超声BI-RADS分类在微小乳腺癌诊断中的临床价值

摘要
图/表
参考文献(12)
相关文章 (15)

全文: PDF (0 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要目的：探讨超声乳腺影像报告和数据系统（BI-RADS）在微小乳腺癌诊断中的临床价值。方法：回顾性分析超声诊断为BI-RADS 3~5级的255例微小乳腺病灶的超声征象描述、分级结果与病理结果。结果：255例病灶经病理证实良性191例，恶性64例。超声BI-RADS诊断微小乳腺癌的灵敏性、特异性、准确性、阳性预测值（PPV）、阴性预测值（NPV）分别为89.06%、80.63%、82.75%、60.64%、95.65%。边缘不光整、形态不规则、纵横比≥1、内部有微钙化、内部血流阻力指数（RI）≥0.7、后方回声衰减、周围组织改变等7个超声征象在良恶性病灶中的差异具有统计学意义（P<0.05），其中灵敏性较高的有边缘不光整（82.81%）、形态不规则（85.94%），特异性较高的有纵横比≥1（89.53%）、内部有微钙化（90.05%）、内部血流RI≥0.7（92.67%）、后方回声衰减（95.29%）、周围组织改变（99.48%）。结论：超声BI-RADS能较准确的评估微小乳腺病灶的良恶性，有助于微小乳腺癌的的早期发现、早期诊断和早期治疗。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	杨莹莹
	黄健源
	黄美枝
	利锡贵
	莫丽

关键词 ：乳腺肿瘤；超声检查, 多普勒, 彩色

Abstract：Objective: To investigate the clinical value of ultrasound breast imaging reporting and data system(BI-RADS) in diagnosis of breast small carcinoma. Methods: We retrospectively analyzed ultrasound features, BI-RADS classification and pathological results of 255 small breast lesions which were diagnosed as 3~5 staged ultrasound BI-RADS. Results: The pathological results suggested that among 255 small breast lesions there are 191 benign lesions and 64 malignant lesions. The sensitivity, specificity, accuracy, positive predictive value(PPV) and negative predictive value(NPV) of ultrasound BI-RADS classification were 89.06%, 80.63%, 82.75%, 60.64% and 95.65%, respectively. The differences in non-circumscribed margin, irregular shape, aspect ratio>1, microcalcification in mass, lesions internal resistance index(RI)≥0.7, shadowing and the changes of surrounding tissue between benign and malignant lesions were statistically significant(P<0.05). Higher sensitivity was found in non-circumscribed margin(82.81%) and irregular shape(85.94%). Higher specificity was found in aspect ratio>1(89.53%), microcalcification in mass(90.05%), lesions internal RI≥0.7(92.67%), shadowing(95.29%) and the changes of surrounding tissue(99.48%). Conclusion: Ultrasound BI-RADS is of great value in diagnosing the benign and malignant breast masses and contributed to early detection, diagnosis, treatment of breast tiny carcinoma.

Key words： Breast neoplasms Ultrasonography, Doppler, color

收稿日期: 2017-02-22

PACS:	Ｒ737.9
	Ｒ445.1

基金资助:广西自然科学基金（2015GXNSFAA139172）。

通讯作者: 黄健源，广西医科大学第一附属医院超声科，530000。E-mail：545495986@qq.com

作者简介: 杨莹莹（1989-），女，广西桂平人，在读硕士研究生。E-mail：499928052@qq.com

引用本文:

杨莹莹，黄健源，黄美枝，利锡贵，莫丽. 超声BI-RADS分类在微小乳腺癌诊断中的临床价值[J]. 中国临床医学影像杂志, 2017, 28(11): 789-792.
YANG Ying-ying, HUANG Jian-yuan, HUANG Mei-zhi, LI Xi-gui, MO Li. The clinical value of ultrasound BI-RADS in diagnosis of breast tiny carcinoma. JOURNAL OF CHINA MEDICAL IMAGING, 2017, 28(11): 789-792.

链接本文:

http://www.jccmi.com.cn/CN/ 或 http://www.jccmi.com.cn/CN/Y2017/V28/I11/789

[1]冯新熠，陆苏，刘红. 亚洲国家及地区乳腺癌筛查指南的发展和实践[J]. 中国肿瘤临床，2015，42（8）：451-454. [2]中华人民共和国卫生医政司. 中国常见恶性肿瘤诊治规范（第八分册）[M]. 2版. 北京：北京医科大学中国协和医科大学联合出版社，1992：58. [3]翁剑华，钟鸣，黄卓雅，等. 乳腺癌腋窝淋巴结转移危险因素的研究[J]. 中华普外科手术学杂志，2016，10（6）：490-492. [4]Chen M, Zhan WW, Wang WP. Cystic breast lesions by conventional ultrasonography: sonographic subtype-pathologic correlation and BI-RADS assessment[J]. Arch Med Sci, 2014, 10(1): 76-83. [5]Arleo EK, Saleh M, Ionescu D, et al. Recall rate of screening ultrasound with automated breast volumetric scanning(ABVS) in women with dense breasts: a first quarter experience[J]. Clin Imaging, 2014, 38(4): 439-444. [6]American College of Radiology(ACR). Breast Imaging Reporting and Data System (BI-RADS)[M]. 4th ed. Reston: American College of Radiology, 2013. [7]Hsu HH, Yu JC, Lee HS, et al. Complex cystic lesions of the breast on ultrasonography: feature analysis and BI-RADS assessment[J]. Eur J Radiol, 2011, 79(1): 73-79. [8]Cheng HD, Cai XP, Chen XW, et al. Computer-aided detection and classification of microcalcifications in mammograms: a survey[J]. Pattern Recognition, 2003, 36(12): 2967-2991. [9]刘金萍，贵玉，马棣，等. 微小乳腺癌的超声恶性征象研究[J]. 临床和实验医学杂志，2016，15（13）：1338-1341. [10]王双辉，杨振江，杨东炜，等. 超声BI-RADS 3、4、5级对乳腺肿瘤临床诊断的意义[J]. 中国现代医生，2014，52（5）：144-147. [11]卢建明，赵淑红，田锦，等. 乳腺超声检查中BI-RADS分级诊断标准对乳腺肿瘤的诊断价值[J]. 宁夏医学杂志，2015，37（2）：140-142. [12]张志斌，吴晓恬. 超声BI-RADS分级标准在乳腺病变检查中的应用[J]. 分子影像学杂志，2015，38（4）：316-318.