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2013版BI-RADS3~5类诊断指标量化研究 被引量:4

Quantitative indicators of diagnosis research on BI-RADS 3~5 classification in the 2013 edition of BI-RADS
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摘要 目的 探讨基于乳腺肿块超声图像特征评分进行BI-RADS 3~5类的意义.方法 回顾分析401例乳腺肿块的超声图像特征,建立回归模型;依据模型筛选结果及各因素的权重提出BI-RADS 3~5类的评分标准,并对另外243例病例进行评分分类,与BI-RADS各类别的理论风险范围相比较,评估该评分系统的诊断价值.结果 多因素回归分析显示最后进入模型的因素为年龄、形态、方位、边缘、回声模式、肿块内微钙化.制定评分标准,BI-RADS 3、4a、4b、4c、5类对应的分值为6分、7~8分、9~15分,16~22分、≥23分.测试病例综合评分对BI-RADS 3~5类的阳性预测值为0%、4.17%、21.43%、84.85%、100%,ROC曲线下面积为0.947.结论 该评分系统能够对乳腺病灶进行客观的评分并分类,为临床评价乳腺病灶的良、恶性提供有效参考依据. Objective To explore the value of BI-RADS scoring system based on the sonographic features in the breast nodules.Methods In order to build a Logistic regression model,regression was made to analyse 401 patients ' sonographic features of breast nodules.A scoring system was developed based on the results of regression's filter and the weight of each factor,used to score and classify the other 243 patients.It's diagnostic value was evaluated through comparing all types of theoretic risk ranges of BI-RADS.Results Age,morphology,orientation,margin,echo pattern and microcalcifications in a mass were selected in the final step of the logistic regression analysis.By means of scoring system,the scores corresponding to BI-RADS 3,4a,4b,4c,5 classes are 6,7-8,9-15,16-22 and ≥23 respectively.Case study comprehensive score of BI-RADS 3-5 classification' s positive predictive values were 0,4.17%,21.43%,84.85%,1 00%,and the area under the ROC curve scoring system was 0.947.Conclusions The scoring system can objectively score and classify breast nodules,and therefore provide an effective reference for clinical evaluation of benign and malignant breast.
出处 《中华超声影像学杂志》 CSCD 北大核心 2016年第5期392-395,共4页 Chinese Journal of Ultrasonography
基金 安徽医科大学临床科学研究项目(2015xkj122)Anhui Medical University Clinical Scientific Research Projects
关键词 超声检查 乳腺疾病 乳腺超声影像报告数据系统 评分 Ultrasonography Beast diseases Breast Imaging Reporting and Data System Score
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  • 1American College of Radiology. ACR BI-RADS Ultrasound. ACR Breast Imaging Reporting and Data System [S].5th ed. Reston, VA:American College of Radiology, 2013.
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