实用临床医药杂志2025，Vol.29Issue(15)：6-11,16,7.DOI:10.7619/jcmp.20243956
基于多模态超声构建预测乳腺结节性质的定量诊断模型研究
A quantitative diagnostic model for predicting nature of breast nodules based on multimodal ultrasound
摘要
Abstract
Objective To construct a quantitative diagnostic model for predicting the nature of breast nodules based on multimodal ultrasound(color Doppler flow imaging,two-dimensional grayscale ultrasound,and ultrasound elastography)and analyze its predictive value.Methods A total of 110 patients with surgical treatment for breast nodules(135 nodules in total)in the hospital from June 2020 to January 2023 were selected as research objects.All patients received ultrasound examinations before surgery.According to the postoperative pathological results,they were divided in-to benign group and malignant group.The general data,color Doppler flow imaging grading,two-di-mensional grayscale ultrasound features,and ultrasound elastography score were compared between the two groups.Principal component analysis(PCA)and a multivariate Logistic regression model were used to explore the risk factors affecting the nature of breast nodules and construct a risk predic-tion model.The receiver operating characteristic(ROC)curve was drawn to analyze the value of the model in predicting the nature of breast nodules.Results The postoperative pathological results showed that among the 135 breast nodules,there were 73(54.07％)benign nodules and 62(45.93％)malignant nodules.The proportion of color Doppler flow imaging grades Ⅱ and Ⅲ in the malignant group was significantly higher than that in the benign group(P＜0.05).The proportions of irregular shape,non-parallel orientation,irregular margin,presence of microcalcifications,posterior echo at-tenuation/mixture,and abnormal lymph node morphology in the malignant group were all significant-ly higher than those in the benign group(P＜0.05).The proportion of elastography scores of 4 to 5 for breast nodules in the malignant group was significantly higher than that in the benign group(P＜0.05).PC A and Logistic regression analysis results showed that color Doppler flow imaging gradesⅡ and Ⅲ(OR=2.474,95％CI,1.226 to 4.991),irregular shape(OR=2.120,95％CI,1.055 to4.261),irregular margin(OR=4.206,95％CI,2.030 to 8.716),non-parallel orienta-tion(OR=2.329,95％CI,1.137 to 4.768),posterior echo attenuation/mixture(OR=2.983,95％CI,1.398 to 6.365),microcalcifications(OR=4.615,95％CI,2.117 to 10.062),abnor-mal lymph node morphology(OR=4.194,95％CI,1.762 to 9.984),and elastography scores of 4 to 5(OR=2.246,95％CI,1.125 to 4.481)were all significantly positively correlated with malig-nant breast nodules.The ROC curve showed that the area under the curve(AUC)of the Logistic re-gression model for predicting the nature of breast nodules was 0.906(95％CI,0.849 to 0.963),with a sensitivity of 0.857,a specificity of 0.868,and a Youden index of 0.725.Conclusion The prediction model constructed based on multimodal ultrasound(color Doppler flow imaging,two-di-mensional grayscale ultrasound,and ultrasound elastography)can effectively differentiate benign and malignant breast nodules.The model is reliable and stable,and conductive to reduce unneces-sary puncture biopsies and surgeries.关键词
乳腺结节性质/彩色多普勒血流显像/二维灰阶超声/超声弹性成像/主成分分析/预测模型/微钙化/曲线下面积Key words
nature of breast nodules/color Doppler flow imaging/two-dimensional grayscale ultrasound/ultrasound elastography/principal component analysis/prediction model/microcalcifi-cations/area under the curve分类
医药卫生引用本文复制引用
宁建霞..基于多模态超声构建预测乳腺结节性质的定量诊断模型研究[J].实用临床医药杂志,2025,29(15):6-11,16,7.基金项目
山西省科学技术研究与开发项目(202004D372161) （202004D372161）
