Suppr超能文献

计算机辅助检测可疑筛查性乳房 X 光摄影中的假阳性标记。

False positive marks on unsuspicious screening mammography with computer-aided detection.

机构信息

Barrett Cancer Center, University of Cincinnati Medical Center, 234 Goodman Street, Mail Location 772, Cincinnati, OH 45267, USA.

出版信息

J Digit Imaging. 2011 Oct;24(5):772-7. doi: 10.1007/s10278-011-9389-7.

Abstract

The contribution of computer-aided detection (CAD) systems as an interpretive aid in screening mammography can be hampered by a high rate of false positive detections. Specificity, false positive rate, and ease of dismissing false positive marks from two CAD systems are retrospectively evaluated. One hundred screening mammographic studies with a BI-RADS assessment code of 1 or 2 and at least 2-year normal mammographic follow-up were retrospectively reviewed using two CAD systems. Breast density, CAD marks, and radiologist's ease of dismissing false positive marks were recorded. Specificities from the two CAD versions considering all marks were 23% and 15% (p value = 0.07); mass marks, 35% and 17% (p value < 0.01); and calcification marks 62% and 75% (p value = 0.01). The two CAD versions did not differ regarding mean and median marks per case for all marks (2.3, 2.0 and 2.3, 2.0, p value = 0.65) or mass marks (1.6, 1.0 and 1.8, 2.0, p value = 0.15), but differed for calcification marks (0.8, 0 and 0.5, 0, p value < 0.01). Slightly higher specificity and fewer marks per case observed in dense breasts did not reach statistical significance. The reviewing radiologist classified most marks from both CAD systems (84% and 88%) as very easy/easy to dismiss. The two CAD versions had small differences in specificity and false positive marks. Differences, although not statistically significant, in specificities and false positive rates between dense and non-dense breasts warrant further research. Most false positive marks are easily dismissed and should not affect clinical performance.

摘要

计算机辅助检测(CAD)系统作为筛查性乳房 X 光摄影的一种解释性辅助手段,其应用可能会受到高假阳性检出率的阻碍。本研究回顾性评估了两种 CAD 系统的特异性、假阳性率和从假阳性标记中轻松排除的能力。使用两种 CAD 系统对 100 项具有 BI-RADS 评估代码 1 或 2 且至少有 2 年正常乳房 X 光摄影随访的筛查性乳房 X 光摄影研究进行回顾性评估。记录乳房密度、CAD 标记和放射科医生轻松排除假阳性标记的能力。考虑到所有标记,两种 CAD 版本的特异性分别为 23%和 15%(p 值=0.07);肿块标记分别为 35%和 17%(p 值<0.01);钙化标记分别为 62%和 75%(p 值=0.01)。两种 CAD 版本在每个病例的平均和中位数标记方面没有差异(所有标记分别为 2.3、2.0 和 2.3、2.0,p 值=0.65)或肿块标记(1.6、1.0 和 1.8、2.0,p 值=0.15),但钙化标记存在差异(0.8、0 和 0.5、0,p 值<0.01)。在致密乳房中观察到的特异性稍高和每个病例的标记较少,但未达到统计学意义。审查放射科医生将两种 CAD 系统的大多数标记(84%和 88%)归类为非常容易/容易排除。两种 CAD 版本在特异性和假阳性标记方面存在细微差异。尽管在致密和非致密乳房之间的特异性和假阳性率差异没有统计学意义,但仍需要进一步研究。大多数假阳性标记很容易排除,不应影响临床性能。

相似文献

2
[Impact of breast density on computer-aided detection (CAD) of breast cancer].[乳腺密度对乳腺癌计算机辅助检测(CAD)的影响]
Zhonghua Zhong Liu Za Zhi. 2012 May;34(5):360-3. doi: 10. 3760/cma.j.issn.0253-3766.2012.05.009.
3
Effect of breast density on computer aided detection.乳腺密度对计算机辅助检测的影响。
J Digit Imaging. 2005 Sep;18(3):227-33. doi: 10.1007/s10278-004-1047-x.

引用本文的文献

本文引用的文献

7
Does computer-aided detection (CAD) contribute to the performance of digital mammography in a self-referred population?
Breast Cancer Res Treat. 2008 Sep;111(2):373-6. doi: 10.1007/s10549-007-9786-2. Epub 2007 Oct 16.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验