乳腺非特殊型浸润性癌超声征象与病理分级的相关性研究

发布时间：2018-01-27 03:42

  本文关键词： 乳腺超声 病理分级 超声弹性成像 乳腺影像报告和数据系统 浸润性癌　出处：《郑州大学》2016年硕士论文　论文类型：学位论文

【摘要】：目的分析BI-RADS标准化超声征象能否用于预测乳腺浸润性癌,非特殊型病理分级,探讨超声弹性图像面积比在乳腺浸润性癌,非特殊型不同病理分级之间差异。方法入选2015年1月至2016年2月的283例单发乳腺浸润性癌,非特殊型患者,所有患者均于本院行超声检查,并经术后病理确诊。术前参考第5版BI-RADS标准化术语进行记录,最终给予BI-RADS分类。应用χ2检验、Spearman相关分析分析各超声征象、弹性成像面积比与病理分级的相关性。弹性图像面积比与浸润性癌,非特殊型不同病理分级之间行方差分析,分析不同病理分级之间弹性图像面积比之间是否存在差异。把浸润性癌病理分级作为因变量,肿块的超声征象(包括BI-RADS分类及弹性图像面积比)为自变量建立Logistic回归模型,对独立影响乳腺浸润性癌病理分级的超声征象进行筛选。结果多因素分析显示边缘、后方回声特征与乳腺浸润性癌病理分级密切相关(OR=50.73、246.60,P均0.05)。并与病理结果吻合度较好(χ2=29.145、62.079,P均0.01),能够预测乳腺浸润性癌,非特殊型病理级别。浸润性癌,非特殊型不同病理级别之间超声弹性图像面积比方差分析,浸润性癌,非特殊型Ⅲ级与I级、II级之间差异有统计学意义(P=0.02,P=0.01),且与与病理级别相关(r=0.519,P=0.00)。结论肿块边缘、后方回声特征能够一定程度上预测乳腺浸润性癌,非特殊型病理分级,且不同病理级别浸润性癌,非特殊型之间超声弹性成像图面积比不同,高级别浸润性癌,非特殊型倾向于边缘不光整、后方回声增强及更大的面积比。
[Abstract]:Objective to analyze whether BI-RADS standardized ultrasound signs can be used to predict invasive breast cancer and non-special pathological grade, and to explore the area ratio of ultrasonic elastic image in invasive breast carcinoma. Methods from January 2015 to February 2016, 283 cases of single invasive breast cancer and non-special type of breast cancer were selected. All the patients were examined by ultrasound in our hospital. It was confirmed by postoperative pathology and recorded with reference to the 5th edition of BI-RADS standardized terminology before operation. Finally, BI-RADS classification was given. 蠂 2 test was used. Spearman correlation analysis was used to analyze the correlation between ultrasound signs, the area ratio of elastic imaging and pathological grade, and the variance analysis between the area ratio of elastic image and invasive carcinoma and different pathological grades of non-special type. To analyze whether there are differences in the elastic image area ratio between different pathological grades and take the pathological grade of invasive carcinoma as a dependent variable. The ultrasonic signs (including BI-RADS classification and area ratio of elastic images) were used as independent variables to establish Logistic regression model. Results Multivariate analysis showed that the posterior echo features were closely related to the pathological grade of invasive breast carcinoma. 246.60 P was 0.05% and had a good agreement with pathological results (蠂 ~ 2 ~ 2 ~ (29.145) ~ 62.079 P, P = 0.01), which could predict invasive breast cancer. Non-special pathological grade. Invasive carcinoma, non-special type of different pathological grade of ultrasound elastic image area ratio analysis of variance analysis, invasive carcinoma, non-special type 鈪，

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