Differentiation of benign and malignant breast lesions by ultrasound localization microscopy.

IF 4.1 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jia Li, Cong Wei, Tao Ying, Yan Liu, Ronghui Wang, Maoyao Li, Chao Feng, Di Sun, Yuanyi Zheng
{"title":"Differentiation of benign and malignant breast lesions by ultrasound localization microscopy.","authors":"Jia Li, Cong Wei, Tao Ying, Yan Liu, Ronghui Wang, Maoyao Li, Chao Feng, Di Sun, Yuanyi Zheng","doi":"10.1186/s13244-025-02013-6","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>We investigated the role of ultrasound localization microscopy (ULM) qualitative and quantitative parameters in distinguishing benign from malignant breast lesions.</p><p><strong>Methods: </strong>The ULM qualitative and quantitative parameters of breast lesions were recorded. A receiver operating characteristic (ROC) curve was applied to assess the diagnostic performance of ULM. Intra- and inter-operator reliabilities of quantitative parameters were assessed.</p><p><strong>Results: </strong>Thirty-one breast lesions were verified by pathologic results, 14 of which were benign and 17 were malignant. Benign lesions were associated with dot-like, line-like, or branch-like patterns (93% vs 6%), whereas malignant lesions were associated with chaotic patterns (94% vs 7%) (p < 0.001). The microvasculature morphology had an area under the curve (AUC) of 0.935, a sensitivity of 94.1%, and a specificity of 92.9%. The microvasculature density, mean diameter, largest diameter, and max tortuosity of malignant lesions were significantly greater than those of benign lesions (p < 0.05, p < 0.001, p < 0.001, p < 0.05). The microvasculature mean flow velocity of benign lesions was significantly greater than that of malignant lesions (p < 0.05). For the quantitative parameters, the AUC was highest for the microvasculature's largest diameter (0.962), with a sensitivity of 88.2% and a specificity of 92.9%. The intra- and inter-operator reliabilities of quantitative parameters were excellent (ICC greater than 0.90).</p><p><strong>Conclusions: </strong>ULM is useful for distinguishing benign from malignant breast lesions. ULM can offer a new diagnostic method for breast lesions, which deserves further research.</p><p><strong>Critical relevance statement: </strong>This study suggests that ULM is a new technology with super-resolution that is helpful for distinguishing benign from malignant breast lesions.</p><p><strong>Trial registration: </strong>ChiCTR, ChiCTR2100048361. Registered 6 July 2021, https://www.chictr.org.cn/ .</p><p><strong>Key points: </strong>ULM is an emerging technology that can detect highly detailed networks of microvasculature. Microvasculature morphology based on ULM can be a good indicator for the differential diagnosis of breast lesions. Among quantitative parameters extracted from ULM, microvasculature largest diameter was the best for the classification of breast lesions.</p>","PeriodicalId":13639,"journal":{"name":"Insights into Imaging","volume":"16 1","pages":"128"},"PeriodicalIF":4.1000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Insights into Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13244-025-02013-6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: We investigated the role of ultrasound localization microscopy (ULM) qualitative and quantitative parameters in distinguishing benign from malignant breast lesions.

Methods: The ULM qualitative and quantitative parameters of breast lesions were recorded. A receiver operating characteristic (ROC) curve was applied to assess the diagnostic performance of ULM. Intra- and inter-operator reliabilities of quantitative parameters were assessed.

Results: Thirty-one breast lesions were verified by pathologic results, 14 of which were benign and 17 were malignant. Benign lesions were associated with dot-like, line-like, or branch-like patterns (93% vs 6%), whereas malignant lesions were associated with chaotic patterns (94% vs 7%) (p < 0.001). The microvasculature morphology had an area under the curve (AUC) of 0.935, a sensitivity of 94.1%, and a specificity of 92.9%. The microvasculature density, mean diameter, largest diameter, and max tortuosity of malignant lesions were significantly greater than those of benign lesions (p < 0.05, p < 0.001, p < 0.001, p < 0.05). The microvasculature mean flow velocity of benign lesions was significantly greater than that of malignant lesions (p < 0.05). For the quantitative parameters, the AUC was highest for the microvasculature's largest diameter (0.962), with a sensitivity of 88.2% and a specificity of 92.9%. The intra- and inter-operator reliabilities of quantitative parameters were excellent (ICC greater than 0.90).

Conclusions: ULM is useful for distinguishing benign from malignant breast lesions. ULM can offer a new diagnostic method for breast lesions, which deserves further research.

Critical relevance statement: This study suggests that ULM is a new technology with super-resolution that is helpful for distinguishing benign from malignant breast lesions.

Trial registration: ChiCTR, ChiCTR2100048361. Registered 6 July 2021, https://www.chictr.org.cn/ .

Key points: ULM is an emerging technology that can detect highly detailed networks of microvasculature. Microvasculature morphology based on ULM can be a good indicator for the differential diagnosis of breast lesions. Among quantitative parameters extracted from ULM, microvasculature largest diameter was the best for the classification of breast lesions.

超声定位显微镜鉴别乳腺良恶性病变。
目的:探讨超声定位显微镜(ULM)定性和定量参数在鉴别乳腺良恶性病变中的作用。方法:记录乳腺病变的ULM定性和定量参数。采用受试者工作特征(ROC)曲线评价ULM的诊断效果。定量参数在操作者内部和操作者之间的可靠性进行了评估。结果:经病理证实的乳腺病变31例,其中良性14例,恶性17例。良性病变呈点状、线状或分支状(93%比6%),而恶性病变呈混沌状(94%比7%)(p结论:ULM可用于区分乳腺良恶性病变。ULM为乳腺病变的诊断提供了新的方法,值得进一步研究。关键相关声明:本研究提示ULM是一种超分辨率的新技术,有助于区分乳腺良恶性病变。试验注册号:ChiCTR, ChiCTR2100048361。ULM是一项新兴技术,可以检测高度详细的微血管网络。基于ULM的微血管形态学可作为乳腺病变鉴别诊断的良好指标。在ULM提取的定量参数中,微血管最大直径对乳腺病变的分类效果最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信