论文部分内容阅读
目的:探讨多模态超声多参数特征分析在乳腺肿块良恶性诊断中的应用。方法:随机抽取2018年1月至2019年12月南华大学附属长沙中心医院收治的女性患者100例(112个乳腺肿块)，均行常规超声、自动乳腺全容积扫描及超声弹性成像检查。以术后病理结果为金标准区分乳腺肿块良恶性，应用Logistic回归方程分析乳腺肿块超声参数特征。结果:结果112个乳腺肿块中恶性结节34个，良性结节78个。Logistic回归筛选出5个诊断乳腺肿块良恶性的超声参数特征，即汇聚征n OR＝14.402，95%n CI 1.819～114.032，腋窝淋巴结异常n OR＝13.576，95%n CI 1.280～144.003，边界n OR＝13.174，95%n CI 2.664～65.146，弹性n OR＝8.810，95%n CI 2.646～29.333，钙化n OR＝6.543，95%n CI 1.432～29.883。n 结论:多模态超声多参数特征分析可以进一步明确乳腺肿块良恶性的诊断，对临床治疗具有一定的指导意义。“,”Objective:To investigate the application of multi-modal ultrasound and multi-parameter feature analysis in the diagnosis of benign and malignant breast masses.Methods:A total of 100 female patients (112 breast masses) admitted to Changsha Central Hospital Affiliated to Nanhua University from January 2018 to December 2019 were selected. All of them underwent conventional ultrasound, automated breast volume scanner, and ultrasound elastography. The postoperative pathological results were used as the gold standard to distinguish benign and malignant breast masses. The Logistic regression equation was used to analyze the ultrasound parameters characteristics of breast masses.Results:Among the 112 breast masses, 34 were malignant nodules and 78 were benign nodules. Logistic regression screened out 5 the ultrasound parameters characteristics for diagnosing benign and malignant breast masses, namely, convergent sign n OR=14.402, 95%n CI 1.819-114.032, axillary lymph node abnormal n OR=13.576, 95%n CI 1.280-144.003, boundary n OR=13.174, 95%n CI 2.664-65.146, elastic n OR=8.810, 95%n CI 2.646-29.333, calcification n OR=6.543, 95%n CI 1.432-29.883.n Conclusions:Multi-modal ultrasound multi-parameter feature analysis can further clarify the diagnosis of benign and malignant breast masses, and has certain guiding significance for clinical treatment.