基于超声射频流的射频时间序列信号对乳腺良恶性病变的鉴别诊断效能分析

Differential diagnostic performance of radio frequency signal time series based on ultrasonic radio frequency flow for benign and malignant breast lesions

目的探讨以超声射频流为基础的射频时间序列信号特征参数对乳腺良恶性病变的鉴别诊断效能。方法收集137例乳腺病灶的超声二维图像和射频数据。所有超声射频数据均使用实验室开发的射频时间序列信号分析软件进行定量分析,最终得出9个谱特征参数,分别为SMR分形维数、Higuchi分形维数、斜率、谱截距、中频、S1、S2、S3及S4。116例病灶经病理结果确诊,其中86例病灶为恶性,30例病灶为良性,21例病灶经随访诊断为良性。建立Logistic回归模型,计算射频时间序列谱特征参数单一参数、回归模型联合参数对乳腺良恶性病灶的灵敏度、特异度、准确度、阳性预测值、阴性预测值,绘制受试者操作特征(ROC)曲线及计算曲线下面积(AUC)评价其对乳腺癌的鉴别诊断价值。结果多因素回归分析显示,最后进入Logistic模型的参数为Higuchi分形维数、S2、S4,射频时间序列谱特征参数诊断乳腺病灶良恶性的灵敏度、特异度、准确度、阳性预测值、阴性预测值最高值分别为90.7%(S2)、92.2%(Higuchi分形维数、S4)、86.1%(回归模型)、93.9%(S4)、79.6%(回归模型),而ROC AUC较高的分别为0.910(S4)、0.930(回归模型),两者比较差异无统计学意义(P>0.05)。结论基于超声射频流的射频时间序列信号特征参数对亚分辨率组织微结构在物理属性方面提供了定量数据,对乳腺疾病良恶性病变的鉴别诊断效能良好。

Objective To assess the differential diagnostic performance of spectral characteristic parameters of radiofrequency(RF)signal time series based on ultrasonic RF flow for benign and malignant breast lesions.Methods Two dimensional B-mode ultrasound images and RF data of 137 breast lesions were collected.All ultrasonic RF data were quantitatively analyzed with a software developed by our laboratory for ultrasonic RF time series analysis.Finally,nine spectral characteristic parameters were obtained,including SMR fractal dimension,Higuchi fractal dimension,slope,intercept,mid-band fit,S1,S2,S3,and S4.All of the 116 breast lesions were pathologically diagnosed.86 lesions were confirmed to be malignant,30 lesions were benign and 21 lesions were diagnosed as benign after follow-up.The sensitivity,specificity,accuracy,positive and negative predictive values of individual parameter of RF time series spectral characteristic parameters and combined parameters of regression models were calculated,as well as Logistic regression model was established.The receiver operating characteristic(ROC)curve and the area under ROC curve(AUC)were obtained to evaluate the differential diagnostic values of these parameters for benign and malignant breast lesions.Results Multivariate regression analysis showed that the parameters finally included into the Logistic model were Higuchi fractal dimension,S2,and S4.The highest sensitivity,specificity,accuracy,positive and negative predictive values of RF time series spectral characteristic parameters in the diagnosis of breast lesions were 90.7%(S2)and 92.2%(Higuchi fractal dimension,S4),86.1%(regression model),93.9%(S4)and 79.6%(regression model),respectively.The AUCs could reach up to 0.910(S4)and 0.930(regression model),and there was no statistical significance between them(P>0.05).Conclusions The characteristic parameters of RF signal time series based on ultrasonic RF flow provide quantitative data on the sub-resolution tissue microstructure in terms of physical properties,which yields high differential diagnostic efficiency for benign and malignant breast lesions.