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超声造影下乳腺非肿块样病变:特征分析、乳腺影像报告和数据系统分类评估

Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment.

作者信息

Xu Ping, Yang Min, Liu Yong, Li Yan-Ping, Zhang Hong, Shao Guang-Rui

机构信息

School of Medicine, Shandong University, Jinan 250100, Shandong Province, China.

Department of Ultrasound, Beijing Shijitan Hospital affiliated to Capital Medical University, Beijing 100038, China.

出版信息

World J Clin Cases. 2020 Feb 26;8(4):700-712. doi: 10.12998/wjcc.v8.i4.700.

DOI:10.12998/wjcc.v8.i4.700
PMID:32149054
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7052556/
Abstract

BACKGROUND

Breast non-mass-like lesions (NMLs) account for 9.2% of all breast lesions. The specificity of the ultrasound diagnosis of NMLs is low, and it cannot be objectively classified according to the 5 Edition of the Breast Imaging Reporting and Data System (BI-RADS). Contrast-enhanced ultrasound (CEUS) can help to differentiate and classify breast lesions but there are few studies on NMLs alone.

AIM

To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography (US), color Doppler flow imaging (CDFI) and CEUS, and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.

METHODS

A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019. All lesions were examined by US, CDFI and CEUS, and their features from those examinations were analyzed. With pathology as the gold standard, binary logic regression was used to analyze the independent risk factors for malignant breast NMLs, and a regression equation was established to calculate the efficiency of combined diagnosis. Based on the regression equation, the combined diagnostic efficiency of US combined with CEUS (US + CEUS) was determined. The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS, and the diagnostic efficiency of CEUS combined with BI-RADS (CEUS + BI-RADS) was calculated based on the results. ROC curves were drawn to compare the diagnostic values of the three methods, including US, US + CEUS, and CEUS + BI-RADS, for benign and malignant NMLs.

RESULTS

Microcalcification, enhancement time, enhancement intensity, lesion scope, and peripheral blood vessels were significantly different between benign and malignant NMLs. Among these features, microcalcification, higher enhancement, and lesion scope were identified as independent risk factors for malignant breast NMLs. When US, US + CEUS, and CEUS + BI-RADS were used to identify the benign and malignant breast NMLs, their sensitivity rates were 82.6%, 91.3%, and 87.0%, respectively; their specificity rates were 71.4%, 89.2%, and 92.9%, respectively; their positive predictive values were 70.4%, 87.5%, and 90.9%, respectively; their negative predictive values were 83.3%, 92.6%, and 89.7%, respectively; their accuracy rates were 76.5%, 90.2%, and 90.2%, respectively; and their corresponding areas under ROC curves were 0.752, 0.877 and 0.903, respectively. tests showed that the area under the ROC curve of US was statistically smaller than that of US + CEUS and CEUS + BI-RADS, and there was no statistical difference between US + CEUS and CEUS + BI-RADS.

CONCLUSION

US combined with CEUS can improve diagnostic efficiency for NMLs. The adjustment of the BI-RADS classification according to the features of contrast-enhanced US of NMLs enables the diagnostic results to be simple and intuitive, facilitates the management of NMLs, and effectively reduces the incidence of unnecessary biopsy.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/12c7721b5a2d/WJCC-8-700-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/4244e7780eae/WJCC-8-700-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/0747134fdd3e/WJCC-8-700-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/e8f2c2ea7c3f/WJCC-8-700-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/12c7721b5a2d/WJCC-8-700-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/4244e7780eae/WJCC-8-700-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/0747134fdd3e/WJCC-8-700-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/e8f2c2ea7c3f/WJCC-8-700-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6294/7052556/12c7721b5a2d/WJCC-8-700-g004.jpg
摘要

背景

乳腺非肿块样病变(NMLs)占所有乳腺病变的9.2%。NMLs的超声诊断特异性较低,且无法根据第5版乳腺影像报告和数据系统(BI-RADS)进行客观分类。超声造影(CEUS)有助于乳腺病变的鉴别和分类,但单独针对NMLs的研究较少。

目的

分析乳腺NMLs在灰阶超声(US)、彩色多普勒血流成像(CDFI)及CEUS中的良恶性特征,探讨NMLs联合诊断的效能以及CEUS对NMLs的BI-RADS分类的影响。

方法

回顾性分析2017年1月至2019年4月我院经病理证实的51例乳腺NMLs。所有病变均行US、CDFI及CEUS检查,并分析其检查特征。以病理为金标准,采用二元逻辑回归分析乳腺NMLs恶性的独立危险因素,建立回归方程计算联合诊断效能。根据回归方程确定US联合CEUS(US + CEUS)的联合诊断效能。根据CEUS确定的独立危险因素调整NMLs的初始BI-RADS-US分类,并根据结果计算CEUS联合BI-RADS(CEUS + BI-RADS)的诊断效能。绘制ROC曲线比较US、US + CEUS及CEUS + BI-RADS三种方法对NMLs良恶性的诊断价值。

结果

乳腺NMLs的微钙化、增强时间、增强强度、病变范围及周边血管在良恶性之间存在显著差异。其中,微钙化、高增强及病变范围被确定为乳腺NMLs恶性的独立危险因素。采用US、US + CEUS及CEUS + BI-RADS鉴别乳腺NMLs的良恶性时,其灵敏度分别为82.6%、91.3%及87.0%;特异度分别为71.4%、89.2%及92.9%;阳性预测值分别为70.4%、87.5%及90.9%;阴性预测值分别为83.3%、92.6%及89.7%;准确率分别为76.5%、90.2%及90.2%;相应的ROC曲线下面积分别为0.752、0.877及0.903。检验显示,US的ROC曲线下面积在统计学上小于US + CEUS及CEUS + BI-RADS,且US + CEUS与CEUS + BI-RADS之间无统计学差异。

结论

US联合CEUS可提高NMLs的诊断效能。根据NMLs的超声造影特征调整BI-RADS分类,使诊断结果简单直观,便于NMLs的管理,有效减少不必要活检的发生率。

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