前进行常规超声检查及剪切波弹性成像检查,分别比较颈部良性与恶性淋巴结的弹性值比值(E-ratio)、病灶的平均弹性值(E-mean)、病灶的最大弹性值(E-max)和标准差(SD);以病理结果为金标准,建立二分类逻辑回归模型,绘制模型预测概率的ROC曲线并计算曲线下面积,确定诊断界值,计算敏感度、特异度、准确度、阳性预测值、阴性预测值和约登指数.结果 Logistic回归模型为logitic(p)=-3.653+1.760X1+0.235X2-0.207X3+0.168X4,X1为E-ratio,X2为E-mean,X3为E-max,X4为SD.模型预测概率ROC曲线的曲线下面积为0.865,以55.66%为模型预测概率的诊断界值时,准确率最高为84.21%,对应的敏感度为80.00%,特异度88.89%,阳性预测值为88.89%,阴性预测值为80.00%,约登指数为68.89%.结论 运用SWE的4个定量参数建立的逻辑回归模型对颈部良恶性淋巴结的鉴别具有中等诊断价值,4个定量参数均可为良恶性淋巴结的鉴别诊断提供依据,而诊断价值最高的定量参数是E-ratio. |
| 英文摘要: |
| Objective To explore the value of shear wave elastography (SWE) in the assessment of cervical lymph nodes, and to screen the quantitative parameters of SWE using model of Logistic regression. Methods Totally 59 patients with 95 suspected malignant cervical lymph nodes underwent conventional ultrasound and SWE before cervical lymphadenectomy. Quantitative parameters (E-ratio, E-mean, E-max, SD) between benign and malignant lymph nodes were compared. According to the pathologic findings, the model of binary Logistic regression was established. ROC curves of model predictive probability were drawn and the area of under curve (AUC) was calculated. The cut-off value was determined, and the sensitivity, specificity, accuracy, positive predictive value, negative predictive value and Youden index were calculated. Results The Logistic regression model was logitic(p)=-3.653+1.760X1+0.235X2-0.207X3+0.168X4,X1, X2, X3, X4 were E-ratio, E-mean, E-max, SD, respectively. The AUC of model predictive probability was 0.865. When cut-off value was 55.66% of model predictive probability, the highest accuracy was 84.21%, sensitivity was 80.00%, specificity was 88.89%, positive predictive value was 88.89%, negative predictive value was 80.00%, and Youden index was 68.89%. Conclusion Using four quantitative parameters of SWE, the Logistic regression model has moderate value in the differentiation of benign and malignant cervical lymph nodes, four quantitative parameters can provide diagnostic evidences, and the most valuable one is E-ratio. |
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