医学
乳腺摄影术
乳房成像
放射科
乳腺X光筛查
模态(人机交互)
人工智能
乳腺癌
计算机科学
内科学
癌症
作者
Jan van Zelst,Ritse M. Mann
出处
期刊:Radiographics
[Radiological Society of North America]
日期:2018-05-01
卷期号:38 (3): 663-683
被引量:58
标识
DOI:10.1148/rg.2018170162
摘要
Automated breast (AB) ultrasonography (US) scanners have recently been brought to market for breast imaging. AB US devices use mechanically driven wide linear-array transducers that can image whole-breast US volumes in three dimensions. AB US is proposed for screening as a supplemental modality to mammography in women with dense breasts and overcomes important limitations of whole-breast US using handheld devices, such as operator dependence and limited reproducibility. A literature review of supplemental whole-breast US for screening was performed, which showed that both AB US and handheld US allow detection of mammographically negative early-stage invasive breast cancers but also increase the false-positive recall rate. Technicians with limited training can perform AB US; nevertheless, there is a learning curve for acquiring optimal images. Proper acquisition technique may allow avoidance of common artifacts that could impair interpretation of AB US results. Regardless, interpretation of AB US results can be challenging. This article reviews the US appearance of common benign and malignant lesions and presents examples of false-positive and false-negative AB US results. In situ breast cancers are rarely detected with supplemental whole-breast US. The most discriminating feature that separates AB US from handheld US is the retraction phenomenon on coronal reformatted images. The retraction phenomenon is rarely seen with benign findings but accompanies almost all breast cancers. In conclusion, women with dense breasts may benefit from supplemental AB US examinations. Understanding the pitfalls in acquisition technique and lesion interpretation, both of which can lead to false-positive recalls, might reduce the potential harm of performing supplemental AB US. Online supplemental material is available for this article. ©RSNA, 2018
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