Suppr超能文献

数字乳腺断层合成在提高乳腺钼靶检查中不确定乳腺病变的BI-RADS分类诊断性能方面的附加价值。

The added value of digital breast tomosynthesis in improving diagnostic performance of BI-RADS categorization of mammographically indeterminate breast lesions.

作者信息

Basha Mohammad Abd Alkhalik, Safwat Hadeer K, Alaa Eldin Ahmed M, Dawoud Hitham A, Hassanin Ali M

机构信息

Department of Radiodiagnosis, Zagazig University, Zagazig, Egypt.

出版信息

Insights Imaging. 2020 Feb 14;11(1):26. doi: 10.1186/s13244-020-0835-2.

Abstract

BACKGROUND

Mammographic findings are seen more clearly in tomographic images with consequent improvement of Breast Imaging Reporting and Data System (BI-RADS) in categorization of indeterminate breast lesions. This study aimed to evaluate the added value of digital breast tomosynthesis (DBT) to BI-RADS classification in categorization of indeterminate breast lesions after digital mammography (DM) as an initial approach.

METHODS AND RESULTS

We prospectively evaluated 296 women with BI-RADS indeterminate breast lesions (BI-RADS 0, 3, and 4) by DM between January 2018 and October 2019. All patients underwent DBT. Two radiologists evaluated lesions and assigned a BI-RADS category to each lesion according to BI-RADS lexicon 2013 classification using DM, DBT, and combined DM and DBT. The results were compared in terms of main radiological features, diagnostic performance, and BI-RADS classification using histopathology as the reference standard. A total of 355 lesions were detected on DBT and 318 lesions on DM. Thirty-seven lesions were detected by DBT and not seen by DM. The final diagnoses of 355 lesions were 58.3% benign and 41.7% malignant. In comparison to DM, DBT produced 31.5% upgrading and 35.2% downgrading of BI-RADS scoring of breast lesions. DBT reduced number of BI-RADS 3 and 4, compared to DM. All upgraded BI-RADS 4 were malignant. The combination of DBT and DM significantly increased the performance of BI-RADS in the diagnosis of indeterminate breast lesions versus DM or DBT alone (p < 0.001).

CONCLUSION

Adding DBT to BI-RADS improves its diagnostic performance in detection and characterization of mammography indeterminate breast lesions.

摘要

背景

在断层图像中,乳腺钼靶检查结果看得更清楚,从而在对不确定的乳腺病变进行分类时改进了乳腺影像报告和数据系统(BI-RADS)。本研究旨在评估数字乳腺断层合成(DBT)在数字乳腺钼靶(DM)作为初始检查方法后,对不确定乳腺病变进行分类时对BI-RADS分类的附加价值。

方法与结果

我们前瞻性地评估了2018年1月至2019年10月期间296例经DM检查显示BI-RADS不确定乳腺病变(BI-RADS 0、3和4类)的女性。所有患者均接受了DBT检查。两名放射科医生对病变进行评估,并根据2013版BI-RADS词典分类,使用DM、DBT以及DM与DBT联合检查结果,为每个病变指定一个BI-RADS类别。以组织病理学作为参考标准,比较了主要放射学特征、诊断性能和BI-RADS分类方面的结果。DBT共检测到355个病变,DM检测到318个病变。DBT检测到37个DM未发现的病变。355个病变的最终诊断为58.3%为良性,41.7%为恶性。与DM相比,DBT使乳腺病变的BI-RADS评分升级31.5%,降级35.2%。与DM相比,DBT减少了BI-RADS 3类和4类病变的数量。所有升级为BI-RADS 4类的病变均为恶性。与单独使用DM或DBT相比,DBT与DM联合使用显著提高了BI-RADS对不确定乳腺病变的诊断性能(p < 0.001)。

结论

在BI-RADS中增加DBT可提高其在检测和鉴别乳腺钼靶检查不确定乳腺病变方面的诊断性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1eeb/7021879/ad053efd6c50/13244_2020_835_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验