| 摘要: |
| 目的：探讨自动乳腺全容积扫描成像（automated breast volume scanner，ABVS）及乳腺BI.RADS分类综合评分法对乳腺病变的诊断价值及判断病变性质的最佳分界点。方法：对经活检或手术病理结果证实的477例656个乳腺肿块的ABVS图像及BI.RADS分类进行回顾性分析，以方位、边缘、毛刺、汇聚征、钙化5个特征加乳腺BI.RADS分类进行综合评分，绘制ROC曲线，探讨其临床应用价值。结果：ABVS方位、边缘、毛刺、汇聚征、钙化5个特征加乳腺BI.RADS分类进行综合评分后对乳腺良、恶性病变的临床诊断界点为6分，ROC曲线下面积为0.965，其诊断的灵敏度、特异度、正确率、误诊率及漏诊率分别为90.4%、94.2%、93.4%、9.6%、3.8%。结论：ABVS加乳腺BI.RADS分类综合评分法可作为诊断乳腺恶性肿瘤的一项新的相对客观的判断指标。 |
| 关键词: 乳腺病变,自动乳腺全容积扫描成像,BI.RADS |
| DOI： |
| 投稿时间：2018-01-22修订日期：2018-02-13 |
| 基金项目: |
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| The Diagnostic Value of the automated breast volume scanner combined with breast BI.RADS classification of Breast LesionsShen Junling1, Li Ting1, Gong Yeqiong1, Wu Xiaoli1, Li Keji1,Zou Jianzhong2 |
| shenjunling,zoujianzhong |
| (The Central Hospital of Panzhihua) |
| Abstract: |
| Objective To explore the best cutoff point of the automated breast volume scanner (ABVS) combined with breast BI.RADS classification for differentiating malignant and benign breast lesions and to assess the diagnostic value using scoring in ABVS+ BI.RADS classification. Methods The ABVS images + BI.RADS classification of 656 breast lesions (477 cases) proved by pathology were reviewed. 5 characteristics of the side, edge, burr, entanglement and calcification + BI.RADS classification were used in scring. A receiver operating characteristic (ROC) curve was used to explore diagnostic value. Results The ratio of scring in ABVS images+ BI.RADS in all of the lesions is 6, and is the best cutoff point for differentiating malignant from benign breast lesions. The Az, sensitivity, specificity, accuracy misdiagnosis rate and missed diagnosis rate were 0.965, 90.4%、94.2%、93.4%、9.6%、3.8%. Conclusion The scring in ABVS image+ BI.RADS is a useful quantitative index for differentiating breast malignant lesion from benign lesion. |
| Key words: breast lesions,automated breast volume scanner,BI.RADS |
