诊断学理论与实践

诊断学理论与实践 ›› 2020, Vol. 19 ›› Issue (06): 583-587.doi: 10.16150/j.1671-2870.2020.06.007

• 论著 • 上一篇    下一篇

超微血管三维立体成像技术对BI-RADS 4类乳腺肿块血流显示及鉴别良恶性的价值研究

李伟伟1a, 吴迎1b, 周伟1a,2(), 詹维伟2, 周庆华1b, 陶玲玲1a, 杨雁雯1a   

  1. 1.上海交通大学医学院附属瑞金医院卢湾分院 a. 超声诊断科,b. 乳腺外科,上海 200020
    2.上海交通大学医学院附属瑞金医院超声诊断科,上海 200025
  • 收稿日期:2020-12-08 出版日期:2020-12-25 发布日期:2022-07-14
  • 通讯作者: 周伟 E-mail:zw11468@126.com
  • 基金资助:
    上海市黄浦区卫健委面上项目(HLM202006);上海交通大学医学院瑞金医院卢湾分院优秀青年人才培养计划(YQB202007)

The diagnostic value of smart three-dimensional superb microvascular imaging in differentiating benign and malignant breast lesions of BI-RADS 4

LI Weiwei1a, WU Ying1b, ZHOU Wei1a,2(), ZHAN Weiwei2, ZHOU Qinghua1b, TAO Lingling1a, YANG Yanwen1a   

  1. 1a. Department of Ultrasound, 1b. Department of General Surgery, Ruijin Hospital, Lu Wan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai 200020, China
    2. Department of Ultrasound, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
  • Received:2020-12-08 Online:2020-12-25 Published:2022-07-14
  • Contact: ZHOU Wei E-mail:zw11468@126.com

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摘要：

目的： 研究超微血管三维立体成像（smart three-dimensional superb microvascular imaging,Smart 3D SMI）对乳腺影像报告和数据系统（breast imaging reporting and data system,BI-RADS）4类乳腺肿块内血流的显示情况及其鉴别良恶性肿块的诊断效能。方法： 收集120例经病理证实的BI-RADS 4类乳腺肿块,将肿块分为良性组(32例)和恶性组（88例）,均行能量多普勒成像（power Doppler flow imaging, PDFI）、高级动态血流成像（advanced dramatic flow imaging, ADFI）及Smart 3D SMI检查,参照半定量分级方式将肿块血流级别分为乏血流与丰富血流,并比较3种成像方法对乳腺良性、恶性BI-RADS 4类肿块血流显示的差异。随后利用Smart 3D SMI的血流显示结果对乳腺肿块BI-RADS分类结果进行校正,比较校正前、后受试者操作特征曲线（receiver operator characteristic curve,ROC曲线）诊断恶性肿块的曲线下面积。结果： 用PDFI、ADFI及Smart 3D SMI 3种方法分别对良性组与恶性组乳腺肿块进行血流级别检测,结果提示3种方法均显示恶性组肿块内的血流较良性组丰富（P<0.001、P<0.001、P=0.004）。采用Smart 3D SMI方法显示血流丰富的病例占比较高,为75.0%（良性18例、恶性72例）,PDFI 法占比为50.0%（良性5例、恶性55例）,ADFI 法占比为56.7%（良性7例、恶性61例）,后2种方法测得的血流级别分布的结果差异无统计学意义（P=0.301）,Smart 3D SMI法检测出血流丰富病例较PDFI 及ADFI法明显增多（P<0.001,P=0.004）。采用Smart 3D SMI血流分级对肿块的BI-RADS分类进行校正后,发现恶性组共有52例（59.1%）病例BI-RADS分类有不同程度的升级,良性组有14例（43.8%）病例BI-RADS分类升级,校正后BI-RADS分类诊断恶性肿块的ROC曲线下面积为0.86,较校正前（曲线下面积为0.80）有所提升（P=0.011）。结论： Smart 3D SMI技术是一种显示血流的新方法,与传统方法比较,其在显示BI-RADS 4类乳腺肿块的血流情况有一定优势;在超声检查中, Smart 3D SMI结合BI-RADS分类,能提高恶性乳腺肿块的检出效能。

关键词: 超微血管三维立体成像, 乳腺影像报告和数据系统, 乳腺肿块

Abstract:

Objective: To study the efficacy of smart three-dimensional superb microvascular imaging (Smart 3D SMI) on displaying blood flow in breast lesions of breast imaging reporting and data system(BI-RADS）4, and analyze the diagnostic value of smart 3D SMI in BI-RADS 4 breast lesions. Methods: A total of 120 breast lesions of BI-RADS 4 confirmed by post-operative pathology were enrolled, and the lesions were divided into benign group (32 lesions）and malignant one (88 lesions). The power Doppler flow imaging (PDFI), advanced dramatic flow imaging (ADFI） and Smart 3D SMI were performed to detect blood flow in the lesions. Referring to the semi quantitative grading method, the blood flow levels in the lesions were divided into two groups: the group lack of blood flow and the group rich of blood flow. The difference in blood flow displayed by PDFI, ADFI and Smart 3D SMI was compared between the benign and malignant breast lesions. Furthermore, the results of Smart 3D SMI were used to correct the BI-RADS classification. The area under receiver operator characteristic curve(ROC curve) for performance of corrected BI-RADS to diagnose malignant breast lesions was compared before and after correction. Results: ALL these three methods showed that the blood flow in malignant lesions were more abundant than that in benign group (P<0.001, P<0.001, P=0.004). The distribution of blood flow levels detected by different detection methods was different. The proportion of patients with abundant blood flow detected by Smart 3D SMI method was 75.0% (benign 18 cases, malignant 72 cases), while it was 50.0% (5 cases of benign and 55 cases of malignant) by PDFI and 56.7% (7 cases of benign and 61 cases of malignant) by ADFI, respectively. There was no significant difference in distribution of blood flow levels between PDFI and ADFI (P=0.301). The percentage of patients with abundant blood flow detected by Smart 3D SMI was significantly higher than that by PDFI (50.0%, P<0.001) and ADFI (56.7%, P=0.004). Corrected with Smart 3D SMI, the BI-RADS classification of 52 cases with malignant lesions (59.1%) up-graded and 14 cases with benign lesion (43.8%) up-graded. The area under ROC curve of corrected BI-RADS for diagnosing malignant lesions was 0.86, which was higher than that of BI-RADS without correction (area under curve 0.80) (P=0.011). Conclusions: The Smart 3D SMI is a new method and have more advantage than traditional methods in detecting blood flow of BI-RADS 4 breast lesions, especially in the diagnosis of malignant tumors.

Key words: Smart three-dimensional superb microvascular imaging, Breast imaging reporting and data system4, Breast lesion

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