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超声直方图与乳腺癌免疫组化、分子分型和病理分级的相关性研究

Correlation between Ultrasound Histogram and Immunohistochemis-try,Molecular Typing and Pathological Grading of Breast Cancer
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摘要 研究超声直方图与乳腺癌免疫组化、分子分型和病理分级的相关性,并评估其鉴别效能。回顾性分析经病理证实的乳腺癌患者68例,基于超声灰度图像运用MaZda软件提取直方图参数包括平均值、方差、偏度、峰度、第1百分位数、第10百分位数、第50百分位数、第90百分位数、第99百分位数。对不同分组间直方图参数进行统计学分析,提取差异具有统计学意义的参数并绘制受试者工作特征曲线(ROC)来评估鉴别效能。ER阳性组和阴性组第1百分位数、第99百分位数差异具有统计学意义(P<0.05),PR阳性组和阴性组第99百分位数差异具有统计学意义(P<0.05),Ki-67阳性组和阴性组第99百分位数差异具有统计学意义(P<0.05)。不同分子分型第99百分位数具有统计学差异(P<0.05)。研究发现,超声直方图对预测乳腺癌免疫组化、分子分型和病理分级具有一定的价值和指导意义。 To study the correlation between ultrasound histogram and immunohistochemistry,molecular typing and pathological grading of breast cancer,and to evaluate its differential efficacy.Retrospectively analyze 68 cases of breast cancer patients con-firmed by pathology.Based on ultrasound gray-scale images,MaZda software was used to extract histogram parameters including mean,variance,skewness,kurtosis,1st percentile,10th percentile,50th percentile,90th percentile and 99th percentile.Perform statistical analysis on histogram parameters between different groups,extract parameters with statistically significant differences,and draw Receiver Operating Characteristic(ROC)curves to evaluate discriminative efficacy.The difference in the 1st and 99th percentiles between the ER positive and negative groups was statistically significant(P<0.05),the difference in the 99th percen-tile between the PR positive and negative groups was statistically significant(P<0.05),and the difference in the 99th percentile between the Ki-67 positive and negative groups was statistically significant(P<0.05).The 99th percentile of different molecular types had a statistical difference(P<0.05).The study found that ultrasound histogram has certain value and guiding significance in predicting the immunohistochemical,molecular typing and pathological grading of breast cancer.
作者 刘璐璐 李军 Liu Luu;Li Jun(Medical Imaging Department,Yantai Affiliated Hospital of Binzhou Medical University,Binzhou,Shandong 264100)
出处 《科技与健康》 2024年第4期5-8,共4页 Technology and Health
基金 山东省自然科学基金面上项目(ZR2022MH064)。
关键词 乳腺癌 分子分型 免疫组化 超声 纹理分析 breast cancer molecular typing immunohistochemistry ultrasound texture analysis
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