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基于视觉分类(BI-RADS)的乳腺密度放射学评估与自动化容积数字软件(Quantra)的比较:对临床实践的影响。

Radiological assessment of breast density by visual classification (BI-RADS) compared to automated volumetric digital software (Quantra): implications for clinical practice.

机构信息

S.C. Radiologia Universitaria, Università di Torino, Dipartimento di Diagnostica per Immagini e Radioterapia, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza di Torino, Via Genova 3, 10126, Turin, Italy,

出版信息

Radiol Med. 2014 Oct;119(10):741-9. doi: 10.1007/s11547-014-0390-3. Epub 2014 Mar 8.

Abstract

OBJECTIVE

This study was done to assess breast density on digital mammography and digital breast tomosynthesis according to the visual Breast Imaging Reporting and Data System (BI-RADS) classification, to compare visual assessment with Quantra software for automated density measurement, and to establish the role of the software in clinical practice.

MATERIALS AND METHODS

We analysed 200 digital mammograms performed in 2D and 3D modality, 100 of which positive for breast cancer and 100 negative. Radiological density was assessed with the BI-RADS classification; a Quantra density cut-off value was sought on the 2D images only to discriminate between BI-RADS categories 1-2 and BI-RADS 3-4. Breast density was correlated with age, use of hormone therapy, and increased risk of disease.

RESULTS

The agreement between the 2D and 3D assessments of BI-RADS density was high (K 0.96). A cut-off value of 21% is that which allows us to best discriminate between BI-RADS categories 1-2 and 3-4. Breast density was negatively correlated to age (r = -0.44) and positively to use of hormone therapy (p = 0.0004). Quantra density was higher in breasts with cancer than in healthy breasts.

CONCLUSIONS

There is no clear difference between the visual assessments of density on 2D and 3D images. Use of the automated system requires the adoption of a cut-off value (set at 21%) to effectively discriminate BI-RADS 1-2 and 3-4, and could be useful in clinical practice.

摘要

目的

本研究旨在评估数字乳腺摄影和数字乳腺断层合成摄影的乳腺密度,根据视觉乳腺影像报告和数据系统(BI-RADS)分类进行评估,比较视觉评估与 Quantra 软件的自动密度测量,并确定该软件在临床实践中的作用。

材料和方法

我们分析了 200 例数字乳腺 2D 和 3D 模式的图像,其中 100 例为乳腺癌阳性,100 例为阴性。使用 BI-RADS 分类评估乳腺密度;仅在 2D 图像上寻求 Quantra 密度截断值,以区分 BI-RADS 1-2 类和 BI-RADS 3-4 类。分析乳腺密度与年龄、激素治疗使用情况以及疾病风险增加之间的关系。

结果

2D 和 3D 评估 BI-RADS 密度的一致性很高(K 值为 0.96)。21%的截断值可以最佳地区分 BI-RADS 1-2 类和 3-4 类。乳腺密度与年龄呈负相关(r = -0.44),与激素治疗的使用呈正相关(p = 0.0004)。Quantra 密度在乳腺癌乳房中高于健康乳房。

结论

2D 和 3D 图像的密度视觉评估之间没有明显差异。使用自动系统需要采用截断值(设定为 21%)来有效区分 BI-RADS 1-2 类和 3-4 类,并且在临床实践中可能有用。

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